Molecular characteristics of Kidney Cancer - KOPS - Universität ...

MOLECULAR CHARACTERISTICS OF
KIDNEY CANCER
DISSERTATION
Zur Erlangung des akademischen Grades des
Doktors der Naturwissenschaften an der Universität Konstanz
Fachbereich Biologie
Vorgelegt von
KERSTIN STEMMER
Konstanz, im Oktober 2008
Tag der mündlichen Prüfung:
15. Dezember 2008
Referenten:
Prof. Dr. Daniel R. Dietrich
Prof. Dr. Christof R. Hauck
PD Dr. Sonja von Aulock
I

“Success consists of going from failure to failure without loss of enthusiasm”
Winston Churchill (1874-1965)
III

Table of Contents
Table of Contents........................................................................................................................................ IV
List of Figures.............................................................................................................................................. XI
List of Tables............................................................................................................................................. XIII
Abbreviations ............................................................................................................................................XIV
Publications and Presentations ..................................................................................................................XV
Zusammenfassung..................................................................................................................................XVIII
Summary...................................................................................................................................................XXI
Chapter 1: Introduction........................................................................................................................... 1
1.1 Kidney Cancer........................................................................................................................... 1
1.1.1 Risk Factors for Kidney Cancer............................................................................................ 1
1.1.2 Genetic and Epigenetic Causes of Cancer........................................................................... 2
1.1.3 Models of Carcinogenesis .................................................................................................... 3
1.1.4 Renal Tumor Pathology........................................................................................................ 4
1.2 Renal Carcinogens.................................................................................................................. 10
1.2.1 Genotoxic Carcinogens ...................................................................................................... 10
1.2.2 Non-Genotoxic Carcinogens .............................................................................................. 11
1.3 Renal Carcinogens Relevant for this Study............................................................................. 13
1.3.1 Aristolochic acid.................................................................................................................. 13
1.3.2 Ochratoxin A....................................................................................................................... 15
1.3.3 Cycasin / Methylazoymethanol........................................................................................... 16
1.4 Methods to Identify Renal Carcinogens................................................................................... 18
1.4.1 Standard carcinogenicity testing......................................................................................... 19
1.4.2 The lifetime rodent bioassay............................................................................................... 19
1.4.3 The Eker Rat Model of Renal Carcinogenesis.................................................................... 21
1.5 Toxicogenomics ...................................................................................................................... 22
1.5.1 Principles of the Microarray Technology............................................................................. 22
1.5.2 Microarrays- a Novel Tool to Study Carcinogenesis........................................................... 24
1.5.3 Microarrays- Current Limitations and Future Directions ..................................................... 27
Chapter 2: Work Hypotheses & Experimental Design.......................................................................... 28
IV

2.1 Part I........................................................................................................................................ 28
2.1.1 Experimental setup............................................................................................................. 29
2.2 Part II....................................................................................................................................... 30
2.2.1 Experimental setup:............................................................................................................ 30
2.3 Part III...................................................................................................................................... 31
2.3.1 Experimental setup............................................................................................................. 31
2.4 Schematic Overview on the Experimental Design................................................................... 32
Chapter 3: Manuscript I........................................................................................................................ 33
3.1 Abstract ................................................................................................................................... 33
3.2 Introduction ............................................................................................................................. 34
3.3 Material and Methods.............................................................................................................. 36
3.3.1 Compounds ........................................................................................................................ 36
3.3.2 Animals............................................................................................................................... 36
3.3.3 Animal treatment and sample collection ............................................................................. 36
3.3.4 Histopathology.................................................................................................................... 37
3.3.5 Immunohistochemistry........................................................................................................ 37
3.3.6 RNA isolation and expression profiling ............................................................................... 37
3.3.7 Microarray data processing and statistical analysis............................................................ 38
3.3.8 Functional analysis of microarray data ............................................................................... 38
3.3.9 Statistical analysis .............................................................................................................. 39
3.4 Results .................................................................................................................................... 39
3.4.1 Cell proliferation data.......................................................................................................... 39
3.4.2 Preneoplastic and neoplastic pathology ............................................................................. 39
3.4.3 Non- neoplastic pathology .................................................................................................. 40
3.4.4 Gene expression profiles.................................................................................................... 42
3.4.5 Functional analysis of significantly deregulated genes....................................................... 43
3.4.6 Genes deregulated by aristolochic acid.............................................................................. 43
3.4.7 Genes deregulated by ochratoxin A ................................................................................... 48
3.5 Discussion............................................................................................................................... 57
3.6 Supplement ............................................................................................................................. 62
V

3.6.1 Supplementary Information ................................................................................................ 62
3.6.2 Supplementary Tables........................................................................................................ 63
Chapter 4: Manuscript II....................................................................................................................... 73
4.1 Abstract ................................................................................................................................... 73
4.2 Introduction ............................................................................................................................. 74
4.3 Material and Methods.............................................................................................................. 76
4.3.1 Compound.......................................................................................................................... 76
4.3.2 Animals............................................................................................................................... 76
4.3.3 Short-term experiments ...................................................................................................... 77
4.3.4 Subchronic and chronic experiments.................................................................................. 77
4.3.5 Sample collection ............................................................................................................... 77
4.3.6 Histopathology.................................................................................................................... 77
4.3.7 Cell proliferation analysis.................................................................................................... 78
4.3.8 RNA isolation microarray hybridization and gene expression profiling ............................... 78
4.3.9 Quantification of O6MG ...................................................................................................... 79
4.3.10 Statistical analysis ......................................................................................................... 79
4.4 Results .................................................................................................................................... 80
4.4.1 Gene expression profiling................................................................................................... 80
4.4.2 Non-neoplastic renal pathology .......................................................................................... 83
4.4.3 (Pre)-neoplastic renal pathology......................................................................................... 84
4.4.4 Cell proliferation.................................................................................................................. 87
4.4.5 Detection of O6MG in MAMAc treated Eker-rats................................................................ 88
4.5 Discussion............................................................................................................................... 89
4.6 Supplement ............................................................................................................................. 92
4.6.1 Supplementary experimental procedures: Real time PCR ................................................. 92
4.6.2 Supplementary Figures ...................................................................................................... 92
4.6.3 Supplementary Tables........................................................................................................ 93
Chapter 5: Manuscript III...................................................................................................................... 95
5.1 Abstract ................................................................................................................................... 95
5.2 Introduction ............................................................................................................................. 96
5.3 Material and Methods.............................................................................................................. 98
VI

5.3.1 Animal treatment and tissue preparation ............................................................................ 98
5.3.2 Sectioning and staining ...................................................................................................... 98
5.3.3 Laser-assisted microdissection........................................................................................... 99
5.3.4 RNA isolation and quality control........................................................................................ 99
5.3.5 RNA amplification ............................................................................................................. 100
5.3.6 Affymetrix chip hybridization and expression profiling ...................................................... 101
5.4 Results .................................................................................................................................. 102
5.4.1 Tissue fixation and staining .............................................................................................. 102
5.4.2 RNA quality and yield from pooled microdissected samples ............................................ 105
5.4.3 RNA amplification and microarray hybridization ............................................................... 106
5.4.4 Performance of the established protocol .......................................................................... 110
5.5 Discussion............................................................................................................................. 111
5.6 Appendix ............................................................................................................................... 112
Chapter 6: Manuscript IV ................................................................................................................... 114
6.1 Abstract ................................................................................................................................. 114
6.2 Introduction ........................................................................................................................... 115
6.3 Material and Methods............................................................................................................ 116
6.3.1 Compounds ...................................................................................................................... 116
6.3.2 Animals............................................................................................................................. 116
6.3.3 Sample collection ............................................................................................................. 117
6.3.4 Histopathology.................................................................................................................. 117
6.3.5 Immunohistochemistry...................................................................................................... 117
6.3.6 Laser microdissection and RNA isolation ......................................................................... 118
6.3.7 Microarray data processing and analysis ......................................................................... 118
6.3.8 Statistical analysis ............................................................................................................ 119
6.4 Results .................................................................................................................................. 119
6.4.1 Non-neoplastic pathology ................................................................................................. 119
6.4.2 Cell proliferation................................................................................................................ 120
6.4.3 (Pre-) neoplastic pathology............................................................................................... 121
6.4.4 Gene expression profiling................................................................................................. 123
VII

6.4.5 Confirmation of TORC1 and TORC2 pathway activation in preneoplastic lesions ........... 127
6.5 Discussion............................................................................................................................. 130
6.5.1 Compound-induced tubular damage and regenerative cell proliferation is critical for the
formation but not for the progression of preneoplastic lesions......................................................... 130
6.5.2 Time dependent tissue adaptation to carcinogen treatment ............................................. 131
6.5.3 Numbers of earliest preneoplastic lesions formed are decisive for later occurrence of
veritable tumors ............................................................................................................................... 132
6.5.4 The balance of TORC1 and TORC2 pathways determines preneoplastic lesion progression
133
6.5.5 Outlook ............................................................................................................................. 134
6.6 Supplemental Material........................................................................................................... 135
6.6.1 Supplementary experimental procedures: Real time PCR ............................................... 135
6.6.2 Supplementary Figures .................................................................................................... 136
Supplemental Tables ....................................................................................................................... 140
Chapter 7: Manuscript V .................................................................................................................... 145
7.1 Abstract ................................................................................................................................. 145
7.2 Introduction ........................................................................................................................... 146
7.3 Material and Methods............................................................................................................ 148
7.3.1 Animals............................................................................................................................. 148
7.3.2 Blood parameters ............................................................................................................. 148
7.3.3 Renal Pathology ............................................................................................................... 149
7.3.4 Cell Proliferation analysis ................................................................................................. 149
7.3.5 Immunohistochemistry...................................................................................................... 149
7.3.6 Statistics ........................................................................................................................... 150
7.4 Results .................................................................................................................................. 150
7.4.1 Wistar rats show widely differing propensity towards body weight gain in response to
prolonged high-fat diet exposure...................................................................................................... 150
7.4.2 Increased levels of adipokines and insulin in DIOsens and DIOres rats........................... 151
7.4.3 High-fat diet exposure causes preneoplasia in DIOsens and DIOres rats........................ 152
7.4.4 High-fat diet-induced changes in kidney pathology are independent from α2u-globulin
accumulation.................................................................................................................................... 155
7.4.5 High fat diet increases cell proliferation in proximal tubule of DIOsens and DIOres rats.. 155
VIII

7.4.6 Involvement of the mTOR pathway .................................................................................. 156
7.5 Discussion............................................................................................................................. 157
7.5.1 Similar renal preneoplasias in DIOsens and DIOres rats suggest a minor role of high body
adiposity or its co-morbidities........................................................................................................... 158
7.5.2 High-fat diet exposure does not induce α2u-globulin accumulation................................... 159
7.5.3 mTor-S6K signaling: The link between obesity and kidney cancer................................... 160
7.5.4 Conclusion........................................................................................................................ 161
Chapter 8: Additional Data ................................................................................................................. 162
8.1 Gender Disparity in Early Ochratoxin A and Aristolochic Acid Mediated Renal Toxicity in Shortterm
Assays ......................................................................................................................................... 162
8.2 Ochratoxin A ......................................................................................................................... 162
8.2.1 Cell proliferation (PCNA labeling index) ........................................................................... 162
8.2.2 Renal pathology................................................................................................................ 163
8.2.3 Conclusion........................................................................................................................ 164
8.3 Aristolochic acid .................................................................................................................... 165
8.3.1 Cell proliferation (PCNA labeling index) ........................................................................... 165
8.3.2 Renal pathology................................................................................................................ 165
8.3.3 Conclusion........................................................................................................................ 166
Chapter 9: Overall Discussion and Future Perspectives .................................................................... 167
9.1 Short-term In Vivo Tests to Identify Renal Carcinogens........................................................ 167
9.1.1 Prerequisite I: Short term treatment would result in detectable compound-specific gene
expression changes ......................................................................................................................... 168
9.1.2 Prerequisite II: Genotoxic and non-genotoxic renal carcinogens can be distinguished by
early gene expression profiles ......................................................................................................... 171
9.1.3 Prerequisite III: Manifestation of early compound-induced expression changes in kidney
tumors. 172
9.1.4 Summary Part I................................................................................................................. 174
9.2 Cellular Signaling Cascades in Preneoplastic Lesion Progression ....................................... 175
9.2.1 Pivotal role of carcinogen-induced tubular damage, regeneration and adaptation processes
for the development of kidney cancer .............................................................................................. 176
9.2.2 Predictive potential of preneoplastic lesions as tumor precursors .................................... 180
9.2.3 Summary Part II................................................................................................................ 183
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9.3 Obesity as biasing factor for a reliable human risk assessment from rodent bioassays........ 184
9.4 Synopsis................................................................................................................................ 186
Chapter 10: References ....................................................................................................................... 188
Erklärung.................................................................................................................................................. 199
Danksagung ............................................................................................................................................. 200
X

List of Figures
Figure 1.1: Overview of the morphological structures of the renal nephron.. ................................ 5
Figure 1.2: Progression of renal lesions........................................................................................ 8
Figure 1.3: Chemical structures of AAI and AAII......................................................................... 13
Figure 1.4: Chemical structure of OTA........................................................................................ 15
Figure 1.5: Chemical structures of cycasin, MAM and methyldiazonium ion............................... 17
Figure 1.6: Composition of an Affymetrix chip............................................................................. 23
Figure 2.1: Overview on the experimental design ....................................................................... 32
Figure 3.1: Comparison of PCNA S-Phase labelling indices: short term assay ......................... 40
Figure 3.2: PCNA staining patterns of control- and OTA-treated Eker rats: short term assay. ... 41
Figure 3.3: AA or OTA induced renal gene expression profiles in short term assays ................. 42
Figure 3.4: Postulated mechanistic pathways of AA and OTA induced toxicity........................... 59
Figure 4.1: Metabolic pathways of cycasin and MAM activation ................................................. 75
Figure 4.2: MAMAc induced renal gene expression profiles in short term assays ...................... 80
Figure 4.3: Representative preneoplastic lesions in MAMAc treated rats ................................... 85
Figure 4.4: Mean number of preneoplastic lesions in MAMAc treated Eker rats......................... 86
Figure 4.5: PCNA S-Phase mean labeling indices in MAMAc treated rats.................................. 87
Figure 4.6: Number of O6MG adducts detected via LC-MS/MS ................................................. 88
Figure 5.1: Histology of H&E stained renal cryo-sections. ........................................................ 103
Figure 5.2: RNA quality in renal cyrosections ........................................................................... 105
Figure 5.3: Comparison of total RNA yields after one- or two cycle amplification .................... 107
Figure 5.4: Expression profiles of differentially expressed genes. ........................................... 108
Figure 5.5.: Principal components analysis: One cycle and two-cyce amplification ................... 109
Figure 5.6. Boxplot: Analyis of Affymetrix genechip data .......................................................... 110
Figure 6.1. Preneoplastic lesions in AA- and OTA-treated rats: chronic exposure.................... 122
Figure 6.2: Heatmap comparing gene expression changes of microdissected lesions ............. 123
Figure 6.3. Postulated mechanisms involved in chemically induced in renal cacinogenesis..... 127
Figure 6.4: mTOR activation in preneoplastic lesions............................................... ............. ...129
Figure 7.1: Adipokine, cytokine, and insulin levels ................................................................... 152
Figure 7.2: Images of renal histopathology in DIOsens and DIOres rats .................................. 154
Figure 7.3: PCNA staining in DIOsens and DIOres rats............................................................ 156
Figure 7.4: pS6RP staining in DIOsens and DIOres rats .......................................................... 157
Figure 8.1: PCNA labelling indices in OTA treated Eker and willd type rats.............................. 163
Figure 8.2: Total numbers and incidences of bATs in OTA treated rats.................................... 164
Figure 8.3: PCNA labelling indices in AA treated Eker and willd type rats. .............................. 165
Figure 8.4: Total numbers and incidences of bATs in AA treated rats ...................................... 166
XI

Figure 9.1: Hypothetical model of chemically-induced renal carcinogenesis ........................... 177
Figure 9.2: Gene expression profiles from short-term treated rats and HT .............................. 179
Figure 9.3: Overview of the mTOR pathway ............................................................................ 183
Supplementary Figures:
Supplementary figure 4.1: Real time PCR MGMT...................................................................................... 92
Supplementary figure 6.1: Overview over the experimental design.......................................................... 136
Supplementary figure 6.2: H&E stained paraffin sections: Renal pathology............................................. 137
Supplementary figure 6.3; Immunmohistochemistry pS6RP, pAKT, Foxo1 ........................................... 138
Supplementary figure 6.4: Real time PCR: OGG1 and CAT .................................................................... 139
XII

List of Tables
Table 1.1: Classification of kidney tumors.................................................................................... 6
Table 1.2: Images of frequent cellular abnormalities in rat kidney tumors ................................... 9
Table 3.1: Gene categories of genes differentially deregulated by AA ...................................... 45
Table 3.2: Gene categories of genes differentially deregulated by OTA.................................... 50
Table 4.1: Genes of genes differentially deregulated by MAMAc .............................................. 81
Table 4.2: Non-neoplastic renal pathology in MAMAc treated Eker r......................................... 84
Table 5.1: Influence of tissue preservation on RNA quality...................................................... 102
Table 5.2: Influence of long-term storage on RNA quality and yield ........................................ 103
Table 5.3: RNA quality and yields from pooled microdissected samples................................. 106
Table 6.1: Comparison of BrdU S-Phase labeling indices: Chronic treatment ......................... 120
Table 6.2: Numbers and categories of deregulated genes in preneoplastic lesions ................ 125
Table 7.1: Overview of antibodies and modifications to the manufacture’s protocols .............. 149
Table 7.2: Life-history traits of chow-fed rats, DIOres and DIOsens rats ................................. 151
Table 7.3: Histopathology in chow-fed, DIOres, and DIOsens rats.......................................... 153
Table 9.1: Pathways involved in AA-, OTA- or MAMAc-induced renal carcinogenicity ............ 170
Table 9.2: Genes and pathways linked to the six hallmarks of cancer......................................181
Supplementary Tables:
Supplementary table 3.1: Numbers and categories of genes deregulated by AA or OTA.......................... 63
Supplementary table 3.2: Incidence and numbers of AA and OTA induced renal lesions.......................... 65
Supplementary table 3.3: Non-neoplastic pathology of AA or OTA treated Eker rats. ............................... 66
Supplementary table 3.4: Non-neoplastic pathology of AA or OTA treated wild type rats. ........................ 70
Supplementary table 4.1: Non-neoplastic pathology of MAMAc treated rats ............................................. 93
Supplementary table 4.2: Incidence and numbers of MAMAc induced renal lesions. ................................ 94
Supplementary table 6.1: Non-neoplastic renal pathology: 6months treatment ....................................... 140
Supplementary table 6.2: (Pre-)neoplastic pathology: 6 months treatment ............................................. 141
Supplementary table 6.3: Genes differentially deregulated in preneoplastic lesions ............................... 142
XIII

Abbreviations
α2u alpha 2 urine-globulin
AA aristolochic acid
AAN aristolochic acid nephropathy
bAT basophilic atypical tubule
bAH basophilic atypical hyperplasia
BEN Balkan endemic nephropathy
bw body weight
CPN chronic progressive nephropathy
DIO diet induced obesity
ECM extracellular matrix
EK Eker
EST expressed sequence tag
HT healthy tubule
IARC International Agency for Research on Cancer
ICH International Conference on Harmonization
i.p. intraperitoneal
LC/MS Liquid Chromatography/ Mass spectrometry
LOH loss of heterozygosity
MAM mehylazoxymethanol
MAMAc mehylazoxymethanol acetate
MTD maximum tolerated dose
mTOR Mammalian target of rapamycin
NNM N-nitrosodimethylamine
NOAEL no observable adverse effect level
NTP National Toxicology Program
OTA ochratoxin A
ROS reactive oxygen species
TSC tuberous sclerosis complex
UT urothelial tumors
WHO World Health Organization
WT wild type
XIV

Journal Articles
Publications and Presentations
• Kerstin Stemmer, Heidrun Ellinger-Ziegelbauer, Hans-Juergen Ahr and Daniel R.
Dietrich: Carcinogen Specific Gene Expression Profiles in Short-Term Treated Eker
and Wild Type Rats Indicative for Pathways Involved in Renal Tumorigenesis.
Cancer Research (2007) May 1;67(9):4052-68
• Kerstin Stemmer, Heidrun Ellinger-Ziegelbauer, Kerstin Lotz, Hans-J. Ahr and
Daniel R. Dietrich: Establishment of a Protocol for the Analysis of Laser
Microdissected Rat Kidney Samples on Affymetrix Genechips. Toxicology and
Applied Pharmacology, 217 (2006) 134-142.
• Kerstin Stemmer, Heidrun Ellinger-Ziegelbauer, Hans-Juergen Ahr and Daniel R.
Dietrich: Earliest preneoplastic renal lesions provide an in-depth understanding of
renal carcinogenesis (American Journal of Pathology, submitted)
• Kerstin Stemmer, Heidrun Ellinger-Ziegelbauer, Katja Strauch, Leonard Collins,
James A. Swenberg, Hans-Juergen Ahr and Daniel R. Dietrich: Renal Carcinogenic
Response of Eker Rats to Low Doses of Methylazoxymethanol Acetate (Mutation
Research, submitted)
• Kerstin Stemmer, Diego Perez-Tilve, Daniel R. Dietrich, Matthias H. Tschöp and
Paul T. Pfluger: High-fat diet exposure is associated with renal carcinogenesis in rats
(manuscript to be submitted)
Poster Presentations
• K. Stemmer, P.T. Pfluger, D. Perez-Tilve, M.H. Tschöp and D.R. Dietrich: Long-term
exposure to high-fat diet leads to renal pathology in rats: SOT 47th Annual Meeting,
2008, Seattle, USA
• D.R. Dietrich and K. Stemmer: Gender disparity in early ochratoxin A mediated
toxicity: SOT 47th Annual Meeting, 2008, Seattle, USA
XV

• K. Stemmer and D.R. Dietrich: Characterisation of Renal Preneoplastic Lesions in
Carcinogen Treated and Untreated Eker Rats: International Congress of Toxicology,
Toxicology Discovery Serving Society, July 2007 Montréal, Canada
• K. Stemmer, H. Ellinger-Ziegelbauer, T. Lampertsdoerfer, K. Lotz, H.J. Ahr and D.R.
Dietrich: Expression Profiles Induced By Renal Carcinogens in Eker Rats Compared
to Wildtype Rats. SOT 45th Annual Meeting, 2006, San Diego, USA
• K. Stemmer, J. Haehnlein, H. Ellinger-Ziegelbauer, H.J. Ahr and D.R. Dietrich:
Identification of Potential Markers for an In Vitro Test System of Renal
Carcinogenesis. 5th World Congress on Alternatives & Animal Use in the Life
Sciences, 2005, Berlin, Germany
• K. Stemmer, H. Ellinger-Ziegelbauer, T. Lampertsdoerfer, M. Thiel, H.J. Ahr and
D.R. Dietrich: Ochratoxin A-Induced Gene Expression Deregulations in the Kidney of
Eker Rats Analyzed on Affymetrix Chips. SOT 44th Annual Meeting, 2005, New
Orleans, USA
• K. Stemmer, H. Ellinger-Ziegelbauer, T. Lampertsdoerfer, M. Thiel, H.J. Ahr and
D.R. Dietrich: Expression Profiles Induced by Renal Carcinogens in Rat Kidney
Analysed on Affymetrix Chips. Joint Speciality Symposium on Renal Toxicology and
Toxicologic Pathology, 2004, Lindau, Germany
• J. Haehnlein, K. Stemmer, H. Ellinger-Ziegelbauer, S. Michel-Kaulmann, H.J. Ahr
and D.R. Dietrich: Cytotoxic Effects of Aristolochic Acid (AA) on NRK-52E and
Primary Rat Kidney Cells and Associated Changes in the Expression Pattern of p21
and MGMT. Joint Speciality Symposium on Renal Toxicology and Toxicologic
Pathology, 2004, Lindau, Germany
XVI

Oral presentations
• Früherkennung Nieren-kanzerogener Substanzen. Projektforum Biotechnologie
German Federal Ministry of Research and Education (BMBF), 10.10.2007,
BIOTECHNIKA Hannover, Germany.
• The Use of Laser Microdissection and Pressure Catapulting to Study Gene
Expression in Renal Preneoplastic Lesions. P.A.L.M MicroBeam Workshop:
16.11.2006, P.A.L.M Microlaser Technologies AG, Bernried, Germany.
• Gene Expression Patterns of Different Stages of Renal Pre-Neoplasia: Biolago
Symposium: Science Meets Economy: 13.10.2006, University of Konstanz,
Germany.
Funding and Awards
• Three months research visit at the University of Tel Aviv in Israel. Funded by the
Young Scientist Exchange Program of the German Federal Ministry of Research and
Education (BMBF) and Israel’s Ministry of Science, Culture and Sports (MOST),
2008.
• Three months PhD-scholarship of the Office of Equal Opportunity and Women‘s
Affairs, University of Konstanz, 2008.
• Congress Grant by the German Research Foundation (DFG), 2008
• Research Grant: Molecular Analysis of the Nephrotoxic Action of the Mycotoxin
Ochratoxin A. Environment and Living Foundation, University of Konstanz, 2006
• Three months PhD-scholarship of the Senate Committee for Research (AFF) of the
University of Konstanz, 2006.
• Travel Award of the Society of Toxicology SOT, 2006
• Finalist for the CVSS (Comparative & Veterinary Speciality Section) Student Poster
Award, SOT 45th Annual Meeting in San Diego, USA, 2006
XVII

Zusammenfassung
Hintergrund: Die Mehrheit aller Krebserkrankungen, darunter auch Nierenkrebs, werden
durch Fremdstoffe verursacht. Zur Untersuchung des möglichen kanzerogenen Potentials
von Fremdstoffen sind zweijährige Kanzerogenesestudien in Nagetieren vom Gesetzgeber
vorgeschrieben. In diesen Tests werden nach zweijähriger Exposition mit der jeweiligen
Testsubstanz die Tumorinzidenz und weitere pathologische Effekte untersucht und
anschliessend eine Risikoabschätzung für den Menschen erstellt. Derartige Studien sind
jedoch äußerst zeitaufwendig und teuer. Hinzu kommt ein hoher Tierverbrauch sowie ein
hoher Bedarf an Testsubstanzen für die zweijährige Dosierung. Erschwerend kommt hinzu,
dass die Ergebnisse dieser Langzeit-Studien oft durch unspezifische Hochdosiseffekte
oder durch eine altersabhängige Pathologie verfälscht werden. Zudem können Nagetierspezifische
Effekte auftreten, die für eine Abschätzung der potentiellen Risiken für den
Menschen nur wenig relevant sind, Umgekehrt vernachlässigen diese Studien jedoch
andere Krebsrisikofaktoren, etwa eine hochkalorische Diät oder Fettleibigeit, die die
kanzerogene Wirkung eines Fremdstoffes verstärken können. Die Entwicklung neuer,
hochsensitiver sowie robuster Kurzzeit-In-Vivo-Testsysteme könnte bereits nach kurzen
Expositionsdauern Aussagen über das kanzerogene Potential sowie den
Wirkungsmechanismus einer Testsubstanz liefern, und zu einer verbesserte
Risikoabschätzung für den Menschen beitragen.
Ziele: Im Rahmen dieser Doktorarbeit sollte untersucht werden, ob Nieren-kanzerogene
Substanzen in Kurzeit-In-Vivo-Studien durch sensitive Microarray-Transkriptomanalysen
identifiziert werden können. Des weiteren sollten molekulare Mechanismen bei der
Entwicklung von Fremdstoff-induzierten Nierentumoren charakterisiert werden. Schließlich
sollten die Einflüsse einer fetthaltigen Diät sowie erhöhter Fettleibigkeit auf frühe Stadien
von Nierenkrebs in der Ratte bestimmt werden.
Experimenteller Aufbau: I) Wildtyp Ratten sowie Eker Ratten mit einer Mutation im TSC2
Tumorsuppressor Gen wurden täglich mit den genotoxischen Nierenkanzerogenen
Aristolochia Säure (AA), Methylazoxymethanol Azetat (MAMAc), oder dem nicht
genotoxischen Nierenkanzerogen Ochratoxin A (OTA) gavagiert. Nach 1, 3, 7 und 14
Tagen wurden von Nierenkortex-Homogenaten aller behandelten und Kontroll-Tiere
Genexpressionsprofile mittels Microarrays erstellt. Paraffinschnitte wurden zur
Untersuchung von Histopathologie und Zellproliferation verwendet. II) Eker Ratten wurden
XVIII

mit AA, MAMAc und OTA über 3 und 6 Monate gavagiert und histopathologische
Veränderungen und Zellproliferationraten bestimmt. Parallel hierzu wurde ein Protokoll
entwickelt, welches erstmals reproduzierbare und verlässliche Genexpressionsanaysen
von mikrodissektierten Nierentubuli ermöglichte: Nach diesem Protokoll wurden
Transkriptionsanalysen aus frühen Vortumorstadien (Prä-neoplasien) sowie aus gesunden
Nierentubuli AA- und OTA- und Vehikel-behandelter Eker Ratten erstellt. Die zentralen
Ergebnisse dieser Genexpressionsanalysen wurden mittels immunhistochemischen
Färbungen verifiziert. III) Adverse Effekte auf Nierenpathologie und zelluläre Signalwege
wurden in zwei Subpopulationen von Wistar-Ratten mit hoher Sensitivitaet bzw. Resistenz
gegenüber nahrungsinduzierter Adipositas nach 11 Monaten Exposition mit fetthaltiger
(45%) Diät, sowie in Wistar-Ratten nach Exposition mit fettarmer (6%) Diät untersucht.
Ergebnisse & Diskussion: Histopatholgische Untersuchungen sowie v.a. die Auswertung
der Genexpressionsprofile aus Nierenkortex-Homogenaten zeigten, dass früheste
substanzspezifische Effekte Nieren-kanzerogener Substanzen bereits nach 1- bis 14tägiger
Exposition mit AA, MAMAc bzw. OTA erkennbar sind. Des weiteren erlaubten
besagte Genexpressionsprofile auch die Unterscheidung von genotoxischen und nichtgenotoxischen
Substanzen. Diese Veränderungen der Genexpression nach 1-14 Tagen
Exposition mit AA, MAMA oder OTA waren zudem prediktiv für die substanzspezifische
Inzidenz und Zahl von prä-neoplastischen Läsionen in Eker Ratten nach 3- bzw. 6monatiger
Exposition.
Genexpressionsprofile aus mikrodissektierten präneoplastischen Läsionen von Eker Ratten
nach 6-monatiger Exposition mit AA, OTA oder dem entsprechenden Vehikel zeigten im
Vergleich zu mikrodissektierten gesunden Tubuli von Vehikel behandelten Ratten eine
stark erhöhte Deregulation zahlreicher Gene. Interessanterweise ähnelten sich die
Expressionveränderungen in den verschiedenen Stadien der Läsionen und nach
Behandlung mit den verschiedenen Kanzerogenen stark. Des weiteren konnten nur
geringfügige Genexpressionveränderungen in gesunden Tubuli AA- und OTA-behandelter
Ratten gemessen werden, was auf deren Insensitivität gegenüber kanzerogenen
Substanzen hindeutetete. Diese Daten weisen darauf hin, dass die Anzahl der
präneoplastischen Läsionen, die während einer begrenzten kritischen Phase der
Substanzbehandlung entstehen, ausschlaggebend für die Inzidenz und Anzahl von
Tumoren am Ende der zweijährigen Kanzerogenese Studie sein könnte. Die klonale
Expansion dieser Läsionen ist demgegenüber eher ein substanzunabhängiger Prozess, der
möglicherweise durch eine gestörte Feedback-Inhibitierung des mTOR Signalwegs
verstärkt wird.
XIX

Im letzten Teil der Dissertation konnte gezeigt werden, dass eine stark fetthaltige Diät eine
deutlich schädliche Wirkung auf Rattennieren ausübt. Hierbei stellte sich jedoch heraus,
dass der Grad der Adipositas nur eine untergeordnete Rolle einnimmt im Vergleich zu den
direkten adversen Effekten der ueber die Nahrung aufgenommenen Lipide.
Immunohistochemische Färbungen der Nieren wiesen zudem auf eine bedeutende Rolle
des mTOR Signalweges bei der Lipid-induzierten preneoplastischen Pathologie der Niere.
Fazit: Kurzzeit-In-Vivo-Studien in Kombination mit Microarrays erlauben die
Charakterisierung von frühesten molekularen Vorgängen bei der Entstehung von
Fremdstoff-induzierten Nierentumoren. Des weiteren erfüllen sie alle wichtigen
Vorraussetzungen für eine verlässliche Identifizierung von Nieren-kanzerogenene
Substanzen, nämlich eine hohe Sensitivität, Spezifität und Prediktivität. Die Ergebnisse
dieser Arbeit zeigen, dass unter Verwendung neuer und sensitiver Detektionstechniken
z,B. Microarrays, zweijährige Kanzerogenesestudien deutlich verkürzt werden könnten. Auf
Basis der hier gezeigten Erkenntnisse erscheint es deshalb durchaus möglich, neue
verbesserte Kanzerogenese-In-Vivo-Tests zu entwickeln, die zudem zu einer Reduktion
der Tierzahl führen und weiterhin molekulare Grundlagen schaffen, die zukünftig zur
Schaffung tierversuchsfreier Methoden dienen könnten.
XX

Summary
Background: The vast majority of all human cancers, including kidney cancer, are caused
by xenobiotica. Two-year rodent bioassays play the central role in evaluating the
carcinogenicity of chemicals and are mainly based on a post-mortem evaluation of tumor
incidences and other pathological changes after two years of exposure. However, such
lifetime bioassays are time-consuming and costly, require large numbers of animals and a
high amount of compound for continuous dosing over the entire period of the assay. In
addition, widespread age-related pathologies, unspecific high-dose effects, or rodentspecific
carcinogenic effects with little or no relevance to humans can confound the
outcome of these studies. Furthermore, they do not account for possible additive effects of
other cancer risk factors, such as diet-induced obesity. Therefore, interest in developing
short, sensitive but robust, and mechanistically based in vivo studies has grown, allowing a
more reliable human risk assessment.
Aims: The overall aim of this thesis was to elucidate whether short-term in vivo assays in
combination with microarray technology can be used to identify renal carcinogens. In
addition, a more detailed understanding of potential additive effects of high fat diet
exposure, and molecular mechanisms underlying chemically induced renal carcinogenesis,
should be obtained.
Experimental Setup: I) TSC2-mutant Eker and wild type rats were gavaged daily with the
genotoxic renal carcinogens aristolochic acid (AA) and methylazoxymethanol acetate
(MAMAc), or with the non-genotoxic ochratoxin A (OTA), respectively. Subsequent 1, 3, 7
and 14 days of exposure, gene-expression profiles from kidney cortex homogenates,
histopathology, and cell proliferation were assessed. II) Eker rats were gavaged with AA,
MAMAc and OTA for 3 or 6 months. Subsequently, renal histopathology and cell
proliferation were evaluated. In addition, a novel protocol for reproducible and reliable gene
expression analysis from laser-microdissected pre-neoplastic renal lesions was
established, and gene expression profiles of different stages of preneoplastic lesions and
healthy tubules were examined from 6 months AA-, OTA- and vehicle-treated male Eker
rats. Key findings from transcriptome analyses were verified by immunohistochemistry. III)
The respective impacts of dietary lipids and high body adiposity on renal pathology and
pathways involved in renal cancer were delineated in diet-induced obesity-sensitive and
XXI

diet-induced obesity-resistant subpopulations of male Wistar rats vs. chow-fed controls,
subsequent to 11 months of high fat diet or standard chow exposure, respectively.
Results & Discussion: Renal histopathology and gene expression profiling of kidney
homogenates of short-term AA-, MAMAc-, and OTA-treated rats revealed that microarray
technology is a sensitive tool to study earliest events of renal carcinogenesis. In addition,
gene expression profiles allowed dissecting genotoxic from non-genotoxic modes of action.
Most importantly, early gene expression changes after short-term exposure were predictive
for the incidence and number of preneoplastic lesions after 3 or 6 months of exposure.
Gene expression profiles from microdissected preneoplastic lesions of 6-month AA-, OTAor
control rats revealed marked gene deregulations, when compared to healthy tissue of
control animals. Notably, gene expression changes were similar in different lesion
progression stages and after treatment with genotoxic or non-genotoxic carcinogens.
Furthermore, gene expression profiles of microdissected healthy tubules of AA- and OTAtreated
rats were only marginally changed, suggesting a low compound-sensitivity. These
findings suggested that the number of preneoplastic lesions initially formed during a critical
period of exposure may primarily drive the incidence and number of solid tumors. In
contrast, clonal expansion of these lesions may be compound-independent and instead be
driven by a disturbed feedback inhibition of the mTOR pathway.
Last, high fat diet exposure of male Wistar rats revealed a clear adverse effect of dietary
lipids, and a minor role of the degree of body adiposity, on renal morphology. In addition,
immunohistochemical analyses suggested a major role of the mTOR pathway in dietary
lipid-induced pre-neoplastic pathology.
Conclusion: Microarray-based short-term in vivo assays not only help to delineate
molecular events important for renal cancer, but also fulfill the most important prerequisites
for reliable carcinogenicity testing, i.e. high sensitivity, high specificity, and high predictivity.
Thus, the duration of the standard two-year rodent bioassay can be reduced to a shorter
period of time by using novel and sensitive methodology such as microarrays. Ultimately,
this thesis provides encouraging first results that may help to reduce, refine and one day
even replace animal experiments.
XXII

1.1 Kidney Cancer
Chapter 1: Introduction
Kidney cancer accounts for 2% of all malignancies worldwide, with approximately 210.000
additional cases per year. Because of its high mortality and increasing incidence in most
countries, it is considered to be one of the most important urologic cancers. The world’s
highest incidence of kidney cancer is observed in Eastern European countries (Czech
Republic, Estonia and Hungary). Germany has the 6th highest incidence with 13.2 cases
and 6.3 mortalities per 100.000 in men and 5.9 cases and 2.9 mortalities per 100.000 in
women (IARC 2002c). Kidney tumors usually do not cause signs or symptoms and often
remain unrecognized in their early and treatable stages. Advanced stages and metastases
are therefore more common with kidney cancer than with many other cancer types.
Secondary tumors of the kidney are typically found in the lung, soft tissue, bone, liver,
cutaneous sites and the central nervous system (Corgna et al. 2007).
1.1.1 Risk Factors for Kidney Cancer
The majority of human kidney tumors occur sporadically and only 1-4% of all kidney cancer
cases are caused by an inherited predisposition (Pavlovich and Schmidt 2004). Sporadic
tumors of the kidneys occur more frequently in men than in women (McLaughlin and
Lipworth 2000). The underlying causes for the sex-specific differences are largely unknown,
but may be due to differences in metabolism or hormonal balance. In both sexes kidney
cancer increases with age and more than 75% of all cases occur over the age of 60.
Besides sex and age, epidemiologic studies point to several other risk factors for renal
cancer, including smoking, prolonged dialysis, hypertension, or the use of diuretics and
other anti-hypertensive medication (McLaughlin and Lipworth 2000). In addition, 1/4 of all
human kidney cancers were attributed to excess body weight (Mellemgaard et al. 1995).
However, the underlying causal mechanisms that link the respective risk factors to kidney
cancer still remain elusive.
1

Chapter 1: Introduction
Due to their predominant role in excretion, the kidneys are highly vulnerable to a variety of
circulating toxicants. Approximately one third of the plasma water reaching the kidney is
filtered by the glomeruli and 98-99% of that filtered plasma water is reabsorbed from the
tubular lumen (Casarett and Doull 1986). Consequently, any drug or chemical that is
present in non-toxic concentrations in the blood can reach the renal epithelial cells in much
higher concentrations after being concentrated with the urine and after being reabsorbed
into the cells.
1.1.2 Genetic and Epigenetic Causes of Cancer
I: Tumor suppressor genes and oncogenes
Cancer is usually caused by mutations that are typically found in two classes of genes:
Cancer-promoting oncogenes and cancer-preventing tumor suppressor genes. Gain of
function mutations in oncogenes, which are often involved in signal transduction and
execution of mitogenic signals, result in a hyperactive growth and proliferation of cells
(Todd and Wong 1999). Loss of function mutations in tumor suppressor genes generally
result in dysregulation of the cell cycle and DNA-replication, the inhibition of programmed
cell death (apoptosis) (Malumbres and Barbacid 2001), or disturbed interaction of tumor
cells with protective cells of the immune system (immunoresistance) (Parsa et al. 2007).
In 1975, Alfred Knudson and colleagues proposed the two-hit hypothesis, stating that both
copies (alleles) of a tumor suppressor gene must be lost or mutated for cancer to occur
(Knudson 1975). Although widely accepted, certain exceptions to the 'two hit' rule were
found. For instance, tumor suppressor genes like p27Kip1 might exhibit haploinsufficiency
after a mutation of a single allele, when the remaining functional allele does not translate
into enough protein to preserve a wild-type phenotype (Fero et al. 1998). For oncogenes,
gain of function mutations in one allele are usually enough to trigger cancer development
(Todd and Wong 1999).
Besides mutations in tumor suppressor genes and oncogenes, tumorigenesis can be
supported by any event that accelerates the spontaneous rate of genetic alterations in the
cell. For instance, hereditary or spontaneous damage in the cellular DNA damage repair
system may favor the accumulation of additional mutations, and genetic or genomic
instability of cells (Schmutte and Fishel 1999; Jefford and Irminger-Finger 2006).
2

II: Epigenetic alterations
Chapter 1: Introduction
Most recently, several studies pointed towards a critical role of reversible epigenetic
alterations in carcinogenesis (Baylin and Herman 2000, Sparmann, 2006, Vucic, 2008).
Epigenetic regulation is generally organized at the level of DNA (post-replicative
methylation), RNA (RNA interference), and protein (histone modifications and polycomb
group protein complexes) (Momparler 2003).
Abnormal patterns of DNA methylation in cancer cells have been recognized for more than
20 years and global hypomethylation and region-specific hypermethylation are frequent
events in tumor cells (Baylin and Herman 2000). The biological significance of DNA
hypomethylation in cancer is less understood. Hypermethylation mainly occurs at CpG
islands within the promoter region of a gene, resulting in its suppressed transcription. The
current model suggests that promoter hypermethylation and transcriptional silencing of
tumor suppressor or DNA repair genes and mutations within these genes occur at least
with a comparable frequency.
Besides DNA methylation, alteration in histone acetylation plays another important role in
the regulation of gene expression. Inactive chromatin mediated by histone deacetylation
was demonstrated as one critical component in the silencing of tumor suppressor genes.
Different histone deacetylase inhibitors are currently in clinical trials for the treatment of
cancer (Martinez-Iglesias et al. 2008).
Although still much has to be learned, epigenetic regulation is already assumed to be
equally important for the onset of cancer as genetic alterations. The interplay between
genetic and epigenetic changes during tumor progression is thus becoming a major focus
of cancer research.
1.1.3 Models of Carcinogenesis
I: Multistage model of carcinogenesis
The process of carcinogenesis is widely accepted as a multistage process, with a sequence
of multiple genetic events preceding the onset of cancer (Armitage and Doll 1954; Barrett
and Wiseman 1987). The process is based on genetic alterations that have to be fixed
during DNA replication, leading to growth advantage of the initiated cell (tumor initiation).
Clonal expansion of these cells may lead to the development of pre-neoplastic foci with
characteristics that favor genetic instability (tumor promotion). Further accumulation of
3

Chapter 1: Introduction
additional mutations in the fast-growing cells can result in the development of a malignant
phenotype that enables the cells to invade the surrounding tissue (tumor progression).
Such a genetic multistage model has been described by Fearon and Vogelstein for
colorectal cancer, where a linear sequence of specific genetic events can be correlated with
evolving pathophysiological stages of colon carcinogenesis (Fearon and Vogelstein 1990).
Ten years later the linear model of multistage carcinogenesis was elaborated by Hanahan
and Weinberg (Hanahan and Weinberg 2000), who described six essential changes in cell
physiology that define the development of malignant tumors: (1) self-sufficiency in growth
signals, (2) insensitivity to growth inhibitory signals, (3) evasion of apoptosis, (4) limitless
replicative potential, (5) sustained angiogenesis and (6) tissue invasion and metastasis. In
contrast to the Fearon-Vogelstein model, the Hanahan–Weinberg model does not depend
on the sequential accumulation of specific mutations for a distinct tumor type but instead
depends on a set of functional changes that can result from many different genetic or
epigenetic alterations, independent of cell-type, species and aetiology.
II: Cancer stem cell model
During recent years, the stem cell model of carcinogenesis gained major attention. The
American Association for Cancer Research Stem Cell Workshop defined a cancer stem cell
as a cell within a tumor that possesses the capacity to self-renew. Thus, heterogeneous
lineages of cancer cells that comprise the tumor may originate from one cancer stem cell.
In this model cancer cells may arise from tissue stem cells that have acquired mutations
that render them cancerous. Cancer cells may also arise from differentiated progenitor cells
that "re-acquired" stem cell like properties due to mutations (Clarke et al. 2006). Cancer
stem cells were originally identified in leukemia (Bonnet and Dick 1997) and later in solid
brain (Singh et al. 2003), breast (Al-Hajj et al. 2003), and colon tumors (O'Brien et al.
2007). However, to date cancer stem cells have not been detected in kidney tumors.
1.1.4 Renal Tumor Pathology
Renal toxicology and pathology are closely related to the kidney’s complex functional
anatomy, with the cortex forming the outer part enclosing the renal medulla and papilla
(Figure 1.1). The functional unit of the kidney is the nephron, consisting of the glomerulus,
proximal tubule, loop of Henle, distal tubule and collecting duct. The proximal tubule is
furthermore dissected into three segments: The tubulus contortus proximalis, consisting of
the post-glomerular portion (P1), and the more distal portion (P2) of the proximal tubule,
4

Chapter 1: Introduction
containing an active endocytosis/lysosomal apparatus, thus representing the site of injury
related to lysosomal overload, as well as to protein-bound toxic moieties (Cristofori et al.
2007). The following straight portion of the P3 segment (tubulus rectus proximalis)
represents the most susceptible site of injury via metabolic activation of xenobiotica and via
their transporter-associated accumulation (Cristofori et al. 2007).
Figure 1.1: Overview of the morphological structures of the renal nephron. Source:
http://de.wikipedia.org/wiki/Nephron.
I: Kidney Tumors in Humans
The majority of kidney tumors in humans (80-85%) are renal cell carcinoma (RCC),
originating from the renal parenchyma. The remaining 15-20% are mainly transitional cell
carcinoma of the renal pelvis, while other neoplasms, e.g. angiomyolipoma or
nephroblastoma (Wilms' Tumor), are rare (Motzer et al. 1996).
RCC are not a single entity but comprise a heterogeneous group of tumors that range from
entirely benign to aggressively malignant. They were sub-classified according to their
histological characteristics into clear cell RCC (70%), papillary RCC (15%), chromophobe
RCC (10%), oncocytoma (5%) and collecting duct carcinoma (

Chapter 1: Introduction
to correlate with distinct histological sub-types in sporadic RCC, which allowed a more indepth
tumor classification and improved diagnostics (for further information see table 1.1)
(Kovacs et al. 1997; Pavlovich and Schmidt 2004).
Table 1.1: Classification of kidney tumors (adjusted from (Bjornsson et al. 1996; Dulaimi et al. 2004;
Pavlovich and Schmidt 2004; Henske 2005))
Histological
type
Presumed
origin
Clear cell RCC Proximal renal
tubule
Papillary RCC
(basophilic
and
eosinophilic)
Chromophobe
RCC
Proximal renal
tubule
Collecting duct
(intercalated
cells)
Oncocytoma Collecting duct
(intercalated
cells)
Collecting
carcinoma
Angiomyolipoma
Frequent cytogenetic
abnormalities in
sporadic tumors *
-3p, +5q, -Y, -8p, -9p, -
14q, t(3;5)(p;q);
+7, +17, -Y, +12, +16,
+20
-1, -2, -6, -10, -13, -17,
-21
-1, -Y, t(5;11)(q35;q13),
t(9;11)(p23;q13)
Collecting duct -1q32, -6p, -8p, -21q,
highly aneuploid
Mesenchymal
cells (immature
smooth muscle
cells, fat cells)
No specific
chromosomal changes
have been identified
Frequent promoter
hypermethylations in
sporadic tumors
VHL, RASSF1A,
p16 INK4a , p14 ARF, APC,
MGMT, GSTP1,
RARß2, E-cadherin,
TIMP3
RASSF1A, p16 INK4a ,
p14 ARF, APC, MGMT,
GSTP1, RARß2, Ecadherin,
TIMP3
RASSF1A, p14 ARF,
RARß2, TIMP3
RASSF1A, p16 INK4a ,
p14 ARF, APC, MGMT,
GSTP1, TIMP3
RASSF1A, p14 ARF,
APC, MGMT, RARß2,
TIMP3
No epigenetic changes
have been identified
Hereditary genetic
syndromes and
implicated genes **
Von Hippel-Lindau disease
(VHL); Birt Hogg Dubé
syndrome (BDH); Tuberous
Sclerosis (TSC1, TSC2)
Hereditary papillary renal
carcinoma (c-MET);
Hereditary leiomyomatosis
renal cell cancer (FH);
Hyperparathyroidism-jaw
tumor (HRPT2); Tuberous
Sclerosis (TSC1, TSC2)
Birt Hogg Dubé syndrome
(BDH); Tuberous Sclerosis
(TSC1, TSC2)
Birt Hogg Dubé syndrome
(BDH); Tuberous Sclerosis
(TSC1, TSC2)
Hereditary leiomyomatosis
renal cell cancer (FH)
Tuberous Sclerosis (TSC1,
TSC2)
* Nomenclature cytogenetics: Loss of a chromosome (-); gain of a chromosome (+); translocation (t); short
arm of a chromosome (p); long arm of a chromosome (q). ** Von-Hippel-Lindau (VHL); Birt Hogg Dubé
(BDH), Fumarat hydratase (FH); Hyperparathroidism 2 (HRPT2); Tuberous Sclerosis 1 (TSC1), Tuberous
Sclerosis 2 (TSC2)
However, cytogenetic studies are mainly based on the analysis of gross tumors that may
have gained numerous mutations after developing genetic instability. Thus, in most cases
the initial genetic or epigenetic cause for the initiation of spontaneous kidney tumors
remains elusive. However, studies of families with hereditary genetic syndromes have
identified several predisposing genes involved in renal carcinogenesis. Due to the similar
histology of hereditary and sporadic RCC, these genes were also suggested to be involved
in the development of sporadic tumors (Table 1.1, right column).
6

II: Kidney Tumors in Rats
Chapter 1: Introduction
Rats are the most common laboratory animal to study renal carcinogenesis. Although the
incidence of spontaneous RCC in laboratory strains is very low (e.g. 0.08% in Sprague-
Dawley and 0.28% in F344 rats) (Chandra et al. 1993), similar tumor types as those
observed in humans have been experimentally induced in rodents by distinct chemicals,
hormones, viruses and radiation (Hamilton 1975; Lock and Hard 2004). Studies in rodents
not only allowed the analysis of the carcinogenic potential of numerous test compounds
(see chapter 1.2.1) but also the identification of the earliest carcinogen-induced foci of cells
(pre-neoplastic lesions) with alterations very similar to those found in end-stage tumors.
From these findings it was concluded that kidney tumor development can occur in
successive stages, from single atypical tubules to hyperplasia to adenoma and/or
carcinoma (Figure 1.2) (Dietrich and Swenberg 1991). However, knowledge of the initial
causes and the process of progression of chemically induced tumors is still limited. Current
findings from rodent bioassays assume that not all carcinogen-induced pre-neoplastic
lesions will progress to a neoplastic lesion and it is often not possible to distinguish lesions
with a neoplastic potential from lesions that are self-limiting or even reversible, and thus
may not have any significance for the testing of carcinogenicity (Alden and Kanerva 1982;
Eustis 1989). To date, the potential contribution of pre-neoplastic lesions to carcinogeninduced
tumor development is mainly assessed by histopathologic evaluation of similarities
between compound-induced pre-neoplastic and neoplastic lesions, by the absence or
presence of a morphological continuum between these lesions, and by the occurrence of
treatment-related cytotoxicity and regenerative cell proliferation (Eustis 1989).
Common cytological alterations found in carcinogenic lesions in rats resemble those of
sporadic lesions in humans and are summarized in table 1.2. Both the chemical properties
of the inducing compounds, as well as their metabolism and location of uptake within the
different tubular segments, most likely determine the type and cellular origin of the lesions.
For instance, clear cell/ acidophilic tumors in N-nitrosomorpholine (NNM)- treated rats were
demonstrated to arise from the distal tubules and collecting ducts, which are also the main
sites of NNM-induced acute cell damage (Bannasch et al. 1989; Nogueira et al. 1989).
Similarly, the most common carcinogen-induced basophilic RCC as well as chromophobe
RCC originate from the proximal tubules, which represent the most susceptible sites of
injury via metabolic activation of xenobiotica or their transporter-associated accumulation
(e.g. ochratoxin A, fumonisine B1) (Boorman et al. 1992; Howard et al. 2001). Oncocytic
cells were found to arise from the intercalated cells of the renal collecting duct of potassium
7

Chapter 1: Introduction
bicarbonate-, NNM-, streptomycin- or lead acetate-treated rats (Nogueira 1987; Mayer et al.
1989; Lina and Kuijpers 2004).
Preneoplastic and neoplastic lesions of mixed cellular phenotypes can occur spontaneously
or subsequent to carcinogen treatment. However, it is not clear whether different cellular
alterations occur by random hits in different tumor suppressor genes or oncogenes or by a
transition process from one to another lesion type.
Figure 1.2: Progression of renal lesions. Adjusted from Dietrich and Swenberg (Dietrich and
Swenberg 1991). Microscopic images represent typical renal basophilic lesions of
Eker rats after exposure with renal carcinogens, and were obtained during the course
of this thesis. For further information, see text.
8

Chapter 1: Introduction
Table 1.2: Representative images of frequent cellular abnormalities and biochemical features of
carcinogen-induced kidney tumors in rats. Adjusted from (Dietrich and Swenberg
1991). Microscopic images kindly provided by Daniel R. Dietrich
Histological type Morphological and cytological characteristics Representative image
Clear cells Large translucent cytoplasm, irregular cell shape
with small chromatin-dense nuclei. Cytoplasmatic
accumulations of glycogen and lipids (Mayer et al.
1988, Steinberg et al. 1992).
Acidophilic
(eosinophilic) cells
Often associated with clear cells and are slightly
larger than normal cells with a strongly eosinophilic
cytoplasm
Basophilic cells Basophilic cytoplasm. Increased abundance of
ribosomes, slightly enlarged nuclei with prominent
nucleoli
Chromophobic cells Enlarged cells with slightly translucent cytoplasm.
Weak eosinophilic or basophilic staining. Extensive
storage of mucopolysaccharides likely enclosed in
cytoplasmatic vacuoles
Oncocytic cells Large polygonal shape with acidophilic/
eosinophilic and granular cytoplasm. Abundance
of atypical mitochondria and a large content of
cytochrome c oxidase. Over-expression of GLUT1
and hexokinase I.
9

1.2 Renal Carcinogens
Chapter 1: Introduction
Based on the general assumption that multigenetic events are required for carcinogenesis,
there are basically two possibilities by which a chemical carcinogen can increase the
possibility of tumorigenesis within a tissue: 1) by increasing the rate of DNA or
chromosomal damage, resulting in more errors per replication, or 2) by increasing the
number of DNA replications and therefore the likelihood of spontaneous errors (Cohen and
Arnold 2008). Initiated and clonally expanding cells might have different characteristics than
their cell of origin and therefore might be differentially influenced by chemical carcinogens.
For instance, it is not entirely clear whether progressing stages of transformed, neoplastic
kidney cells are still capable of taking up or metabolizing carcinogens or rather
dedifferentiate in favor of proliferation.
Chemical carcinogens have been categorized according to two general mechanisms of
action into genotoxic and non-genotoxic carcinogens:
1.2.1 Genotoxic Carcinogens
Genotoxicity is induced by compounds that are able to directly interact with the DNA
(mutagens), compounds that break chromosomes (clastogens) and compounds that
damage the spindle apparatus (aneugens). Genotoxic carcinogens are either electrophilic
molecules per se or are absorbed as stable pro-carcinogens that have to be bio-activated
to their active electrophilic form, which can then covalently interact with any nucleophilic
site in the cell, such as the DNA resulting in DNA adducts. Groups of genotoxins can
therefore often be recognized by their structural features (e.g. alkenes, aromatic amines,
nitrosamines or polycyclic aromatic hydrocarbons).
According to their relatively simple mode of action, which involves a single chemical
interaction with one specific target molecule, DNA adduct formation was expected as a
linear function of the administered dose of the DNA-reactive compound. In fact most
carcinogenicity studies that have used low doses of genotoxic compounds have been
interpreted as showing no threshold (Lijinsky et al. 1988; Peto et al. 1991). It was therefore
concluded that even the smallest doses of DNA-reactive compounds increase susceptibility
to cancer and that a zero-risk or safe-dose may not be defined. However, it is now
recognized that many factors e.g. efficiency of absorption, distribution, metabolism, DNA
damage repair and mutation fixation, can affect the linear shape of the dose-response
10

Chapter 1: Introduction
curve, leading to a sublinear and supralinear curve progression (Williams et al. 1995;
Swenberg et al. 2008). Due to these findings it is now frequently discussed, whether a
threshold or no-observable-adverse-effect-level (NOAEL) may exist at least for some
genotoxic compounds (Williams et al. 1995; Oesch et al. 2000; Hengstler et al. 2003).
1.2.2 Non-Genotoxic Carcinogens
Non-genotoxic carcinogens are a heterogeneous group of carcinogens that are not directly
DNA-reactive. However, they are capable of inducing epigenetic effects on cells that 1)
either indirectly result in DNA modification and subsequently pro-carcinogenic mutations, or
2) promote the development of initiated cells into neoplasms. Numerous tumor promoting
mechanisms have been identified for a wide range of non-genotoxic compounds. Many of
these are cell type-, tissue-, sex- or species-dependent and usually require sustained and
high (above threshold) exposures to induce a carcinogenic effect. For kidney
carcinogenesis non-genotoxic carcinogens can be categorized into three basic groups:
I: Cytotoxic Carcinogens
A number of non-genotoxic carcinogens were demonstrated to induce tumors at high
cytotoxic doses. It is assumed that exposure to cytotoxic carcinogens results in tissue
damage, and the subsequent regenerative cell proliferation may either contribute to the
fixation of spontaneous mutations, or to the promotion of naturally occurring tumors in
tissues with a high spontaneous tumor rate (Dietrich and Swenberg 1990; Cohen and
Arnold 2008). One of the best studied species-, sex- and tissue-specific mechanisms is the
chemically induced α2u-globulin nephropathy, which is associated with the onset of renal
neoplasms in male rats (Swenberg 1993). α2u-globulin is a plasma protein that binds
hydrophobic small molecules for subsequent absorption and lysosomal degradation by the
P2 segment of the renal proximal tubule. Binding of xenobiotica, e.g. unleaded petrol,
decalin or d-limonene, may result in a structural alteration of α2u-globulin and its protection
from lysosomal degradation. Subsequent accumulation of lysosomal protein droplets in the
kidney frequently results in tubular necrosis, compensatory cell proliferation (regeneration),
and an increased chance for the fixation of spontaneous genetic damage and therefore the
onset of renal tumorigenesis (Dietrich and Swenberg 1990; Swenberg and Lehman-
McKeeman 1999; Dill et al. 2003).
11

II: Non-Cytotoxic Carcinogens
Chapter 1: Introduction
Non-cytotoxic carcinogens exert their tumor promoting potential without causing prior cell
loss. Instead, they are able to influence a variety of cellular signaling pathways that are
often controlled by tumor suppressor genes and proto-oncogenes. Non-cytotoxic
carcinogens may cause a cell to commence cell division by triggering mitosis or inhibiting
apoptosis. Such ‘mitogens’ often mimic the activation of extracellular growth factors by
either directly activating the corresponding receptor, or by modulating downstream
signaling events through interaction with kinases, phosphatases, scaffold proteins or
chaperons, ultimately inducing mitosis (Perona 2006; Lawrence et al. 2008). Other noncytotoxic
carcinogens can inhibit intercellular communication via gap junctions and affect
cellular growth regulation and differentiation (Chipman et al. 2003; Leithe et al. 2006).
III: Indirect genotoxic carcinogens
The induction of oxidative stress has been proposed as one possible mechanism of action
for non-genotoxic carcinogens, either by increasing the production of reactive oxygen
species (ROS), or by inhibiting the antioxidant capability of the target cell. ROS can not only
modify cellular lipids and proteins but also directly oxidize and damage the DNA. The best
studied oxidative DNA lesion is 8-hydroxydeoxyguanosine (OH8dG) which occurs from
oxidation of guanine at the C8 position within the DNA, or from oxidation of dGTP and its
later incorporation into the DNA. Both can result in site-specific mutagenesis (Shibutani et
al. 1991; Hussain and Harris 1998). Recent evidence shows that ROS and oxidative DNA
damage can modulate DNA methylation patterns (Turk et al. 1995) which may result in
epigenetic silencing of tumor suppressor genes or activation of oncogenes. Besides their
role in tumor initiation, ROS were further shown to be involved in tumor promotion and
progression. High doses of cellular ROS or ROS-promoting agents are clearly cytotoxic and
can result in regenerative cell proliferation and fixation of mutations. Low doses of ROS
may contribute to abnormal gene expression, cell signaling and alteration of second
messenger systems. For instance, ROS can activate both mitogen-activated protein (MAP)
kinase/AP-1 and NFkappa-B pathways, which are critically involved in cell proliferation and
apoptosis (Klaunig and Kamendulis 2004).
12

1.3 Renal Carcinogens Relevant for this Study
Chapter 1: Introduction
For this thesis, three naturally occurring renal carcinogens were used and the following
chapter will give an overview of the chemical and biological properties of the respective
compounds.
1.3.1 Aristolochic acid
Aristolochic acid (AA) represents a mixture of aristolochic acid I (AAI) and aristolochic acid
II (AAII) (Figure 1.3) and is primarily found in the Aristolochia and Asarum species of the
Aristolochiaceae family of plants. It can be found in a number of botanical products such as
traditional medicines, dietary supplements and weight loss remedies.
Figure 1.3: Chemical structures of aristolochic acid I and aristolochic acid II, from
(Balachandran et al. 2005)
I: Acute and Chronic Toxicity
The kidneys are the primary target organ for acute and chronic AA toxicity in both
laboratory animals (rats, mice and rabbits) and humans. In rats, the oral LD50 (the quantity
of a compound per kg per body weight (bw) that kills 50% of the study population) was
reported to be 203.4 mg/kg bw in males and 183.9 mg/kg bw in females (Mengs 1987).
Rats treated with a single or continuous high oral doses 1-10mg/kg BW) of AA developed
renal failure with tubular necrosis of the corticomedullary junction (Mengs 1987; Mengs and
Stotzem 1993), and had elevated plasma creatinine and urea levels (Mengs and Stotzem
1993; Liu et al. 2003; Cui et al. 2005). In addition, in some studies interstitial fibrosis was
observed (Debelle et al. 2002; Sun et al. 2006), although this finding could not be replicated
13

Chapter 1: Introduction
by others (Cosyns et al. 1998; Cui et al. 2005). In humans, consumption of AA-containing
botanical products has been associated with the onset of aristolochic acid nephropathy,
characterized by mild tubular proteinuria, extensive interstitial fibrosis, tubular atrophy,
global sclerosis of glomeruli, and rapid progression to renal failure (Nortier and
Vanherweghem 2002; Cosyns 2003).
II: Carcinogenicity
AA is mutagenic and carcinogenic in mice, rats, rabbits and humans (Arlt et al. 2002).
Recently, AA-containing products were classified as carcinogenic to humans (Group 1) by
the International Agency for Research on Cancer (IARC) (IARC 2002b). In rats, application
of high oral doses (50mg/kg bw) for three days resulted in increased incidences of
preneoplastic and neoplastic lesions of the kidney after a latency of 6 months (Cui et al.
2005). In another study, continuous gavage with 1-10mg/kg bw for 3 to 6 months resulted
in a dose-dependent increase of a variety of tumors predominantly observed in the
forestomach, the kidneys (epithelial adenomas and adenocarcinomas of the renal cortex)
and tumors of the renal pelvis or urinary bladder (Mengs et al. 1982; Cosyns et al. 1999)
A number of single case reports as well as studies from a large cohort of patients of a
Belgian slimming regimen, who received AA-contaminated products by accident, have
reported a high prevalence of urothelial cancer in patients with aristolochic acid
nephropathy (AAN) (Cosyns et al. 1999; Nortier et al. 2000). Most recently, AA was also
associated with the etiology of the Balkan Endemic Nephropathy (BEN), a form of interstitial
fibrosis associated with urothelial tumors which is most prevalent in the Balkan countries
Bosnia, Serbia Croatia, Romania and Bulgaria (Arlt et al. 2007; Grollman et al. 2007).
However, until now it has not been unequivocally established that the inhabitants of BEN
areas are indeed exposed to higher concentration of AA than inhabitants of other regions,
and the routes of exposure remain largely unknown.
The genotoxic action of AA is based on its bioactivation to an intermediate aristolactamnitrium
ion (Krumbiegel et al. 1987; Chan et al. 2006; Stiborova et al. 2008), which is able
to form bulky adducts at purine bases of the DNA (Schmeiser et al. 1988), including
dAdenin-AAI adducts which were identified as the main effectors for the mutagenic and
carcinogenic action of AA (Pfau et al. 1990; Pfau et al. 1991). The mutagenic potential for
AA was demonstrated in a number of in vitro systems (Schmeiser et al. 1984; Arlt et al.
2002; Zhang et al. 2004). Increased mutation frequencies were also seen in the kidneys,
bladder and forestomach of carcinogenicity models such as the transgenic Muta TM Mouse
(Kohara et al. 2002) and Big Blue rats (Mei et al. 2006). In another study, analysis of
14

Chapter 1: Introduction
mutational spectra from tumors of AA-treated rats revealed activating AT to TA transversion
mutations in codon 61 of the H-ras oncogene in forestomach, lung and ear duct tumors, but
not in kidney tumors (Schmeiser et al. 1990), suggesting an H-ras independent pathway of
renal tumor induction. In humans, AT to TA transversion mutations were observed in the
p53 tumor suppressor gene in urothelial tumors derived from AAN and BEN patients (Lord
et al. 2004; Arlt et al. 2007).
1.3.2 Ochratoxin A
Ochratoxin A (OTA) is a naturally occurring mycotoxin, commonly produced by a variety of
Penicillium and Aspergillus species (Figure 1.4). It occurs as a notorious contaminant of
grains and cereals and is also commonly found in food and beverages, e.g. in dried fruits,
chocolate, juices, wine or beer (Kuiper-Goodman 1991; Clark and Snedeker 2006).
Figure 1.4: Chemical structure of ochratoxin A. From: www.wikipedia.org/wiki/Ochratoxin
I: Acute and Chronic Toxicity
Acute toxicity of OTA is highly species-specific with an oral LD50 ranging from 0.2-
1.0mg/kg bw for species such as sheep, pigs, rabbits and dogs, to 20mg/kg bw in rats, and
to 46-58mg/kg bw in mice. In rats, chronic exposure with OTA targets primarily the kidney.
OTA accumulates to high amounts in the proximal tubule where it provokes morphological
changes predominantly in the S3 segment of the proximal convoluted tubule, including
cytoplasmatic alterations, karyomegaly, and tubular degeneration as well as the
development of cortical fibrosis. Functional alterations in response to OTA treatment are
reflected by a decreased creatinine, inulin and p-aminohippurate clearance, polyuria,
glucosuria, and a decreased osmolarity of the urine (NTP 1989).
15

II: Carcinogenicity
Chapter 1: Introduction
OTA is a potent renal carcinogen in rodents (NTP 1989; Boorman et al. 1992; Rasonyi et
al. 1999; Mantle et al. 2005). However, due to inadequate evidence for carcinogenicity in
humans, it was classified by IARC as possibly carcinogenic to humans (group 2B). Rats
exposed for two years with 210µg/kg bw/day developed a massive increase of benign and
malignant tumors arising from tubular renal epithelial cells (Boorman et al. 1992). The 60%
tumor incidence in male rats was 10-fold higher than observed in female rats, suggesting a
sex-specific mode of action. To date, the mechanism of OTA-induced carcinogenicity is still
not well defined and controversial results regarding a genotoxic (Faucet et al. 2004) or a
non-genotoxic (Mally et al. 2005) mode of action have been published. Since OTA has not
been clearly demonstrated to form reactive intermediates capable of covalently interacting
with the DNA (Kamp et al. 2005; Mally et al. 2005; Delatour et al. 2008), a non-genotoxic
mechanism of action is suggested by the majority of studies. Recent data indicate that renal
toxicity as well as the observed DNA damage are most likely attributable to oxidative stress
(Kamp et al. 2005; Marin-Kuan et al. 2006; Domijan et al. 2007). Notably, MAPK-ERK
pathway activation as well as histone deacetylase-induced gene silencing are suggested to
play an important role in OTA-induced tumorigenesis (Marin-Kuan et al. 2007).
Similar to aristolochic acid, OTA is assumed to be involved in the onset of BEN, based on
studies that revealed a higher frequency of BEN in inhabitants of areas endemic for OTAcontaining
foods (Fuchs and Peraica 2005; Clark and Snedeker 2006). Moreover, OTA was
more frequently detected in blood samples of patients with BEN than in healthy individuals
(Fuchs and Peraica 2005). Based on data from one human volunteer who ingested 395ng
of radioactivelly labelled [3H]-OTA, the half-life of 35,5 days was about eight-fold longer the
OTA half-life determined for rats (Studer-Rohr et al. 2000). Therefore, although a causal
relationship between OTA and the onset of BEN and urothelial tumors still remains elusive,
the long half-life in humans might contribute to the accumulation of OTA in various target
organs, and thus to the onset of BEN or OTA-mediated cancers.
1.3.3 Cycasin / Methylazoymethanol
Methylazoxymethanol (MAM) is the biologically active metabolite of cycasin (Figure 1.5, A),
which is a toxic glycoside of the cycad plants Cycas circinalis and Cycas revoluta. Nuts,
roots and leaves of these plants have been sources for food and medicine for the
indigenous people of the Western pacific (e.g. Guam).
16

A: B: C:
Chapter 1: Introduction
Figure 1.5: Chemical structures of (A) cycasin, (B) MAM and (C) methyldiazonium ion. From:
(Sohn et al. 2001)
I: Acute and Chronic toxicity
The acute oral LD50 of cycasin is highly species-dependent, ranging from less than 20
mg/kg bw in the guinea pig to 562 mg/kg bw in the rat (Hirono 1972). In rats, a 6.5 fold
lower oral LD50 was detected when the active metabolite MAM was directly gavaged
(Hirono 1972). Acute toxic effects of MAM and cycasin mainly occurred in the liver,
including glycogen, RNA and phospholipid depletion, cellular necrosis, and haemorrhage
(Williams and Laqueur 1965). Moreover, MAM was described as a developmental
neurotoxin in rats when administered during fetal or neonatal periods of CNS development
(Singh 1980). In humans, consumption of cycasin-containing products resulted in liver
damage and was associated with the etiology of the neurological disorder Amyotrophic
Lateral Sclerosis-Parkinson Dementia Complex (ALS-PDC) in people of the Western
Pacific (Ince and Codd 2005; Borenstein et al. 2007).
II: Carcinogenicity
Cycasin was found to be a potent genotoxic carcinogen in rodents, and the duration of
exposure was shown to highly influence the site of tumor development (Hirono 1972). In
cycasin treated rats, the target sites of tumor development w highly dependent on the dose
regimen. In rats, one single high oral doses of cycasin (100 to 500 mg/kg bw) (Hirono et al.
1968; Laqueur 1968; Fukunishi et al. 1971; Uchida and Hirono 1981) or repeated oral
doses (25mg/kg bw for 12 weeks) (Fukunishi et al. 1971) predominantly resulted in tumors
of the kidneys, followed by neoplasms of the liver and colon. In contrast, life long exposure
to lower doses of cycasin (4mg/kg bw via drinking water) primarily induced mammary and
testicular cancer, while tumors of the liver, kidney and intestine only occurred sporadically
(Fukunishi et al. 1971). Cycasin was carcinogenic only after passage through the
gastrointestinal tract (Laqueur 1964), where it was deglucosylated by ß-glucosidases of the
17

Chapter 1: Introduction
gut microflora to release the principal metabolite MAM (Spatz et al. 1967; Matsushima et al.
1979; Choi et al. 1996). Under physiological conditions, MAM spontaneously hydrolyzes to
water, formaldehyde, and the “ultimate carcinogen” methyldiazonium ion (Figure 1.5, C), an
active DNA methylating agent, responsible for N7-methylguanine- and O6-methylguanine-
DNA-alkylations, as observed in vitro (Matsumoto and Higa 1966) and in vivo (Zedeck and
Brown 1977; Sohn et al. 2001) after MAM exposure. However, to date a reliable
determination of the respective adducts in kidneys of MAM-treated rats remains difficult.
Intragastric or intraperitoneal administration of MAM induced similar tumors as observed
with cycasin, although with a 15% higher incidence (Laqueur 1968). Due to the chemical
instability of MAM most studies were performed using synthetic MAM acetate (MAMAc).
MAMAc is highly sensitive to hydrolysis by various blood and organ esterases, and
therefore is deacetylated to MAM almost immediately following administration (Zedeck and
Brown 1977).
Up to now, no case reports of cancer in humans exposed to cycasin or MAM have been
reported. Since further epidemiological studies did not show increased cancer mortality 2 to
7 years after heavy intake of cycad plants or plant products, cycasin and MAM were
classified by the IARC as possibly carcinogenic to humans (group 2B carcinogen).
1.4 Methods to Identify Renal Carcinogens
The vast majority of all kidney cancers are expected to be caused by exogenic factors, like
exposure to industrial or environmental chemicals, pesticides or mycotoxins (McLaughlin
and Lipworth 2000). Identification of potential carcinogens and assessing their risk for
humans is therefore the first step in disease prevention. For decades, methods for the
identification of renal and other carcinogens have been extensively developed, including
the rodent bioassays (see below), animal models for cancer induction at distinct organ sites
(e.g. the Eker rat model of renal cancer, for details see chapter 1.4.3), in vitro methods to
study the effects of carcinogens in cells and organ slice cultures, and mechanistic assays to
study various molecular events such as metabolic activation and detoxification of
carcinogens, DNA damage and repair and mutagenicity.
18

1.4.1 Standard carcinogenicity testing
Chapter 1: Introduction
For almost 40 years, carcinogenicity testing has been used in an attempt to predict the
potential of chemicals and pharmaceuticals to cause cancer in humans. According to
different guidelines in the United States, Japan and Europe, carcinogenicity testing is
required when human exposure to the respective compound is expected in a continuing or
intermittent manner for at least three months (according to the U.S. Food and Drug
Administration (FDA)) or six months (according to Japan’s Guidelines for Toxicity Studies of
Drugs Manual, or to European rules governing medicinal products, respectively). At any
rate, carcinogenicity testing is required when there is concern about the potential of a
chemical known to have a carcinogenic effect (based e.g. on structure activity
relationships).
The standard carcinogenicity testing procedure consists of a battery of genotoxicity tests
involving: 1) a bacterial reverse mutation test (Ames test), 2) an in vitro genotoxicity test
(e.g. in vitro mammalian chromosome aberration test, in vitro mammalian cell gene
mutation test, or unscheduled DNA synthesis test in mammalian cells), and 3) an in vivo
genotoxicity test (e.g. mammalian erythrocyte micronucleus test, mammalian bone marrow
chromosome aberration test or unscheduled DNA synthesis test with mammalian liver cells
in vivo).
To be designated as a genotoxic carcinogen, compounds must have been proven positive
in the Ames test combined with at least one in vitro and one in vivo genotoxicity test. Only
compounds with negative or substantially negative results in these tests are further
evaluated in the rodent lifetime bioassay for their carcinogenic potential.
1.4.2 The lifetime rodent bioassay
To date almost 1500 chemicals have been tested by a standard protocol originally
developed by the National Toxicology Program (NTP). The protocol involves exposing
distinct strains of rats (Sprague Dawley or Wistar rats) and mice (B6C3F1) of both sexes to
the respective compound for a period of 104 weeks. Typically 50 animals per sex and dose
group and 4 doses, i.e. 0 (control), the maximum tolerated dose (MTD), MTD/2 and MTD/4
are used The MTD of a test compound is generally determined from a preceding 90-day
study using the route and method of administration that will be used in the lifetime
bioassay. During the two year bioassay, animals of all groups are dosed for the indicated
19

Chapter 1: Introduction
time and subsequently sacrificed for a post-mortem evaluation of tumor incidences and
pathological changes in 24 target organs (OECD 1981; NTP 1992).
Utilizing the rodent bioassay for identifying potential cancer hazards for humans is generally
based on two assumptions: a) that high dose effects can be extrapolated to lower doses
and b) that an interspecies extrapolation between animals and humans is possible (Ward
2007). The latter assumption may be reasonable at least for genotoxic compounds that
tend to be carcinogenic across species, in both sexes and at all dose levels (e.g. aflatoxin
B1 or vinyl chloride). In contrast, non-genotoxic carcinogens often do not induce adverse
effects if dosed below a certain threshold (see 1.2.2) and may act via species-specific
mechanisms that have no relevance for humans. Since current standard test procedures
are based on high-dose regimens to warrant a potential detection of carcinogenic
properties of a compound, an overestimation of the carcinogenic potential of a testsubstance
is possible.
The long duration of the rodent bioassay together with the high number of animals leads to
enormous costs. Especially for drug development, low specificity of the standard test
battery is a major drawback, and promising drug candidates may be taken out at late
stages of the developmental process when tested “false positive”. In case of xenobiotica,
positive carcinogenicity testing determines the intensity of regulatory management and
restriction of marketing.
To improve in vivo carcinogenicity testing without compromising human safety, current
efforts try to augment the depth of studies by introducing more mechanistic data. Moreover,
by adopting the directive on the protection of experimental animals in 1986, the protection
and welfare of animals has become a European value. The European Union and its
Member States are obliged to ensure that the number of experimental animals, their
possible pain, suffering, distress or lasting harm as a consequence of procedures being
conducted upon them, shall be kept to an absolute minimum. The directives thus can be
summarized as the “3R- principle”, to reduce, replace and refine animal experiments.
Recently, international governmental organizations and industry partners agreed upon the
new International Conference on Harmonization (ICH) guideline “Testing for
Carcinogenicity of Pharmaceuticals” (ICH 1997). This new guidance allows the use of only
one rodent species (preferably the rat) and the replacement of the second species by newly
developed models like the newborn mouse assay or one of various transgenic mouse
models (e.g. the p53+/- mouse). The alternative usage of genetically engineered models
might also provide additional mechanistic information not readily available from the
20

Chapter 1: Introduction
conventional long-term assay. In addition, the ‘International Agency for Research on
Cancer’ working group has recommended the use of preneoplastic lesions as early
indicators for carcinogenic activity (Williams 1999).
Other promising model systems under development include non-mammalian species, in
vitro cell systems, computer-based predictive toxicology models, or microarray-based
toxicogenomics (described in chapter 1.6.). However, to allow reliable dose- and speciesextrapolation
through the use of these systems requires a much more in-depth
understanding of mechanistic processes involved in the onset and progression of
chemically induced carcinogenesis
1.4.3 The Eker Rat Model of Renal Carcinogenesis
Eker rats are a rodent model of hereditary kidney cancer. Their hereditary tumors resemble
chemically induced tumors in other rat strains, as well as human renal adenomas and
carcinomas. Thus, Eker rats were applied to study the etiology and mechanisms underlying
kidney cancer. Their genetic predisposition is caused by a heterozygous insertion of a
retroviral element into the tuberous sclerosis 2 (TSC2) tumor suppressor gene (Yeung et al.
1994; Hino et al. 1995). Under physiological conditions, TSC2 encodes a protein called
tuberin that binds to the TSC1 gene product hamartin to form a complex which acts as a
GTPase-activating protein (GAP), thereby preventing Rheb-GTP-dependent stimulation of
the PI3K-Akt-Tsc1/2-Rheb-mTor pathway. Consequently, TSC2 and TSC1 are key
mediators of growth factors or various nutrients to regulate cell growth, proliferation,
migration and differentiation (Mak and Yeung 2004; Jozwiak 2006; Wullschleger et al.
2006; Hanna et al. 2008).
The inheritance of the TSC2 mutation follows Mendelian genetics. While a homozygous
loss of the TSC2 gene causes embryonic lethality, the heterozygous offspring is
predisposed to the spontaneous development of multiple and often bilateral RCC with a
100% incidence by one year of age (Everitt et al. 1995). Loss of heterozygosity (LOH) was
only seen in 60% of the renal tumors in Eker rats, suggesting that a second genetic hit
within the TSC2 gene is not the exclusive rate-limiting step for the development of renal cell
carcinomas in this strain (Yeung, 1995). Rather, alternative pathogenic mechanisms such
as haploinsufficiency seem possible.
Additional studies have demonstrated that Eker rats are highly susceptible towards
genotoxic and non-genotoxic renal carcinogens, which makes them a useful model for the
21

Chapter 1: Introduction
early detection of renal carcinogens. Eker rats treated with a single dose of the DNA
alkylating dimethylnitrosamine (DMN) had a 70-fold higher average number of tumors per
animal, compared to DMN-treated wild type rats (Walker, 1992). Furthermore,
transplacental administration of N-ethyl-nitrosamine (ENU) resulted in the early occurrence
of gross RCC after 8 weeks of age (Hino et al. 1993). No increased incidence but an
advanced progression of preneoplastic lesion was observed in Eker rats that were
subchronically treated with the tumor promoter sodium barbital (Wolf et al. 1998). In
contrast, genotoxic non-renal carcinogens had no consistent effect on total numbers or
incidence of preneoplastic and neoplastic lesions in the Eker rat kidney (Morton et al.
2002). From these studies, it was concluded that Eker rats represent a useful tool to identify
renal carcinogens and to study the underlying mechanisms.
1.5 Toxicogenomics
Microarrays have been used as a powerful and widespread tool for the simultaneous
measurement of gene expression from thousands of genes within a target tissue. Soon
after the first microarrays were applied to analyze molecular events that underlie chemically
induced toxicity (toxicogenomics), toxicologists became fascinated by the multitude of
possibilities for safety assessment: Gene expression data may be used to identify
mechanistic pathways involved in the dose-, tissue-, inter- and intra-specific heterogeneity
of compound-induced toxicity. In addition, toxicogenomics can be used to identify and
characterize novel biomarkers which might serve as early predictors for adverse effects of
test compounds in short term in vivo or in vitro experiments (Luhe et al. 2005).
1.5.1 Principles of the Microarray Technology
To date various types of microarrays are commercially available, such as cDNA arrays or
oligonucleotide arrays. Currently Affymetrix GeneChips® are the most popular commercial
arrays, and were also used for this thesis.
Affymetrix GeneChips® consist of up to 1.3 million 25-mer oligonucleotide probes attached
to a quartz surface, each with a gene-specific DNA sequence able to bind complementary
target RNA of a test sample. Probe-target hybridizations can be quantified to determine the
22

Chapter 1: Introduction
relative abundance of an expressed gene in a test sample. The main feature of Affymetrix
chips is that each gene is represented by an ensemble of probes (probe set) mapping to
eleven different regions of the gene (Figure 1.6, A). Each of the eleven oligonucleotides is
furthermore represented by a set of perfect match probes (PM) and identical mismatched
probes (MM), with the exception of a single base difference in a central position. The
mismatch probes serve as controls to determine the specificity of target-probe
hybridizations and therefore to receive a higher reliability of gene expression data. As an
example, Affymerix Rat Genome RAE_230_2 GeneChips® used for this thesis cover the
entire genome of the rat by containing 30.199 probe sets encoding known annotated genes
and unknown open reading frames (expressed sequence tags (EST)).
Figure 1.6: (A) Composition of an Affymetrix chip. MM: mismatch oligonucleotide; PM: perfect
match oligonucleotide. (B) Overview on Affymetrix chip hybridization. (C) Staining of
the DNA-cRNA hybrides using streptavidin-phycoerythrin. Modified from Affymetrix
Expression Analysis: Technical manual for eukaryotic sample and array processing.
23

Chapter 1: Introduction
For gene expression analysis using Affymetrix chips, RNA is isolated from different test
samples for subsequent cDNA preparation using a T7-Oligo(dT) promoter primer (Figure
1.6, B). Following RNase H-mediated second-strand cDNA synthesis, the double-stranded
cDNA serves as a template for in vitro transcription (IVT). The IVT reaction is carried out in
the presence of T7 RNA polymerase and a mix of biotinylated nucleotides for
complementary RNA (cRNA) amplification and biotin labeling. The biotinylated cRNA
targets are then cleaned up, fragmented, and hybridized onto an Affymetrix GeneChip
expression array (Figure 1.6, B). Biotinylated probe-target hybridizations are visualized by
staining the arrays with a streptavidin/phycoerythrin solution and the addition of a
biotinylated anti-streptavidin antibody, followed by a second streptavidin/phycoerythrin
staining step (Figure 1.6, C). Hybridization and staining of Affymetrix arrays are performed
with specialized robots, which increase both reproducibility and throughput.
Fluorescence signals can be scanned and raw data image files (DAT) can be converted
into CEL-files using Affymetrix Microarray Suite (MAS) 5.0 algorithm. In CEL files, the scan
data from 36 pixels per PM/ MM probe set are averaged, background, gradients and
distortions are corrected. The fluorescent intensities of the eleven PM/MM probe pairs per
gene are then condensed to one intensity value per probe set, associated with a statistical
detection of a p-value calculated from the intensity differences of the PM and corresponding
MM oligonucleotides. This p-value indicates how reliably a transcript is detected and
transcripts below a distinct quality setting p-value can be excluded from further statistical
analysis. Different statistical tests can then be used to elucidate significant gene
deregulations between two or more test samples.
1.5.2 Microarrays- a Novel Tool to Study Carcinogenesis
I: Diagnostic approach
Microarrays have been used to study renal carcinogenesis and a number of publications
have focused on the molecular classification of the different subtypes of kidney cancers in
humans (Takahashi et al. 2006; Furge et al. 2007; Young et al. 2008). These studies not
only revealed specific gene expression profiles for different histopathological subtypes, but
also offered a more detailed insight into the underlying pathways. In addition, a number of
studies have suggested the use of microarrays as promising tool for refining the diagnosis
and staging of RCC, as well as for highlighting potential therapeutic targets (Tan et al.
2004).
24

II: Mechanistic Approach
Chapter 1: Introduction
Thus far, only a relatively small number of studies employing toxicogenomics to study
mechanisms underlying renal carcinogenesis in rats were performed. One study was
designed to identify differential gene expression in kidneys of Tsc2 heterozygous mutant
Eker rats compared to wild-type rats, and thereby to elucidate whether those differences
may be involved in tumorigenesis (Sen et al. 2004). The authors found only 3.2% of 4395
evaluated genes significantly deregulated, which mainly belonged to the functional
categories of cell cycle regulation, cell proliferation, cell adhesion and endocytosis. Notably,
many of these genes appear to be directly or indirectly regulated by the PI3K/Akt pathway,
thereby pointing towards mechanistic pathways that may be associated with the enhanced
susceptibility of the Tsc2 mutant Eker rats to develop kidney tumors. Prior to this thesis,
gene expression changes in Eker and wild-type rats were not addressed after carcinogen
treatment. It was therefore unknown whether and how genotoxic and non-genotoxic
carcinogens would influence the TSC2 pathway.
Other mechanistic studies used microarrays for the identification of deregulated genes and
pathways subsequent to treatment with known genotoxic and non-genotoxic nephrocarcinogens.
For example, Marin-Kuan and colleagues applied microarray technology for
the analysis of gene expression changes in kidney samples from F344 rats that were orally
dosed with 300 µg/kg bw OTA during a two year carcinogenicity study. The authors
demonstrated a prominent down regulation of genes involved in antioxidant defense, which
was assumed to result in an increase of reactive oxygen species, leading to oxidative DNA
damage and tumor initiation (Marin-Kuan et al. 2006). In another study, Chen et al. (Chen
et al. 2006) demonstrated that gene expression profiling can reveal differential effects of AA
exposure on the kidneys and liver of rats, i.e. significant alterations of genes previously
associated with biotransformation and carcinogenesis, apoptosis and immune response
mainly in kidney, but not in liver, Therefore, in the respective study gene expression
profiling served to explain underlying mechanisms for the tissue-specific toxicity and
carcinogenicity of AA.
These and a number of other studies have demonstrated that microarrays facilitate the
interpretation of a toxic or carcinogenic mechanism of action. The use of mechanistic data
in preclinical trials would not only allow to assess differences between acute and chronic
toxicity, but also to extrapolate toxic effects between different species. Moreover,
microarrays were previously used to study gene expression changes in F344 rats
subsequent to treatment with already known non-effective doses and carcinogenic doses of
potassium bromate. The dramatic increase in global gene expression changes in response
25

Chapter 1: Introduction
to the carcinogenic dose and compared to non-carcinogenic doses suggests that
microarrays are indeed useful tools to determine thresholds and safety levels for test
compounds (Delker et al. 2006).
III: Predictive approach
Histopathology and clinical chemistry subsequent to the two year rodent bioassay are still
benchmarks for evaluating the toxic and carcinogenic potential of test compounds.
However, since the kidneys can function relatively normal with low grade damage, altered
blood or urine parameters used for clinical chemistry (e.g. blood urea, nitrogen or serum
creatinine) are not readily observed until a significant portion of the kidney is damaged
(Duarte and Preuss 1993). Similarly, histopathologic examinations of organ sections require
that toxic lesions (e.g. pre-neoplastic and neoplastic lesions) have become manifested for
microscopic detection. Early or compound-related alterations at a molecular level (e.g. DNA
damage response) thus remain unobserved with these techniques. Microarrays therefore
appear promising for a sensitive prediction of toxicity and carcinogenicity.
In general, predictive toxicogenomics require databases with expression profiles derived
from standardized in vivo or in vitro studies subsequent to treatment with well characterized
pharmaceuticals and chemicals, including time-courses, doses, and clinical pathology
information. These “training profiles” can then be used to extract sets of marker genes to
classify unknown test compounds. Studies employing microarrays for predictions have
been mainly reported for hepatotoxins to extract marker genes representing distinct classes
of hepatotoxicity, e.g. liver necrosis or steatosis (Hamadeh et al. 2002; Steiner et al. 2004;
Raghavan et al. 2005). These studies have demonstrated that toxicogenomics can be used
to determine toxicologically relevant changes at very early time points (Steiner et al. 2004)
and at very low doses (Hamadeh et al. 2002). To date, only a few in vivo and in vitro
studies have utilized microarrays to identify early biomarkers that predict chronic endpoints
such as cancer, and that may refine the lifetime rodent bioassay (van Delft et al. 2004;
Tsujimura et al. 2006; Fielden et al. 2007). Most important for this thesis, Ellinger-
Ziegelbauer and colleagues demonstrated that hepatic gene expression profiles of rats
treated for up to 14 days with known genotoxic and non-genotoxic carcinogens allow to
distinguish both groups of carcinogens (Ellinger-Ziegelbauer et al. 2005). However, none of
the available studies dealt with renal cancer.
26

1.5.3 Microarrays- Current Limitations and Future Directions
Chapter 1: Introduction
After several years of research, toxicogenomics came into the focus of regulatory agencies
and may influence the future decision making on drug safety. Currently, the U.S. Food and
Drug Administration is developing a framework to review gene expression data from
classical toxicological studies (Leighton et al. 2006). However, more research is needed to
adequately assess the potential of microarrays for carcinogenicity testing and for the
analysis of mechanisms underlying carcinogenesis.
Most of the recent studies that analyzed gene expression changes to elucidate mechanism
involved in cancer used whole tumor- or biopsy samples as a source for RNA isolation (Ellis
et al. 2002; Li et al. 2002; Goley et al. 2004; Marin-Kuan et al. 2006; Jones and Pantuck
2008). These samples often contain different amounts of non-cancerous cells, e.g. stromal
or endothelial cells or infiltrating inflammatory cells, thereby complicating an accurate
delineation of gene expression changes in non-tumor versus tumor samples. Nevertheless,
the characteristics of a gross tumor may be influenced by the interaction with these
different, non-cancerous cell types that may contribute to a microenvironment that is
essential for cancer growth, invasion and metastatic progression. Thus it may be relevant
for some, however not for all purposes, to take these cell types under investigation.
In addition, gene expression profiling seems challenging when analyzing toxic effects in
complex target organs. For instance, the kidney is composed of various tubular segments
and cell types, which all have highly specific physiological functions and different
susceptibility towards xenobiotica. Distinct segment-specific nephrotoxic effects may
therefore not be readily detectable by gene expression profiling when “diluted” by other,
unaffected nephron parts. Separation of the kidney into its basal segments (cortex, medulla
and papilla) would serve to highly improve the outcome of gene expression experiments.
A major improvement was the development of laser capture microdissection (Emmert-Buck
et al. 1996; Schutze et al. 1998), which allows the isolation of single cells from a tissue
section, and to collect pure populations of morphologically similar cells for subsequent
molecular analysis. Gene expression profiling from isolated, early preneoplastic lesions
could for instance allow a direct identification of gene expression changes underlying
earliest morphologic pathologies. However, previous to this thesis, gene expression
profiling had not been used for the analysis of microdissected pre-neoplastic lesions.
27

Chapter 2: Work Hypotheses & Experimental Design
Lifetime rodent bioassays play a central role in evaluating the carcinogenicity of chemicals,
yet are critically viewed especially with regard to their long duration, high dose regimens,
high animal numbers and financial costs. By detecting end-stage adenomas and
carcinomas current protocols enable the identification of carcinogens which can act on any
stage of tumorigenesis (tumor initiation, promotion and progression). However, they do not
allow drawing detailed conclusions on the underlying molecular mechanisms and their
relevance for human risk assessment. Accordingly, interest in improving carcinogenicity
testing by developing mechanistic and predictive short-term in vivo studies has grown. One
promising approach might be the use of microarrays to analyze compound-induced gene
expression changes in different target organs after short-term exposure. However, at the
beginning of this thesis:
1. No studies had been performed that elucidated the applicability of short-term in vivo
assays in predicting the carcinogenic potential of genotoxic and non-genotoxic
renal carcinogens.
2. The identity of deregulated genes and pathways involved in the early onset and
progression of carcinogen-induced and hereditary renal preneoplastic lesions was
largely unknown.
3. One principal biasing factor for a reliable human risk assessment from rodent
bioassays, i.e. the impact of high-fat diet and adiposity on pathways involved in
renal cancer, was never addressed in detail.
2.1 Part I
The first aim of this thesis was to investigate the hypothesis that short-term (14 days) in
vivo assays, using microarrays as the detection system, can be used as a tool to evaluate
the renal carcinogenic potential of test compounds. Specifically, the most important
prerequisites for short-term in vivo assays to allow for such a sensitive and specific
detection of renal carcinogens should be examined, as specified in the below subhypotheses:
28

Chapter 2: Work Hypotheses & Experimental Design
1. Short-term treatment with known renal carcinogens will result in detectable
compound-specific gene expression changes in kidney cortex homogenates of rats
(Sensitivity).
2. Gene expression profiles will serve to distinguish a genotoxic from a non-genotoxic
mode of action of respective carcinogens (Specificity).
3. Exposure to carcinogens with early genotoxic or non-genotoxic expression changes
in short-tem assays will also result in a carcinogen-specific onset of kidney tumors
after subchronic or chronic exposure (Predictivity).
2.1.1 Experimental setup
Short-term exposure: male and female TSC2-mutant Eker rats or wild-type rats were
gavaged daily for 1, 3, 7 and 14 days with the genotoxic carcinogens AA or MAMAc, the
non-genotoxic carcinogen OTA, or vehicle. Subsequent to exposure, kidneys were taken
for the analysis and comparison of the following parameters:
• Gene expression profiles derived from the kidney cortex of male Eker and wild-type
rats to detect compound-induced expression changes in both a sensitive and a
conventional rat strain.
• Non-neoplastic and neoplastic renal histopathology in all dose groups to elucidate
specific adverse effects induced by the respective compounds in both rat strains.
• Cell proliferation via immunohistochemical PCNA staining to detect early mitogenic
effects in all dose groups.
• O6-methylguanine DNA adducts levels in 1, 7 and 14 days MAMAc-treated male and
female Eker rats, respectively, indicative for the mutagenic potential of MAMAc.
Subchronic and chronic exposure: Male and female Eker rats were gavaged 5 days per
week for 3 or 6 months, respectively, with AA, MAMAc, OTA or vehicle. Subsequently,
kidneys were harvested and analyzed for:
• Sex- and compound-specific differences in non-neoplastic and neoplastic
histopathology (type, incidence and total number of lesions).
• Sex- and compound-specific differences in cell proliferation, analyzed by
immunohistochemical BrdU staining.
29

2.2 Part II
Chapter 2: Work Hypotheses & Experimental Design
The second hypothesis of this thesis was, that gene expression profiling from isolated
preneoplastic lesions allows a direct identification of gene expression deregulations
underlying earliest morphologic pathologies of renal cancer. Specifically the following subhypothesis
should be examined:
1. Different stages of preneoplastic lesions can be distinguished by their gene
expression profiles, therefore allowing the study of mechanisms underlying
preneoplastic lesion progression
2. Renal carcinogens differentially affect gene expression preneoplastic lesions,
based on their compound specific mode of action (genotoxic vs. non-genotoxic)
3. The comparison of gene expression profiles from short-term treated rats with
microdissected healthy tissue and preneoplastic lesions will serve to identify novel
mechanistic and predictive markers involved in chemical induced renal
carcinogenesis, applicable in short-term assays.
2.2.1 Experimental setup:
Protocol establishment: Before addressing the specific hypotheses, a protocol had to be
established that allows the reliable and reproducible analysis of laser microdissected renal
preneoplastic lesions by using Affymetrix Genechips. Specifically, the following conditions
were optimized:
• Effects of different histopathological staining techniques in combination with different
sample processing techniques on RNA quantity and quality.
• RNA amplification of lowest amounts of RNA from dissected lesions to allow reliable
gene expression profiling.
Microdissection and gene expression analysis: In the next step, the optimized protocol was
adapted to perform large scale gene expression analyses from laser microdissected
lesions:
• Laser microdissection of different stages of preneoplastic lesions and healthy tubules
from cryosectioned kidneys of male Eker rats treated with AA, OTA or vehicle.
30

Chapter 2: Work Hypotheses & Experimental Design
• RNA isolation and microarray analysis of the microdissected tissue and comparison
of gene expression profiles between different stages of preneoplastic lesions and
healthy tissue.
• Verification of deregulated genes, involved in the initiation and progression of
preneoplastic lesions at the protein level via immunohistochemistry.
2.3 Part III
In the third part of this thesis it was hypothesized that chronic high-fat diet causes early
stages of renal cancer in rats via mechanisms similar to those observed following exposure
to renal carcinogens. The following sub-hypotheses were addressed:
1. Early stages of renal cancer are a direct effect of dietary lipids, and largely
independent from the degree of body adiposity.
2. Exposure to chronic high fat diet results in the activation the mTOR pathway, a
central component of the nutrient-hormonal signaling network and known mediator
of renal carcinogenesis.
2.3.1 Experimental setup
From a large pool of male Wistar rats fed a customized high-fat diet for 11 months, 2
subgroups of diet-induced obesity sensitive and diet-induced obesity resistant rats were
selected, and compared to each other and with low-fat (standard) diet controls for the
following parameters:
• Life history traits (body weight, local fat depots) and plasma parameters (blood
glucose, triglycerides, insulin, leptin, IL-1ß, MCP-1 and PAI-I)
• Possible accumulation of renal levels of fatty acid binding protein α2u-globulin
• Renal histopathology
• Renal cell proliferation
• Immunodetection of hyperphosphorylated S6-ribosomal protein indicative for the
activation of the mTOR pathway, a central component of the nutrient-hormonal
signaling network and known mediator of renal carcinogenesis
31

Chapter 2: Work Hypotheses & Experimental Design
2.4 Schematic Overview on the Experimental Design
Figure 2.1: Overview on the experimental design
32

Chapter 3: Manuscript I
Carcinogen Specific Gene Expression Profiles in Short-Term
Treated Eker and Wild Type Rats Indicative for Pathways
Involved in Renal Tumorigenesis
Kerstin Stemmer 1 , Heidrun Ellinger-Ziegelbauer 2 , Hans-J. Ahr 2 and Daniel R. Dietrich 1*
1 Human and Environmental Toxicology, University of Konstanz, Konstanz, Germany
2 Molecular and Special Toxicology, Bayer Healthcare AG, Wuppertal, Germany
* Corresponding author: Daniel R. Dietrich: daniel.dietrich@uni-konstanz.de
Published in Cancer Research (2007) May 1;67(9):4052-68
3.1 Abstract
Eker rat heterozygous for a dominant germline mutation in the tuberous sclerosis 2 (Tsc2)
tumor suppressor gene, were used as a model to study renal carcinogenesis. Eker and
corresponding wild type rats were exposed to genotoxic aristolochic acid (AA) or nongenotoxic
ochratoxin A (OTA) in order to elucidate early carcinogen specific gene
expression changes and to test whether Eker rats are more sensitive for carcinogen
induced changes in gene expression. Male Eker and wild type rats were gavaged daily with
AA (10mg/kg BW) or OTA (210µg/kg BW). After 1, 3, 7 and 14 days of exposure, renal
histopathology, tubular cell proliferation and Affymetrix gene expression profiles from renal
cortex/outer medulla were analyzed. AA-treated Eker and wild type rats were qualitatively
comparable in all parameters assessed, suggesting a Tsc2-independent mechanism of
action. OTA treatment resulted in slightly increased cortical pathology and significantly
elevated cell proliferation in both strains, although Eker rats were more sensitive.
Deregulated genes involved in PI3K-AKT-Tsc2-mTor signalling, amongst other important
genes prominent in tumorigenesis, in conjunction with the enhanced cell proliferation and
presence of preneoplastic lesions suggested involvement of Tsc2 in OTA- mediated toxicity
33

Chapter 3: Manuscript I
and carcinogenicity, especially as deregulation of genes involved in this pathway was more
prominent in the Tsc2 mutant Eker rat.
3.2 Introduction
Eker rats, heterozygous for a loss-of-function mutation in the tuberous sclerosis 2 (Tsc2)
tumor suppressor gene, appear ideal models to study the aetiology of renal carcinogenesis
(Yeung et al. 1994; Hino et al. 1995). Heredity of the Tsc2 mutation follows Mendelian
genetics (Yeung et al. 1994; Kobayashi et al. 1995) and heterozygous progeny are
predisposed to spontaneous development of multiple bilateral renal neoplasms originating
from the proximal tubular epithelium with complete penetrance by one year of age (Everitt
et al. 1995). Approximately 60% of the spontaneous renal tumors in Eker rats also exhibit a
functional inactivation of the second Tsc2 allele, suggesting, in accordance with Knudson’s
two-hit hypothesis that a second somatic mutation might be the rate-limiting step for the
development of renal cell carcinomas (RCC) in Eker rats (Yeung et al. 1995). Eker rats
have been employed to elucidate the mechanism of renal carcinogens, primarily using
histopathological and statistical analyses of the number, multiplicity and progression of
renal lesions (Walker et al. 1992; Wolf et al. 2000). Accordingly, treatment of Eker rats with
dimethylnitrosamine resulted in a 70-fold increase in the induction of renal adenomas and
carcinomas, when compared to wild type rats (Walker et al. 1992). No increased lesion
incidence, albeit an advanced lesion progression was observed in Eker rats, subchronically
treated with the tumor promoter sodium barbital (Wolf et al. 2000). Although the latter data
highlight that Eker rats are sensitive to genotoxic and non-genotoxic compounds, the
involvement of Tsc2 protein (tuberin) in renal carcinogenesis remains to be established.
Several studies suggest that functional Tsc2 promotes the GTP-hydrolysis of the Ras
homologe Rheb, thereby acting as a negative regulator of the PI3K-Akt-Tsc1/2-Rheb-mTor
pathway. Consequently, Tsc2 is suspected to play a central role in mediating growth factor,
nutrient and energy sensing to regulate cell growth, proliferation, migration and
differentiation (Mak and Yeung 2004).
The objective of this study was to elucidate whether short-term exposure of Eker and wild
type rats to a non-genotoxic and a genotoxic renal carcinogen would result in compound
specific changes in renal non-neoplastic and preneoplastic pathology and cell proliferation
rates. Subsequently the hypothesis was investigated, whether compound specific changes
34

Chapter 3: Manuscript I
in histopathology and cell proliferation can be associated with respective changes in gene
expression and whether Eker and wild type rats respond differently. This should allow
identification of deregulated genes involved in known and novel pathways possibly
mediating carcinogen-induced renal tumorigenesis. Accordingly, Eker and wild type rats
were treated with daily doses of the genotoxic and the non-genotoxic renal carcinogen
aristolochic acid (AA) and ochratoxin A (OTA), respectively, for which renal tumor induction
in long-term in vivo studies was previously demonstrated (Mengs et al. 1982; Boorman et
al. 1992).
Indeed, intragastric administration of 10mg AA /kg BW/day (representing a mixture of
structurally related nitrophenanthrene carboxylic acids (mostly AAI and AAII)) to rats over
three months was demonstrated to induce tumors in the forestomach, kidney and the
urinary bladder (Mengs et al. 1982). DNA reactivity of AA was confirmed in that the most
frequent and persistent dAdenin- AAI adduct could lead to mutation and activation of the Hras
oncogene in the forestomach but not in kidneys of rats (Schmeiser et al. 1991; Cheng
et al. 2006) or to p53-mutations in urothelial tumors of humans (Lord et al. 2004). Despite
the lack of H-ras mutations, higher levels of AA adducts were found in renal tissues than in
the forestomach of orally treated Wistar rats (5mg AA/kg BW/day) after only one week of
exposure (Dong et al. 2006), suggesting an H-ras independent pathway of renal tumor
induction. The genotoxic properties of AA are explained by the metabolic activation of AA
by several phase I enzymes to a DNA-reactive aristolactam-nitriumion (Pfau et al. 1990;
Arlt et al. 2002; Stiborova et al. 2003). Similarly, the mycotoxin OTA increased the
incidence of renal adenoma and carcinoma in rats, when exposed for up to two years to
dietary OTA (Mantle et al. 2005) or 210µg OTA /kg BW/day via gavage (Boorman et al.
1992). However, as OTA has not been convincingly demonstrated to covalently interact
with DNA, a non-genotoxic mechanism of action is assumed (Kamp et al. 2005; Mally et al.
2005).
The comparison of cell proliferation, pathology and expression profiles of AA- and OTAtreated
Eker and wild type rats should allow for a more in-depth understanding of the
involvement of the Tsc2-mTor pathway as well as of other early gene expression changes
in the etiology of carcinogen induced renal tumors.
35

3.3 Material and Methods
3.3.1 Compounds
Chapter 3: Manuscript I
Ochratoxin A (>98% purity, benzene free) was kindly provided by Dr. M.E. Stack, US FDA,
Washington DC. Aristolochic acid sodium salt mixture (AA I: 41% and AA II: 56%) was
purchased from Sigma Aldrich, Germany.
3.3.2 Animals
Six to ten week old, genotyped heterozygous Tsc2 mutant Eker rats (Tsc2+/-, Long Evans)
were purchased from the MD Anderson Cancer Center, Smithville, Texas, USA and
maintained at the University of Konstanz animal research facility under standard conditions
with food and water ad libitum. Male rats were randomly assigned to dose groups (three
animals per compound (or vehicle) and time-point) and allowed to acclimatize to laboratory
conditions for 4 weeks. Two weeks prior to exposure, rats were handled daily to reduce
non-compound related stress during exposure.
Heterozygous Eker rats were bred and wild type (Tsc2+/+) genotypes of the progeny were
determined via PCR (Rennebeck et al. 1998). Two weeks prior to exposure, 8-9 week old
genotyped male wild type rats, were randomly allocated to dose groups and accustomed to
daily handling (see above).
3.3.3 Animal treatment and sample collection
Eker and wild type rats were gavaged daily with OTA (210µg/ kg BW) or AA (10mg/ kg
BW), dissolved in 0,1M sodium bicarbonate. Time-matched vehicle controls were gavaged
with 0,1M sodium bicarbonate. Following 1, 3, 7, and 14 days of treatment, Narcoren®
(pentobarbital) anesthetized rats were sacrificed by exsanguination subsequent to
retrograde perfusion with PBS. Left kidneys were collected, cross-sectioned into 5mm
slices and stored in RNAlater (Qiagen, Germany) or in PBS buffered histology fixative
buffer, containing 2% paraformaldehyde and 1% glutaraldehyde for subsequent paraffin
embedding and sectioning.
36

3.3.4 Histopathology
Chapter 3: Manuscript I
For histopathological examinations, H&E stained sections were randomized and
pathological analysis was carried out by light microscopy at 40-400-fold magnification. Nonneoplastic
changes were classified as none (0), mild (1), moderate (2), strong (3), and
severe (4), including intermediate classes (e.g. 0.5, 1.5 etc.), while total numbers of
preneoplastic and neoplastic lesions were counted.
3.3.5 Immunohistochemistry
Cell proliferation was evaluated by immunohistochemical staining for proliferating cell
nuclear antigen (PCNA) using monoclonal primary anti-PCNA antibody (PC-10; DAKO,
Germany) in paraffin-embedded kidney sections.
Sections were deparaffinized, rehydrated in a decreasing alcohol series and washed with
PBS. For antigen retrieval, slides were placed in 0,1M sodium citrate buffer (pH 6.0),
microwaved to boiling point 3-times and cooled to room temperature for 20min. Sections
were denatured with 4 N HCl (20min at 37°C), washed with PBS (2x 5min) and non-specific
protein binding blocked by preincubation with casein solution (Power BlockTM, BioGenex,
USA) for 20 minutes. Sections were incubated with PC-10 primary antibody (diluted 1:50 in
Power BlockTM) at 4°C for 16 hours. Antigen- antiserum complexes were visualised using
the Super SensitiveTM alkaline phosphatase labelled, biotin streptavidine amplified
detection system and Fast Red as chromogen according to the manufacturer’s instructions
(BioGenex, USA).
Cell proliferation was quantified on PCNA stained sections, randomized across all
treatment and control groups. Twenty microscopic fields (10x ocular, 40x objective) were
randomly chosen in the outer cortex and inner cortex/outer medulla. All tubule cell nuclei
were counted, concurrently differentiating between negative and positive PCNA staining.
Nuclear labeling indices for PCNA (LI%) (PCNA positive nuclei/total number of nuclei
counted) were determined based on a minimum of at least 2.000 nuclei evaluated.
3.3.6 RNA isolation and expression profiling
RNA isolation from RNAlater fixed kidneys was performed as described previously
(Ellinger-Ziegelbauer et al. 2005). Starting with 5µg of total RNA with a 28S/18S rRNA peak
37

Chapter 3: Manuscript I
ratio >1.7, biotin-labeled cRNA was prepared and subsequently hybridized on Affymetrix
Rat Genome RAE230A arrays according to the manufacturer’s instructions (Affymetrix,
USA; GeneChip® Expression Analysis 701194 Rev.1). This specific array contains 15.866
probe sets, corresponding to approx. 5399 annotated rat genes and 10467 expressedsequence
tags (ESTs).
3.3.7 Microarray data processing and statistical analysis
Microarray quality control was performed as described previously (Ellinger-Ziegelbauer et
al. 2005) and gene expression data were submitted to the GEO repository
(http://www.ncbi.nlm.nih.gov/projects/geo; accession number: GSE5923). Expressionist
Analyst software (Genedata AG, Switzerland) was used for statistical analysis. Significantly
deregulated genes per compound were selected based on the factors treatment and time
as both, single and interaction effects, in a 2-way ANOVA with a p-value cut-off of 0.005,
combined with a 1.7-fold deregulation threshold for at least one time point. Significantly
deregulated genes were divided into gene groups with distinct expression profiles over the
time-course using self-organizing map (SOM) analysis. SOM analysis also allowed
deselection of genes showing inconsistent expression between the controls at different time
points. Using the adjusted datasets, gene expression ratios of individual genes were
calculated by dividing the respective expression values of single treated replicate samples
by the mean expression value of all corresponding time-matched control samples.
Heatmaps were used to graphically display the relative expression data, after onedimensional
clustering of the genes (for the validation of microarray data, see
supplementary information).
3.3.8 Functional analysis of microarray data
For functional analysis each significantly deregulated gene was characterized according to
the biochemical role of its encoded protein, whenever sufficient information from
databases, e.g. NetAffx from Affymetrix (update from August 2006), Swissprot, Proteome
and Pubmed was available. The consequence of the direction of deregulation was
interpreted specifically with regard to possible downstream pathophysiological effects. This
allowed distribution of the deregulated genes into toxicological categories (Supplementary
table 3.1) and facilitated the comparison of specific pathophysiological pathways, involved
38

Chapter 3: Manuscript I
in the response of Eker and wildy type rats to AA and OTA treatment. In addition, the
pathophysiological pathways were compared with major pathways suspected to be
involved in AA- and OTA- induced carcinogenesis (Tables 3.1 and 3.2) and
histopathological changes observed.
3.3.9 Statistical analysis
Statistical analysis of histopathological and cell proliferation changes were carried out using
GraphPad Prism 4® (USA) Software. Statistical significant differences in nuclear labeling
indices (LI %) or total number of lesions in treated and control animals were analyzed by an
unpaired (two tailed) t-test. A statistical significant effect of the treatment- time response
was tested with a 2-Way ANOVA.
3.4 Results
3.4.1 Cell proliferation data
AA treatment resulted in no overt change in cell proliferation rate (Figure 3.1, A and B) in
either strain, despite that occasional AA groups appeared to have a significantly lower
proliferation then the corresponding controls. Conversely, OTA treatment increased the
proliferation rate on day 14 (Figure 3.1, C and D, Figure 3.2, A and B) 3.8- and 3.4-fold
above control in Eker and wild type rats, respectively. Moreover, Eker rats appeared to be
more sensitive to OTA as an increased cell proliferation rate was already observed at day 7
of treatment.
3.4.2 Preneoplastic and neoplastic pathology
While no preneoplastic or neoplastic lesions (Dietrich and Swenberg 1991) were observed
in any of the wild type rat controls, the Eker rat control groups presented with atypical
tubules (AT, Figure 3.2, C), atypical hyperplasia (AH, Figure 3.2, D) and an occasional
adenoma (Supplementary table 3.2). Neither AA nor OTA treatment induced an increase in
preneoplastic or neoplastic lesions in wild type rats. Similarly, AA treatment of Eker rats
39

Chapter 3: Manuscript I
resulted in no significant increase in AT or AH. However, two carcinomas were observed in
the day 14 AA-treated Eker group, and an adenoma in the day one group. In contrast, OTA
treatment of Eker rats resulted in a significant increase of AT on day 14 (Figure 3.1, E).
However, no significant increase in AH or neoplastic lesions were observed.
Figure 3.1: Comparison of PCNA S-Phase labelling indices (LI %) in the renal cortex of AA or
OTA treated Eker and wild type rats (A-D), respectively, at various treatment timepoints.
E: Mean number of atypical tubules (preneoplastic lesion) per animal in
control and OTA treated Eker rats. Data represent the mean + SEM of n=3 animals per
group. Significant differences between treated and time-matched control groups: *p <
0.05; **p < 0.01 and ***p

Chapter 3: Manuscript I
Figure 3.2: Representative PCNA staining patterns of control- (A) and OTA-treated (B) Eker rats.
C: Atypical tubule; D: Atypical hyperplasia; E: karyomegally (arrows) and F: apoptotic
nuclei (arrow) observed in OTA treated rats.
41

3.4.4 Gene expression profiles
Chapter 3: Manuscript I
Oral treatment of Eker and wild type rats with AA and OTA, respectively, led to a significant
deregulation of gene expression already after one day of exposure. Compared to the
respective time-matched controls, the number of significantly deregulated genes increased
with the duration of exposure in both strains. At all time-points compound-treated Eker rats
consistently showed a higher number of significantly deregulated genes compared to their
wild type counterparts (Figure 3.3). Overall, AA treatment led to the significant deregulation
of 111 non-redundant genes in Eker rats compared to 81 genes in wild type rats. However,
the visualization of the expression profiles of the union of the Eker- and wild type- selected
genes revealed a qualitatively comparable profile in AA-treated Eker and wild type rats. In
contrast, treatment with OTA resulted in 375 significantly deregulated, non-redundant
genes in Eker rats compared to 141 genes in wild type rats, with a strikingly different
expression profile of at least half of the genes (Figure 3.3).
Figure 3.3: Heat map of compound-specific unions of genes found significantly deregulated (red:
upregulated; green: downregulated) from the corresponding control in AA or OTA
induced renal gene expression profiles of Eker or wild type rats after 1, 3, 7 or 14 days
of treatment (n=3 per time-point). Color scale (left side): gene expression ratio.
42

3.4.5 Functional analysis of significantly deregulated genes
Chapter 3: Manuscript I
Many of the non-redundant genes, deregulated by AA (Table 3.1) or OTA (Table 3.2)
treatment in Eker and wild type rats, respectively, could be associated with major
pathophysiological processes involved in renal toxicity and regeneration (Supplementary
table 3.1).
3.4.6 Genes deregulated by aristolochic acid
Metabolism and bioactivation: Treatment of Eker and wild type rats with AA led to a
prominent up-regulation of genes encoding phase I or phase II biotransformation enzymes
or drug transporters. Most of the genes were either constantly upregulated over the whole
exposure time-frame or increasingly upregulated with prolonged duration of exposure in
both Eker and wild type rats. In addition to the genes significantly deregulated in both
strains, some genes met the significance criteria only in one or the other strain. Yet the
direction of deregulation was mostly comparable (e.g. GSTM2 or CES3, apparently specific
for Eker or wild type rats, respectively).
DNA damage response (incl. oxidative stress): P53 is inducible by DNA damage and
oxidative stress. The upregulation of several p53 pathway genes, as observed in Eker and
wild type rats, was therefore summarized as DNA damage response (incl. oxidative stress).
Most genes involved in this category showed a time-dependent increase with highest
deregulation values after 14 days of treatment and met the significance criteria in both
strains.
Inhibited cell survival and proliferation: In conjunction with the DNA damage response
described above, downregulation of anti-apoptotic genes and genes involved in DNA
replication, cell cycle progression, as well as the upregulation of pro-apoptotic genes was
observed. These genes demonstrated a comparable time-dependent increase in
expression as the genes representing the DNA damage response (see above), with highest
deregulation values after 14 days of treatment. In contrast to the DNA damage response
genes, many of these genes showed an apparently strain-specific deregulation, yet again
with a qualitatively similar expression pattern for most of them in both strains. An exception
to the latter observation, were genes directly involved in the G2/M transition of the cell
cycle, which were specifically and consistently downregulated in wild type rats.
43

Chapter 3: Manuscript I
Enhanced cell survivial/cell proliferation: Only three genes were assigned to this
category. The Tsc1 (tuberous sclerosis 1) tumor suppressor gene, which is known to be
associated with Tsc2 (Mak and Yeung 2004), was significantly downregulated in Eker but
not wild type rat. Enhanced cell survival and proliferation induced by AA was suggested by
the observed upregulation of a positive regulator of cell proliferation (KEG1) and the
downregulation of a proapoptotic gene (WWOX).
44

Chapter 3: Manuscript I
Table 3.1: Categories of genes differentially deregulated by AA in Eker- and wild type rats. For the major toxicological categories the associated genes
are listed together with their Genebank accession number. The main biochemical functions or pathways in which these genes are involved are
indicated in column four. For Eker- and wild type rats, the fold deregulation ratios of genes that were significantly deregulated over all timepoints
according to N-way ANOVA are shown in the last eight columns. Genes meeting the significance criteria are indicated in bold.
Toxicological
category
Metabolism and
Biotransformation
Accession
number
Gene title Biochemical category Fold deregulation (mean of three replicate animals
per time-point)
AI233740 AKR1B8 Aldo-keto reductase 1B8 Biotransformation, Phase I 2.2 3.4 2.5 23.3 1.8 2.0 2.7 2.7
NM_012844 EPHX1 Epoxide hydrolase 1 (microsomal) Biotransformation, Phase I 1.7 1.7 1.5 1.9 1.2 1.3 1.4 1.8
AW142784 CYP4A10 Cytochrome P450 4a10 Biotransformation, Phase I 2.0 1.6 1.6 2.1 1.6 1.8 1.9 1.8
J02679 NQO1 NADPH-Quinone Oxidoreductase Biotransformation, Phase I 2.4 1.9 1.6 3.1 2.0 2.1 1.5 2.0
U27518 UGT2B8 UDP-glucuronosyltransferase 2B8, micros. Biotransformation, Phase II 6.1 4.5 3.3 4.7 3.1 2.5 1.7 1.7
NM_031980 UGT2B12 UDP-glucuronosyltransferase 2B12, micros. Biotransformation, Phase II 2.0 2.1 1.9 2.2 2.2 2.0 2.0 1.9
M31109 UGT2B3 UDP-glucuronosyltransferase 2B3, micros. Biotransformation, Phase II 4.1 4.6 4.5 6.7 2.7 2.0 4.7 3.6
M28241 GSTM1 Glutathione-S-transferase M1 Biotransformation, Phase II 4.2 5.5 5.4 15.8 3.9 3.1 3.6 7.1
NM_031154 GSTM3 Glutathione-S-transferase M3 Biotransformation, Phase II 1.1 2.0 1.6 2.0 1.3 1.3 1.4 2.1
NM_053293 GSTT1 Glutathione-S-transferase T1 Biotransformation, Phase II 1.3 1.6 2.0 2.0 1.3 1.3 1.6 1.8
AA945082 GSTA2 Glutathione-S-transferase A2 Biotransformation, Phase II 4.1 4.5 2.9 3.8 3.9 4.3 4.2 5.0
X02904 GSTP1 Glutathione-S-transferase P1 Biotransformation, Phase II 4.8 5.7 3.9 4.8 4.9 4.9 5.3 6.0
NM_013215 AKR7A3 Aldo-keto reductase family 7, member A3 Biotransformation, Phase I 1.8 1.7 1.5 2.0 1.5 1.4 1.5 1.7
NM_017084 GNMT Glycine-N-methyltransferase Biotransformation, Phase I 1.4 1.6 1.8 1.6 1.2 1.2 1.0 1.9
NM_133586 CES2 Carboxylesterase 2 (intestine, liver) Biotransformation, Phase I -1.1 1.1 1.1 2.1 -1.4 1.1 1.5 2.9
AW142784 CYP51 Cytochrome P450 51 Biotransformation, Phase I 1.1 -1.4 -1.7 -1.1 1.0 1.0 -1.6 -1.1
BI285792 GSTM7-7 Similar to glutathione transferase GSTM7-7 Biotransformation, Phase II 1.5 1.7 1.5 2.1 1.3 1.5 1.3 1.5
AI169331 GSTM2 Glutathione-S-transferase M2 Biotransformation, Phase II 1.1 1.2 1.7 2.1 1.0 1.2 1.3 1.9
AF461738 UGT1A UDP-glucuronosyltransferase 1A, micros. Biotransformation, Phase II 1.9 1.7 1.5 1.8 1.5 1.6 1.6 1.5
Ek
d1
Ek
d3
Ek
d7
Ek
d14
wt
d1
wt
d3
wt
d7
wt
d14
45

DNA damage
response (incl.
oxidative stress
response)
Inhibited cell
survival and
proliferation
Accession
number
Chapter 3: Manuscript I
Gene title Biochemical category Fold deregulation (mean of three replicate animals
per time-point)
NM_133547 SULT1C2 Sulfotransferase K1 (SULTK1) Biotransformation, Phase II -1.3 -1.2 -1.3 -2.0 1.0 -1.3 -1.1 -1.3
AY082609 MDR1B Mutlidrug resistance-1B (ABCB1b) Drug transport 1.1 1.2 1.2 5.5 -1,1 1.1 1.6 2.5
NM_012833 MRP2 Multidrug resistance-associated protein 2 Drug transport 1.5 1.5 1.2 4.6 1.1 1.3 1.1 1.6
L46791 CES3 Carboxylesterase 3 Biotransformation, Phase I 1.1 1.5 1.5 1.7 1.4 1.6 1.6 2.3
NM_134349 MGST1 Microsomal glutathione S-transferase 1 Biotransformation, Phase II 1.5 1.4 1.3 1.5 1.6 1.4 1.5 1.8
AF072816 MRP3 Multidrug resistance-associated protein 3 Drug transport 4.1 -1.7 1.3 2.2 2.3 1.3 1.9 7.8
NM_012861 MGMT O6-methylguanine-DNA methyltranferase DNA repair -1.1 1.2 1.7 3.1 1.1 1.2 1.9 2.7
AW520812 PHLDA3 Pleckstrin homology-like domain family A3 DNA damage response 1.1 1.1 1.3 3.2 1.4 1.4 2.4 3.2
Q64315 CDKN1A Cyclin-dependent kinase inhibitor 1A (p21) Cell cycle checkpoint 1.5 1.1 6.9 14.2 1.1 2.7 2.8 9.8
NM_031821 SNK Serum-inducible kinase (PLK2) Cell cycle checkpoint 1.2 1.3 2.2 6.6 1.4 1.2 2.0 4.3
NM_012923 CCNG1 Cyclin G1 Cell cycle checkpoint 1.1 1.5 2.3 3.8 1.1 1.6 2.1 4.1
BI296301 MDM2 Ubiquitin E3 ligase Mdm2 (predicted) Cell cycle checkpoint 1.0 1.7 1.4 4.9 -1.2 1.0 1.9 2.4
NM_022547 FTHFD 10-formyltetrahydrofolate dehydrogenase Cell cycle 2.0 1.9 1.5 1.8 1.7 1.7 1.6 1.8
AI411345 PRODH Similar to Proline dehydrogenase (oxidase) 1 Proapoptotic 1.4 2.5 1.7 2.0 1.2 1.7 1.8 1.9
NM_057153 OXR1 Oxidation resistance 1 DNA damage response -1.1 1.2 1.6 1.5 1.2 -1.1 1.2 1.7
AA801395 TNFAIP8 Tumor necrosis factor α-induced protein 8 Antiapoptotic 1.1 -1.3 -1.4 -2.5 1.0 1.1 1.2 -1.4
M14050 HSPA5 Heat shock 70kD protein 5 (GRP78) Antiapoptotic 1.5 -1.7 -1.6 -1.4 1.0 1.2 1.1 -1.3
AF106659 USP2 Ubiquitin-specific protease 2 Proapoptotic -1.1 1.9 1.6 3.5 1.0 2.0 1.5 1.4
BF288101 SNN Stannin Proapoptotic -1.2 1.1 1.1 1.9 -1.1 1.1 1.0 1.8
AI714002 Ki-67 (predicted) DNA replication -2.4 -2.2 -1.9 -1.2 1.5 -1.4 1.0 -1.4
AI072892 FRZB Frizzled-related protein Signalling cascades -1.1 1.2 1.8 1.3 1.6 1.2 1.0 1.3
M15481 IGF1 Insulin-like growth factor 1 Regulation of proliferation -1.1 -1.2 -1.7 -2.4 1.0 1.2 -1.1 -2.0
NM_022266 CTGF Connective tissue growth factor Cell adhesion / migration 1.2 -1.1 -1.1 -1.9 1.4 1.1 1.2 -1.9
Ek
d1
Ek
d3
Ek
d7
Ek
d14
wt
d1
wt
d3
wt
d7
wt
d14
46

Enhanced cell
survival/
proliferation
Accession
number
Chapter 3: Manuscript I
Gene title Biochemical category Fold deregulation (mean of three replicate animals
per time-point)
BI275994 TGM2 Tissue-type transglutaminase Cell adhesion / migration -1.7 -1.5 -1.5 -2.9 -1.9 -2.0 -1.9 -1.9
AI102530 NAB2 Ngfi-A binding protein 2 (predicted) Transcriptional corepressor -1.1 1.2 1.8 2.0 1.1 1.0 1.0 1.7
BF417638 CDCA3 Cell division cycle associated 3 (TOME1) Cell cycle (G2/M) 1.1 -1.1 -1.3 1.3 -1.2 -1.7 -1.6 -1.5
X64589 CCNB1 Cyclin B1, G2/M-specific Cell cycle (G2/M) 1.0 -1.3 -1.3 1.0 -1.4 -2.2 -1.3 -1.6
AI171185 HMMR Hyaluronan mediated motility receptor Cell cycle (G2/M) 1.2 -1.4 -1.4 1.2 -1.6 -2.0 -1.4 -1.7
NM_019296 CDC2 Cell division cycle 2 protein kinase (CDK1 Cyclin
dependent kinase 1)
Ek
d1
Ek
d3
Ek
d7
Ek
d14
Cell cycle (G2/M) -1.2 -1.4 -2.5 1.2 -1.5 -2.4 -2.0 -1.6
AA944180 CKS2 Cyclin-dependent kinases regulatory subunit 2 Cell cycle (G2/M) 1.0 1.1 -1.7 2.5 -1.6 -2.3 -2.6 -1.3
BF396602 SFRP2 secreted frizzled-related protein 2 Antiapoptotic -1.1 -1.2 -1.6 -1.4 -1.1 -1.1 -1.4 -1.7
NM_012593 KLK7 Kallikrein 7 Antiapoptotic 1,2 -1.3 -1.8 -2.2 -1.4 -1.1 -1.2 -1.8
NM_021854 TSC1 Tuberous sclerosis 1 Tumor suppressor gene -1.9 -2.1 -1.3 -2.3 -1.1 -1.8 1.0 -1.5
BE098555 WWOX WW-domain oxidoreductase (predicted) Proapoptotic -1.4 -1.5 -1.5 -1.7 -1.5 -1.5 -1.9 -1.9
NM_134330 KEG1 kidney expressed gene 1 Regulation of proliferation 1.2 1.0 1.8 1.3 1.7 1.2 1.8 2.2
wt
d1
wt
d3
wt
d7
wt
d14
47

3.4.7 Genes deregulated by ochratoxin A
Chapter 3: Manuscript I
Biotransformation: OTA treatment downregulated the expression of several phase I and
phase II enzymes and drug transporter genes in both strains. While this effect appeared
constant over time for some genes, most deregulated genes demonstrated an enhanced
downregulation with increasing exposure time. Besides the downregulation of numerous
genes coding for components of the biotransformation machinery, OTA treatment resulted
in an increased upregulation of the phase I gene CYP4A12 in both strains and a consistent
upregulation of phase I ALDH6A1 in Eker rats.
DNA damage response (incl. oxidative stress): OTA treatment led to significant
upregulation of p53 pathway genes in both strains. However, the upregulation of these
genes differed between the two strains. Eker rather than wild type rats demonstrated an
upregulation of genes known to be involved in oxidative stress responses as well as
downregulation of genes that code for products with extra-cellular antioxidant activities. The
latter genes and the upregulated KEAP1, which suppresses the transactivation of
antioxidant responsive elements, were categorized as “enhanced oxidative stress”.
Cellular stress: A general stress response, as indicated primarily by the upregulation of
several components of the stress-inducible MAP-kinase pathway, was predominantly
detectable in Eker rats, since the latter genes were not significantly deregulated in wild type
rats.
Inhibited cell survival and proliferation: Predominantly OTA-treated Eker rats presented
with an upregulated expression of tumor suppressor-, negative cell proliferation controland
pro-apoptotic response genes. However, in both strains an inhibited cell survival
response could be inferred from the upregulation of a pro-apoptotic gene and the
downregulation of an anti-apoptotic and a DNA replication gene.
Enhanced cell survival and proliferation: Numerous genes coding for regulators of cell
survival signalling pathways, e.g. the IGF-PI3K-PKB pathway, anti-apoptosis, mitosis,
growth and proliferation (incl. proto-oncogenes) were primarily upregulated in Eker rats,
while a tumor suppressor gene and a gene coding for a signal cascade inhibitor (OVCA2)
was downregulated. In comparison, the latter genes were not or only marginally
deregulated in the wild type rats treated with OTA.
48

Chapter 3: Manuscript I
Cell cycle progression and mitosis: Upregulation of genes, more directly involved in the
cell cycle progression, was categorized separately as they appeared as an entity distinct
from the category “enhanced cell survival and proliferation”. Remarkably, gene deregulation
that would further cell cycle progression was exclusively observed in Eker rats.
Cell structure remodeling: Similar to the effects observed for genes involved in enhanced
cell survival and proliferation (see above), genes coding for components and regulators of
the cytoskeleton, altered cell cell-adhesion or communication, and components of the Rac
and Rho signalling were almost exclusively upregulated in Eker rats.
Epithelial mesenchymal transition (EMT)/ Fibrosis: This category includes regulators of
cell proliferation, growth factor activation, cell adhesion and extracellular matrix (ECM)
known to be associated in the process of EMT and/ or fibrosis, and which could be
associated with the progression of renal and urothelial tumors. Such increased expression
of components of the TGFß pathway and of a hepatocyte growth factor activator-inhibitor
gene in conjunction with a downregulated expression of extracellular matrix protease genes
were predominantly deregulated in Eker rats.
49

Chapter 3: Manuscript I
Table 3.2: Categories of genes differentially deregulated by OTA in Eker- and wild type rats. For the major pathophysiological categories the associated
genes are listed together with their Genebank accession number. The main biochemical functions or pathways in which these genes are
involved are indicated in column four. For Eker- and wild type rats, the fold deregulation ratios of genes that were significantly deregulated
over all time points according to N-way ANOVA are shown in the last eight columns. Genes meeting the significance criteria are indicated in
bold.
Toxicological
category
Metabolism and
Biotransformation
DNA damage
response
Accession
number
Gene title Biochemical category Fold deregulation (mean of three replicate animals
per time-point)
NM_031565 CES1B Carboxylesterase RL1 Biotransformation phase I 1.0 -1.7 -2.7 -1.9 -1.1 -1.5 -2.2 -2.2
L46791 CES3 Carboxylesterase 3 Biotransformation phase I 1.0 -1.4 -2.7 -3.4 -1.2 -1.7 -2.7 -1.9
NM_020538 AADAC Arylacetamide deacetylase Biotransformation phase I -1.4 -1.3 -1.9 -2.5 1.0 -1.2 -1.5 -2.0
AW142784 CYP4A12 Cytochrome P450 4a12 Biotransformation phase I 1.0 1.6 1.5 1.9 1.7 1.8 2.0 1.9
NM_133558 CML1 Camello-like 1 Biotransformation phase II -1.1 -1.3 -2.6 -2.9 -1.2 -1.1 -2.0 -2.1
NM_022635 NAT8 N-acetyltransferase 8 Biotransformation phase II -1.2 -2.1 -3.3 -2.9 -1.3 -1.5 -2.4 -2.9
AI072042 GGT6 Gamma-glutamyl transpeptidase type VI Biotransformation phase II -1.4 -2.0 -2.9 -2.7 -1.3 -1.3 -1.6 -1.8
NM_134349 MGST1 Microsomal glutathione S-transferase 1 Biotransformation phase II -1.3 -1.4 -1.8 -1.8 -1.1 -1.3 -1.7 -1.7
NM_134369 CYP2T1 Cytochrome P450 2T1 Biotransformation phase I 1.0 -1.1 -2.0 -1.9 1.1 -2.0 -1.3 -1.3
BF283000 WBSCR21 Williams-Beuren syndr. chromosome region 21 Biotransformation phase I 1.1 -1.4 -1.7 -1.9 -1.1 -1.1 -1.3 -1.4
AI407458 ALDH6A1 Aldehyde dehydrogenase 6A1 Biotransformation phase I 1.8 2.0 1.6 2.1 1.1 1.1 -1.1 -1.1
NM_022270 OCTN1 Organic cation carnitine transporter 1 Drug transport -1.1 -1.1 -2.1 -1.8 1.0 -1.1 -1.5 -1.2
NM_017224 OAT1 Organic anion transporter 1 (SLC22A6) Drug transport -1.1 1.1 -1.9 -1.7 1.1 -1.2 -1.3 -1.6
NM_019303 CYP2F4 Cytochrome P450 2F4 Biotransformation phase I 1.3 1.0 -1.4 -1.8 1.2 -1.8 -1.8 -1.1
NM_017084 GNMT Glycine-N-methyltransferase Biotransformation phase II 1.0 -1.4 -1.4 -1.6 -1.4 -1.5 -1.9 -1.5
U76379 OCT1 Organic cation transporter 1 (SLC22A1) Drug transport 1.1 -1.3 -1.4 -1.7 -1.1 -1.4 -1.7 -1.7
BM388545 SUPT16H Suppressor of Ty 16 homolog (predicted) DNA damage repair 1.0 1.8 1.4 1.8 1.6 1.8 2.1 2.4
NM_053677 CHEK2 Checkpoint kinase 2 Cell cycle checkpoint 1.0 1.8 2.8 2.2 1.0 -1.1 1.1 -1.1
Ek
d1
Ek
d3
Ek
d7
Ek
d14
wt
d1
wt
d3
wt
d7
wt
d14
50

Oxidative
stress
response
Enhanced
oxidative stress
Cellular stress
Reduced cell
survival/
proliferation
Accession
number
Chapter 3: Manuscript I
Gene title Biochemical category Fold deregulation (mean of three replicate animals
per time-point)
BF548539 MDM2 Ubiquitin E3 ligase Mdm2 (predicted) Cell cycle checkpoint 5.3 4.4 1.8 2.4 -1.4 -1.4 -1.4 1.0
AI178158 RBBP6 retinoblastoma binding protein 6 (predicted) Cell cycle checkpoint 1.0 1.1 1.0 1.0 1.2 1.5 2.0 1.5
NM_019192 SEPP1 Selenoprotein P Oxidative stress response 1.1 3.5 3.4 3.9 4.1 4.2 4.9 4.2
NM_019235 GGTLA1 Gamma-glutamyltransferase-like activity 1 Oxidative stress response 1.4 2.6 1.8 4.2 1.3 -1.4 2.1 1.0
NM_031614 TXNRD1 Thioredoxin reductase 1, cytoplasmic Oxidative stress response 1.7 1.7 1.4 1.7 -1.1 1.0 -1.3 -1.1
AI231438 CN1 Carnosine dipeptidase 1 Oxidative stress response -1.2 -1.2 -2.9 -2.5 -1.2 -1.5 -1.8 -1.3
BM386741 HSP40-3 Heat shock protein hsp40-3 (predicted) Protein folding (cytosol) -1.3 -1.8 -1.7 -1.4 1.0 1.0 -1.5 -1.1
BF414210 KEAP1 Kelch-like ECH-associated protein 1 Regulation of transcription 1.7 1.6 2.0 2.4 1.1 1.0 -1.1 1.0
NM_053307 MSRA Methionine sulfoxide reductase A Oxidative stress response 1.4 1.4 1.0 -1.3 1.0 -1.6 -2.0 -1.8
BM387750 DUSP11 Dual specificity phosphatase 11 MAPK pathway -1.1 -1.7 -1.7 -1.5 -1.5 -1.5 -1.4 -1.8
BE110108 DUSP1 Dual specificity protein phosphatase 1 MAPK pathway 1.9 1.6 2.3 2.3 -1.1 -1.3 -1.3 1.0
NM_031032 GMFB Glia maturation factor beta MAPK pathway 2.4 4.0 5.9 5.6 1.5 1.3 2.7 1.5
AAH61870 JNK2 c-Jun N-terminal kinase 2 MAPK pathway 1.8 1.3 1.4 1.3 1.2 -1.4 -1.1 -1.3
AA851481 BRE Brain and reproductive organ-expressed protein MAPK pathway 1.8 1.7 1.5 1.7 1.1 -1.1 -1.2 -1.2
L48060 PRLR Prolactin receptor MAPK pathway 1.5 2.1 1.3 1.7 1.1 1.2 1.2 1.2
NM_023090 HIF2 alpha Hypoxia-inducible factor 2 alpha HIF pathway 2.5 1.8 2.0 1.7 1.2 1.1 -1.2 1.0
BF403837 NFE2L1 Nuclear factor (erythroid-derived) 2 like 1 Regulation of gene expression 1.4 1.3 1.3 1.7 1.0 -1.3 -1.1 -1.1
AI598399 RBM3 RNA-binding motif protein 3 RNA metabolism 1.0 1.0 -1.3 1.0 1.4 1.1 1.2 1.8
BF281976 POLD4 Polymerase (DNA-directed), delta 4 DNA replication 2.0 -2.2 -2.0 -2.1 -1.1 -1.4 -1.6 -2.0
NM_057138 CFLAR CASP8 and FADD-like apoptosis regulator Antiapoptotic -1.3 -1.9 -2.9 -4.3 1.2 -3.6 -2.9 -3.4
AW253957 ENDOG Endonuclease G Proapoptotic 1.1 1.9 2.3 1.9 1.3 1.4 1.8 2.5
AA944698 BAT3 HLA-B associated transcript 3 Proapoptotic 6.5 4.4 3.9 5.0 1.2 1.3 1.1 -1.1
NM_019208 MEN1 Multiple endocrine neoplasia 1 Tumor suppressor gene 1.9 1.2 1.6 1.9 -1.1 -1.2 1.1 -1.1
Ek
d1
Ek
d3
Ek
d7
Ek
d14
wt
d1
wt
d3
wt
d7
wt
d14
51

Increased cell
survival/
proliferation
Accession
number
AI113091 TSSC4 Tumor-suppressing subchromosomal transferable
fragment 4 (predicted)
Chapter 3: Manuscript I
Gene title Biochemical category Fold deregulation (mean of three replicate animals
per time-point)
Ek
d1
Ek
d3
Ek
d7
Ek
d14
Tumor suppressor gene 1.8 1.4 1.2 2.2 -1.1 1.0 -1.1 1.0
AA996685 PKIA cAMP-dependent protein kinase inhibitor alpha Signalling cascades 3.0 3.1 2.5 2.4 -1.3 1.2 1.3 2.6
BI290885 FSTL Follistatin-like 1 Signalling cascades 1.9 1.2 1.7 1.9 1.1 -1.1 1.1 1.3
BG663107 AKAP12 A kinase anchor protein 12 (gravin) Signalling cascades 1.7 1.4 2.0 1.5 -1.1 -1.2 -1.1 -1.2
M86708 ID1 Inhibitor of DNA binding 1 Regulation of transcription 1.1 -1.3 1.4 1.0 -1.3 -1.1 -1.3 -1.9
NM_031546 RGN Regucalcin (SMP-30) Antiapoptotic -1.4 1.9 -3.7 -4.5 1.2 -1.7 -1.9 -2.6
BE108969 IGFBP-4 Insulin-like growth factor binding protein 4 (IGF)-PI3K-AKT pathway -1.3 -1.4 -3.0 -3.8 1.0 -1.3 -3.0 -2.8
AI145815 MKRN-1 Makorin-1 Protein metabolism -1.1 -1.6 -1.9 -1.9 -1.3 -1.7 -1.7 -1.6
BM986536 HIST1H4I Histone 1 H4i Nucleosome assembly 1.4 3.1 2.7 3.0 1.3 2.2 2.5 2.3
NM_022265 PDC4 Programmed cell death 4 Antiapoptotic 1.5 2.1 1.7 1.9 1.0 -1.1 -1.3 1.1
BE112895 PEA15 Phosphoprotein enriched in astrocytes 15 Antiapoptotic -1.5 1.3 1.9 1.9 1.2 1.1 1.4 1.1
NM_021846 MCL1 Myeloid cell leukemia 1 Antiapoptotic 1.6 1.4 1.5 1.8 1.1 -1.3 -1.1 -1.4
NM_022943 MERTK C-Mer proto-oncogene tyrosine kinase Protooncogene 3.3 4.9 4.3 2.9 -1.3 1.0 1.2 1.1
NM_012807 SMOH Smoothened Protooncogene 1.8 1.3 1.6 1.5 -1.1 1.0 -1.3 1.0
NM_022264 V-KIT Hardy-Zuckerman 4 feline sarcoma viral oncogene
homolog (c-Kit)
NM_012843 TMP Tumor-associated membrane protein (EMP1 Epithelial
membrane protein 1)
Protooncogene 2.9 3.7 2.4 2.5 -1.2 -1.3 -1.5 1.2
Protooncogene 2.8 1.7 2.2 4.3 1.0 -1.3 -1.2 -1.3
AA943541 OVCA2 Candidate tumor suppressor OVCA2 (predicted) Tumor suppressor gene -1.3 -1.4 -1.6 -1.8 -1.3 -1.1 -1.4 -1.6
NM_053481 PIK3CB Phosphatidylinositol-4,5-bisphosphate 3-kinase
catalytic beta subunit
(IGF)-PI3K-AKT pathway 2.0 2.9 -1.3 2.0 1.3 1.0 1.0 -1.1
AI102030 AKT1S1 AKT1 substrate 1 (proline-rich) (IGF)-PI3K-AKT pathway 2.4 4.0 2.0 2.1 1.0 1.0 -1.1 -1.1
AI105076 AKT2 Thymoma viral proto-oncogene 2 (IGF)-PI3K-AKT pathway 1.5 1.5 1.2 1.9 1.0 1.1 -1.1 -1.2
AW434982 SBF1 Similar to SET binding factor 1 (IGF)-PI3K-AKT pathway 2.4 3.5 2.2 3.6 1.2 1.0 -1.1 1.0
wt
d1
wt
d3
wt
d7
wt
d14
52

Cell cycle
progression
and mitosis
Accession
number
Chapter 3: Manuscript I
Gene title Biochemical category Fold deregulation (mean of three replicate animals
per time-point)
NM_012593 KLK7 Glandular kallikrein 7 Protein metabolism 1.8 1.3 1.9 1.6 -1.1 -1.2 -1.2 -1.1
BI300565 ADAM10 A-disintegrin and metalloprotease domain 10 Protein metabolism 1.6 1.8 1.3 1.4 1.1 -1.3 -1.3 -1.3
NM_053665 AKAP1 A kinase (PRKA) anchor protein 1 Signalling cascades 5.9 3.8 4.1 7.8 1.0 1.2 -1.1 1.0
NM_017094 GHR Growth hormone receptor Signalling cascades 1.7 2.8 1.2 2.0 1.2 -1.1 1.0 1.1
NM_012850 GHRHR Growth hormone releasing hormone receptor Signalling cascades 1.2 1.3 1.8 1.7 1.6 1.4 1.1 -1.1
BI294916 KLF2 Kruppel-like factor 2 Regulation of gene expression 1.6 1.4 1.9 1.9 1.1 -1.1 -1.2 1.2
NM_131904 MGEA5 Meningioma expressed antigen 5 Protein metabolism 2.1 1.7 1.8 1.4 -1.1 -1.1 -1.5 -1.7
AF080594 VEGF Vascular endothelial growth factor Angiogenesis 2.3 2.0 1.6 2.6 1.1 -1.3 1.0 1.0
AW524517 VEZF1 Vascular endothelial zinc finger 1 Angiogenesis 1.9 1.6 1.2 1.4 1.1 1.0 -1.1 1.1
NM_133569 ANGPTL2 Angiopoietin-like 2 Angiogenesis 1.3 1.9 1.2 1.9 1.2 -1.1 -1.1 1.1
NM_017089 EPHB1 Ephrin B1 Angiogenesis 1.9 1.6 1.6 1.9 1.1 1.0 -1.3 1.0
AB035507 MCAM Melanoma cell adhesion molecule Angiogenesis 2.1 1.5 1.6 1.3 1.0 -1.3 1.1 -1.1
NM_022615 TOP1 DNA topoisomerase 1 DNA replication 1.5 1.8 1.6 2.2 1.0 -1.1 1.0 1.1
BM385181 SMARCA4 SWI-SNF related matrix associated actin
dependent regulator of chromatin subfamily A4
Ek
d1
Ek
d3
Ek
d7
Ek
d14
Chromatin remodelling 1.3 1.1 1.7 1.7 -1.1 1.4 1.0 1.1
U75920 MAPRE1 Microtubule-associated protein RP/EB family 1 Mitotic spindle formation 2.4 2.6 2.0 2.8 1.1 1.0 -1.1 1.0
AJ306292 AJUBA Ajuba protein Mitotic spindle formation 1.4 1.3 1.3 1.8 1.0 -1.2 -1.1 -1.2
BE118382 NEK9 NIMA related kinase 9 Mitotic spindle formation 2.1 1.9 1.8 2.4 1.0 1.0 1.0 -1.1
U77583 CSNK1A1 Casein kinase 1, alpha 1 Mitotic spindle formation 1.6 1.5 1.6 1.8 1.1 1.0 -1.1 1.0
NM_057148 SEPT2 Septin 2 Mitotic spindle formation 2.5 2.2 2.1 2.5 -1.1 -1.1 1.0 -1.1
NM_080907 PPP4R1 Protein phosphatase 4, regulatory subunit 1 Mitotic spindle formation 2.1 1.7 1.3 2.0 1.0 1.0 -1.2 -1.1
NM_013194 NMMHC-A Nonmuscle myosin heavy chain A Mitotic spindle formation 1.6 1.6 1.7 2.0 1.3 -1.1 1.1 1.2
Cell structure AA955773 PCDH1 Protocadherin 1 Cell adhesion molecule -1.1 -1.7 -1.6 -1.9 -1.3 -1.7 -2.2 -1.8
wt
d1
wt
d3
wt
d7
wt
d14
53

emodelling
Accession
number
Chapter 3: Manuscript I
Gene title Biochemical category Fold deregulation (mean of three replicate animals
per time-point)
BE097805 PCDH4 Protocadherin 4 Cell adhesion molecule 2.7 1.2 3.6 2.3 1.5 1.3 1.6 1.3
AA955091 ITGA6 Integrin alpha 6 Cell adhesion molecule 2.0 1.3 1.7 1.5 1.0 1.0 -1.3 -1.4
NM_031699 CLDN1 Claudin 1 Cell adhesion molecule 1.6 1.2 2.0 1.8 1.0 -1.2 -1.3 -1.2
NM_031329 OCLN Occludin Cell adhesion molecule 2.5 1.9 1.3 2.2 1.4 1.0 -1.1 1.0
NM_013217 AF-6 Afadin Regulation of cell adhesion/
migration
BF284125 IQGAP1 IQ motif containing GTPase activating protein 1 Regulation of cell adhesion/
migration
AB020726 PODXL Podocalyxin Regulation of cell adhesion/
migration
NM_020085 RPTPK Receptor-like protein tyrosine phosphatase kappa
extracellular region
Ek
d1
Ek
d3
Ek
d7
Ek
d14
wt
d1
wt
d3
wt
d7
wt
d14
1.6 1.7 1.7 1.9 1.0 1.0 -1.2 -1.2
1.3 1.3 1.8 1.8 1.0 -1.1 -1.3 -1.2
1.6 1.3 1.5 1.8 1.2 1.0 1.1 -1.1
Signalling cascades 5.6 5.7 3.2 5.4 1.0 -1.4 -1.8 -1.4
NM_057115 PTPN12 Protein tyrosine phosphatase, non-receptor type12 Signalling cascades 1.9 1.5 2.7 3.6 -1.1 -1.3 -1.2 -1.2
NM_031034 GNA12 Guanine nucleotide-binding protein alpha 12 Signalling cascades 2.2 2.2 1.6 2.4 1.1 1.2 1.1 -1.1
BE115857 PARVA Parvin alpha Cytoskeleton organization 2.4 2.1 1.6 2.1 1.0 1.0 1.1 -1.1
NM_024401 AVIL Advillin (Pervin) Cytoskeleton organization 1.2 1.3 1.9 2.6 1.0 1.1 1.5 1.8
AF054618 CTTN Cortactin Cytoskeleton organization 1.8 1.5 1.9 2.0 1.1 1.0 1.1 1.1
NM_032613 LASP1 LIM and SH3 protein 1 Cytoskeleton organization 3.1 1.8 1.5 2.0 1.1 1.0 -1.2 1.1
NM_023982 ARHGEF11 Rho guanine nucleotide exchange factor 11 Cytoskeleton organization 1.7 2.5 2.8 3.1 1.7 2.1 2.1 1.4
AI170442 DSTN Destrin Cytoskeleton organization 1.5 1.5 1.7 2.0 1.0 1.1 1.0 -1.1
NM_030873 PFN2 Profilin 2 Cytoskeleton organization 1.6 2.5 2.1 3.4 1.3 -1.1 -1.2 1.2
AA875047 CCTZ Chaperonin containing T-complex 1 zeta Cytoskeleton organization 9.0 2.0 6.7 5.0 -2.2 2.4 -1.5 -1.1
V01217 ACTB Actin beta Cytoskeleton constituent 2.2 2.1 2.1 3.1 1.0 -1.1 -1.1 1.0
NM_016990 ADD1 Alpha adducin Cytoskeleton constituent 2.0 1.3 1.5 2.1 1.2 1.2 -1.1 1.1
X70706 PLS3 Plastin 3 T-isoform (T-plastin) Cytoskeleton constituent 2.0 2.4 1.8 2.9 1.0 1.1 1.0 1.2
54

EMT / Fibrosis
Accession
number
Chapter 3: Manuscript I
Gene title Biochemical category Fold deregulation (mean of three replicate animals
per time-point)
NM_030863 MSN Moesin Cytoskeleton constituent 1.7 1.8 1.6 1.9 1.3 -1.2 1.0 1.1
BF392456 SPNB2 Spectrin beta 2 Cytoskeleton constituent 1.9 1.9 1.5 2.4 1.1 1.1 1.0 1.0
BI284344 KRT2-7 Keratin complex 2, basic, gene 7 (predicted) Cytoskeleton constituent -1.1 -1.4 -1.8 -2.0 1.0 -1.3 -1.4 -1.6
BI295970 TPM3 Tropomyosin 3 gamma (Tropomyosin alpha 3) Cell morphology / motility 1.7 1.7 1.6 2.1 1.0 1.0 -1.1 -1.1
NM_012678 TPM4 Tropomyosin 4 Cell morphology / motility 2.2 1.8 2.3 2.0 1.0 -1.1 -1.4 1.1
NM_053986 MYO1B Myosin IB (Brush border myosin I) Cell morphology / motility 1.7 1.3 1.5 1.8 -1.1 1.1 -1.1 -1.1
NM_023092 MYO1C Myosin 1C (Unconventional myosin Myr2 I heavy
chain)
Ek
d1
Ek
d3
Ek
d7
Ek
d14
Cell morphology / motility 1.5 1.4 1.7 1.7 1.1 1.1 1.0 1.1
BG380723 CAP1 Adenylyl cyclase-associated protein 1 Cell morphology / motility 2.0 1.5 1.9 2.3 -1.1 1.2 1.0 1.0
AA997129 LAMC1 Laminin gamma 1 Extracellular matrix component 2.2 1.5 1.6 1.6 1.1 -1.2 1.0 1.3
AW435213 NANS N-acetylneuraminic acid synthase (sialic acid
synthase)
Cell adhesion / migration 1.4 1.3 1.5 1.7 1.0 1.1 -1.3 -1.2
U61261 LAMA3 Laminin alpha 3 (Laminin-5 alpha 3) Extracellular matrix component 1.2 1.1 1.2 -1.3 -1.2 -1.7 -1.6 -2.0
BF284673 FGD1 Faciogenital dysplasia homolog Cell adhesion/ migration 1.1 1.3 1.2 1.5 1.5 1.2 1.9 2.2
NM_013085 PLAU Urokinase-type plasminogen activator Cell adhesion/ migration -1.3 -1.3 -2.1 -1.9 -1.3 -2.0 -1.7 -2.1
NM_013143 MEP1A Meprin A alpha-subunit Protein degradation -1.2 1.0 -2.5 -2.9 -1.2 -1.6 -1.6 -2.1
L09653 TGFBR2 TGF-beta receptor type II TGF-beta family pathway 3.9 5.5 5.9 3.4 1.0 -1.4 -1.1 1.0
NM_013130 SMAD1 (MADH1) Mothers against decapentaplegic homolog
1
NM_013095 SMAD3 (MADH3) Mothers against decapentaplegic homolog
3
NM_019275 SMAD4 (MADH4) Mothers against decapentaplegic homolog
4)
TGF-beta family pathway 2.1 1.5 1.6 1.4 1.0 1.1 1.0 1.7
TGF-beta family pathway 2.1 3.5 1.6 2.8 1.2 1.1 -1.1 1.1
TGF-beta family pathway 1.7 1.7 1.3 1.6 -1.2 -1.2 -1.3 -1.6
NM_053357 CTNNB1 Beta-catenin Regulation of proliferation 1.7 1.6 1.3 1.9 1.0 -1.2 -1.1 1.0
NM_031317 PDGFC Platelet derived growth factor C Regulation of proliferation 2.1 1.7 1.4 2.4 1.0 -1.4 -1.1 -1.1
wt
d1
wt
d3
wt
d7
wt
d14
55

Accession
number
Chapter 3: Manuscript I
Gene title Biochemical category Fold deregulation (mean of three replicate animals
per time-point)
BE095528 HAI-1 Hepatocyte growth factor activator inhibitor 1 Regulation of proliferation 3.9 9.2 5.4 3.0 1.0 1.0 -1.1 1.0
AF172255 NPHS1 Nephrosis 1 homolog (nephrin) Cell adhesion / migration 1.7 2.3 2.0 1.8 -1.1 1.0 1.0 1.1
NM_012886 TIMP3 Tissue inhibitor of metalloproteinase 3 Cell adhesion / migration 1.8 1.4 1.4 1.8 1.0 -1.1 -1.4 -1.7
BI278545 DPT Dermatopontin Cell adhesion / migration 1.6 1.5 1.7 1.8 1.1 1.0 1.2 1.2
NM_012924 CD44 antigen (ECMR-III Extracellular matrix receptor-III) Cell adhesion / migration 2.3 3.3 1.2 1.6 -1.2 -1.1 1.1 1.2
NM_024358 NOTCH2 Notch homolg 2 Differentiation / organogenesis 2.4 2.2 3.2 7.4 1.0 1.0 -1.1 -1.1
AA997458 Similar to CSRP2 Cysteine and glycine-rich protein 2 Differentiation / organogenesis 1.0 -1.5 -1.8 -1.6 -1.3 -1.5 -1.6 -1.6
NM_012901 AMBP Alpha-1-microglobulin/bikunin precursor Extracellular transport 1.1 2.0 2.6 1.9 1.0 1.3 1.8 1.9
NM_017309 CNB Calcineurin B regulatory subunit isoform 1 Signalling cascades 4.5 7.6 1.8 5.8 -1.1 -1.4 -1.3 -1.3
Ek
d1
Ek
d3
Ek
d7
Ek
d14
wt
d1
wt
d3
wt
d7
wt
d14
56

3.5 Discussion
Chapter 3: Manuscript I
As expected for the short-term duration and dose-regimen employed (Mengs et al. 1982;
Boorman et al. 1992), neither AA nor OTA induced pronounced non-neoplastic renal
pathology in either strain of rats. While AA treated rats presented with a slightly higher
inflammatory response than the corresponding controls, OTA treated rats responded with
the typical pathological changes, e.g. karyomegaly, apoptosis, cell shedding, regenerative
proliferation and an inflammatory response in the renal cortex, as reported earlier (Boorman
et al. 1992; Rasonyi et al. 1999). However, the AA and OTA induced non-neoplastic
pathology was clearly distinct from one another, and this was also reflected in the cell
proliferation assessment (Figure 3.1). Lack of overt cell necrosis and subsequent cell
shedding and regeneration in the tubuli of AA treated rats coincided with absence of
increased cell proliferation, demonstrating that AA had neither a cytotoxic nor a mitogenic
effect on the kidneys of either strain of rats. In contrast, OTA- induced tubular toxicity and
possibly mitogenic activity was reflected in the overt cell regeneration observed with the
histopathological as well as immunohistological assessments. Moreover, the observed
effects increased with the duration of treatment and were comparable in extent of effect in
both strains. Based on above observations, the age of animals used and the duration and
type of exposure, the expectation was confirmed that no increased prevalence (no. of
animals affected) or number (no. of lesions per animal) of preneoplastic and neoplastic
lesions were to be encountered in the wild type control and AA treated rats. Moreover, AA
treatment of the arguably more susceptible Eker rats did not increase the prevalence or
number of lesions, suggesting that the Tsc2 mutation was not critical for AA induced
effects. The two carcinomas observed on day 14 in AA exposed Eker rats cannot be
conclusively associated with AA treatment, as adenomas were also observed in the
corresponding Eker rat control and AA treatment groups already on day 1 (Supplemetary
table 3.2). As the number of animals employed for this experiment limited statistical
evaluation, a progression of already present adenomas to carcinomas due to AA treatment
cannot be excluded.
Similar to AA, OTA treatment was not associated with an increased prevalence or number
of lesions in wild type rats, despite the clearly enhanced cell proliferative response in the
renal cortex. The latter observation corroborates numerous earlier findings (Boorman et al.
1992; Rasonyi et al. 1999) suggesting that non-genotoxic compound- induced renal
carcinogenesis can only be observed after a prolonged compound exposure period. In
contrast to the situation in wild type, Eker rats presented with a significantly increased
57

Chapter 3: Manuscript I
prevalence and number of AT on day 14 of OTA treatment (Figure 3.1, E, Supplementary
table 3.2). The latter finding suggests that the increased cell proliferative stimulus (Figure
3.1, C) provided for an enhanced manifestation of the predisposition for renal neoplasia
mediated by the Tsc2 mutation and thus a direct or indirect interaction of OTA with Tsc2
(tuberin) pathway.
At the outset of this experiment it was assumed that each compound would induce a
distinct gene expression profile, which is reflected by the short-term pathology but also
displays characteristic genes representative for pathways involved in the compoundspecific
type of renal carcinogenesis. Consequently, the genotoxic AA was expected to
induce a gene expression profile, most likely involving genes of cell cycle arrest and DNA
damage repair but not cell proliferation and most likely would not involve Tsc2. Indeed, the
expression profiles of AA- treated Eker and wild type rats (Figure 3.3) were not distinctly
different and were comparable to expression profiles obtained with AA in kidneys of Big
Blue transgenic F344 rats (Chen et al. 2006). Several phase I genes were deregulated by
AA treatment from the first day of exposure. The gene product of one of the upregulated
phase I genes, NQOI, was previously demonstrated to be capable of reducing the nitro
group of AAI leading to metabolic activation. NQOI up-regulation could therefore be at least
partly responsible for DNA adduct formation (Stiborova et al. 2003). Although DNA adduct
formation could not be measured with the study design employed, previously published
reports support the assumption that AA DNA-adducts are formed (Dong et al. 2006).
Indeed, upregulation of several p53 pathway genes, including p53 target genes carrying a
p53 consensus sequence in the promotor region, was most prominent on day 7 and 14 of
exposure, indicating a DNA damage response upon bioactivation of AA. This interpretation
is further supported by the fact that several of the p53 target genes, e.g. MDM2, p21 or
CCNG1, have also been shown to be upregulated in rat liver after short-term exposure to
different known genotoxic compounds (Ellinger-Ziegelbauer et al. 2005). DNA damage and
activation of p53 pathway genes are expected to result in cell cycle arrest (Figure 3.4, A),
followed by damage repair or programmed cell death (Sionov and Haupt 1999). AAtreatment
led to the deregulation of several genes involved in apoptosis, with a comparable
time profile to the p53- pathway and target genes. Although cell cycle components are
predominantly regulated on the protein level, downregulation of genes crucial for the G2/M
transition, e.g. CDC2, Cyclin-B, TOME1 and CKS2 and downregulation of genes required
for mitotic spindle formation like TUBA1 or HMMR, suggest a G2 arrest. Deregulation of the
latter genes in wild type rats only, may be explained by 12-fold lower PI3K mRNA
expression compared to Eker rats (Sen et al. 2004). Increasing evidence suggest that
constitutive activation of the PI3K pathway could lead to defects in DNA damage checkpoint
control (Liang and Slingerland 2003). Consequently, AA-induced G2/M arrest would
58

Chapter 3: Manuscript I
therefore not be readily detectable in Eker rats, although they responded with upregulation
of proapoptotic genes, as well as downregulation of Ki-67, an observation also supported
by the cell proliferation and pathological analysis (Figure 3.1, A and B).
Figure 3.4: Postulated mechanistic pathways of AA (A) and OTA (B) induced toxicity in Eker and
wild type rats and potential influence of Tsc2 in the manifestation of short- and longterm
effects discussed. Black: pathways and processes suggested from the literature;
Blue: pathways and processes implicated by gene expression analysis; Red:
Pathways and processes implicated by histopathology and corroborated by gene
expression analysis.
In contrast to AA, the gene expression profiles of OTA-treated Eker and wild type rats were
distinctly different (Figure 3.3). However, in both strains up-regulation of CYP4A12 and
down-regulation of other phase I and II genes could provide for increased generation of
reactive oxygen species (ROS) and enhanced oxidative DNA damage (Kamp et al. 2005;
Mally et al. 2005), that could lead to cellular damage and regenerative cell proliferation.
Indeed, enhanced proximal tubular damage and cell regeneration/proliferation (Figure 3.1,
C and D) was observed in both rat strains, corroborating the above interpretation. OTA
induced oxidative stress and ensuing DNA damage in combination with enhanced cell
59

Chapter 3: Manuscript I
proliferation could increase the likelihood of neoplastic transformation (Dietrich and
Swenberg 1991). Presence of oxidative DNA damage, as also suggested by earlier findings
(Luhe et al. 2003; Cavin et al. 2006; Marin-Kuan et al. 2006), is supported by the
upregulation of the p53 pathway genes SUPT16H in both strains, MDM2 and CHEK2 in
Eker rats, and RBBP6 in wild type rats, as well as by the time-dependent downregulation of
HSP 40-3, CN1, MSRA and MGST1, responsible for the protection of cells against oxidative
stress. Indeed, recent findings demonstrated that overexpression of glia maturation growth
factor beta (GMFB) resulted in reduced antioxidant enzyme activities, subsequent
accumulation of H2O2, and finally enhanced oxidative injury of renal proximal tubular cells
(Kaimori et al. 2003). The 5.9-fold upregulation of GMFB in Eker rats, shown here, and the
known reduced 8-oxoguanine-DNA glycosylase expression in Eker rats (Habib et al. 2003),
may suggest that Eker rats are more susceptible to oxidative stress than wild type rats. This
interpretation is supported by the observation that Eker rats responded with increased cell
proliferation already on day 7 (Figure 3.1, C) and increased formation of AT (Figure 3.1, E).
However, OTA induced regenerative proliferation may not have been the sole contributor to
the propagation of preneoplastic lesions. Indeed, OTA has previously been assumed to
have mitogenic properties (Horvath et al. 2002; Gekle et al. 2005), a hypothesis supported
by downregulation of IGFBP-4, a negative regulator of the (IGF)-PI3K-AKT mitogenic
pathway, in Eker and wild type rats. Despite this, only Eker rats demonstrated a significant
increase of preneoplastic lesions. The latter can be explained with the renal gene
expression profile of OTA-treated Eker rats which contains deregulated genes characteristic
of the most pertinent hallmarks involved in cancer progression (Hanahan and Weinberg
2000), namely: 1) the evasion of programmed cell death via upregulation of antiapoptotic
genes e.g. PDC 4, PEA15 or MCL1; 2) insensitivity to growth inhibitory signals via
upregulation of protooncogenes e.g. MERTK, SMOH, V-KIT, TMP; 3) self sufficiency in
growth signals e.g. via an activated (IGF)-PI3K-AKT pathway (PIK3CB, AKT1S1, AKT2 or
SBF1); 4) limitless replication potential e.g. via an upregulation of genes involved in DNA
replication (TOP1), chromatin remodelling (SMARCA4), or mitotic spindle formation
(MAPRE1, AJUBA, NEK9); 5) sustained angiogenesis via upregulation of VEGF, VEZF1,
ANGPTL2; and 6) tissue invasion and metastasis via a broad set of deregulated genes
involved in cell structure remodelling (e.g. Rho guanine nucleotide exchange factor
ARHGEF11 or IQGAP1, an effector for CDC42 and RAC1) and EMT (TGFßR-II, SMADs,
CD44, TIMP3).
As demonstrated, OTA treatment of Eker rats led to the expression of genes that could be
intricately involved in, or are the result of, activated mTor signalling (Thomas 2006). Thus
OTA treatment and the Tsc2-mutation may have acted in concert or separately on the
(IGF)-PI3K-AKT pathway thus resulting in a co-joint activation of mTor signalling. Additional
60

Chapter 3: Manuscript I
stimulation of the mTor pathway could be possible by OTA-mediated ERK activation
(Horvath et al. 2002). Tsc2 was demonstrated to be a direct substrate of ERK (Ma et al.
2005a). As Eker rats exhibit only one functional allele of the Tsc2 gene, OTA mediated
ERK-dependent inactivation of Tsc2 could lead to more drastic and therefore earlier
detection of proliferative effects and neoplastic transformation in Eker rats (Figure 3.4, B).
In summary, gene expression profile comparisons with histopathologic findings from AAand
OTA- treated Eker and wild type rats discussed here, highlight that gene expression
analysis subsequent to short-term in vivo assays may have the potential to identify
deregulated genes involved in compound- and strain- specific pathology. Moreover,
deregulation of genes, for which a similar direction of deregulation has been reported for
various types of cancers, suggests that pathways linked to tumorigenesis may be
deregulated already after short-term carcinogen exposure. Whether these changes in gene
expression are transient or can be causally linked to a compound-specific tumorigenicity
cannot be determined without gene expression profile analysis of the respective
preneoplastic and neoplastic lesions in rats chronically treated with AA or OTA. This
analysis, as currently carried out in this laboratory using laser-capture microdissection
(Stemmer et al. 2006) will provide further information as to the relevance of the pathways
identified in short-term experiments for the understanding of the mechanisms underlying
AA- and OTA- induced renal carcinogenesis.
Acknowledgements
We would like to thank the Federal Ministry of Education and Research for funding the
project (BMBF: 0313024), Tanja Lampertsdörfer and Gudrun von Scheven for skillful
assistance during the whole animal experiment, Evelyn O’Brien and Alexandra Heussner
for help with the animal sacrifice, and Margot Thiel and Kerstin Lotz for microarray
hybridization.
61

3.6 Supplement
3.6.1 Supplementary Information
Chapter 3: Manuscript I
The significance of microarray data for biological interpretations and the necessity of
confirming them by another method were extensively discussed by Rockett et al. (Rockett
and Hellmann 2004). The authors suggested that microarrays as well as quantitative realtime
polymerase chain reaction (QRT-PCR) are at best semi-quantitative, while quantitative
detection of gene expression cannot be achieved with any of the currently available
methodologies. Based on 284 individual comparisons, a regression coefficient of 0.94
between the natural log ratios for Affymetrix RAE230A arrays and QRT-PCR (Taqman®
technology) data was previously obtained in this laboratory (data not shown). This supports
the assumption that both technologies deliver at least semi-quantitatively comparable
expression ratios. Therefore, it was assumed that the expression profiles generated with
the Affymetrix platform, as presented here, can be used for semi-quantitative comparisons
of gene deregulation and subsequent data interpretation.
62

3.6.2 Supplementary Tables
Supplementary table 3.1: Numbers and categories of genes deregulated by AA or OTA
# genes
Ek
specific
# genes
Ek and wt
specific
# genes
wt
specific
# genes
Ek
specific
# genes
Ek and wt
specific
# genes
wt
specific
Compound AA AA AA OTA OTA OTA
# all significantly
deregulated genes
Pathophysiological
categories
Metabolism and
biotransformation
77 34 47 314 61 80
Description
Chapter 3: Manuscript I
10 12 3 5 6 3 Deregulation of genes encoding biotransformation enzymes and drug transporters
DNA damage response 1 7 1 2 1 1 Upregulation of genes encoding DNA damage repair enzymes and p53 target genes
Oxidative stress response - - - 2 1 - Upregulation of ARE A target genes and other genes known to be involved in oxidative stress
responses
Enhanced oxidative stress - - 1 2 3 1 Downregulation of genes mediating the cellular antioxidant defense or upregulation of genes
encoding Nrf2 B inhibitors
Response to unfolded and
damaged proteins
1 - - 6 - 2 Upregulation of genes encoding members of the heat shock- or glucose-regulated protein
family and others involved in the response to unfolded or damaged proteins
Cellular stress 1 - - 6 2 1 Upregulation of immediate early genes, target genes of the stress kinase-, NFkB C -, or HIF D
pathways or other stress related pathways. Downregulation of genes encoding inhibitors of
these pathways
Inhibited cell survival and
proliferation
Enhanced cell survival/
proliferation
Cell cycle progression and
mitosis
8 1 7 6 3 2 Downregulation of antiapoptotic genes, genes involved in cell cycle progression or genes
encoding components of the mitotic spindle apparatus. Upregulation of proapoptotic genes
or tumour suppressor genes
1 - 3 23 2 - Upregulation of genes encoding growth and survival factors, (IGF)- PI3K-AKT E pathway
components, antiapoptotic genes, genes of the VEGF F pathway and functioning in growth
and survival of endothelial cells. Downregulation of tumour suppressor genes.
- - - 10 1 - Upregulation of genes involved in DNA replication, mitotic spindle/ cytokineses or
nucleosome formation.
63

Cell structure remodelling
Chapter 3: Manuscript I
2 2 2 32 1 2 Up- and downregulation of genes coding for components or regulators of the cytoskeleton,
cell adhesion molecules and components of the ECM. Upregulation of gene transcripts
involved in glycoprotein synthesis.
EMT/ Fibrosis - - - 12 2 - Upregulation of genes involved in the TGF-ßG pathway, ECMH accumulation or deregulation
of other genes known to be involved in the process of epithelial mesenchymal transition
(EMT) and /or fibrosis
Inflammation 8 2 2 13 - 2 Upregulation of genes encoding components of the TNF I / cytokine pathway, of the antigene
presentation machinery, or inflammatory factors. Downregulation of inhibitors of blood
coagulation.
Altered ion homeostasis 6 1 2 24 - 1 Deregulation of genes encoding proteins involved in ion storage or transport
Energy mobilisation 1 2 1 17 4 3 Upregulation of genes primarily involved in glycolysis, fatty acid oxidation or the pentose
phosphate pathway.
Increased transcription and
RNA processing
6 - 2 15 1 6 Upregulation of genes encoding transcription factors, coactivators, or enzymes involved in
the metabolism of nucleotides and nucleosides and RNA splicing
Increased protein synthesis 1 - 2 4 1 1 Upregulation of genes involved in translation or protein folding in the endoplasmatic
reticulum
Increased protein
trafficking
- - 2 28 - - Upregulation of genes involved in protein sorting, vesicular transport or endo-/exocytosis
Dedifferentiation 10 2 7 9 9 4 Downregulation of genes mediating the physiological homeostasis of the cell and/or organ.
Neuronal differentiation 2 2 - 14 1 4 Upregulation of genes involved in neuronal signal transmission or neuronal differentiation
Deregulation of the
circadian rhythm
Unknown toxicological
category
4 1 - - - - Deregulation of genes involved in the regulation of the circadian rythm
9 1 2 20 7 12 Genes with known biochemical function, but whose deregulation could not be given a
specific meaning
unknown ESTs 6 1 10 60 16 35 Genes which are not annotated
A B C D E
: ARE: Arylhydrocarbon responsive elements; : NFkB: Nuclear transcription factor B; : Nrf2: NF-E2-related factor-2; : HIF: Hypoxia inducible factor; : (IGF)- PI3K-
AKT: Insulin growth factor- Phosphoinositol-triphosphate kinase-AKT; F : VEGF: Vascular endothelial growth factor; G : TGF-ß: Transforming growth factor ß; H : ECM:
Extracellular matrix; I : TNF: Tumor necrosis factor
64

Chapter 3: Manuscript I
Supplementary table 3.2: Incidence and mean numbers of preneoplastic and neoplastic lesions. Mean + SD of atypical tubule (AT), aypical hyperplasia (AH)
and neoplastic (adenoma, carcinoma) lesions of AA or OTA treated Eker and wild type rats and their respective controls (n=3). Incidences of
respective lesions in treated or control animals are given in parentheses. Significant differences (unpaired t-test) between treated and timematched
control groups are indicated (*p

Chapter 3: Manuscript I
Supplementary table 3.3: Non-neoplastic pathology of AA or OTA treated Eker rats. Mean + SD of non-neoplastic changes. ranked according to the following
severity classes: none (0). mild (1). moderate (2). strong (3). and severe (4). including intermediate classes (e.g. 0.5. 1.5) of AA or OTA treated
Eker rats and their respective controls (n=3). Incidences of respective lesions in treated or control animals are given in parentheses.
Necrosis
Apoptosis
Fibrosis
Basement
membrane
(thickening)
Mesangia
(thickening)
Bowmans Space
with erythrocytes)
Calcium cast
Glomerulo-
Sclerosis
Glomerulo-
Nephritis
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
Control (AA) AA Control (OTA) OTA
d1 d3 d7 d14 d1 d3 d7 d14 d1 d3 d7 d14 d1 d3 d7 d14
0,17 ±
0,24
(1/3)
0.0 ±
0.0
(0/3)
0.33 ±
0.47
(1/3)
0,17 ±
0,24
(1/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.33 ±
0.47
(1/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.33 ±
0.47
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.3 ±
0.34
(2/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0,17 ±
0,24
(1/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.5 ±
0.71
(1/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.5 ±
0.41
(2/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
Glomeruli
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0,17 ±
0,24
(1/3)
0.0 ±
0.0
(0/3)
0.33 ±
0.24
(2/3)
0.67 ±
0.47
(2/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0±
0.0
(0/3)
0.33 ±
0.24
(2/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0,17 ±
0,24
(1/3)
0.67 ±
0.24
(3/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.17 ±
0.24
(1/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.33 ±
0.47
(2/3)
0.83 ±
0.47
(3/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.17 ±
0.24
(1/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.83 ±
0.24
(3/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0,17 ±
0,24
(1/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.5 ±
0.0
(3/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.5 ±
0.0
(3/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0,17 ±
0,24
(1/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.67 ±
0.47
(2/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
66

Pigment Deposits
Necrosis
Apoptosis
Karyomegally
Vacuolization
Hyaline droplets
Cell shedding
Proteinaceous
casts
Tubular dilatation
Calcium casts
Tubular
regeneration
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
Control (AA) AA Control (OTA) OTA
Chapter 3: Manuscript I
d1 d3 d7 d14 d1 d3 d7 d14 d1 d3 d7 d14 d1 d3 d7 d14
0.33 ±
0.47
(2/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.17 ±
0.24
(1/3)
0.50 ±
0.41
(2/3)
0.33 ±
0.47
(2/3)
0.67 ±
0.24
(3/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.33 ±
0.24
(2/3)
0.0 ±
0.0
(0/3)
0.50 ±
0.41
(2/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.33 ±
0.47
(2/3)
0.0 ±
0.0
(0/3)
1.0 ±
0.41
(3/3)
0.0 ±
0.0
(0/3)
0.50 ±
0.41
(2/3)
0.17 ±
0.24
(1/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.33 ±
0.47
(1/3)
0.0 ±
0.0
(0/3)
0.17 ±
0.24
(1/3)
0.17 ±
0.24
(1/3)
0.5 ±
0.41
(2/3)
0.33 ±
0.47
(1/3)
0.50 ±
0.41
(2/3)
0.17 ±
0.24
(1/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.50 ±
0.0
(3/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.17 ±
0.24
(1/3)
0.0 ±
0.0
(0/3)
0.17 ±
0.24
(1/3)
0.17 ±
0.24
(1/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.17 ±
0.24
(1/3)
0.17 ±
0.24
(1/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.17 ±
0.24
(1/3)
0.17 ±
0.24
(1/3)
0.33 ±
0.24
(2/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(1/3)
0.0 ±
0.0
(0/3)
0.50 ±
0.41
(2/3)
Cortex
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.17 ±
0.24
(1/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.17 ±
0.24
(1/3)
0.33 ±
0.24
(2/3)
0.17 ±
0.24
(1/3)
0.17 ±
0.24
(1/3)
0.83 ±
0.24
(3/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.67 ±
0.62
(2/3)
0.0 ±
0.0
(0/3)
0.17 ±
0.24
(1/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
1.0 ±
0,41
(3/3)
0.0 ±
0.0
(0/3)
0.33 ±
0.24
(2/3)
0.0 ±
0.0
(0/3)
0.17 ±
0.24
(1/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.33 ±
0.47
(1/3)
0.0 ±
0.0
(0/3)
0.83 ±
0.47
(3/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.50 ±
0.0
(3/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.17 ±
0.24
(1/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.83 ±
0.62
(2/3)
0.0 ±
0.0
(0/3)
0.50 ±
0.0
(3/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.17 ±
0.24
(1/3)
0.0 ±
0.0
(0/3)
0.17 ±
0.24
(1/3)
0.0 ±
0.0
(0/3)
1.83 ±
0.62
(3/3)
0.0 ±
0.0
(0/3)
0.67 ±
0.47
(2/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.33 ±
0.24
(2/3)
1.5 ±
0.41
(3/3)
0.0 ±
0.0
(0/3)
0.67 ±
0.47
(3/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.83 ±
0.24
(3/3)
1.0 ±
0.41
(3/3)
0.33 ±
0.47
(1/3)
0.0 ±
0.0
(0/3)
1.33 ±
0.62
(3/3)
0.0 ±
0.0
(0/3)
1.17 ±
0.24
(3/3)
0.0 ±
0.0
(0/3)
1.50 ±
0.41
(3/3)
67

CPN
Inflammation
Hypertrophy
Pigment Deposits
Necrosis
Apoptosis
Karyomegally
Vacuolization
Hyaline droplets
Cell shedding
Proteinaceous
casts
Tubular dilatation
0.33 ±
0.47
(1/3)
0.33 ±
0.47
(1/3)
0.17 ±
0.24
(1/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.17 ±
0.24
(1/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.17 ±
0.24
(1/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
0.33 ±
0.47
(1/3)
0.33 ±
0.47
(1/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
0.33 ±
0.47
(1/3)
0.50 ±
0.41
(2/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
0.17 ±
0.24
(1/3)
0.83 ±
0.24
(3/3)
0.33 ±
0.47
(1/3)
0.17 ±
0.24
(1/3)
1.5 ±
0.0
(3/3)
0.0 ±
0.0
(0/3)
Medulla/ Papilla
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
0.50 ±
0.0
(1/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
0.17 ±
0.24
(1/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
0.17 ±
0.24
(1/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(3/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
0.0 ±
0.0
(0/3)
0.33 ±
0.47
(1/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
Chapter 3: Manuscript I
0.17 ±
0.24
(1/3)
0.50 ±
0.0
(3/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
0.5 ±
0.41
(2/3)
0.67 ±
0.24
(3/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
0.50 ±
0.0
(3/3)
1.0 ±
0.0
(3/3)
0.33 ±
0.47
(1/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
68

Calcium casts
Tubular
regeneration
CPN
Inflammation
Hypertrophy
Chapter 3: Manuscript I
(0/3) (0/3) (0/3) (0/3) (0/3) (0/3) (0/3) (0/3) (0/3) (0/3) (0/3) (0/3) (0/3) (0/3) (0/3) (0/3)
0.33 ±
0.24
(2/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.17 ±
0.24
(1/3)
0.0 ±
0.0
(0/3)
0.17 ±
0.24
(1/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.17 ±
0.24
(1/3)
0.0 ±
0.0
(0/3)
0.33 ±
0.24
(2/3)
0.0 ±
0.0
(0/3)
0.50 ±
0.41
(2/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.33 ±
0.47
(1/3)
0.0 ±
0.0
(0/3)
0.33 ±
0.34
(2/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.33 ±
0.47
(1/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
1.33 ±
0.94
(2/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.17 ±
0.24
(1/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.17 ±
0.24
(1/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.17 ±
0.24
(1/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.17 ±
0.24
(1/3)
0.17 ±
0.24
(1/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
0.0 ±
0.0
(0/3)
69

Chapter 3: Manuscript I
Supplementary table 3.4: Non-neoplastic pathology of AA or OTA treated wild type rats. Mean + SD of non-neoplastic changes, ranked according to the
following severity classes: none (0), mild (1), moderate (2), strong (3), and severe (4), including intermediate classes (e.g. 0.5, 1.5) of AA or OTA
treated wild type rats and their respective control (n=3). Incidences of respective lesions in treated or control animals are given in parentheses.
Pigment Deposits
Necrosis
Apoptosis
Fibrosis
Basement membrane
(thickening)
Mesangia
Bowmans Space with
erythrocytes)
Calcium cast
Glomerulo- Sclerosis
Glomerulo- Nephritis
Control (AA, OTA) AA OTA
d1 d3 d7 d14 d1 d3 d7 d14 d1 d3 d7 d14
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.17 ±
0.24 (1/3)
0.0 ± 0.0
(0/3)
0.50 ±
0.71 (1/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.33 ±
0.47 (1/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.33 ±
0.24 (2/3)
0.0 ± 0.0
(0/3)
0.83 ±
0.62 (2/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.50 ±
0.71 (1/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.5 ± 0.71
(1/3)
0.67 ±
0.62 (2/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
Glomeruli
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.33 ±
0.24 (2/3)
0.0 ± 0.0
(0/3)
0.50 ±
0.71 (1/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.33 ±
0.24 (2/3)
0.0 ± 0.0
(0/3)
1.0 ± 0.71
(2/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.17 ±
0.24 (1/3)
0.17 ±
0.24 (1/3)
1.0 ± 0.41
(3/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.33 ±
0.24 (1/3)
0.0 ± 0.0
(0/3)
0.33 ±
0.47 (1/3)
0.17 ±
0.24 (1/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.33 ±
0.24 (2/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.17 ±
0.24 (1/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.17 ±
0.24 (1/3)
0.17 ±
0.24 (1/3)
0.33 ±
0.24 (2/3)
0.67 ±
0.24 (3/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
70

Pigment Deposits
Necrosis
Apoptosis
Karyomegally
Hyaline droplets
Cell shedding
Proteinaceous
casts
Tubular dilatation
Calcium casts
Tubular
regeneration
CPN
Inflammation
Hypertrophy
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.17 ±
0.24 (1/3)
0.17 ±
0.24 (1/3)
0.33 ±
0.47 (1/3)
0.17 ±
0.24 (1/3)
0.33 ±
0.24 (2/3)
0.17 ±
0.24 (1/3)
0.50 ±
0.41 (2/3)
0.33 ±
0.47 (1/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.17 ±
0.24 (1/3)
0.0 ± 0.0
(0/3)
0.17 ±
0.24 (1/3)
0.0 ± 0.0
(0/3)
0.33 ±
0.47 (1/3)
0.50 ±
0.41 (2/3)
0.50 ±
0.41 (2/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.17 ±
0.24 (1/3)
1.0 ± 0.0
(3/3)
0.0 ± 0.0
(0/3)
0.17 ±
0.24 (1/3)
0.17 ±
0.24 (1/3)
0.0 ± 0.0
(0/3)
0.33 ±
0.47 (1/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.17 ±
0.24 (1/3)
0.83 ±
0.62 (2/3)
0.17 ±
0.24 (1/3)
0.50 ±
0.41 (2/3)
0.50 ±
0.41 (2/3)
0.67 ±
0.24 (3/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.17 ±
0.24 (1/3)
0.33 ±
0.24 (2/3)
0.33 ±
0.47 (1/3)
0.0 ± 0.0
(0/3)
0.17 ±
0.24 (1/3)
0.33 ±
0.23 (2/3)
0.50 ±
0.41 (2/3)
0.33 ±
0.47 (1/3)
Cortex
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.50 ± 0.0
(3/3)
0.17 ±
0.24 (1/3)
0.67 ±
0.24 (3/3)
0.17 ±
0.24 (1/3)
0.50 ±
0.41 (2/3)
0.17 ±
0.24 (1/3)
0.83 ±
0.24 (3/3)
0.33 ±
0.47 (1/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.50 ±
0.41 (2/3)
0.0 ± 0.0
(0/3)
0.83 ±
0.62 (2/3)
0.0 ± 0.0
(0/3)
0.17 ±
0.24 (1/3)
0.17 ±
0.24 (1/3)
0.83 ±
0.24 (3/3)
0.67 ±
0.47 (2/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.17 ±
0.24 (1/3)
0.17 ±
0.24 (1/3)
0.50 ±
0.41 (2/3)
0.0 ± 0.0
(0/3)
0.17 ±
0.24 (1/3)
0.0 ± 0.0
(0/3)
1.33 ±
0.24 (3/3)
0.0 ± 0.0
(0/3)
0.17 ±
0.24 (1/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.50 ±
0.41 (2/3)
0.33 ±
0.24 (2/3)
1.17 ±
0.62 (3/3)
0.0 ± 0.0
(0/3)
0.33 ±
0.24 (2/3)
0.17 ±
0.24 (1/3)
0.33 ±
0.24 (2/3)
0.67 ±
0.47 (2/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.17 ±
0.24 (1/3)
0.0 ± 0.0
(0/3)
0.33 ±
0.24 (2/3)
0.0 ± 0.0
(0/3)
0.83 ±
0.85 (2/3)
0.0 ± 0.0
(0/3)
0.50 ±
0.41 (2/3)
0.33 ±
0.47 (1/3)
0.33 ±
0.47 (1/3)
0.0 ± 0.0
(0/3)
Chapter 3: Manuscript I
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.50 ± 0.0
(3/3)
0.0 ± 0.0
(0/3)
0.67 ±
0.24 (3/3)
0.33 ±
0.24 (2/3)
0.67 ±
0.47 (2/3)
0.0 ± 0.0
(0/3)
0.50 ±
0.41 (2/3)
0.67 ±
0.24 (3/3)
0.50 ±
0.41 (2/3)
1.0 ± 0.0
(3/3)
0.0 ± 0.0
(0/3)
0.17 ±
0.24 (1/3)
0.83 ±
0.24 (3/3)
0.50 ± 0.0
(3/3)
0.0 ± 0.0
(0/3)
0.67 ±
0.47 (2/3)
0.17 ±
0.24 (1/3)
1.0 ± 0.0
(3/3)
0.0 ± 0.0
(0/3)
0.83 ±
0.85 (2/3)
0.50 ±
0.41 (2/3)
0.83 ±
0.24 (3/3)
0.33 ±
0.47 (1/3)
71

Pigment Deposits
Necrosis
Apoptosis
Karyomegally
Vacuolization
Hyaline droplets
Cell shedding
Proteinaceous
casts
Tubular dilatation
Calcium casts
Tubular
regeneration
CPN
Inflammation
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.33 ± 0.47
(1/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.17 ± 0.24
(1/3)
0.0 ± 0.0
(0/3)
0.17 ± 0.24
(1/3)
0.17 ± 0.24
(1/3)
Medulla/ Papilla
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
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0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.33 ± 0.47
(1/3)
0.33 ± 0.47
(1/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
(0/3)
0.0 ± 0.0
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0.0 ± 0.0
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0.0 ± 0.0
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(0/3)
Chapter 3: Manuscript I
0.0 ± 0.0
(0/3)
0.33 ± 0.47
(1/3)
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0.0 ± 0.0
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0.0 ± 0.0
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0.0 ± 0.0
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0.0 ± 0.0
(0/3)
0.0 ± 0.0
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0.0 ± 0.0
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0.0 ± 0.0
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0.0 ± 0.0
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0.0 ± 0.0
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0.0 ± 0.0
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0.0 ± 0.0
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0.0 ± 0.0
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0.0 ± 0.0
(0/3)
0.0 ± 0.0
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0.0 ± 0.0
(0/3)
0.0 ± 0.0
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0.0 ± 0.0
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0.0 ± 0.0
(0/3)
0.0 ± 0.0
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0.0 ± 0.0
(0/3)
0.0 ± 0.0
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0.0 ± 0.0
(0/3)
72

Chapter 4: Manuscript II
Renal Carcinogenic Response of Eker Rats to Low Doses of
Methylazoxymethanol Acetate
Kerstin Stemmer 1 , Heidrun Ellinger-Ziegelbauer 2 , Katja Strauch 3 , Leonard Collins 3 , James A.
Swenberg 3 , Hans-J. Ahr 2 and Daniel R. Dietrich 1*
1
Human and Environmental Toxicology, University of Konstanz, Konstanz, Germany
2
Molecular and Special Toxicology, Bayer Healthcare AG, Wuppertal, Germany
3
Environmental Sciences and Engineering, University of North Carolina at Chapel Hill, Chapel
Hill, North Carolina, USA
* Corresponding author: Daniel R. Dietrich: daniel.dietrich@uni-konstanz.de
Submitted to Mutation Research
4.1 Abstract
Methylazoxymethanol-actetae (MAMAc), the stabilized aglycone of cycasin, is a potent
renal carcinogen in rodents, which acts via direct alkylation of the DNA. Current knowledge
on MAMAc carcinogenicity is based on the use of very high doses, which may reflect a
carcinogenic mechanism different from the one active at low doses. This study compared
the renal response of male and female Tsc2-mutant Eker rats exposed to low doses of
MAMAc (250µg/kg bw day -1 ) after 1, 3, 7 and 14 days of exposure using gene expression
profiling, histopathology, including the assessment of preneoplastic and neoplastic lesions,
cell proliferation analysis and LC-MS/MS for demonstration of O6-methylguanine (O6-meG)
DNA adducts. Following 3 and 6 months of exposure renal histopathology, including
preneoplastic and neoplastic lesions and cell proliferation was assessed.
Gene expression profiles revealed only a small number of deregulated genes in short-term
MAMAc treated males, which mainly revealed a reduced protein synthesis, including downregulation
of tumor suppressor genes. An exposure dependent increase in O6-meG
adducts was indicated following 1-14 days of exposure, whereas the number of O6-meG
adducts detected were generally higher in female than in male rats. 250µg/kg bw day -1 of
73

Chapter 4: Manuscript II
MAMAc for 3 and 6 months induced increased cell proliferation and number of
preneoplastic lesions only in female but not in male rats. However, surprisingly male Eker
rats presented with an increased incidence and total higher number of adenomas and
carcinomas compared to female rats after 6 months of exposure.
In conclusion, above findings suggests that subchronic and –chronic exposure to low doses
of MAMAc results in gender-specific differences in response. Indeed, in female rats the
increase in early tumor stages and absence of late stages points to a tumor initiating role of
MAMAc, while in male rats, the increase in later tumor stages after 6 months exposure is
suggestive of a tumor promoting role of MAMAc.
4.2 Introduction
Cycasin (methylazoymethanol-ß-D-glucoside) is a natural constituent of nuts, root and
leaves of the cycad plants Cycas circinalis and Cycas revoluta that have been sources of
food and medicine for the indigenous people of the Western Pacific, e.g. the island of
Guam (Whiting 1963). Cycasin contamination mainly depend on food procession, for
instance flour from washed cycad nuts from Guam only contain marginal concentrations,
while up to 2.3% cycasin was detected when unwashed nuts were used (Hirono 1981). In
rats (Laqueur 1964; Laqueur and Matsumoto 1966), mice (O'Gara et al. 1964), guinea pigs
(Spatz 1964), rabbits (Hirono 1972) and nonhuman primates (Sieber et al. 1980), cycasin
was found to be a potent carcinogen resulting primarily in epithelial and mesenchymal
tumors of the kidneys, tumors of the liver and colon.
The carcinogenic action of cycasin appears mainly dependent on its deglucosylation by ßglucosidases
of the gut microflora to release its principal metabolite methylazoxymethanol
(MAM) (Spatz et al. 1967; Matsushima et al. 1979; Choi et al. 1996). The release of the
“ultimate carcinogen” methyldiazonium ion from MAM (Figure 4.1) is either catalyzed by
different enzymes including alcohol dehydrogenase (Grab and Zedeck 1977; Notman et al.
1982), choline dehydrogenase (Tan et al. 2004) and cytochrome P450-2E1 (Sohn et al.
2001), however, may also occur spontaneously under normal physiological conditions
(Nagasawa et al. 1972; Sohn et al. 2001). The methyldiazonium ion, is also metabolically
formed from other DNA alkylating pro-carcinogens, e.g. dimethylnitrosamine (DMN) (Shank
and Magee 1967; Weisburger 1978) and was demonstrated to be responsible for the
formation of pro-mutagenic and pro-carcinogenic N7-methylguanine- and O6-
74

Chapter 4: Manuscript II
methylguanine- DNA- adducts observed in different target organs of rats, treated with DNA
alkylating pro-carcinogens (Matsumoto and Higa 1966; Sohn et al. 2001).
C
H 3
N +
O -
I
N
CH2 O
O
OH
CH 2 OH
OH OH
β-glucosidase
Glycoside
C
H 3
N + N
IV
O -
H
C O
enzymatic
C
H 3
N + N
DNA
O -
H
CH2 O
spontaneous
II
C
H 3
nucleophilic
attack
C
H 2
V
N +
III
O
+
H3C +
VI
N
+ OH -
Figure 4.1: Metabolic pathways of cycasin and MAM activation, from (Laqueur 1968; Nagasawa et
al. 1972; Sohn et al. 2001). I: cycasin; II: MAM; III: formaldehyde; IV:
methylazoxyformaldehyde; V: methyldiazonium ion, VI: methylcarbonium ion.
However, since earlier cycasin and MAM carcinogenicity studies used high oral doses (4-
500mg kg-1 bw), either as single or as multiple applications over a short exposure period
(Hirono et al. 1968; Laqueur 1968; Fukunishi et al. 1971), it remains unclear whether the
exposure to acute, subchronic or chronic low doses of MAM is sufficient to induce initiate
and/or promote carcinogenic lesions or other adverse effects in the rat kidney.
To elucidate this question, a sensitive rat model for the detection of renal carcinogens was
employed: Eker rats carrying an inherited heterozygous mutation in the tuberous sclerosis
(TSC2) tumor suppressor gene (Yeung et al. 1994; Hino et al. 1995; Kobayashi et al. 1997)
are predisposed to develop renal cancer early of age and were previously characterized to
be highly sensitive towards renal carcinogens (McDorman and Wolf 2002; Hino 2004). For
instance, when treated with a single dose of the DNA alkylating DMN (30mg/kg bw ), 8
months later, Eker rats demonstrated a 70-fold higher average number of tumors per
animal when compared to the corresponding wild type rats exposed under identical
conditions (Walker et al. 1992 8).
Based on above findings it was expected that Eker rats, continuously exposed to low doses
of MAM-acetate (MAMAc, 250µg/kg bw), should present with a detectable increase of preneoplastic
and neoplastic lesions already following 6 months of exposure. Gene-expression
profiling was previously demonstrated to be a sensitive and reliable tool that allows
N 2
75

Chapter 4: Manuscript II
detection of the activation of a specific mode of action of renal or liver carcinogens (toxicity
and carcinogenicity) already after 1 to 14 days of carcinogen exposure in Eker (Stemmer et
al. 2007) or Wistar rats (Ellinger-Ziegelbauer et al. 2004; Ellinger-Ziegelbauer et al. 2005),
respectively. Indeed, an up-regulation of genes involved in the DNA damage response was
reported in livers of DMN-treated Wistar rats after one single dose of 4mg/kg bw (Ellinger-
Ziegelbauer et al. 2004). Thus, gene expression profiling, subsequent to 1-14 days low
dose MAMAc treatment of Eker rats, should allow the detection of a possible DNA damage
response as well as other specific responses associated with the toxicity and/or the
carcinogenicity of MAMAc. The latter in combination with renal pathology and cell
proliferation analysis would therefore allow the determination of the acute toxic effects and
earliest events of MAMAc induced renal tumorigenesis, whereas renal histopathology,
including the assessment of preneoplastic and neoplastic lesions, and cell proliferation
analysis following 3 and 6 months of exposure would allow to determine whether
subchronic and chronic low dose MAMAc treatment of Eker rats manifests in the onset of
preneoplastic and neoplasic renal lesions. Possible sex-specific effects as observed for
other renal carcinogens (Boorman et al. 1992) were addressed via employing male and
female Eker rats.
4.3 Material and Methods
4.3.1 Compound
Highly purified methylazoxymethanol acetate (MAMAc) was purchased from the Midwest
Research Institute, NCI Chemical Resource Repository (64 FR 72090, 64 FR 28205). Prior
to the in vivo experiments, the stability of MAMAc in 0.1M sodium bicarbonate (NaHCO3)
was confirmed by HPLC using a method published previously (Fiala et al. 1976). Stabilized
MAMAc is highly sensitive to hydrolysis by various blood and organ esterases, and
therefore is deacetylated to MAM almost immediately following administration (Zedeck and
Brown 1977)
4.3.2 Animals
Six to ten week old, genotyped heterozygous Tsc2 mutant Eker rats (Tsc2+/-, Long Evans)
were purchased from the MD Anderson Cancer Center, Smithville, Texas, USA and housed
at the University of Konstanz animal research facility under standard conditions. Prior to
76

Chapter 4: Manuscript II
exposure, male and female Eker rats were randomly assigned to dose groups and allowed
to acclimatize to laboratory conditions for 4 weeks.
4.3.3 Short-term experiments
Groups of three male and female Eker rats were gavaged daily with MAMAc (250µg/ kg
BW) dissolved in sterile 0.1M NaHCO3 for 1, 3, 7, and 14 days, respectively (Table 4.1).
Time-matched vehicle controls (n=3) were gavaged with corresponding volumes of 0,1M
NaHCO3.
4.3.4 Subchronic and chronic experiments
Groups of 10 Male and female Eker rats were gavaged with MAMAc (250µg/ kg BW),
dissolved in 0.1M NaHCO3 at five days a week for 3 and 6 months. Time-matched vehicle
controls were gavaged with 0.1M NaHCO3. For post-mortem immunohistochemical
analysis of cell proliferation, 5 of 10 rats per dose group and sex were s.c. implanted with
osmotic ALZET-pumps (Model 2ML1, Charles River Laboratories, Germany) containing 5bromo-2-deoxyuridine
(BrdU, 20mg/ml sterile saline, Sigma Aldrich, Germany) 5 days prior
to sacrifice.
4.3.5 Sample collection
At the end of each treatment period, anesthetized rats were sacrificed by exsanguination
subsequent to retrograde perfusion with PBS and kidneys were collected, longitudinally
sectioned into 5mm slices and stored in RNAlater (Qiagen, Germany) or in PBS buffered
histology fixative buffer, containing 2% paraformaldehyde and 1% glutaraldehyde for
subsequent paraffin embedding and sectioning.
4.3.6 Histopathology
Haematoxilin and Eosin (H&E) stained renal paraffin section were randomized and
histopathological analysis was carried out by light microscopy at 40-400-fold magnification.
Non-neoplastic changes were classified as none (0), mild (1), moderate (2), strong (3), and
severe (4), including intermediate classes (e.g. 0.5, 1.5 etc.), while preneoplastic and
77

Chapter 4: Manuscript II
neoplastic lesions were classified as reported previously (Dietrich and Swenberg 1991).
Absolute numbers and incidences of preneoplastic and neoplastic lesions were determined.
4.3.7 Cell proliferation analysis
Immunostaining: Subsequent to short term experiments (1-14 days), cell proliferation was
evaluated by immunohistochemical staining for proliferating cell nuclear antigen (PCNA)
using monoclonal primary anti-PCNA antibody (PC-10; DAKO, Germany) in paraffinembedded
kidney sections, as described previously (Stemmer et al. 2007).
Five days prior to the sub-chronic (3 months) and chronic (6 months) experiments 5 of 10
rats per dose group and sex were s.c. implanted with osmotic ALZET-pumps (Model 2ML1,
Charles River Laboratories, Germany) containing 5-bromo-2-deoxyuridine (BrdU, 20mg/ml
sterile saline, Sigma Aldrich, Germany) to allow post-mortem immunohistochemical
analysis of cell proliferation. BrdU-immunostaining was performed as described previously
(Stemmer et al. 2007), using a monoclonal mouse anti-BrdU primary antibody (MU247-UC,
Biogenex, USA) diluted 1:100 in Power BlockTM (BioGenex, USA) in an overnight
application at 4°C.
Quantification of S-phase nuclei: Subsequent to short-term, sub-chronic and chronic
experiments, PCNA- or BrdU- positive stained S-phase nuclei were quantified on
randomized sections. 20 microscopic fields (10x ocular, 40x objective) were randomly
chosen within the area of the renal outer cortex and inner cortex/outer medulla. Proximal
and distal tubules and collecting ducts were counted separately per field. A minimum of
1.000 and 500 nuclei were counted in proximal and distal tubules and collecting ducts,
respectively, distinguishing between negative and positive BrdU or PCNA-stained nuclei.
Nuclear labeling indices (LI%) were calculated as positive nuclei/total number of nuclei
counted.
4.3.8 RNA isolation microarray hybridization and gene expression
profiling
RNA isolation from RNAlater fixed kidneys and Affymetrix Rat Genome RAE230A array
hybridization was performed as described previously (Stemmer et al. 2007). Microarray
quality control was performed as published by Elling-Ziegelbauer (Ellinger-Ziegelbauer et
al. 2004). Statistical analysis was performed using Expressionist Analyst software
(Genedata AG, Switzerland). To select significantly deregulated genes due to treatment or
78

Chapter 4: Manuscript II
time (single effects) and to treatment and time (interaction effect), 2-way ANOVA with a pvalue
cut-off of 0.005, combined with a 1.7-fold deregulation threshold for at least one timepoint
was applied. Significantly deregulated genes were subsequently divided into gene
groups with distinct expression profiles over the time-course using self-organizing map
(SOM) analysis. SOM analysis also allowed the identification of genes showing inconsistent
expression between the controls at different time points. Such genes were manually
discarded from the subsequent functional analysis. Using this adjusted dataset, gene
expression ratios of individual genes were calculated by dividing the respective expression
values of single treated replicate samples by the mean expression value of all
corresponding time-matched control samples. Heat-maps were used to graphically display
the relative expression data, after one-dimensional clustering of the genes.
Significantly deregulated genes were characterized according to the physiological role of its
encoded protein, using information from databases, e.g. NetAffx (update: August 2006),
Swissprot, Proteome and Pubmed.
4.3.9 Quantification of O6MG
DNA was isolated and extracted from pooled kidney samples of three replicate animals
using an ABI 340A nucleic acid extractor with two phenol/chloroform and one chloroform
extraction, followed by precipitation with sodium acetate and isopropanol. DNA adduct
formation in kidneys of MAMAc-treated rats was measured by liquid chromatography
coupled with mass spectrometry. The actual analyses were conducted under a pay-for
service contract in the analytical core facility of the Environmental Sciences and
Engineering, University of North Carolina at Chapel Hill, USA, using undisclosed
methodology.
4.3.10 Statistical analysis
Statistical analysis of histopathological and cell proliferation data were carried out using
GraphPad Prism 4® Software. Significant differences in nuclear labeling indices (LI %) or
total number of lesions in treated and control rats were analyzed by Bonferroni’s test for
multiple comparisons. Lesion incidences were tested for significance using the 2-sided
Fisher’s exact test. Ranked non-neoplastic pathology data were analyzed using the
nonparametric Mann-Whitney test.
79

4.4 Results
4.4.1 Gene expression profiling
Chapter 4: Manuscript II
Oral treatment of male Eker rats with MAMAc for 1, 3, 7 and 14 days resulted in only a
small number of significantly deregulated genes in the renal cortex. From overall 59
significantly deregulated annotated genes 15 were down-regulated. Many of the up- and
down-regulated genes demonstrated a transient deregulation, with highest gene expression
values after one day of exposure (Figure 4.2).
Figure 4.2: Heat map of compound-specific unions of genes found significantly deregulated (red:
up-regulated; green: down-regulated) from the corresponding control in MAMAc
induced renal gene expression profiles of Eker after 1, 3, 7 or 14 days of treatment
(n=3 per time-point). Color scale (left side): gene expression ratio.
Interpretation of significantly deregulated genes according to their physiological role and
their direction of deregulation allowed categorization of genes into different functional
classes. MAMAc treatment resulted in a deregulation of two prominent gene clusters
pointing to a reduced transcription and protein synthesis and an up-regulation of the TGFß
pathway. An overview of these categories is given in table 4.1, while specific responses are
detailed below. Other clusters included genes involved in ion homeostasis, intracellular
transport and regulation of the cytoskeleton. Importantly, MAMAc treatment did not result in
genes encoding proteins involved in DNA damage response (Table 4.1 and below).
80

Chapter 4: Manuscript II
Table 4.1: Categories of genes differentially deregulated by MAMAc in Eker- and wild type rats. For the major genes cluster are listed together with their
Genebank accession number and their main biochemical function. For Eker- and wild type rats, the fold deregulation ratios of genes that were
significantly deregulated at least at on time point according to N-way ANOVA are indicated bold in the last four columns.
Cluster Accession
number
Reduced
transcription
Gene title Biochemical category Fold deregulation (mean of three replicate animals
per time-point vs. mean controls)
AI235236 H2AFO H2A histone family member O Regulation of gene expression /
chromatin assembly
BF398015 CBX5 chromobox homolog 5 (Drosophila HP1a) Regulation of gene expression/
chromatin assembly
BI300772 RING1 Ring finger protein 1 Regulation of gene expression/
chromatin assembly
M25804 NR1D1 Nuclear receptor subfamily 1D1 (Rev-ErbAalpha)
BF284190 NR1D2 Nuclear receptor subfamily 1D2 (Rev-ErbAbeta)
BF420722 NFIX Nuclear factor I-X (CCAAT-binding
transcription factor)
Regulation of gene expression
(Transcription factor)
Regulation of gene expression
(Transcription factor)
Regulation of gene expression
(Transcription factor)
AI008883 FKHL18 Forkhead-like 18 (Drosophila) [predicted] Regulation of gene expression
(Transcription factor)
NM_012760 PLAGL1 Pleiomorphic adenoma gene-like 1 Regulation of gene expression
(Transcription factor)
1387874_at DBP D-site albumin promoter binding protein 1 Regulation of gene expression
(Transcription factor)
NM_133303 BHLHB3 Basic helix-loop-helix protein B3 Regulation of gene expression
(Transcription factor)
BG371810 BAT1A ATP-depende nt RNA helicase P4
(Spliceosome RNA helicase Bat1)
NM_053849 PDIA4 Protein disulfide isomerase A4 (CABP2
Calcium-binding protein 2)
Ek d1 Ek d3 Ek d7 Ek d14
0.49 + 0.02 0.64 + 0.06 0.94 + 0.02 0.79 + 0.14
0.79 + 0.20 0.72 + 0.10 0.65 + 0.04 0. 56 + 0.21
0.52 + 0.17 0.83 + 0.13 0.94 + 0.07 0.69 + 0.12
0.57 + 0.10 0.74 + 0.13 0.51 + 0.04 0.33 + 0.08
0.66 + 0.11 0.74 + 0.02 0.45 + 0.02 0.32 + 0.07
0.22 + 0.00 0.28 + 0.01 0.80 + 0.21 0.85 + 0.10
0.94 + 0.07 0.50 + 0.10 1.32 + 0.25 0.73 + 0.18
0.58 + 0.07 0.80 + 0.09 0.86 + 0.05 0.90 + 0.15
0.53 + 0.16 0.94 + 0.09 0.81 + 0.12 1.06 + 0.03
0.56 + 0.15 1.06 + 0.18 0.97 + 0.10 0.99 + 0.07
RNA metabolism (Splicing) 0.88 + 0.03 0.74 + 0.03 0.48 + 0.00 1.10 + 0.07
Protein metabolism (Folding) 0.67 + 0.07 0.47 + 0.05 0.61 + 0.07 0.68 + 0.05
81

TGFß pathway
activation
DNA-damage
response
Accession
number
Chapter 4: Manuscript II
Gene title Biochemical category Fold deregulation (mean of three replicate animals
per time-point vs. mean controls)
NM_012775 TGFBR1 TGF-beta receptor type I (ALK5) Signaling cascades (TGF-ß
family pathway)
L09653 TGFBR2 TGF-beta receptor type II Signaling cascades (TGF-ß
family pathway)
NM_013095 SMAD3 (MADH3 Mothers against decapentaplegic
homolog 3)
NM_020085 PTPRK Protein tyrosine phosphatase, (receptortype,
kappa), extracellular region
Signaling cascades (TGF-ß
family pathway)
Signaling cascades (TGF-ß
family pathway)
Ek d1 Ek d3 Ek d7 Ek d14
1.97 + 0.13 1.66 + 0.19 1.32 + 0.18 1.15 + 0.19
5.07 + 0.79 1.33 + 0.27 3.75 + 1.45 2.08 + 0.73
2.06 + 0.21 1.44 + 0.15 1.06 + 0.11 1.17 + 0.19
2.79 + 0.79 2.78 + 0.30 1.73 + 0.73 1.11 + 0.30
NM_012861 MGMT O-6-methylguanine-DNA methyltransferase DNA damage repair 0.86 + 0.79 0.97 + 0.03 1.03 + 0.17 0.91 + 0.06
NM_012601 MPG N-methylpurine-DNA glycosylase DNA damage repair (BER) 1.15 + 0.11 1.03 + 007 1.14 + 0.04 1.18 + 0.15
AF311054
NM_017141
NM_021662
APEX1 apurinic/apyrimidinic endonuclease 1 DNA damage repair (BER) 1.04 + 0.20 0.79 + 0.20 0.79 + 0.34 0.99 + 0.11
POLB Polymerase (DNA directed). beta DNA damage repair (BER) 1.02 + 0.06 0.96 + 0.09 0.84 + 0.07 0.83 + 0.08
POLD polymerase (DNA directed). delta DNA damage repair (BER) 0.92 + 0.12 1.06 + 0.34 1.11 + 0.22 1.11 + 0.35
82

Chapter 4: Manuscript II
DNA damage response: Due to the known genotoxic action of MAMAc, special focus was
set on genes coding for proteins that could be indicative for a MAMAc induced DNA
damage. However, genes involved in the expected O6meG adduct repair, including O6methylguanine-DNA
methyltransferase (MGMT) and enzymes of the base excision repair
pathway involving N-methylpurine-DNA glycosylase (MPG), apurinic endonuclease
(APEX), DNA polymerase ß and δ (Sedgwick et al. 2007) were not up-regulated in MAMAc
treated male rats (Table 4.1). Deregulating of other genes involved in DNA damage repair,
cell cycle arrest or apoptosis could also not be detected (data not shown).
Reduced mRNA synthesis: The most prominent deregulated gene cluster detectable after
MAMAc treatment includes 11 of the overall 15 down-regulated genes point to a decreased
overall mRNA synthesis, including down-regulated genes involved in chromatin remodeling
(H2A, CBX5, RING1), basic transcription factors (e.g. PLAGL1, NR1D1, NR1D2, NFIX,
FKHL18, DBP, BHLHB3), RNA splicing and translation (BAT1A).
Signaling cascades: Up-regulated genes and gene-clusters following MAMAc treatment
included 4 genes involved in TGFß signaling (TGFBR1, TGFBR2, SMAD3 and PTPRK),
see table 4.1.
4.4.2 Non-neoplastic renal pathology
Up to 6 months treatment with MAMAc did not result in overt renal non-neoplastic
pathology in male or female Eker rats when compared to the respective controls
(Supplementary tables 4.1 and 4.2). Both MAMAc treated and control rats of either sex
presented with minimal renal pathology i.e. cell shedding, tubular dilatation, protein casts,
tubular regeneration and chronic progressive nephropathy (Table 4.2). Notably, epithelial
vacuolar degeneration in the corticomedullary was observed exclusively in MAMAc treated
and control female rats, while this was absent in the corresponding male rats.
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Chapter 4: Manuscript II
Table 4.2: Non-neoplastic renal pathology of male and female Eker rats treated with MAMAc for
three and six months respectively. Histopathological changes were ranked from none
(0) to severe (4) including intermediate classes. Values are presented as median ±
median absolute deviation.
3 months 6 months
males females males females
Control MAMAc Control MAMAc Control MAMAc Control MAMAc
Necrosis 0.0 + 0.0 0.0 + 0.0 0.0 + 0.0 0.0 + 0.0 0.0 + 0.0 0.0 + 0.0 0.0 + 0.3 0.5 + 0.3
Apoptosis 0.0 + 0.0 0.0 + 0.0 0.0 + 0.0 0.0 + 0.1 0.0 + 0.0 0.0 + 0.0 0.0 + 0.0 0.0 + 0.0
Karyomegaly 0.0 + 0.0 0.0 + 0.0 0.0 + 0.1 0.0 + 0.1 0.0 + 0.0 0.0 + 0.0 0.0 + 0.0 0.0 + 0.1
Vacuolization 0.0 + 0.0 0.0 + 0.1 0.0 + 0.2 0.0 + 0.0 0.0 + 0.0 0.0 + 0.2 2.0 + 0.4 1.5 + 0.6
Cell shedding 1.0 + 0.6 0.8 + 0.3 1.0 + 0.3 0.5 + 0.3 1.0 + 0.6 0.5 + 0.3 1.0 + 0.4 1.0 + 0.3
Protein casts 0.3 + 0.6 0.3 + 0.3 0.5 + 0.5 0.5 + 0.4 1.0 + 0.5 1.3 + 0.6 0.0 + 0.7 1.0 + 0.7
Tubular
dilatation
0.5 + 0.5 0.5 + 0.2 1.0 + 0.6 0.8 + 0.4 0.5 + 1.0 1.0 + 0.3 0.5 + 0.5 0.5 + 0.3
Ca 2+ Casts 0.0 + 0.4 0.0 + 0.1 0.0 + 0.2 0.0 + 0.4 0.0 + 0.0 0.0 + 0.2 0.0 + 0.0 0.0 + 0.2
Regeneration 0.5 + 0.2 0.5 + 0.3 0.3 + 0.4 0.5 + 0.2 0.0 + 0.5 1.0 + 0.3 0.5 + 0.5 0.5 + 0.4
CPN 0.5 + 0.2 0.5 + 0.2 0.5 + 0.2 0.5 + 0.4 0.8 + 0.5 1.0 + 0.3 1.0 + 0.3 0.8 + 0.4
Inflammation 0.3 + 0.3 0.0 + 0.1 0.5 + 0.2 0.0 + 0.1 0.5 + 0.4 0.3 + 0.3 0.5 + 0.3 0.0 + 0.3
Pigment
deposit
0.1 + 0.2 0.0 + 0.1 0.1 + 0.2 0.0 + 0.1 0.0 + 0.1 0.0 + 0.2 0.0 + 0.3 0.0 + 0.1
4.4.3 (Pre)-neoplastic renal pathology
Histopathological analysis demonstrated the occurrence of preneoplastic and neoplastic
lesions of different progressional stages, i.e. basophilic atypical tubules (bATs), basophilic
hyperplasia (bAHs), adenomas and carcinomas of a basophilic phenotype in all groups
examined. Representative images of preneoplastic and neoplastic lesions are shown in
Figure 4.3, A-C.
One to 14 days MAMAc treatment did not result in a significant increase of preneoplastic
and neoplastic lesions in either sex. Yet a clear, but non-significant increase in total bAT
numbers were found in 14 days (Figure 4.4, A and B).
84

Chapter 4: Manuscript II
Figure 4.3: Representative preneoplastic lesions as observed in H&E stained renal sections (A)
bAT; (B) bAH, (C) carcinoma, (D) BrdU staining.
Although a 100% incidence of bATs was found in all treatment and control groups after
three and six months of exposure, no significant increase of absolute numbers could be
detected in MAMAc treated males, when compared to the respective controls (Figure 4.4, C
and D). Only female Eker rats presented with a significant 1.7-fold increase of bATs after
three months of MAMAc treatment (Figure 4.4, C). However, the latter effect appeared to
be transient as it was not seen in the 6 month treated females (Figure 4.4, D). A higher yet
non-significant total number and incidence of microscopically detected adenomas and
carcinomas was present in 6 months MAMAc treated male than in female rats, when
corrected for the numbers and incidences observed in the respective controls.
85

Chapter 4: Manuscript II
Figure 4.4: Mean number of preneoplastic lesions in male and female Eker rats after 1, 3, 7 and 14 days (A-B) or 3 and 6 month (C-D) of MAMAc exposure
compared to the respective control groups.Light grey bars: bAT; white bars: bAHs, black.
86

4.4.4 Cell proliferation
Chapter 4: Manuscript II
Site-specific cell proliferation analysis was assessed via PCNA and BrdU immunostaining
(Figure 4.3, D) after acute and chronic MAMAc treatment respectively. In general nuclei
with positive PCNA staining were rare (below 1% of all nuclei counted) and mainly localized
in proximal tubules of the inner and outer cortex. As demonstrated in figure 4.5, A, 14 days
treatment with MAMAc resulted in no significant change in cell proliferation rate in the
proximal tubules in the outer or inner cortex of male Eker rats. In contrast 14 days
treatment of females with MAMAc resulted in a significant 1.5 fold increase of cell
proliferation in the inner cortex compared to the time-matched controls (Figure 4.5, B).
Figure 4.5: (A-B) PCNA S-Phase mean labeling indices (LI %) in the outer and inner renal cortex
of 14 days MAMAc treated male (A) and female (B) Eker rats, respectively (n=3 per
group). (C-F) BrdU S-Phase mean labeling indices of male and female Eker rats
treated with MAMAc for 3 (C-D) and 6 months (E-F), respectively (n=5 per group). Data
represent the mean + SD. Significant differences between treated and time-matched
control groups was analyzed using one-way ANOVA and Bonferroni's Post Test for
multiple comparisons (*p < 0.05; **p < 0.01 and ***p

Chapter 4: Manuscript II
BrdU-immunostaining based analysis of cell proliferation demonstrated no significant
changes in cell proliferation rates in proximal tubules of three or six month treated male rats
(Figure 4.5, C-F). Female rats showed a transient 1.8 fold increase of cell proliferation after
3 months of MAMAc treatment in the inner cortex, whereas this was not observable after 6
months of treatment (Figure 4.5, D and F). Distal tubules and collecting ducts did not show
a significant increased cell proliferation compared to the control animals (data not shown).
4.4.5 Detection of O6MG in MAMAc treated Eker-rats
LC-MS/MS analysis of 100µg of pooled DNA, from three animals of the same treatment
group i.e. 1, 7 and 14 days treatment, demonstrated a time-dependent accumulation of
O6MG (Figure 4.6). Concurrent O6MG adduct levels in the corresponding control rats were
under the limit of detection. MAMAc treated female rats demonstrated slightly higher O6MG
adduct levels than the corresponding treated males at all time-points examined.
Figure 4.6: Number of O6MG adducts per 106 dG detected via LC-MS/MS in DNA of male and
female Eker rats after 1, 7 and 14 days of MAMAc treatment (n=1, with DNA pooled
from three replicate animals)
88

4.5 Discussion
Chapter 4: Manuscript II
Cycasin and its active metabolite MAM(Ac) were shown to be carcinogenic in rodents when
administered at very high doses (Hirono et al. 1968; Laqueur 1968; Fukunishi et al. 1971).
However, the use of high doses of carcinogens may not reflect the carcinogenic potential of
a test compound und realistic exposure scenarios, since unspecific additional enhancing
effects such as cytotoxicity and regenerative cell proliferation may occur at the high doses
employed (Ames and Gold 1990; Foran 1997; Cohen and Arnold 2008). In addition, dosedependant
differences in metabolism, as well as in pharmacokinetics of a compound, could
also have an influence on carcinogenesis.
Previous studies with rats exposed to low doses of DNA alkylating compounds
demonstrated that short-term treatment with genotoxic (renal or hepatic) carcinogens
resulted in a characteristic expression profile, including the up-regulation of numerous
genes involved in DNA damage response, cell cycle arrest and apoptosis (Ellinger-
Ziegelbauer et al. 2004; van Delft et al. 2004; Ellinger-Ziegelbauer et al. 2005; Stemmer et
al. 2007). Consequently and based on its genotoxic properties, it was assumed that
MAMAc would result in a similar expression profile as observed for other DNA alkylating
compounds, even when administered at low doses. However, contrary to expectations
treatment with 250µg/kg BW MAMAc did not result in an up-regulation of the expected
genes, i.e. genes involved in DNA damage response, cell cycle arrest and apoptosis (Table
4.1). This lack of deregulation observed in the microarray analyses was furthermore
corroborated via quantitative real time PCR. For instance, MGMT, an important protein in
the repair of alkylated DNA, was unchanged in male and female rats of both treatment
groups, and at any exposure time (Supplementary Figure 4.1).
In contrast to the latter, a time-dependent increase of MAMAc induced O6-methylguanine
(O6meG) DNA-adducts in male and female Eker rats was observed (Figure 4.6). The lack
of a measurable DNA damage response, as suggested from the data presented here, may
be explained by: a) a time-dependent accumulation of O6meG DNA-adducts with a
corresponding DNA damage response, yet changes in the DNA damage response genes
were too small to be detected by gene expression analysis; b) the DNA adducts were not
recognized, thereby leading to the observed lack of response at the gene expression level;
and c) the DNA adducts were recognized but not sufficiently repaired with the DNA damage
machinery expressed. The question, whether MAMAc-induced O6meG-adducts were
sufficiently repaired and/or were not sufficiently recognized and therefore not repaired and
thus have the potential to result in the onset of cancer could be answered by comparing
89

Chapter 4: Manuscript II
total numbers of preneoplastic lesions in 3 and 6 months MAMAc treated and control Eker
rats. Indeed, 3 and 6 months exposure to renal carcinogens were previously demonstrated
to be effective in the identification of genotoxic compounds in Eker rats (Walker et al. 1992;
McDorman and Wolf 2002; Morton et al. 2002; Stemmer et al. 2007). Within this timeperiod
genotoxic compounds may cause a second hit mutation in the remaining allele of the
Tsc2 tumor suppressor gene. Therefore, a higher total number of preneoplastic renal
lesions in chronically treated rats would indicate a genotoxic action of MAMAc, and an
insufficient DNA damage response, when compared to vehicle control animals.
However, treatment with MAMAc resulted only in a marginal increase of total numbers of
preneoplastic lesions (bATs and bAHs) at all time-points examined, and statistical
significance was only reached in female rats after 3 months of treatment (Figure 4.4). The
latter corresponding to the increased cell proliferation observed at 3 but not 6 months of
MAMAc treatment in female but not in male rats (Figure 4.5). The concurrent increase of
cell proliferation and preneoplastic lesions not only points to a critical role of cell
proliferation for the formation of renal preneoplastic lesions, but also suggests a higher
susceptibility of female rats towards MAMAc treatment. The latter is corroborated by the
finding that an increased cell proliferation in female but not in male rats was already
detectable after 14 days of MAMAc treatment. Since MAMAc treatment did not induce overt
tubular damage, increased cell proliferation may rather result from a mitogenic mode of
action, than from a regenerative response.
Above data thus suggest higher susceptibility of female rats to MAMAc-induced toxicity
and/or carcinogenicity. Indeed, MAMAc treatment resulted in higher O6meG-adduct levels
in females than in males (Figure 4.6). O6meG-adducts in turn may give rise to guanine to
adenine transitions typically detected as a consequence of this adducts type. In
combination with a higher MAMAc-induced cell proliferation, these mutations may be fixed
before a sufficient repair is possible, and may explain the significantly increased number of
pre-neoplastic lesions in female Eker rats. In contrast in male Eker rats, prolonged
treatment with MAMAc resulted in an increased total number and incidence of kidney
tumors (adenomas and carcinomas), but not in a significant increase of preneoplastic
lesions (Figure 4.4). Thus, in male rats low doses of MAMAc may exert their carcinogenic
action rather by accelerating the progression of pre-existing (hereditary) preneoplastic
lesions, than by lesion initiation. However, since MAMAc did not increase overall cell
proliferation in male rats, tumor promotion cannot be explained by a mitogenic effect of
MAMAc. Another possible mechanism leading to MAMAc tumor promotion is suggested
from the gene expression profiles of male Eker rats treated for 1, 3, 7 and 14 days with
MAMAc. Although a relatively small number of genes appeared to be deregulated by
90

Chapter 4: Manuscript II
MAMAc, the most prominent gene cluster with 20% of all deregulated genes included
down-regulated genes encoding basic transcription factors, and proteins involved in RNA
splicing, translation and folding. This response is in agreement with previous findings of an
early and transient inhibition of DNA-, RNA- and protein synthesis in the rat liver within the
first hours of MAMAc treatment (Zedeck et al. 1970). More importantly, down-regulated
genes included targets that are known for their tumor suppressing properties, such as the
transcription factor PLAGL1, which encodes a growth suppressor protein frequently deleted
in cancer (Abdollahi 2007), or BHLHB3, a candidate tumor suppressor gene in lung cancer
(Falvella et al. 2008), leading to an overall reduced tumor suppressing environment in the
kidney.
In male rats, MAMAc furthermore resulted in an up-regulation of 4 genes involved in TGF-ß
signaling, a pathway which plays an important role in the modulation of cellular functions
such as immune function, cell proliferation, cell motility, glycolysis and epithelial-tomesenchymal
transition (Leivonen and Kahari 2007). TGF-ß signaling is further known to
posses janus-properties, i.e. it can function as a tumor suppressor at early stages of kidney
cancer but it can also promote tumor progression and metastasis in later stages (Gold
1999; Laping et al. 2007). Early stimulation of the TGF-ß pathway in male rats could
therefore still be involved in tumor suppression, but may also result in tumor promotion at
later time-points.
In summary, above findings demonstrate that the combination of sensitive methods such as
gene expression profiling and adduct analysis via LC-MS/MS with established methods e.g.
cell proliferation analysis and histopathology allows to detect earliest carcinogen induced
effects at low dose levels and at time-points when histopathological changes are not yet
readily detectable. Above findings suggests that subchronic and –chronic exposure to low
doses of MAMAc results in gender-specific differences in the carcinogenic response. In
female rats the increase in early tumor stages and absence of late stages may point to a
tumor initiating role of MAMAc, while in male rats, the increase in later tumor stages after 6
months exposure is suggestive of a tumor promoting function.
Acknowledgement:
We would like to thank the Federal Ministry of Education and Research for funding the
project (BMBF: 0313024), Tanja Lampertsdörfer and Gudrun von Scheven, Alexandra
Heussner and Evelyn O’Brien for skilful assistance during the animal experiment, Kerstin
Albrecht for microarray hybridization, Valeriy Afonin for DNA extraction for LC-MS/MS
analysis and Paul T. Pfluger for critically reading the manuscript.
91

4.6 Supplement
4.6.1 Supplementary experimental procedures: Real time PCR
Chapter 4: Manuscript II
To evaluate gene expression by real time PCR, total RNA was extracted from RNAlater
(Qiagen, Germany) fixed renal cortex of 14-days MAMAc treated and control male and
female Eker rats (n=3) using RNEasy Mini Kit (Qiagen, Germany), according to
manufacturer’s instructions. Following DNase treatment, reverse transcriptions were
performed using SuperScript III (Invitrogen) and random primers (Invitrogen). Real-time
PCRs of the house keeping gene hypoxanthin phosphoribosyl transferase (HPRT: forward
primer: aagacagcggcaagttgaat; reverse primer: ggctgcctacaggctcatag) and of candidate
genes O6-methylguanine–DNA methyltransferase (MGMT: forward primer:
cagtaggaggagcgatgagg; reverse primer: gctggaagactcgaaggatg) were performed on an
Eppendorf Cycler using iQ-SybrGreen Supermix (Biorad). All samples were performed in
technical duplicates. Relative amounts of gene-specific mRNAs were calculated via Ct
values, based on a standard curve of five points with known amounts of template cDNA.
4.6.2 Supplementary Figures
Supplementary figure 4.1: Gene expression analysis of MGMT in male and female Eker rats
following 14-days treatment with MAMAc. Data of three replicate animals are shown
as mean + SEM. One-way ANOVA with Bonferroni's post test, demonstrated no
significant difference of male and female MAMAc treated Eker rats vs. the respective
controls.
92

4.6.3 Supplementary Tables
Chapter 4: Manuscript II
Supplementary table 4.1: Non-neoplastic pathology of the renal cortex of male Eker and wild type rats treated with MAMAc for 1, 3 7 and 14 days respectively
(n=3 per group). Histopathological changes were ranked from none (0) to severe (4) including intermediate classes. Values are presented as
median ± median absolute deviation. Incidences are given in parenthesis.
Pigment
Deposits
Necrosis
Apoptosis
Karyomegally
Vacuolization
Cell shedding
Proteinaceous
casts
Tubular
dilatation
Calcium casts
Control (male Eker rats) MAMAc (maleEker rats) Control (female Eker rats) MAMAc (femaleEker rats)
d1 d3 d7 d14 d1 d3 d7 d14 d1 d3 d7 d14 d1 d3 d7 d14
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.0+0.2
(1/3)
0.0+0.0
(0/3)
0.0+0.2
(1/3)
0.5+0.2
(2/3)
0.5+0.2
(2/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.0+0.2
(1/3)
0.0+0.0
(0/3)
0.5+0.2
(2/3)
0.0+0.2
(1/3)
0.0+0.2
(1/3)
0.0+0.0
(0/3)
0.0+0.2
(1/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.0+0.2
(1/3)
0.0+0.0
(0/3)
0.5+0.2
(2/3)
0.5+0.0
(3/3)
0.0+0.2
(1/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.0+0.2
(1/3)
0.5+0.2
(2/3)
0.0+0.0
(0/3)
0.0+0.2
(1/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.0+0.2
(1/3)
0.0+0.0
(0/3)
0.5+0.2
(2/3)
0.5+0.0
(3/3)
0.0+0.2
(1/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.0+0.2
(1/3)
0.5+0.2
(2/3)
0.0+0.0
(0/3)
0.0+0.2
(1/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.0+0.2
(1/3)
0.0+0.0
(0/3)
0.5+0.2
(2/3)
0.5+0.0
(3/3)
0.0+0.2
(1/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.0+0.2
(1/3)
0.5+0.2
(2/3)
0.0+0.0
(0/3)
0.0+0.2
(1/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.0+0.2
(1/3)
0.0+0.0
(0/3)
0.5+0.2
(2/3)
0.5+0.0
(3/3)
0.0+0.2
(1/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.0+0.2
(1/3)
0.5+0.2
(2/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.5+0.0
(3/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.0+0.2
(1/3)
0.5+0.3
(2/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.5+0.2
(3/3)
0.5+0.2
(2/3)
0.0+0.2
(1/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.5+0.2
(3/3)
0.5+0.2
(2/3)
0.0+0.2
(1/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.0+0.2
(1/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.5+0.2
(2/3)
0.5+0.2
(2/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.0+0.0
(0/3)
0.5+0.3
(2/3)
0.5+0.0
(3/3)
0.5+0.2
(2/3)
0.0+0.0
(0/3)
93

Tubular
regeneration
CPN
Inflammation
Chapter 4: Manuscript II
Control (male Eker rats) MAMAc (maleEker rats) Control (female Eker rats) MAMAc (femaleEker rats)
d1 d3 d7 d14 d1 d3 d7 d14 d1 d3 d7 d14 d1 d3 d7 d14
0.0+0.0
(0/3)
0.5+0.2
(2/3)
0.0+0.2
(1/3)
0.0+0.2
(1/3)
0.0+0.2
(1/3)
0.0+0.0
(0/3)
0.0+0.2
(1/3)
0.5+0.2
(2/3)
0.0+0.2
(1/3)
0.0+0.2
(1/3)
0.0+0.2
(0/3)
0.0+0.2
(0/3)
0.0+0.2
(1/3)
0.5+0.2
(2/3)
0.0+0.2
(1/3)
0.0+0.2
(1/3)
0.0+0.2
(0/3)
0.0+0.2
(0/3)
0.0+0.2
(1/3)
0.5+0.2
(2/3)
0.0+0.2
(1/3)
0.0+0.2
(1/3)
0.0+0.2
(0/3)
0.0+0.2
(0/3)
Supplementary table 4.2: Incidence and mean numbers of preneoplastic and neoplastic lesions of the renal cortex. Mean + SD of atypical tubule (AT), aypical
hyperplasia (AH) and neoplastic (adenoma, carcinoma) lesions of male and female MAMAc treated Eker and wild type rats and their respective
controls (n=3). Incidences of respective lesions in treated or control animals are given in parentheses.
Group Sex AT: Mean + SD AH: Mean + SD Neoplastic lesions: Mean + SD
d1 d3 d7 d14 d1 d3 d7 d14 d1 d3 d7 d14
Control male 1.7 ± 0.9 1.3 ± 0.5 2.7 ± 3.8 1.3 ± 1.2 0.7 ± 0.5 0.0 ± 0.0 0.3 ± 0.6 0.3 ± 0.5 0.3 ± 0.5
(3/3) (3/3) (2/3) (2/3) (2/3) (0/3) (1/3) (1/3)
A
0.0 ± 0.0 0.0 ± 0.0 0.0 ± 0.0
(1/3)
(0/3) (0/3) (0/3)
MAMAc male 1.7 ± 1.2 2.0 ± 1.4 1.0 ± 0.8 1.0 ± 0.8 0.0 ± 0.0 0.0 ± 0.0 0.0 ± 0.0 0.0 ± 0.0 0.3 ± 0.5
(2/3) (3/3) (2/3) (2/3) (0/3) (0/3) (0/3) (0/3)
A
0.0 ± 0.0 0.0 ± 0.0 0.0 ± 0.0
(1/3)
(0/3) (0/3) (0/3)
Control female 3.0 ± 2.2 2.0 ± 1.4 1.7 ± 1.5 2.7 ± 0.9 0.0 ± 0.0 0.7 ± 0.5 0.0 ± 0.0 0.3 ± 0.5 0.0 ± 0.0 0.0 ± 0.0 0.0 ± 0.0 0.0 ± 0.0
(2/3) (3/3) (2/3) (3/3) (0/3) (2/3) (0/3) (1/3) (0/3)
(0/3) (0/3) (0/3)
MAMAc female 2.0 ± 0.8 2.7 ± 3.1 2.7 ± 2.5 5.0 ± 1.4 0.3 ± 0.5 0.0 ± 0.0 0.0 ± 0.0 0.0 ± 0.0 0.0 ± 0.0 0.0 ± 0.0 0.0 ± 0.0 0.3 ± 0.5
(3/3) (2/3) (3/3) (3/3) (1/3) (0/3) (0/3) (0/3) (0/3)
(0/3) (0/3)
A
(1/3)
A C
: Adenoma; : Carcinoma
0.0+0.2
(1/3)
0.5+0.2
(2/3)
0.0+0.2
(1/3)
0.0+0.2
(1/3)
0.0+0.2
(0/3)
0.0+0.2
(0/3)
0.0+0.0
(0/3)
0.5+0.0
(3/3)
0.0+0.0
(0/3)
0.0+0.2
(1/3)
0.5+0.2
(2/3)
0.0+0.0
(0/3)
0.0+0.2
(1/3)
0.5+0.2
(2/3)
0.0+0.0
(0/3)
0.0+0.2
(1/3)
0.5+0.2
(2/3)
0.0+0.0
(0/3)
0.0+0.2
(1/3)
0.5+0.2
(2/3)
0.0+0.0
(0/3)
0.0+0.2
(1/3)
0.5+0.0
(3/3)
0.0+0.0
(0/3)
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Chapter 5: Manuscript III
Establishment of a Protocol for the Analysis of Laser
Microdissected Rat Kidney Samples on Affymetrix Genechips
Kerstin Stemmer a, 1 , Heidrun Ellinger-Ziegelbauer b, 1 , Kerstin Lotz b , Hans-J. Ahr b and
Daniel R. Dietrich a, *
a
Human and Environmental Toxicology, University of Konstanz, Konstanz, Germany
b
Molecular and Special Toxicology, Bayer Healthcare AG, Wuppertal, Germany
1
These authors contributed equally to this work.
* Corresponding author: Daniel R. Dietrich: daniel.dietrich@uni-konstanz.de
Published in Toxicology and Applied Pharmacology (2006) Nov 15; 217(1):134-42
5.1 Abstract
Laser microdissection in conjunction with microarray technology allows selective isolation
and analysis of specific cell populations, e.g., preneoplastic renal lesions. To date, only
limited information is available on sample preparation and preservation techniques that
result in both optimal histomorphological preservation of sections and high-quality RNA for
microarray analysis. Furthermore, amplification of minute amounts of RNA from
microdissected renal samples allowing analysis with gene chips has only scantily been
addressed to date. The objective of this study was therefore to establish a reliable and
reproducible protocol for laser microdissection in conjunction with microarray technology
using kidney tissue from Eker rats p.o. treated for 7 days and 6 months with 10 and 1mg
aristolochic acid/kg bw, respectively. Kidney tissues were preserved in RNAlater or snap
frozen. Cryosections were cut and stained with either H&E or cresyl violet for subsequent
morphological and RNA quality assessment and laser microdissection. RNA quality was
comparable in snap frozen and RNAlater-preserved samples, however, the
histomorphological preservation of renal sections was much better following
cryopreservation. Moreover, the different staining techniques in combination with sample
processing time at room temperature can have an influence on RNA quality. Different RNA
amplification protocols were shown to have an impact on gene expression profiles as
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demonstrated with Affymetrix Rat Genome 230_2.0 arrays. Considering all the parameters
analyzed in this study, a protocol for RNA isolation from laser microdissected samples with
subsequent Affymetrix chip hybridization was established that was also successfully
applied to preneoplastic lesions laser microdissected from aristolochic acid-treated rats.
5.2 Introduction
An exponentially increasing number of publications indicate that microarray technology is
now an accepted and powerful tool for large-scale gene expression profiling. However, the
outcome and interpretation of microarray studies can be strongly affected by inherent tissue
heterogenicity. For example the kidney represents a tissue of high complexity with various
structurally and functionally different compartments. It is therefore very difficult to causally
link changes in gene expression patterns from whole kidney homogenates to cell-typespecific
gene expression, the associated pathways and subsequent physiological effects. In
addition, site-specific pathology-related gene expression changes, e.g., within a distinct
tubular segment or a preneoplastic or neoplastic lesion can be diluted by the gene
expression profile of other cell types in a whole tissue homogenate and thus not be readily
detectable. Laser-assisted microdissection could be a useful tool to overcome such
obstacles. Two of the most common technologies are laser capture microdissection (LCM)
(Emmert-Buck et al. 1996) and laser microdissection and pressure catapulting (LMPC)
(Schutze et al. 1998). Both technologies allow the dissection of cell populations, single cells
or even sub-cellular structures from frozen or paraffin-embedded tissues. As the
microdissected structures remain morphologically intact and macromolecules are not
damaged by the laser beam, proteins, DNA or RNA can be isolated for subsequent
analyses. However, the combination of laser-assisted microdissection and microarray
technology has to cope with three main challenges: (1) minimizing RNA degradation over
several tissue (section) processing steps, (2) preserving tissue morphology for accurate
histological examination of lesions selected for microdissection and (3) maintaining the
proportionality of specific RNA species after several rounds of RNA amplification, required
to obtain sufficient RNA for chip hybridization. It is important to conserve high-quality RNA,
as degraded RNA can result in detection of an altered expression pattern (Spiess et al.
2003). RNA must therefore be protected during all processing steps, e.g., tissue harvesting,
storage, sectioning, staining and fixation and finally during microdissection. Most of these
steps are conducted at room temperature. The use of the commercially available stabilizing
reagent RNAlater (e.g., from Ambion or Qiagen) could therefore be a promising tool for
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RNA preservation in cryo-fixed sections. As a first step of the experiments presented here,
the use of RNAlater-preserved to snap frozen tissue with respect to tissue morphology and
RNA quality was compared. Furthermore, the influence of long term-storage, repeated use
of same cryo-samples and different staining techniques on histomorphological tissue
preservation and RNA quality was determined.
Besides maintaining tissue morphology and high-quality RNA, another challenge to be
dealt with is the low amount of RNA obtained from microdissected material. Standard
protocols for microarray analysis are based on starting amounts of 1–5μg total RNA. Yet
laser-assisted microdissection yields at best nanograms of RNA. To overcome this
obstacle, it is necessary to employ RNA amplification methods to generate the required
microgram amounts of RNA. Linear one-cycle mRNA amplification by a T7-based in vitro
transcription (IVT) protocol was first described by Van Gelder et al. (Van Gelder et al. 1990)
and became the standard amplification and labeling protocol for the Affymetrix Chip
technology. A second amplification round can be performed to further increase the RNA
yield. However, a major concern remains as to whether the amplification via IVT maintains
the proportionality of RNA species present in the original sample, since it was shown
previously that gene expression ratios were not completely conserved between linearly
amplified and non-amplified material (Baugh et al. 2001; Goley et al. 2004; Nygaard et al.
2005). Consequently, the comparability of one- and two-cycle amplification protocols on the
gene expression profiles of rat kidney samples was elucidated and presented here. Kidney
samples were taken from rats treated with vehicle control or Aristolochic acid (AA), a potent
genotoxic renal toxicant and carcinogen that was previously shown to induce tumors in
kidney, forestomach and urinary bladder of the rat (Mengs et al. 1982) as well as renal
toxicity, progradient fibrosis and urothelial tumors in women exposed to AA in Chinese
slimming teas (Vanherweghem et al. 1993; Nortier et al. 2000). Based on the results of the
experiments presented here, a protocol for RNA isolation from laser microdissected
samples with subsequent Affymetrix chip hybridization was established that was also
successfully applied to preneoplastic lesions laser microdissected from Aristolochic acidtreated
rats.
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5.3 Material and Methods
5.3.1 Animal treatment and tissue preparation
Chapter 5: Manuscript III
Heterozygous Tsc2 mutant Eker rats were purchased at 6–8weeks of age from the
University of Texas MD Anderson Cancer Center, Smithville, USA. Upon arrival, rats were
allowed to acclimatize to laboratory conditions for 4 weeks. For the short-term experiment
(7-day treatment) three randomly selected male Eker rats were gavaged daily with 10mg
per kg BW Aristolochic acid (AA) per kg BW dissolved in 0.1M sodium bicarbonate, or with
vehicle (0.1Msodium bicarbonate) alone. At the end of the experiment, rats were
anesthetized and then killed via exsanguination subsequent to retrograde perfusion with
PBS. Kidneys were collected, cross sectioned to 5-mm slices and either snap frozen with
liquid nitrogen and stored at −80°C or fixed in RNAlater (Qiagen, Hilden, Germany)
according to the manufacturer's instructions. For the latter procedure, kidney slices were
incubated at room temperature for at least 1h, kept at 4°C for up to 1 week, and then
removed from the RNAlater reagent. From these kidney slices, kidney cortex was isolated
and cortex and medulla stored separately in cryovials at −80°C. The RNA of the kidney
cortex samples fixed in RNAlater was used for the comparison of the one- and two-cycle
protocols shown in Figs. 3–5. In the long-term exposure (6months) five male Eker rats per
group were gavaged on 5 days per week for 6months with 1mg per kg BWAA dissolved in
0.1M sodium bicarbonate and with vehicle (0.1M sodium bicarbonate) respectively.
Following treatment, kidneys were collected as described for the short-term experiment
(above) and then stored using two different protocols: one set of kidney cross-sections was
stored in RNAlater as described above, and a second set of kidney slices was snap frozen
in liquid nitrogen immediately after harvesting and subsequently stored at −80°C. The
kidney samples of these animals were used for results shown in (Figs. 1, 2, and 6) and in
all tables.
5.3.2 Sectioning and staining
Due to the high chaotrophic salt concentration of the RNAlater reagent, RNAlater preserved
samples will not freeze in the cryostate and thus were thawed and then washed for 2×5min
or 2×15min in ice-cold RNase-free PBS. For embedding samples were refrozen in the
cryostate at −20°C. To avoid interference of frozen tissue embedding reagent OCT
(Cryoblock, medite Medizintechnik GmbH, Burgdorf, Germany) with laser efficiency and
RNA isolation, samples were frozen only on a small drop of OCT instead of being fully
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embedded in the medium. Both RNAlater- and snap-frozen kidney samples were cut to 10μm-thick
sections on a cryotome. Sections were mounted onto RNase-free membranecovered
slides (PALM Microlaser GmbH, Bernried, Germany) and air-dried on ice for 20 s.
Subsequently, sections were fixed in ice-cold 70% ethanol (RNase-free) for 3min and airdried
for 5 to 10min. For H&E (hematoxylin–eosin) staining, air-dried sections were stained
with RNase-free Mayer's hematoxylin (Sigma Aldrich, Taufkirchen, Germany) for 3min,
rinsed with RNase-free tap water and counterstained with RNase-free eosin Y (Sigma
Aldrich, Taufkirchen, Germany), for 3min. For cresyl violet staining, ethanol-fixed sections
were stained with 1% (w/v) cresyl violet acetate (Sigma Aldrich, Taufkirchen, Germany) in
ACS-grade 100% EtOH for 20s. Excess staining solution was removed by placing the
sections on an absorbent surface. Subsequent to H&E or cresyl violet staining, sections
were dehydrated by shortly dipping the sections in 70% and then 100% ethanol. For further
information, see the customer protocol page of the PALM homepage at: www.palmmicrolaser.com.
5.3.3 Laser-assisted microdissection
For laser-assisted microdissection, a PALM laser microdissection and pressure catapulting
(LMPC) system (PALM Microlaser GmbH, Bernried, Germany) was used. Areas of variable
size were dissected from H&E-stained whole kidney sections (cresyl violet-stained sections
were not used due to the poor histomorphological preservation of the sections, see below).
The microdissected samples were collected in a non-contact and contamination-free
manner, immediately lysed by addition of 300μl RLT lysis buffer (RNeasy Micro Kit, Qiagen,
Hilden, Germany) containing 1% of β-mercaptoethanol (Sigma Aldrich,Taufkirchen,
Germany) and stored at −80°C. For quality control, total RNA was isolated from additional,
non-dissected and unstained whole sections from each kidney examined.
5.3.4 RNA isolation and quality control
RNA of microdissected tissue was isolated using the RNeasy Micro Kit (Qiagen, Hilden,
Germany). RNA from whole kidney cortex immersed in RNAlater was isolated with Qiagen
RNeasy Mini Kits. All isolations were performed according to the manufacturer's
instructions. The quality of the total RNA was analyzed with the Agilent 2001 Bioanalyzer
(Agilent Technologies GmbH, Germany) using RNA 6000 Nano or Pico chips. Agilent 2100
expert software was used to determine RNA quality, designated as RNA Integrity Number
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(RIN). RIN is calculated from the entire electrophoretic trace by Agilent 2100 expert
software and thus represents the relative ratios of several RNA regions, e.g., the 5S rRNA
region, the region between the 5S and 18S rRNA and the 18S and 28S rRNA bands.
Based on more than 1000 RNA samples of different quality, an algorithm was generated
that describes RNA integrity much more reliably then than the mere ratio of the ribosomal
(18S and 28S rRNA) bands. A RIN of 7–10 is indicative of high RNA quality, whereas a RIN
of 1 marks a completely degraded RNA sample (Schroeder et al. 2006). For RNA
concentrations ≥5ng/μl (kidney cortex samples), the RNA quantity was determined using
Ribogreen (Molecular Probes, Eugene, USA). For lower RNA concentrations (LMPC
samples) the RNA quantity estimate by the Agilent 2100 expert software was utilized. Data
were statistically analyzed using GraphPad Prism 4 software with oneway ANOVA followed
by Bonferroni's post test for multiple comparisons or Student's t-test for individual
comparisons.
5.3.5 RNA amplification
For the synthesis of biotin-labeled cRNAwith one or two rounds of amplification, the
Affymetrix One-cycle and Two-cycle kits were used according to the manufacturer's
instructions, the latter in conjunction with the Megascript T7 kit from Ambion (Austin, USA).
5μg of total RNAwas used for the one-cycle protocol, during which the RNA is first reversetranscribed
in the presence of an oligo-dT primer coupled with a primer sequence for
bacterial T7-polymerase. Following the synthesis of the second cDNA strand, this cDNA
template is then transcribed with T7-polymerase in the presence of biotin-labeled
ribonucleotides to yield biotin-labeled antisense cRNA. The concentration, corrected for
input RNA, and the RNA quality was determined based on OD 260/280 measurement and
the Agilent 2100 Bioanalyzer profile. Up to 50ng of total RNA was employed as starting
material with the two-cycle protocol. After the first round of cDNA synthesis as described
above, unlabeled antisense cRNA was synthesized with the Megascript T7 kit from Ambion
(Austin, USA). The cRNA from this first round of amplification was quantified after column
purification using Ribogreen. The first strand of the second round of cDNA synthesis was
primed with random primers, whereas the second strand was primed with the oligo-dT-T7
primer as described above. Finally, biotin-labeled cRNA was synthesized, quantified and
quality controlled as described for the one-cycle kit.
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5.3.6 Affymetrix chip hybridization and expression profiling
Chapter 5: Manuscript III
15μg of the fragmented biotin-labeled cRNA samples was hybridized on Affymetrix Rat
Genome RAE230_2.0 Genechips according to the manufacturer's instructions.
RAE230_2.0 Genechips contain 31,000 probe sets represented by 11 pairs of 25mer
oligonucleotides. Each probe pair consists of a perfect match oligo (PM) complementary to
the cRNA target sequence, and a mismatch oligo (MM) with a single base change in the
middle to control for background and nonspecific hybridization. Raw data image files (DAT)
were converted into CEL files by averaging the scan data from the 36 pixels per oligo set.
With GeneData Expressionist Refiner software, dark and white spots, gradients and
distortions were detected and corrected using the CEL file data. Using the MAS 5.0
statistical algorithms implemented in the Refiner software, the intensities of all 11 probe
pairs were condensed to one intensity value per probe set associated with a statistical
detection p-value calculated from the intensity differences of the PM and corresponding
MM oligos. This p-value indicates how reliably a transcript is detected. After condensing,
which also includes overall microarray background correction, microarrays were scaled to
an average signal intensity of 100 after excluding the highest 2% and lowest 2% of the
data.
To select significantly deregulated genes between replicate sample groups representing
kidney samples from short-term Aristolochic acid-treated and vehicle control Eker rats, a ttest
(p≤0.005) combined with a 1.7-fold deregulation cut-off implemented in Genedata
Expressionist Analyst software was employed. Genes with an intensity of expression

5.4 Results
5.4.1 Tissue fixation and staining
Chapter 5: Manuscript III
I: Influence of tissue preservation on histology of the sections and on RNA
quality
Degradation of RNA can result in detection of altered gene expression patterns. Therefore,
the question was asked whether tissue preservation with RNAlater would stabilize RNA in
cryosections and whether the required PBS washing steps would negatively influence RNA
stability. Two RNAlater fixed kidney pieces, each of three replicate animals was washed for
2×5min or 2×15min in RNase-free, ice-cold PBS. Subsequently, cryosections were cut and
RNA was isolated from a complete unstained and an H&E-stained section. As control, RNA
was isolated from tissue homogenate of a third, unwashed RNAlater fixed kidney piece.
Table 5.1 depicts the RNA quality of the samples, displayed as RNA integrity number
(RIN).
Table 5.1: Influence of tissue preservation on RNA quality. RNAlater-immersed kidney pieces
from three replicate animals were washed for 2x 5min or 2x 15min in ice-cold PBS
before freezing and cryo-sectioning. RNA was isolated from one unstained or one
H&E-stained section each. Control RNA was isolated directly from RNAlater-fixed,
homogenized kidney cortex. RNA quality is displayed as mean RNA integrity number
(RIN) ± SD. One-way ANOVA and Bonferroni’s post test (p< 0.05(*) and p< 0.01 (**))
suggested the absence of significant differences between the samples.
Sample Staining Washing in PBS RIN (mean and SD of 3 replicates)
Control N/A N/A 8,8 ± 0,5
Section 1 No 2 x 5min 8,8 ± 0,6
Section 2 H&E 2 x 5min 8,0 ± 0,1
Section 3 No 2 x15min 8,6 ± 0,4
Section 4 H&E 2 x15min 7,6 ± 0,7
The RNA quality is very good after 2×5min or 2×15min of washing in ice-cold PBS, with no
significant difference to the control RNA from unwashed RNAlater-fixed tissue. The
comparison with the RNA quality retrieved from snap-frozen tissue (Table 5.2, see below),
RNAlater preservation provided for slightly lower RNA quality.
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Table 5.2: Influence of long-term storage on RNA quality (RIN) and yield (ng RNA). RNA was
isolated from one complete section from the kidneys of 4 replicate animals. Kidney
samples were snap-frozen rather than RNAlater immersed. The duration the tissues
were kept frozen at –80°C as of initial freeze-storing is shown in the first column.
Duration frozen at –80°C RIN (mean ± SD of 4 replicates) RNA ng yield (mean ± SD of 4 replicates)
5 months 9,4± 0,4 681.6 ±103.3
12 months 9,2 ± 0,2 493.5 ±135.7
Kidney morphology from RNAlater-fixed tissue sections was hardly discernible in unwashed
kidney sections and also in sections washed for 2×5min (Figure 5.1, A). Further washing in
PBS appeared to improve the preservation of renal tubular morphological characteristics of
the renal cortical structure (Figure 5.1, B). However, cryosections from RNAlater fixed
tissue never achieved the histomorphological quality of cryosections from snap-frozen
tissue even when stored up to 12months at −80°C (Figure 5.1, C). Use of snap-frozen
kidneys instead of RNAlater-fixed tissue appeared to allow a more precise histological and
pathological examination, especially with regard to the identification of tubular structural
detail, and thus to facilitate the structural identification required for LMPC.
Figure 5.1: Histology of H&E stained sections. (A) Section from RNAlater-fixed tissue after
2x5min washes in PBS. (B) Section from RNAlater fixed tissue after 2x15min washes
in PBS. (C) Section from snap-frozen tissue, without an RNAlater presoak.
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II: RNA stability in snap-frozen kidney samples
Chapter 5: Manuscript III
Since long-term storage of frozen tissue samples may have a negative impact on
preservation of histological features and RNA stability, the influence of cryo-storage on
histomorphological characteristics and RNA quality was investigated with snap-frozen
tissue stored at −80°C for 5 or 12 months post initial cryopreservation. RNA was isolated
from renal cryosections of four independent animals. No significant decrease of RNA
quality (RIN) or yield (ng) could be observed in frozen tissue stored up to 12months at
−80°C (Table 5.2). To elucidate whether repeated “thawing” of tissue samples from −80°C
to cryostate temperature (−18°C to −20°C) has any influence on RNA stability or tissue
morphology, RNAwas isolated from complete cryosections of three replicate animals, that
had been snap frozen, stored at −80°C for 12months, and were then subjected to one or
three cycles of “thawing” and refreezing. The mean RIN number of the respective samples
only slightly decreased from 9.3±0.2 to 8.5±0.2 after the first and the third freeze–thaw
cycle, respectively, yet still providing for high-quality RNA. Microscopic examination of
multiple thawed samples demonstrated that tissue morphology was not adversely affected,
thus also allowing pathological examination and histological differentiation (see also Figure
5.1, C and above).
III: Influence of the duration of section staining procedure on RNA quality
Current working procedures require cryosections to be microdissected at room
temperature. Depending on the number of areas that have to be collected from one specific
cryosection, the actual dissection could last for several hours. However, both time and
temperature could be critical factors for the isolation of high-quality RNA. RNA yield (ng)
and quality (RIN) may in addition be adversely influenced by different staining methods.
However, for kidney pathology H&E staining is indispensable because it facilitates the
distinction of morphological features as well as allows the detection of characteristic
basophilic and eosinophilic preneoplastic and neoplastic lesions (Dietrich and Swenberg,
1991). Therefore, the influence of H&E staining, temperature and LMPC duration on RNA
yield and quality from H&E-stained cryosections was investigated. In addition, RNA stability
of H&E-stained sections were compared with that of cresyl violet-stained sections, since
cresyl violet is a recommended staining method for subsequent RNA applications
(customer protocol page at: http://www.palm-microlaser.com). The comparison of RNA
immediately retrieved from unstained control sections and H&E-stained sections
demonstrated no significant influence of staining on RNA quality (Figure 5.2, 1st and 2nd
bar). Additional handling of the sections at room temperature, up to 3 h, tendentially but not
significantly decreased RNA quality. Additional handling time, 6h to overnight, decreased
RNA quality significantly with RIN number decreasing to values below 7.0 (Figure 5.2, bar
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Chapter 5: Manuscript III
2–6). In contrast cresyl violet staining resulted in a significant decrease of the RIN number
directly after staining (Figure 5.2, 1st and 8th bar). However, as of then RNA quality
appeared to remain stable over time (Figure 5.2, bar 8–12). Storing the differently stained
sections overnight at −20 °C in general appeared to reduce the rate of RNA degradation.
When comparing the RIN numbers of the H&E with the cresyl violet stained sections within
the first 3 h of handling at room temperature, thus representing a reasonable processing
time, H&E sections provided for a higher RNA quality than the corresponding cresyl violetstained
sections. Therefore, RNA of high quality that allows additional RNA processing,
e.g., chip hybridization, can be best obtained from H&E-stained cryosections within 3h post
staining.
Figure 5.2: Kidney tissue was frozen immediately after sacrifice and stored at –80°C for 12
months. RNA was isolated from one complete kidney section of 3 independent
replicate animals. Sections were stained with Hematoxylin and Eosin (H&E, black
bars) or Cresyl Violet (white bars) and subsequently incubated for 0- 6 hours or over
night (ON) at RT or at -20°C. The control sections (1st bar) were lysed immediately
after sectioning. Significant differences, analyzed by Bonferroni’s multiple
comparison test, are indicated using significance levels of p< 0.05(*) and p< 0.001
(**).
5.4.2 RNA quality and yield from pooled microdissected samples
To investigate whether the area of pooled microdissected samples had an influence on
RNA quality and yield, areas of 1mm 2 and 2mm 2 were laser microdissected from H&Estained
cryosections and analyzed. These analyses as shown in table 5.3 suggested that
total RNA from pooled sections were of comparably high quality (RIN >8.0). RNA yields
from both 1mm2 or 2mm2 sections (Table 5.3, also see below) indicated that
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microdissection of an approximate area of at least 2mm 2 was necessary to achieve the
minimum amount of RNA (5ng to 100ng of total RNA) required for the two-cycle
amplification protocol. For area comparison, a cross-sectioned glomerulus has an average
area of 0.02mm 2 .
Table 5.3: RNA quality and yields from pooled microdissected samples. RNA was isolated from
pooled microdissected samples of an overall area of 1mm 2 or 2mm 2 .
Pooled area RIN (mean ± SD of 3 replicates) Yield ng RNA (mean ± SD of 3 replicates)
1mm 2 8,0 ±0,2 3,4 ±0,3
2mm 2 8,3 ±0,4 8,8 ±1,7
5.4.3 RNA amplification and microarray hybridization
I: Influence of one-cycle and two-cycle amplification on the expression profile
Laser-assisted microdissection only yielded nanograms of RNA, thus necessitating global
mRNA amplification for an intended subsequent microarray analysis. Therefore, microarray
experiments with different starting amounts of kidney RNA were subjected to one- or twocycle
amplification to investigate the influence of one-cycle or two-cycle amplification on the
expression pattern. Figure 5.3 depicts that the RNA amplification factor is highly dependent
on the starting amount of RNA. Using 10ng of starting RNA, two-cycle amplification led to a
12,000- to 14,000-fold increase in RNA yield. With 50ng of starting RNA, the same protocol
resulted in 2500- to 3000-fold RNA yield. One-cycle amplification with 5μg of starting RNA
led to a 20- to 30-fold increase of the RNA yield. Irrespective of the amount of starting RNA
or the amplification protocol employed, the RNA yield was comparable (Figure 5.3).
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Figure 5.3: Comparison of total RNA yields after either one-cycle (OC) amplification with 5µg of
starting RNA or two-cycle (TC) amplifications with 10ng or 50ng of starting material,
respectively. Data represent mean yield ±SD (n = 6 replicates).
The latter observation was tested with a Bonferroni's multiple comparison test which
suggested that no significant differences can be observed. This further suggests a
saturation of the amplification process, an artifact that could lead to preferential
amplification of certain genes and consequently in the generation of aberrant expression
profiles. To test this hypothesis, the expression profiles of above samples were analyzed
using Affymetrix Rat Genome RAE230_2.0 arrays. The heat maps in figure 5.4 depict the
ratios of gene expression calculated by dividing the expression values in the single AAtreated
replicate samples by the mean expression value of the corresponding time-matched
control replicates.
Most of the genes selected with both the one-cycle protocol and the two-cycle protocol
starting with 10ng were similarly upregulated after one- and two-cycle amplification. Only
ca. 20% of the genes were qualitatively differently expressed in the two protocols, i.e.,
approximately 80% of the genes were found to be significantly and similarly deregulated
following one-cycle and two-cycle amplification. Furthermore, a preliminary analysis of
specific genes that were deregulated following AA treatment demonstrated that the same
main biological pathways were identified in the two amplification protocols thus suggesting
that no preferential/aberrant gene expression is observed due to differing amplification
protocols (Stemmer et al., in preparation).
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Figure 5.4: Expression profiles of differentially expressed genes. Genes that were assigned to be
differentially expressed after one (OC)- or Two (TC)- cycle amplification of the
indicated amount of RNA from rat kidney after treatment with Aristolochic acid for 7
days were subjected to one-dimensional cluster analysis using Euclidian as distance
metric. The heat maps show ratios of gene expression calculated by dividing the
expression values in the single treated replicate samples through the mean
expression value of all corresponding time-matched control replicates. The left
diagram depicts the genes commonly selected with the TC- (10ng) and the OC-
protocol, the diagram in the middle those specifically selected with the TC (10ng)
protocol, and the diagram on the right those specifically selected with the OC
protocol. The red color illustrates up-regulated and green down-regulated genes
always in comparison to the corresponding control, as indicated by the color scale.
II: Reproducibility of RNA amplification and microarray hybridization
Absolute expression profiles of all genes on a microarray may be influenced by the reagent
lots used. Therefore, hybridization of cRNA prepared at different dates with different
reagent lots was carried out at varying dates. This was done with RNA from the short-term
AA-treated and vehicle control samples described above and whose separation in the
three-dimensional space (PCA) is illustrated in figure 5.5.
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Figure 5.5.: Principal components analysis based on the expression of all genes of the RAE230A
subset (15923 probe sets) on the RAE230_2.0 chip. Black and grey dots depict kidney
samples of control and of aristolochic acid-treated rats, respectively. Ellipses indicate
samples processed with identical protocols. (A) Different amounts of the same RNA
sample subjected to One-cycle (OC) or Two-cycle (TC) amplification. (B) 10 ng of the
same RNA sample subjected to TC amplification and chip hybridization at two
different dates (Feb05, Oct05). (C) 10 ng of the same RNA sample subjected to TC
amplification at two different dates (Feb05, Oct05), yet hybridized on the same day.
The principle components after the one- and two-cycle protocols separate from each other
only in one dimension, whereas the principle components of treated and control samples
separate in another dimensions namely the amplification procedure dimension and the
treatment dimension. The 20% of the total deregulated genes observed that differed
between the two amplification protocols may have been responsible for the shift in the
dimension observed in the PCA (Figure 5.5, A). From these observations it can be
concluded that genes deregulated between treated and control samples can be detected
reliably, as reported above, but that microarrays from treated samples must be compared
with control microarrays employing the identical amplification and hybridization protocol.
Preparation of cRNA at different dates using separate reagent kits leads to a separation of
the overall expression profile in PCA space (Figure 5.5, B). This appears mainly due to the
separate cRNA synthesis and not as a result of microarray hybridization at different dates,
an interpretation that is corroborated by the PCA in figure 5.5, C, for which two separate
cRNA preparations were hybridized on the same day, yielding a very similar dimensional
separation as observed for the PCA in figure 5.5, B. Despite the influence of amplification
protocols and possibly hybridization, profile separation between treated and control is
always maintained. The conclusion of the above findings thus would be that in order to
select differentially expressed genes due to a given treatment, samples of the control and
treatment groups must be prepared using the identical protocol and within the same
protocol handling run.
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5.4.4 Performance of the established protocol
Chapter 5: Manuscript III
To test the reliability of above protocol RNA was isolated from microdissected samples of
control and AA exposed male Eker rats (n=3) of the 6-month experiment for Affymetrix chip
hybridization. Three different types of renal lesions, namely basophilic atypical tubules
(bAT) basophilic hyperplasia (bHA) and chronic progressive nephropathy (CPN), as well as
healthy tissue (HT) of the same rats were excised via LMPC. RNA (5ng) was isolated from
each sample type (lesion type or HT) and analyzed on Affymetrix RAE230_2.0 chips (one
chip per lesion type or HT and animal). Amplification factors were comparable for excised
sample types. A box plot, displaying the absolute expression values after scaling to a mean
target expression value of 100 per microarray, was used as a quality check of the
hybridized chips (Figure 5.6). No outliers or significant variations in chip hybridizations were
found. The data thus demonstrated that the procedure developed generated reproducible
and reliable gene expression determinations.
Figure 5.6. Boxplot analyis of Affymetrix genechip data obtained from microdissected renal
samples. 5 ng kidney RNA isolated from various sample types of rats (n=3) treated
with AA for 6 months. Sample types: healthy tissue (HT), basophilic atypical tubuli
(bAT), basophilic hyperplasia (bHA), and chronic progressive nephropathy (CPN).
Isolated RNA was subjected to two-cycle amplification and Affymetrix RAE230_2.0
chip hybridization. After scaling to a target intensity of 100, the expression intensity
distribution of each Affymetrix chip, corresponding to a given sampletype and animal,
was visualized in a boxplot format. The box itself is limited by lower and upper
hinges, which correspond to the 25% and 75% quantiles, respectively.
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5.5 Discussion
Chapter 5: Manuscript III
Gradual degradation of RNA can introduce a variable bias in the quantification and
amplification of gene transcripts. This degradation, especially during a protocol
encompassing various processing steps, can severely affect the results of downstream
applications, e.g., gene expression profiling. It is therefore crucial to protect the RNA from
degradation in order to obtain reliable gene expression results. RNA integrity numbers can
be used as standard to define an individual minimum threshold of RNA quality. For the
study presented here a RIN number threshold of 7.0 was used. This threshold was chosen
based on recommendations by the manufacturer Agilent, who also provides the RINcalculating
software (Schroeder et al. 2006). The comparison of different preservation and
staining techniques demonstrated that RNA with the required high quality as well as optimal
conservation of tissue morphology can be obtained from cryosections of snap-frozen tissue
samples that were stained with H&E. The latter findings, however, stand in contrast to
previously published data by Ellis et al. (Ellis et al. 2002) where RNAlater-fixed and PBSwashed
pancreas samples provided reasonably good tissue morphology. Thus caution is
advised as to generalizations of fixation and processing protocols, while emphasizing that
protocol optimization procedures, as presented here, are advisable for every animal and
organ prior to embarking on expression profile analyses of microdissected tissue samples.
From all parameters tested, processing of cryosections at room temperature had the most
adverse effect on RNA quality, emphasizing that in order to conserve high-quality RNA
from stained cryosections, 3h of processing should not be exceeded. In addition to
maintenance of RNA quality, standardization of RNA amplification and chip hybridization is
of utmost importance. Indeed, optimization of amplification protocols also entailed starting
with comparable RNA quantities in order to avoid saturation effects, as demonstrated here.
Due to the tubular structure of the kidney, microdissected areas of comparable size (mm 2 )
can vary in RNA yields. A minimum area of 2mm 2 should be microdissected for reliable
RNA quantification and subsequent two-cycle amplification. In addition, it was
demonstrated that samples should be prepared with an identical protocol during the same
time frame and quality analysis by box plot analysis, to ensure reliable gene expression
data. In conclusion, a protocol for laser-assisted microdissection in conjunction with
Affymetrix microarray technology was established that allows investigation of rat kidney
gene expression profiles with high reproducibility and reliability (Figure 5.6). This protocol is
described in detail in Appendix A.
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Acknowledgments
Chapter 5: Manuscript III
We would like to thank the Federal Ministry of Education and Research (BMBF: 0313024)
for funding the project, T. Lampertsdoerfer and G. von Scheven for their skillful assistance
during the whole animal experiment, E. O'Brien and A.H. Heussner for help with the animal
sacrifice.
5.6 Appendix
Recommended protocol for laser-assisted microdissection in conjunction with Affymetrix
microarray technology
1. Collect kidneys from sacrificed animals and section each kidney into ca. 5mm
replicate slices.
2. Wrap kidney slices into sterile (oven baked-RNAse free) aluminium foil and
immediately snap-freeze samples in liquid nitrogen.
3. Use samples directly or store at −80°C.
4. For preparation of cryosections, cool cryostat to −20°C and “thaw” the respective
sample from −80°C to cryostat temperature. It is possible to refreeze the samples at
−80°C for later use. However 3 “freeze and thaw” cycles should not be exceeded.
5. Freeze samples onto a small drop of OCT embedding media in the cryostat.
6. Prepare 10 μm cryosections and mount onto special RNase-free membrane
covered slides, recommended for the respective microdissection system, e.g., the
LMPC system from PALM Microlaser GmbH, Bernried Germany.
7. Air dry freshly cut sections for 20s in the cryostat and subsequently fix them in
−20°C cold ethanol (70% in RNase-free ddH2O) for 3min.
8. Air dry sections for 10min at RT.
9. Stain sections with RNase-free, ice-cold Mayer's hematoxylin for 3min.
10. Rinse with RNase-free tap water for 3min.
11. Counterstain with RNase-free, ice-cold eosin Y for 3min.
12. Remove excess staining solution on absorbent surface and dehydrate section by
shortly dipping into ice-cold 70% and 100% ethanol.
13. Air-dry sections at RT and directly use for laser-assisted microdissection
employing, e.g., the PALM LMPC system (PALM Microlaser GmbH, Bernried
Germany).
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14. For RNA isolation from microdissected kidney samples pool a minimum area of
2mm 2 and collect samples into an appropriate sampling cup of the respective
microdissection system.
15. After completion of the sample collection, immediately lyse pooled samples via
addition of 300μl lysis buffer containing 1% β-mercaptoethanol (e.g., component of
the RNeasy Micro Kit, Qiagen, Hilden, Germany).
16. Do not exceed 3h between staining and lysis of pooled samples.
17. Isolate RNA using e.g. RNeasyMicro Kit (Qiagen, Hilden, Germany) according to
the manufacturer's instruction.
18. Analyze total RNA quality and estimate quantity, using an Agilent Bioanalyzer. For
later amplification and hybridization procedures, use only RNA samples with a RIN
numbers >7.0.
19. Amplify RNA and convert to biotin-labeled cRNA using e.g. the Affymetrix Twocycle
Target labeling kit according to the manufacturer’s instructions. Always use
same starting quantity of RNA, e.g., 5ng or 10ng RNA.
20. Use 15μg biotin-labeled cRNA samples for Affymetrix chip hybridization and
process the hybridizations according to the manufacturer's instruction.
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Earliest preneoplastic renal lesions provide an in-depth
understanding of renal carcinogenesis
Kerstin Stemmer 1 , Heidrun Ellinger-Ziegelbauer 2 , Hans-J. Ahr 2 and Daniel R. Dietrich 1 *
1
Human and Environmental Toxicology, University of Konstanz, Konstanz, Germany
2
Molecular and Special Toxicology, Bayer Healthcare AG, Wuppertal, Germany
* Corresponding author: Daniel R. Dietrich: daniel.dietrich@uni-konstanz.de
American Journal of Pathology, submitted
6.1 Abstract
Although the mTOR pathway appears critical both in human and rat renal tumors, it
remains to be established whether both TORC1 and TORC2 pathways are involved in the
genesis and/or progression of renal preneoplastic lesions to tumors. Eker rats
heterozygous for a mutation in the TSC2 tumor suppressor gene, thus predisposed for the
early development of renal lesions with morphologic similarities with human renal cancer,
were used to analyze the specific involvement of TORC1 and TORC2 in the carcinogenand
sex-dependent formation and progression of preneoplastic lesions.
Our data demonstrate activation of both, TORC1 and TORC2 dependent mTOR pathways
and comparable gene expression profiles in laser-microdissected preneoplastic lesions
from genotoxic (aristolochic acid) and non-genotoxic (ochratoxin A) treated and control
Eker rats. Co-localised immunostaining of phospho-ribosomal protein S6, phospho-Akt
(Ser473) and cytoplasmatic FOXO1 confirmed TORC1 and TORC2 activation, thus
corroborating disruption of the mTOR-AKT feedback inhibition in preneoplastic lesions.
Moreover, the here presented findings strongly suggest that the compound-dependent
formation of preneoplastic lesions is limited to a critical period of time, while lesion
progression appears compound-independent. Therefore, preneoplastic lesion initiation
seems to be influenced by multiple events, whereas clonal expansion appears primarily
dependent on the deregulation of the AKT-TSC2-TORC1 and TORC2-AKT pathways.
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Together these findings indicate that continuous dosing with carcinogens may not have an
augmenting influence exciting lesions. In addition, further in-depth understanding of the
TORC1 and TORC2 balance in preneoplastic lesions may be critical for improved renal
cancer treatment strategies.
6.2 Introduction
The mammalian target of rapamycin (mTOR) pathway is upregulated in several human
cancers (Albanell et al. 2007), amongst which are renal cell carcinomas (Pantuck et al.
2006; Radulovic and Bjelogrlic 2007). Under non-pathological conditions this pathway is
tightly controlled by the tumor suppressor complex tuberous sclerosis 2 (TSC2, tuberin)
and its obligate binding partner, TSC1 (hamartin) (Jozwiak 2006). Inactivating mutations of
TSC2 were shown to be accompanied by Rheb mediated activation of the raptor containing
mTOR complex 1 (TORC1) and its effectors p70S6K, S6 ribosomal protein (S6RP), 4E-
BP1 and eIF4G (Kenerson et al. 2002; Mak and Yeung 2004). As a consequence, TORC1
dependent protein translation is activated, affecting several cell growth regulators, e.g.
stabilization of the transcription factor hypoxia-inducible-growth-factor α (HIF1α)
(Brugarolas et al. 2003), which in turn can drive diverse processes involved in
tumorigenesis, including cell growth, angiogenesis and glycolysis (Semenza 2002).
Moreover, the antiproliferative capacity of TSC2 was shown to be inhibited by the c-Myc
oncogene in vitro (Rosner et al. 2003; Ravitz et al. 2007), demonstrating the broad
dimension of the TSC2 tumor suppressor network. To date, it remains to be established,
whether TSC2 is also involved in the regulation of rictor containing mTOR complex 2
(TORC2). This complex was previously shown to function as an important regulator of the
cytoskeleton through members of the Rho small GTPase family and phosphorylation of
Protein Kinase Cα (PKCα) (Jacinto et al. 2004; Sarbassov et al. 2004), and to
phosphorylate AKT at Ser473, one of the key residues, required for full AKT activation
(Sarbassov et al. 2005). AKT regulates numerous signal transduction processes involved in
cell survival and proliferation, one being direct phosphorylation and inactivation of tumor
suppressor FOXO1 (Manning and Cantley 2007).
Although the mTOR pathway was described to be altered in human renal cancer (Pantuck
et al. 2006) and functional loss of TSC2 was found in spontaneous and chemically-induced
rat renal tumors (Walker et al. 1992; Kubo et al. 1994; Kenerson et al. 2002), it remains to
be established whether the TORC1 and TORC2 pathways are involved in the formation
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and/or progression of renal preneoplastic lesions to tumors. Furthermore the influence of
genotoxic and non-genotoxic carcinogens on these pathways remains unknown.
To characterize the specific involvement of TORC1 and TORC2 in the carcinogen- and
sex-dependent formation and progression of preneoplastic lesions, Eker rats carrying a
heterozygous loss-of-function mutation in the TSC2 gene, therefore predisposed for the
early development of renal lesions with morphologic similarities with human renal cancer
(Yeung et al. 1995; Hino 2004), appeared an ideal model. Therefore, male and female Eker
rats were treated for 3 and 6 months with low doses of the genotoxic aristolochic acid (AA)
(Mengs et al. 1982; Arlt et al. 2002) and the non-genotoxic carcinogen ochratoxin A (OTA),
for which a 10-fold higher tumor incidence was found in male than in female F344 rats
(Boorman et al. 1992; O'Brien and Dietrich 2005). Both are associated with the occurrence
of human urothelial tumors and nephropathy in Balkan countries, suggesting a direct link
between human and rat renal carcinogenesis (Stoev 1998; Grollman et al. 2007).
Compound-induced non-neoplastic and neoplastic renal pathology, site-specific renal cell
proliferation, incidence, phenotype and progression stage of the preneoplastic lesions, and
the rate of preneoplastic lesion progression were determined at the 3- and 6-month timepoint
in both sexes. For the first time, laser-microdissected preneoplastic lesions and
healthy tubules of AA and OTA treated as well as control male Eker rats were analyzed
using microarrays, allowing to investigate gene expression profiles specifically induced by
AA and OTA and to differentiate pathways specific for the progression stage of
preneoplastic lesions. Activation of TORC1 and TORC2 pathways were visualized via
immunohistochemical detection of phosphorylated downstream targets.
6.3 Material and Methods
6.3.1 Compounds
Aristolochic acid sodium salt mixture (AA I: 41% and AA II: 56%) was purchased from
Sigma Aldrich, Germany. Ochratoxin A (>98% purity) was kindly provided by M.E. Stack,
US FDA, Washington DC.
6.3.2 Animals
Eker rats were purchased at 6-8 weeks of age from the University of Texas MD Anderson
Cancer Center, Smithville, USA. Groups of females and males were randomly assigned to
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dose groups (10 rats per compound (or vehicle) and time-point) and acclimatized for 4
weeks. Groups of 10 Eker rats per sex were gavaged with OTA (210µg/kg BW) or AA
(1mg/kg BW), dissolved in 0.1M NaHCO3 at five days a week. Time-matched vehicle
controls were gavaged with 0.1M NaHCO3. 5 of 10 rats per dose group and sex were s.c.
implanted with osmotic ALZET-pumps (Model 2ML1, Charles River Laboratories, Germany)
containing 5-bromo-2-deoxyuridine (BrdU, 20mg/ml sterile saline, Sigma Aldrich, Germany)
5 days prior to sacrifice to allow post-mortem immunohistochemical analysis of cell
proliferation. After 3 and 6 months of treatment, anesthetized rats were sacrificed by
exsanguination subsequent to retrograde perfusion with PBS and kidneys were collected
(Supplementary figure 6.1).
6.3.3 Sample collection
One half of the freshly isolated kidney was cross-sectioned to 5mm slices, slices snap
frozen in liquid nitrogen and stored at -80°C for subsequent cryosectioning. The other half
was fixed in PBS buffered fixative (2% paraformaldehyde and 1% glutaraldehyde) for
subsequent paraffin embedding and sectioning.
6.3.4 Histopathology
H&E stained sections from 10 rats per group were randomized for histopathological
evaluation. Non-neoplastic pathology was classified as none (0), mild (1), moderate (2),
strong (3), and severe (4), while preneoplastic and neoplastic lesions were classified
according to the lesion type (Dietrich and Swenberg 1991) and numbers of each lesion type
counted.
6.3.5 Immunohistochemistry
Cell proliferation was evaluated via BrdU-immunohistochemistry. Immunostaining was
carried out as described previously (Stemmer et al. 2007), yet using a monoclonal mouse
anti-BrdU primary antibody (MU247-UC, Biogenex, USA) diluted 1:100 in Power BlockTM
(BioGenex, USA) in an overnight application at 4°C. Cell proliferation was quantified on
randomized sections. 20 microscopic fields (10x ocular, 40x objective) were randomly
chosen within the area of the renal outer cortex and inner cortex/outer medulla. Proximal
and distal tubules and collecting ducts were counted separately per field, distinguishing
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between negative and positive BrdU-stained nuclei. Nuclear labeling indices for BrdU (LI%)
(BrdU positive nuclei/total number of nuclei counted) were determined. Subsequently, the
LIs of proximal tubules without pathological changes were determined. For LI(%)determination,
at least 1.000 and 500 nuclei were counted in proximal and distal tubules
and collecting ducts, respectively.
Immunohistochemistry of phospho-S6 ribosomal protein (pS6RP), phospho-Akt (pAKT) and
FOXO1 in paraffin sections was carried out according to manufacturers’ instructions (Cell
Signaling Technology). Primary rabbit anti-pS6RP (Ser235/236), (Cat No: 2211) was
diluted 1:100, while rabbit anti-p-AKT (Ser473) (Cat No: 3787), was diluted 1:10 and rabbit
anti-FOXO1 (Abcam ab39656) 1:200 in 5% normal goat serum. Antigen–antibody
complexes were visualized using the Super SensitiveTM (BioGenex, USA) alkaline
phosphatase-labeled, biotin–streptavidin amplified detection system and Fast Red as
chromogen.
6.3.6 Laser microdissection and RNA isolation
For microdissection of preneoplastic lesions from H&E stained renal cryosections, a laser
microdissection and pressure catapulting (LMPC) system (ZEISS, Germany) was used.
Atypical tubule (bAT), basophilic atypical hyperplasia (bAH) or healthy tubules (HT) were
micodissected separately (Stemmer et al. 2006) from each of three replicate rats per dose
group. bAT, bAH and HT from each individual animal were pooled. RNA isolation from
pooled samples and subsequent Affymetrix Rat Genome RAE_230A_2.0 chip hybridization
was carried out as previously described (Stemmer et al. 2006).
6.3.7 Microarray data processing and analysis
Microarray quality control was performed as described previously (Ellinger-Ziegelbauer et
al. 2005) and gene expression data were submitted to the NCBI-GEO repository (GSE
10608). For statistical analysis Expressionist Analyst software (Genedata AG, Switzerland)
was used. Significantly deregulated genes per compound and lesion type vs. healthy
tubules of control rats were selected by student’s T-test with a p-value cut-off of 0.005,
combined with a 2.0-fold deregulation threshold. Identical cut-offs were applied for
comparing healthy tubules of AA and OTA treated rats with healthy tubules of control rats.
Heatmaps were used to graphically display the relative expression data after one-
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dimensional clustering of the genes. See supplemental information for details on the
validation of microarray data.
For functional analysis, significantly deregulated genes were characterized according to the
biochemical role of its encoded protein, using information from databases, e.g. NetAffx,
Swissprot, Proteome and Pubmed. Depending on the direction of deregulation, genes were
further assigned to pathophysiological categories allowing the comparison of deregulated
pathways in different types of lesions and healthy tubules.
6.3.8 Statistical analysis
Statistical analysis of histopathological and cell proliferation data were carried out using
GraphPad Prism 4® (USA). Significant differences in nuclear labeling indices or total
number of lesions in treated and control rats were analyzed by Bonferroni and Dunnett’s
test for multiple comparisons. Lesion incidences were tested for significance using the 2sided
Fisher’s exact test. Ranked non-neoplastic pathology data were analyzed using the
nonparametric Mann-Whitney test.
6.4 Results
6.4.1 Non-neoplastic pathology
Treatment of male and female Eker rats with AA or OTA resulted in increased nonneoplastic
renal pathology compared to respective control rats (Supplementary table 6.1).
OTA treatment significantly and time-dependently increased chronic progressive
nephropathy (CPN), as characterized by a thickened basal membrane, an increased
regeneration and monocytes infiltration in both sexes (Supplementary figure 6.2). In
agreement with previously described OTA-induced non-neoplastic pathology (Boorman et
al. 1992; Rasonyi et al. 1999), male and female Eker rats treated with OTA for 6 months
presented with increased apoptosis, necrosis, karyomegally, prevalence of dilated tubule
and protein casts, as well as an increased tubular regeneration and inflammatory response
primarily within the inner cortex. In contrast, treatment with AA resulted in weaker pathology
compared to OTA treated rats. A significantly enhanced severity of CPN and inflammation
and an increased prevalence of dilated tubule and protein casts in male rats were observed
only at the 6-month time-point. Moreover, AA treated females generally presented with
weaker pathology than males.
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6.4.2 Cell proliferation
Chapter 6: Manuscript IV
Site-specific cell proliferation (Supplementary figure 6.2, C-F), i.e. specific to proximal
tubule, distal tubule or collecting ducts, was assessed via BrdU immunostaining (Table
6.1). Female Eker rats at the 6-month time-point showed an approximately 2-3-fold higher
basal cell proliferation rate than males at all sites, whereas this was not apparent at the 3month
time-point.
Table 6.1: Comparison of BrdU S-Phase labeling indices (LI%) of Eker rats treated with AA or
OTA for 3 and 6 months, respectively. LI%, determined for proximal tubules (PT)
within randomly chosen fields of the outer or inner cortex, of healthy proximal tubule
(hPT), distal tubule (DT) and collecting ducts (CD). For PT >1000 nuclei were counted,
for DT and CD >500 nuclei were counted. LI% were tested for significance using oneway
ANOVA and Bonferroni's Post Test for multiple comparisons.
Male Eker rats Female Eker rats
3 months treatment Control AA OTA Control AA OTA
# animals 5 5 5 5 5 5
PT outer cortex 2.4 + 0.9 2.1 + 0.7 1.9 + 0.8 1.8 + 0.4 3.3 + 2.1 2.5 + 0.8
PT inner cortex 2.0 + 1.0 2.2 + 1.0 12.3 + 3.5 b,d 2.2 + 0.3 4.8 + 1.5 12.6 + 4.0 b,d
Male Eker rats Female Eker rats
6 months treatment Control AA OTA Control AA OTA
# animals 5 5 5 5 3 5
PT outer cortex 2.0 + 0.4 4.1 + 2.1 4.9 + 0.7 3.7 + 1.2 6.7 + 0.6 4.8 + 0.8
PT inner cortex 2.7 + 1.3 6.6 + 2.8 a 15.6 + 2.0 b,d 4.9 + 1.8 12.2 + 0.8 b,c,e 14.8 + 3.3 b,d
hPT, outer cortex 1.9 + 0.4 2.3 + 0.6 2.6 + 0.6 4.4 + 0.7 5.3 + 0.3 3.9 + 0.6
hPT, inner cortex 1.9 + 0.5 1.9 + 0.4 2.8 + 0.9 4.9 + 1.1 6.3 + 1.3 4.9 + 1.9
DT 1.9 + 1.1 0.9 + 0.5 1.2 + 0.4 4.5 + 2.5 5.3 + 0.8 4.2 + 1.5
CD 1.5 + 1.7 0.9 + 0.5 1.9 + 2.0 4.4 + 1.9 5.4 + 0.2 5.8 + 2.0
a b
Significantly higher than the respective control group (p< 0.05), Significantly higher than the respective
control group (p< 0.001), c Significantly higher in inner, than outer cortex, within the same treatment group
(p< 0.05), d Significantly higher in inner, than outer cortex, within the same treatment group (p< 0.001), e
Significantly higher in 6 months than 3 months treated rats (same sex, compound and tubular segment)
(p< 0.001)
OTA: 3 months OTA-treatment significantly increased cell proliferation rates 6.2-fold and
5.7-fold above controls in the proximal tubules of the inner cortex of male and female rats,
respectively. In contrast, a higher cell proliferation was observed following 6 months OTAtreatment
in the inner cortex of male rats (5.8-fold) compared to females (3.0-fold).
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AA: 3 months AA-treatment did not change cell proliferation rates in the proximal tubules of
the inner or the outer cortex in both male and female rats. However, at the 6-month timepoint
a 2.4- and 2.5-fold increase in cell proliferation in the proximal tubules of the inner
cortex was observed in both males and females, respectively (Table 6.1).
When restricting cell proliferation analysis to proximal tubules with a normal (nonpathologic)
phenotype (Supplementary figure 6.2, A), mean cell proliferation rates were not
significantly different in the outer or inner cortex of control and treated rats of both sexes
(Table 6.1). No increased cell proliferation was observed in proximal tubules of the outer
cortex, distal tubule or collecting ducts of either sex, irrespective of the treatment.
6.4.3 (Pre-) neoplastic pathology
Preneoplastic (atypical tubule (AT) and atypical hyperplasia (AH)) and neoplastic (adenoma
and carcinoma) lesions observed in male and female Eker rats after 3 or 6 months of
treatment were primarily of the basophilic phenotype i.e. bAT (Figure 6.1, A) and bAH
(Figure 6.1,B). Other lesion types, e.g. oncocytic tubules and cysts, were rare and thus not
evaluated further. Despite a 100% incidence of bATs in all treatment and control groups
(Figure 6.1, C and D, Supplementary table 6.2), a time- and compound-dependent increase
of total numbers of bATs and bAHs was observable in treated males and females, when
compared to the respective controls at both time points.
OTA: 3 months OTA-treatment induced a 3.3-fold and a 2.8-fold increase in total bATs in
male and female rats, respectively. A similar increase in bATs was also observed at the 6month
time-point, when compared to the respective controls, suggesting continued OTAinduced
bAT formation in all groups. In males, total numbers of bAH increased approx. 3fold
over the time, while the total number of bAH in OTA-treated females remained at
similar levels at both time-points, indicating a higher formation of preneoplastic lesions in
male rats. This was confirmed by the 80% bAH incidence in male rats compared to the
30% incidence in females (Figure 6.1, D).
AA: A significant 3.0- and 5.6-fold increase of the bATs/rat was observed in female rats at
the 3-and 6-month time-points, while male Eker rats showed a significant 3.5 fold increase
of bATs at the 6-month time-point only (Figure 6.1, D). Similarly, both male and female rats
presented with a higher total number of bAH following 3 and 6-months AA-treatment when
compared to the corresponding controls. However, the bAH/rat ratio was significantly
higher at the 6-month time-point only in female rats.
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Figure 6.1. Representative preneoplastic lesions as observed in H&E stained renal sections (A) bAT; (B) bAH. Mean number of preneoplastic lesions in
AA- and OTA-treated male and female control Eker rats after 3 (C) and 6 months (D). Grey bars: bAT; white bars: bAH. Dunnett’s test: *p < 0.05;
**p < 0.01.
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6.4.4 Gene expression profiling
Chapter 6: Manuscript IV
As preneoplastic lesions exhibited a similar basophilic phenotype in both sexes, gene
expression profile analyses were restricted to preneoplastic lesions of male Eker rats.
Laser microdissected preneoplastic lesions (bAT and bAH) and healthy tubules of AA- and
OTA-treated and control males were analyzed using microarrays in order to investigate
gene expression profiles induced by AA and OTA as well as to differentiate pathways
specific for the progression stage of the preneoplastic lesions.
Preneoplastic lesions: Gene expression profiling of microdissected lesions resulted in
570 significantly deregulated annotated and non-redundant genes when compared to
healthy tubules of control rats. Although different total numbers of genes appeared to be
significantly deregulated in different samples (Table 6.2), visualization of expression
profiles of the union of selected genes revealed a qualitatively similar expression profile in
all preneoplastic lesions, irrespective of treatment or lesion type (Figure 6.2).
Figure 6.2: Heatmap comparing gene expression changes of microdissected bATs and bAHs of
AA, OTA and vehicle treated Eker rats, and microdissected healthy tubule from AA
and OTA treated rats. Expression profiles were compared to microdissected healthy
tubules (HT) of control rats. Gene expression ratios are indicated by the color scale:
Red: upregulated; Green: downregulated.
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Healthy tubules (HT): Gene expression profiles of microdissected morphologically
“healthy” tubules (Supplementary figure 6.2, A) of AA- and OTA-treated rats were
compared with HT of the respective control rats HT(C) to evaluate the effect of AA and
OTA treatment on gene expression in HT after 6 months treatment. Seven and six genes
were significantly deregulated in HT of AA and OTA treated males, respectively of which
the most important ones are listed (Supplementary table 6.3).
Functional analysis of significantly deregulated genes: Functional analysis of genes
deregulated in preneoplastic lesions of treated and control rats identified a number of
pathophysiologically relevant endpoints. Table 6.2 specifies the criteria used to assign
deregulated genes to these categories. The most prominent categories, containing the
majority of deregulated genes, were similar in all lesion types. Moreover, many deregulated
genes of these categories could be directly associated with activated AKT, TORC1 and/or
TORC2 pathways (Supplementary table 6.3 and below), and may result from a functional
loss of the TSC2 gene in preneoplastic lesions (Figure 6.3, C), i.e. genes involved in: Cell
cycle progression (upregulation of CDC2, CCNB1, CCNB2, AURKB; downregulation of
NUP50); cell growth, survival and proliferation (upregulation of CTGF, POSTN, ITGB4,
PINK, IGFBP1 and PIK3AP1; downregulation of FOXOA1); protein synthesis (upregulation
of RPS15A); upregulation of HIF1α target genes involved in angiogenesis (PAI1, CXCR4)
and glucose uptake and glycolysis (PFKM, PFKC, ENO2, PGAM2 and GLUT2);
cytoskeleton rearrangement (upregulation of genes coding for Rac/Rho/Cdc42 signal
transduction proteins e.g. RHOQ, RAC2, PAK3, IQGAP1, CDC42SE1, CDC42EP1,
ELMO2, DOCK6, RAC2 and PLEKHG2; upregulation of PKCα substrates MARCKS and
AKAP12)
Moreover, a direct correlation between functional loss of TSC2 in preneoplastic lesions and
active c-myc oncogene is indicated by upregulation of C-MYC itself and its target genes
EMP1 and EMP3, which may point to additional mutations up- or down-stream of the
TSC2/TSC1 complex (Figure 6.3, A and C).
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Table 6.2: Numbers and categories of significantly deregulated genes in preneoplastic lesions
Endpoints % of all significantly deregulated
annotated genes per group
bAT bAT bAT bAH bAH bAH
C AA OTA C AA OTA
Description
Chapter 6: Manuscript IV
Oxidative stress 2.9 2.7 4.7 1.9 1.4 2.4 Up regulation of ARE target genes and other genes known to be involved in oxidative stress responses. Down
regulation of genes mediating the cellular antioxidant defence
DNA damage
response
4.4 0.9 1.6 1.1 4.1 0 Up regulation of genes encoding p53 target genes and genes coding for proteins involved in DNA damage repair
Apoptosis 4.3 2.4 1.6 3.4 1.4 1.2 Up regulation of pro-apoptotic genes, down regulation of anti-apoptotic genes
Tumour- and
metastasis
suppression
Cell cycle
progression
Cell growth/
survival/
proliferation
2.9 3.0 4.7 2.3 2.7 3.5 Up regulation of genes coding for tumour suppressor genes or genes. Up regulation of tissue inhibitor of
metalloproteinases or down regulation of genes facilitating metastasis
2.9 5.1 5.5 3.1 5.5 3.5 Up regulation of genes involved in DNA replication cell cycle progression, mitotic spindle/ cytokineses or
nucleosome formation.
10.1 8.3 8.6 6.9 6.8 10.6 Up regulation of genes encoding growth and survival factors, (IGF)-PI3K-AKT and the mTOR/S6K pathway
components, anti-apoptotic genes, oncogenes. Down regulation of tumor suppressor genes.
Tumourigenesis 1.4 0.9 1.6 1.1 2.7 1.2 Deregulation of genes with unclear biochemical function, however for which a similar direction of deregulation has
been reported previously in different types of cancer.
Cytoskeleton
rearrangement
Enhanced cell
adhesion
7.2 7.1 7.8 10.7 6.8 7.1 Up regulation of genes coding for Rho-GTPases, other proteins involved in positive regulation of actin
polymerization, actin remodelling, stress fibre formation or microtubule dynamics.
1.4 1.2 0.8 0.8 4.1 2.4 Up regulation of genes coding for cell adhesion molecules
Angiogenesis 2.9 4.5 5.5 1.9 4.1 4.7 Up regulation of genes of the VEGF pathway and functioning in growth and survival of endothelial cells, vascular
development and remodelling.
125

Endpoints % of all significantly deregulated
annotated genes per group
bAT bAT bAT bAH bAH bAH
C AA OTA C AA OTA
Description
Chapter 6: Manuscript IV
Metastasis 1.4 2.7 2.3 3.4 2.7 1.2 Up regulation of genes coding for serin proteinases involved in ECM degradation, down regulation of genes coding
for cell adhesion molecules, or gap junction proteins.
Dedifferentiation 0 6.5 3.9 7.7 0 5.9 Down regulation of genes mediating the physiological homeostasis of the cell and/ or organ. Down regulation of
genes involved in biotransformation
Stromatogenesis 2.9 4.5 6.3 7.7 5.5 12.9 Up regulation genes encoding ECM components and components involved in stroma-cell interaction like integrins or
integrin binding proteins.
Immune response 10.1 15.5 15.6 19.2 15.1 15.3 Up regulation of genes encoding components of the acute phase response, inflammation, innate or adaptive
immunity, complement system, TNF/ cytokine pathway, or up regulation genes coding for proteins involved in
antigen presentation.
Lysosomal
autophagy
1.4 2.7 2.3 1.9 1.4 2.4 Up regulation of genes coding for lysosomal enzymes and proteins of the lysosomal membrane
Energy provision 5.8 4.5 2.3 2.7 4.1 1.2 Up regulation of genes coding for proteins supporting uptake of glucose, lipids and amino acids into the cell, as well
as for proteins supporting glycogenolysis, glycolysis, gluconeogenesis, citrate cycle, and glutaminolysis.
Precursor provision 5.8 8.0 8.6 8.8 5.5 5.9 Up regulation of genes coding for proteins involved in fatty acid synthesis, lipid storage, cholesterol uptake,
cholesterol metabolism and phospholipid / glycolipid synthesis. Down regulation of genes involved in ß-oxidation
fatty acids and amino acid degradation
Protein synthesis
and trafficing
4.3 1.2 3.1 3.4 2.7 3.5 Up regulation of genes involved in protein sorting, vesicular transport or endo-/exocytosis. Up regulation of genes
involved in translation or protein folding in the endoplasmatic reticulum
Protein degradation 4.3 3.3 0 0.4 0 0 Up regulation of genes coding for components of the ubiquitin-dependent protein catabolism
Neuronal
differentiation
2.9 3.3 3.1 2.7 5.5 2.4 Up regulation of genes involved in neuronal signal transmission or neuronal differentiation
Cellular stress 4.3 2.7 1.6 3.1 8.2 3.5 Up regulation of genes involved in the stress kinase-, NFkB-, or HIF pathways pathway or other stress related
pathways involved in hypoxia, acidosis or tubular damage. Down regulation of genes encoding inhibitors of these
pathways and endpoints
Osmotic stress 7.2 1.5 2.3 1.1 1.4 1.2 Up regulation of genes involved in water and sodium resorption, down regulation of genes cell mediating volume
homeostasis. Up regulation of genes involved in hyperosmotic response.
Unknown endpoint 10.1 7.7 6.3 5.0 8.2 8.2 Genes with known biochemical function, but whose deregulation could not be given a specific meaning, due to the
lack of information from literature
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Chapter 6: Manuscript IV
6.4.5 Confirmation of TORC1 and TORC2 pathway activation in
preneoplastic lesions
Above presented gene expression profiles point to a concomitant activation of AKT,
TORC1 and/or TORC2 pathways. To prove this, immunostaining of phosphorylated
ribosomal protein S6 at Ser235/236 (pS6RP) was used as an indicator of TORC1 activity
(Kenerson et al. 2002). Staining of AKT phosphororylated at Ser473 (pAKT) provided
confirmation of active TORC2 since active TORC2 was shown to directly phosphorylate
AKT at Ser473 (Sarbassov et al. 2005).
Figure 6.3. Schematic overview over the postulated processes (incl. activated mTOR, cell clone
survival and expansion) involved in the formation of preneoplastic lesions. (B)
Postulated time curve of tissue adaptation vs. formation of preneoplastic lesions. (C)
Suggested mechanistic involvement of TORC1 and TORC2 dependent mTOR
pathways involved in renal carcinogenesis. Blue: pathways and processes implicated
by gene expression analysis. Red: protein expression or phosphorylation verified by
immunostaining.
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Chapter 6: Manuscript IV
Comparable pS6RP staining was observed within bATs and bAHs of AA, OTA and control
male and female Eker rats (Figure 6.4, A and B). Sporadic preneoplastic tubules were
negative for pS6RP staining (a maximum of 6 bATs in the 6 months AA treatment group).
Positive pS6RP staining was also present in adenomas, carcinomas and oncocytic cysts of
all rats examined. pS6RP positive immunostaining of preneoplastic lesions and tumors may
thus be interpreted as corroborative evidence for activation of the TORC1/S6K/S6RP
pathway.
pAKT-immunostaining of bAT and bAH and tumors resulted in a weak but specific
cytoplasmic and sporadic nuclear staining in treated and control male rats, suggesting the
involvement of TORC2/AKT pathway in renal carcinogenesis (Figure 6.4, C and D).
However, as pAKT staining appeared faint, additional immunostaining of AKT target
FOXO1 was employed, since FOXO1 shuttles from the nucleus to cytoplasm for
degradation when phosphorylated by active AKT (Tran et al. 2003). Since, FOXO1
phosphorylation was demonstrated to be strongly reduced in mice lacking TORC2 member
rictor (Jacinto et al. 2006), cytoplasmatic localization of FOXO1 can be interpreted as
TORC2 dependent AKT activation. Healthy tubules presented primarily with nuclear
FOXO1 staining. In contrast, strong cytoplasmic and nuclear staining in bATs and bAHs
was detected, as expected for deregulated FOXO1 activation and/or half-life (Figure 6.4, E
and F). Thus, the FOXO1 staining pattern further supports activation of the TORC2-AKT
pathway in preneoplastic renal lesions.
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Chapter 6: Manuscript IV
Figure 6.4: Proof of principle staining for concurrent TORC1 and TORC2 activation in
preneoplastic lesions. Serial sectioned bAT with positive pS6RP (A), pAKT (C) and
cytoplasmatic accumulation of FOXO1 (E). Representative images of bAH
immunopositive for pS6RP (B), p-AKT (D), and FOXO1 (F). Additional images of
pS6RP, p-AKT and FOXO1 are shown in Figure S3
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6.5 Discussion
Chapter 6: Manuscript IV
6.5.1 Compound-induced tubular damage and regenerative cell
proliferation is critical for the formation but not for the progression of
preneoplastic lesions
Increased cell proliferation can result in carcinogenesis, most likely by the fixation of
mutations as well as by survival and promotion of initiated cells (Barrett and Wiseman
1987; Dietrich and Swenberg 1991). By distinguishing nephron specific effects and
“healthy” from pathologically altered nephron-sections, above data demonstrated that AAand
OTA-induced increase of cell proliferation is restricted to pathologically altered
proximal tubules as well as to preneoplastic lesions at the time points evaluated.
If compound induced nephrotoxicity/genotoxicity and accompanying regenerative cell
proliferation is a main contributor to renal carcinogenesis, compound-induced cell
proliferation should correspond to increased numbers and/or progression rates of
preneoplastic lesions in a compound- and sex-specific manner. Indeed the 2-fold higher
cell proliferation in OTA-treated males than in females at the 6-month time-point
corresponded well with the 1.7-fold higher increase of preneoplastic lesions in males than
in females (Figure 6.1, Supplementary table 6.2). Since ratios of bAT and bAH numbers
remained unchanged, the 80% incidence of bAHs in males compared to the 30% in
females (Figure 6.1, D) suggest an earlier onset of preneoplastic lesion development in
males and thus points to a sex-dependent difference in OTA-induced formation of
preneoplastic lesions rather than to an OTA-mediated lesion progression. The sexdependent
difference in formation of preneoplastic lesions, as reported here, may result
from a higher OTA-induced oxidative stress and subsequent DNA damage in male rats
(Kamp et al. 2005). This interpretation is supported by the finding that 14-days oral
treatment of Eker and wild type female rats with OTA resulted in an upregulation of the 8oxoguanine
DNA glycosylase (an enzyme critically involved in the repair of oxidative DNA
damage) than in the corresponding males (Supplementary figure 6.4). Moreover, catalase
expression was reduced in OTA-treated male Eker and wild type rats, while females
showed an increased expression.
The critical role of compound induced nephrotoxicity/genotoxicity and accompanying cell
proliferation for the onset of preneoplastic lesion formation is corroborated by the findings in
the AA-treatment groups. Indeed, the 2-fold higher cell proliferation in female than in male
rats after 3 months of AA-treatment corresponded to the 2-fold higher number of
preneoplastic lesions in females at the same time point. Moreover, a similar sex-dependent
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Chapter 6: Manuscript IV
trend for cell proliferation and preneoplastic lesions, although not as pronounced, was also
observed at the 6 months time-point (Figure 6.1, Supplemetary figure 6.2, Table 6.1 and
Supplemetary table 6.2). As noted for OTA-treated rats, the comparable bAT to bAH ratio in
male and female AA-treated rats is suggestive of only a limited influence of AA on bAT to
bAH progression. The sex-dependent difference in the formation of AA-induced lesions
may result from the previously reported 2-fold higher levels of dG-AAI and dA-AAII DNA
adducts in kidneys of female than male Wistar rats following treatment with oral doses of
0.15mg/kg body weight for 3 months (Arlt et al. 2001). Given a comparable cellular uptake
and metabolism of AA in Eker and Wistar rats, the higher number of DNA adducts and
regenerative cell proliferation observed in female rats may have led to a higher fixation of
mutations and therefore explain the observed corresponding formation of preneoplastic
lesions.
6.5.2 Time dependent tissue adaptation to carcinogen treatment
Gene expression analysis of preneoplastic lesions demonstrated that bATs and bAHs of
control, AA- and OTA-treated male rats were qualitatively indistinguishable (Figure 6.2),
thus supporting the above assumption that once initiated, in a compound- and sexdependent
manner, clonal expansion of preneoplastic lesions is compound-independent.
Moreover, while 14-days AA- and OTA- treatment of Eker and corresponding wild type rats
resulted in substantial gene expression changes in the renal cortex, e.g. response to
oxidative stress and DNA damage (Stemmer et al. 2007), only marginal gene expression
changes were observed in healthy tubules of male rats following 6 months AA- and OTAtreatment
(Figure 6.2). This suggests that part of the renal cells may have the potential to
adapt to compound treatment, thus further supporting the observation that compounds are
important for the formation but not the clonal expansion of preneoplastic lesions. These
findings thus imply the existence of a critical, albeit compound-specific, period of exposure
for genotoxic, or non-genotoxic carcinogens (Figure 6.3, B), where normal renal tissue is
not yet adapted. In this critical period normal renal tissue appears incapable of sufficiently
repairing compound-induced damage despite active regenerative cell proliferation, thus
providing the possibility for fixation of mutations and thereby formation of preneoplastic
lesions.
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Chapter 6: Manuscript IV
6.5.3 Numbers of earliest preneoplastic lesions formed are decisive for
later occurrence of veritable tumors
The existence of a critical period of carcinogen exposure would imply, that extended
compound exposure may add little to the formation of additional preneoplastic lesions
(Figure 6.3, B), thus suggesting that the incidence and number of veritable tumors is
primarily driven by the number of preneoplastic lesions formed during this critical period.
Indeed, the incidences of preneoplastic lesions (bAH) observed in the Eker rat study (80%
in males vs. 30% in females) correspond well to the tumor incidences observed at the end
of the OTA 2-year bioassay (87.2% in male versus 22.9% in female F344 rats) at the same
dose (Boorman et al. 1992). This could imply that the incidence and number of veritable
tumors is primarily driven by the number of preneoplastic lesions initially formed during a
critical period of carcinogen exposure (see above). This interpretation is supported by study
of Wolf and co-workers who reported an indistinguishable number of preneoplastic lesions
and tumors in Eker rats treated with 500 ppm sodium barbital (NaBB) in feed for 4.5
months and sacrificed at 12 months and Eker rats treated with 500 ppm NaBB in feed for
the whole 12 months (Wolf et al. 2000). The latter phenomenon is not restricted to Eker
rats, as confirmed by a previous study (Dietrich and Swenberg 1991), where male NBR
rats, deficient for α2u-globulin and male F344 were initiated with the genotoxic N-ethyl-N-
hydroxyethylnitrosamine (EHEN) and/or promoted with α2u-globulin binding d-limonene for
6 months. D-limonene exposure was demonstrated to induce concentration-dependent
regenerative cell proliferation in F344 but not in the α2u-globulin deficient NBR rats. Both
EHEN and d-limonene treatment resulted in the formation of preneoplastic lesions (AT and
AH) in F344 rats in nearly comparable numbers but not in the formation of veritable tumors.
Similarly, treatment of NBR rats with EHEN or EHEN and d-limonene led to comparable
numbers of ATs and AHs but no tumors. In contrast, treatment of F344 rats with a
combination of EHEN and d-limonene led to highest number of ATs and AHs as well as to
the formation of veritable tumors.
The latter data thus strongly support the observation that the number of preneoplastic
lesions initially formed, resulting from genotoxicity, fixation of spontaneous mutations via a
mitogenic stimulus or regenerative cell proliferation or a combination thereof (Figure 6.3, A
and B), are decisive for the later development of renal tumors in rats.
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Chapter 6: Manuscript IV
6.5.4 The balance of TORC1 and TORC2 pathways determines
preneoplastic lesion progression
Since carcinogen treatment may mainly affect early tumor formation in a compound- and
sex-specific manner, similar gene expression profiles in preneoplastic lesions of AA, OTA
and control Eker rats may point to a central pathway involved in lesion progression.
Functional analysis of deregulated genes in bATs and bAHS as well as
immunohistochemical staining of pS6RP, pAKT and FOXO1 in bATs and bAHs of control,
AA- and OTA-treated Eker rats clearly demonstrated that both mTOR pathways (TORC1
and TORC2 dependant) were activated. The latter may result from a functional loss of the
TSC2 gene in preneoplastic lesions either via loss-of heterozygosity (Yeung et al. 1995) or
additional mutations up- or down-stream of the TSC2/TSC1 complex e.g. the c-myc
oncogene (Figure 6.3, A and C). Eker rat preneoplastic lesion analysis demonstrated an
upregulation of several HIF1α �target genes (Supplemetary table 6.3) and numerous
additional genes involved in downstream responses of HIF1α e.g. angiogenesis and
energy provision (Table 6.2 and S3). The latter findings correspond well to the role of
activated TORC1 shown to regulate several cell growth regulators, including stabilization of
the transcription factor HIF1α (Brugarolas et al. 2003), thereby providing for sufficient
oxygen and energy supply of proliferating cells, e.g. via angiogenesis and glycolysis
(Semenza 2002). Under physiological conditions, activated S6K leads to phosphorylation
and degradation of insulin receptor substrate proteins (Harrington et al. 2004; Shah et al.
2004) and consequently to reduced downstream PI3K-AKT-TSC1/2 activation in
mammalian cells. Since intact S6K dependent negative feedback inhibition and limited
oncogenic PI3K-AKT signaling was still present in growth-limited benign hamartomas
(Kwiatkowski 2003; Manning et al. 2005), continued and uncontrolled activation of both
S6K and AKT could be a critical trigger in the progression of benign to rapidly growing
malignant lesions.
The concomitant activation of TORC1 and TORC2 (Figure 6.3, C and 6.4) and therefore
likely disturbance of feedback inhibition of mTOR-AKT signaling in renal preneoplastic
lesions, as shown here, appears important for survival and clonal expansion of
preneoplastic lesions. Facilitated AKT activation due to TORC2 dependent Ser473
phosphorylation (Bellacosa et al. 2005), would not only further enhance the AKT-TSC2-
TORC1 pathway, but also influence other targets of the oncogenic AKT leading to reduced
apoptosis and cell cycle progression (Table 6.2 and S3).
Moreover, preneoplastic lesion gene expression profiles support the previously shown
function of TORC2 as an important regulator of the cytoskeleton through members of the
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Chapter 6: Manuscript IV
Rho small GTPase family and phosphorylation of Protein Kinase Cα (PKCα) (Jacinto et al.
2004; Sarbassov et al. 2004), which were discussed to play a role in cell proliferation,
transformation and metastasis (Jaffe and Hall 2002). TORC2 dependent AKT
phosphorylation and upregulation of members of the Rho small GTPase family however
also suggest that TORC2 may be important initial formation of preneoplastic lesions.
Indeed, Kenerson and co-workers (Kenerson et al. 2005), demonstrated that rapamycin
inhibited renal preneoplastic progression to veritable renal tumors in Eker rats but not the
formation of earliest preneoplastic lesions, suggesting that the balance between rapamycin
sensitive TORC1 and the insensitive TORC2 may be critical for preneoplastic lesion
survival and clonal expansion. Rapamycin treatment may inhibit only the TORC1/HIF1α
dependent precursor-, energy- and oxygen supply, necessary for rapid clonal expansion of
larger preneoplastic renal lesions to veritable tumors, while TORC2/AKT dependent cell
cycle progression and apoptosis inhibition may be important for the survival and
proliferation of initiated cells and earliest preneoplastic lesions.
6.5.5 Outlook
In view of the current interest in the use of rapamycin, and analogous inhibitors of the
mTOR pathway for treatment of human renal cancer and the close analogy of rat and
human renal tumors, the results presented here suggest that TORC1 inhibitors (e.g.
rapamycin analogues) would reduce the rate of preneoplastic to neoplastic progression but
not the origin of the disease. Concurrent treatment with rapamycin analogues and a
specific TORC2 inhibitor thus holds the promise that growth and survival of both the initial
preneoplastic lesions and advanced progression stages could be specifically affected.
Acknowledgements
We would like to thank the Federal Ministry of Education and Research for funding the
project (BMBF: 0313024), T. Lampertsdörfer, G. von Scheven, A. Heussner and E. O’Brien
for help with the animal experiment, M. Thiel and K. Lotz for microarray hybridization and P.
Pfluger for critically reading the manuscript.
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6.6 Supplemental Material
6.6.1 Supplementary experimental procedures: Real time PCR
Chapter 6: Manuscript IV
To evaluate gene expression by real time PCR, total RNA was extracted from frozen renal
cortex of 14-days OTA treated and control male and female Eker and wild type rats (n=3)
using RNEasy Mini Kit (Qiagen), according to manufacturer’s instructions. Following DNase
treatment, reverse transcriptions were performed using SuperScript III (Invitrogen) and
random primers (Invitrogen). Real-time PCRs of the house keeping gene 18S RNA and of
candidate genes 8-oxoguanine DNA glycosylase (OGG1) and catalase (CAT) were
performed on Biorad iCycler using iQ SybrGreen Supermix (Biorad). All samples were
performed in technical duplicates. Relative amounts of gene-specific mRNAs were
calculated via Ct values, based on a standard curve of five points with known amounts of
template cDNA.
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6.6.2 Supplementary Figures
Chapter 6: Manuscript IV
Supplementary figure 6.1: Overview over the experimental design: The experiments were
performed according to the German Animal Protection Law, approved by the relevant
German authority, the Regierungspräsidium in Freiburg, Germany (registry number:
G-03)
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Chapter 6: Manuscript IV
Supplementary figure 6.2: H&E stained paraffin sections: (A) proximal tubules with a normal (nonpathologic)
phenotype (healthy tubules; HT); (B) chronic progressive nephropathy;
(C-F) representative BrdU staining patterns of different tubular sections: Red nuclei:
BrdU positive, blue nuclei: haematoxylin counterstaining; (C) proximal tubules of the
outer renal cortex (P1/P2 segments); (D) proximal tubules of the inner renal cortex (P3
segments); (E) distal tubules; and (F) collecting duct.
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Chapter 6: Manuscript IV
Supplementary figure 6.3; Representative immunmohistochemical staining of renal paraffin
sections demonstrating positive pS6RP (A), pAKT (B) and cytoplasm accumulation of
Foxo1 (C) demonstrate the concurrent activation of both mTOR pathways.
Representative images of bAHs positively with antibodies against pS6RP (D), pAKT
(E) and Foxo1 (F).
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Chapter 6: Manuscript IV
Supplementary figure 6.4: Gene expression analysis of OGG1 and CAT in male and female Eker
and wild type rats following 14-days treatment with ochratoxin A (Stemmer et al.
2007). Data of three replicate animals are shown as mean + SD. Newman-Keuls
Multiple Comparison Test was performed to test for significance: * < 0.05, ** < 0.01.
139

Supplemental Tables
Chapter 6: Manuscript IV
Supplementary table 6.1: Non-neoplastic renal pathology of Eker rats treated with AA or OTA for
three and six months respectively. Histopathological changes were ranked from none
(0) to severe (4) including intermediate classes. Values are presented as median ±
median absolute deviation.
Male Eker rats 3 months 6 months
Control AA OTA Control AA OTA
Necrosis 0.0 + 0.0 0.0 + 0.1 0.0 + 0.2 0.0 + 0.0 0.0 + 0.2 0.8 + 0.6 b
Apoptosis 0.0 + 0.0 0.0 + 0.1 1.0 + 0.2 a 0.0 + 0.0 0.0 + 0.2 0.3 + 0.4 a
Karyomegaly 0.0 + 0.0 0.0 + 0.2 2.0 + 0.5 a 0.0 + 0.0 0.0 + 0.1 1.8 + 0.5 c
Vacuolization 0.0 + 0.0 0.0 + 1.0 0.0 + 0.4 0.0 + 0.0 0.3 + 0.7 1.5 + 0.9 b
Cell shedding 1.0 + 0.6 1.0 + 0.3 1.3 + 0.5 1.0 + 0.6 1.0 + 0.6 0.5 + 0.4
Protein casts 0.3 + 0.6 0.5 + 0.4 1.0 + 0.6 1.0 + 0.5 1.8 + 0.7 1.3 + 0.9
Tubular dilatation 0.5 + 0.5 0.5 + 0.3 1.0 + 0.6 0.5 + 1.0 1.0 + 0.4 1.0 + 0.8
Calcium Casts 0.0 + 0.4 0.0 + 0.0 0.0 + 0.0 0.0 + 0.0 0.0 + 0.0 0.0 + 0.0
Regeneration 0.5 + 0.2 0.5 + 0.3 1.0 + 0.3 0.0 + 0.5 1.0 + 0.6 1.0 + 0.5 a
CPN 0.5 + 0.2 0.5 + 0.1 1.0 + 0.3 a 0.8 + 0.5 1.5 + 0.4 a 2.0 + 0.3 b
Inflammation 0.3 + 0.3 0.5 + 0.2 0.5 + 0.3 0.5 + 0.4 1.0 + 0.6 a 1.3 + 0.6 a
Deposit of pigments 0.1 + 0.2 0.0 + 0.1 0.0 + 0.3 0.0 + 0.1 0.0 + 0.2 0.3 + 0.4
Female Eker rats 3 months 6 months
Control AA OTA Control AA OTA
Necrosis 0.0 + 0.0 0.0 + 0.1 0.0 + 0.1 0.0 + 0.3 1.0 + 0.6 1.3 + 0.6 b
Apoptosis 0.0 + 0.0 0.0 + 0.1 0.5 + 0.2 c 0.0 + 0.0 0.0 + 0.2 0.0 + 0.2
Karyomegaly 0.0 + 0.1 0.0 + 0.2 1.0 + 0.8 c 0.0 + 0.0 0.0 + 0.3 1.3 + 0.6 c
Vacuolization 0.0 + 0.2 0.0 + 0.0 0.0 + 0.0 2.0 + 0.4 2.3 + 0.9 2.5 + 0.4 b
Cell shedding 1.0 + 0.3 1.0 + 0.4 1.3 + 0.6 1.0 + 0.4 1.0 + 0.5 1.0 + 0.5
Protein casts 0.5 + 0.5 0.5 + 0.3 0.8 + 0.5 0.0 + 0.7 1.8 + 0.9 1.5 + 0.6
Tubular dilatation 1.0 + 0.6 0.3 + 0.7 1.0 + 0.6 0.5 + 0.5 1.0 + 1.0 1.0 + 0.5
Calcium Casts 0.0 + 0.2 0.0 + 0.4 0.0 + 0.1 0.0 + 0.0 0.0 + 0.0 0.0 + 0.1
Regeneration 0.3 + 0.4 0.0 + 0.3 0.0 + 0.4 0.5 + 0.5 1.0 + 0.6 1.0 + 0.5
CPN 0.5 + 0.2 0.5 + 0.3 1.5 + 0.3 c 1.0 + 0.3 1.3 + 0.5 1.5 + 0.3 a
Inflammation 0.5 + 0.2 0.5 + 0.2 0.5 + 0.4 0.5 + 0.3 0.5 + 0.2 1.0 + 0.2 a
Deposit of pigments 0.1 + 0.2 0.0 + 0.1 0.0 + 0.2 0.0 + 0.3 0.3 + 0.4 0.0 + 0.2
a b
Significantly higher than the respective control group. Mann-Whitney test (p< 0.05). Significantly higher
than the respective control group. Mann-Whitney test (p< 0.005). c Significantly higher than the respective
control group. Mann-Whitney test (p< 0.001)
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Chapter 6: Manuscript IV
Supplementary table 6.2: (Pre-) neoplastic pathology of the renal cortex of male and female Eker
rats treated with AA or OTA for three and six months respectively. Incidence and
numbers of bAT, bAH and microscopic (m) and gross (g) tumours (adenoma and
carcinoma) are displayed. Ratios of bATs and bAHs and tumours per rat are
presented as mean + standard deviation. Additional ratios of mean bAT/rat to mean
bAH/rat are indicative for a bAT to bAH progression.
bAT
bAH
Tumor
bAT
bAH
Tumor
Male Eker rats 3 months 6 months
Control AA OTA Control AA OTA
Incidence 10/10 10/10 10/10 10/10 10/10 10/10
Outer cortex 15 27 32 20 66 42
Cortex/Medulla 20 28 84 30 107 107
Total bAT 35 55 116 50 173 150
bAT / rat 3.5 + 2.0 5.5 + 2.6 11.6+2.0 a 5.0 + 3.3 17.3+5.7 a 15.0+2.2 a
Incidence 4/10 5/10 5/10 5/10 8/10 8/10
Outer cortex 1 1 3 1 16 9
Cortex/Medulla 4 4 6 10 15 17
Total 5 5 9 11 31 26
bAH / rat 0.6 + 0.9 0.5 + 0.5 0.9 + 1.0 1.1 + 1.5 3.1 + 2.8 2.6 + 1.9
Ratio 5.8 9.2 12.9 4.5 5.5 5.7
Incidence (m) 0/10 3/10 1/10 1/10 3/10 2/10
Total (m) 0 3 1 1 3 2
Total (g + m) 1 3 1 1 3 5
Tumour / rat 0.0 + 0.0 0.3 + 0.7 0.1 + 0.3 0.1 + 0.3 0.3 + 0.5 0.2 + 0.4
Female Eker rats 3 months 6 months
Incidence 10/10 10/10 10/10 9/9 8/8 10/10
Outer cortex 16 46 24 16 67 36
Cortex/Medulla 19 61 76 12 63 54
Total bAT 35 107 100 28 130 90
bAT / rat 3.5 + 1.7 10.7+6.2 a 10.0+3.3 a 3.1 + 1.3 16.3+4.8 a 9.0 + 3.8 a
Incidence 1/10 3/10 5/10 2/9 7/8 c 3/10
Outer cortex 0 4 0 2 13 2
Cortex/Medulla 1 2 5 0 6 5
Total 1 6 5 2 19 7
bAH / rat 0.1 + 0.3 0.6 + 1.0 0.5 + 0.5 0.2 + 0.4 2.4 + 1.6 b 0.7 + 1.5
Ratio 35 17.8 20.0 15.5 6.8 12.9
Incidence (m) 3/10 0/10 0/10 1/10 1/10 3/10
Total (m) 3 0 0 1 1 3
Total (g + m) 3 0 0 1 2 4
Tumour / rat 0.3 + 0.5 0.0 + 0.0 0.0 + 0.0 0.1 + 0.3 0.1 + 0.6 0.3 + 0.5
a b
Significantly higher than the respective control group. Dunnett`s test (p< 0.01). Significantly higher than
the respective control group. Dunnett`s test (p< 0.05). c Significantly higher incidence than the respective
control group. Fisher`s exact test (p< 0.05). d Mortality: One female control animal died 2 weeks before
sacrifice. Two female AA treated Eker rats died 10 and 3 weeks before sacrifice.
141

Chapter 6: Manuscript IV
Supplementary table 6.3: Genes differentially deregulated in preneoplastic lesions compared to HT of control animals. For the major signalling pathways
(activated (+) or inhibited (-)), genes are listed together with their Genebank accession number and the suspected pathophysiological
consequence of deregulation (endpoint). The mean fold deregulation + SD are given for every lesion type. Significant deregulations vs. HT(C)
were tested by Student’s t- test: b p< 0.005; c p< 0.001 which matched the p-value cut-off of 0.005 and 2.0 fold deregulation cut-off. (a)
Significantly deregulated (p< 0.05), however not matching the chosen p-value cutoff

Accession
number
Protein synthesis NM_053982 RPS15A Ribosomal protein
S15a
Angiogenesis
Glucose uptake
and glycolysis
Cytoskeleton
rearrangement
NM_012620 PAI1 Plasminogen activator
inhibitor-1
AA945737 CXCR4 CXC chemokine
receptor 4
NM_031715 PFKM 6-phosphofructokinase,
muscle (PFK-A)
BM389769 PFKC 6-phosphofructokinase,
type C (PFKP)
AF019973 ENO2 Enolase 2 (Gamma
enolase)
NM_017328 PGAM2 Phosphoglycerate
mutase 2
NM_012879 GLUT2 Glucose transporter
type 2, liver (SLC2A2)
NM_022590 SGLT2 Sodium/glucose
cotransporter2
AA849961 RHOQ Ras homolog gene
family, member Q
NM_019210 PAK3 p21-activated kinase 3
(PAK beta)
BM387072 IQGAP1 IQ motif containing
GTPase activating protein 1
BI275583 CDC42EP1 CDC42 effector
protein
BM389459 CDC42SE1 CDC42 small
effector 2
BM386781 ELMO2 Engulfment and cell
motility protein 2
AI102881 DOCK6 Dedicator of cytokinesis
6 (predicted)
Gene title References (Pub Med
ID)
PMID: 18092230
PMID: 16990457
Chapter 6: Manuscript IV
Fold deregulation vs. HT control (mean and p-value of 3 replicate animals per
lesion)
1.04+
0.15
PMID: 18381294 1.41+
0.96
PMID: 18375114
PMID: 15802268
1.06+
0.32
PMID: 17661163 1.20+
0.28
PMID: 17661163 1.50+
0.27
PMID: 16227210 1.62+
0.62
PMID: 9688259 0.79+
0.32
PMID: 17203215 2.13+
0.30 (a)
PMID: 17581928 2.58+
0.67
PMID: 12234610
PMID: 15467718
1.03+
0.26
PMID: 18054038 0.65+
0.35
PMID: 15890984
PMID: 15890984
1.60+
0.36
NETAFFX 1.11+
0.13
PMID: 10816584 1.26+
0.04 (a)
PMID: 12879077 1.11+
0.25
PMID: 18291711
PMID: 17196961
1.67+
0.03
1.22+
0.11
4.19+
3.74
0.66+
0.37
1.13+
0.67
1.49+
0.67
1.72+
0.65
5.03+
3.47
2.43+
0.49 (a)
1.52+
0.36
1.07+
0.10
0.86+
0.76
1.11+
0.50
0.71+
0.12
1.06+
0.28
1.12+
0.10
1.48+
0.18 (a)
1.48+
0.45
5.85+
2.45 (a)
2.06+
0.31 b
2.54+
0.33 b
3.30+
0.60 (a)
1.79+
0.61
24.40+
5.76 (a)
2.99+
1.39
3.21+
1.71
1.31+
0.15 (a)
0.91+
0.09
3.89+
0.80 b
2.28+
0.70 a
2.24+
0.39 b
2.01+
0.55 (a)
1.44+
0.22
1.95+
0.15 b
4.70+
2.74
1.79+
0.44 (a)
1.60+
0.16 (a)
4.51+
0.56 b
2.22+
0.30 b
6.02+
2.90
11.25+
1.34 c
4.29+
0.77 b
2.36+
0.24 c
14.85+
3.14 c
3.24+
0.7 (a)
1.89+
0.27 (a)
2.45+
0.22 c
2.01+
0.09 b
1.55+
0.25
1.81+
0.44 (a)
13.72+
1.70 c
1.68+
0.25
0.93+
0.22
2.40+
0.25
2.83+
0.88 (a)
1.68+
1.16
13.43+
3.14 c
2.48+
0.10
1.67+
0.33 (a)
6.20+
2.22 (a)
1.75+
0.20
0.84+
0.08
1.77+
0.13 (a)
1.59 +
0.14 (a)
1.73+
0.14 (a)
1.85+
0.48
7.79+
3.17 b
3.11+
0.71 b
1.68+
0.35 (a)
3.09+
0.71 (a)
2.75+
0.43 b
9.54+
2.61 (a)
6.58+
1.16 c
3.51+
1.94 a
1.82+
0.80
8.28+
9.93
3.32+
0.31 b
2.04+
0.27 b
2.21 +
0.22 c
2.23+
0.19 b
1.68+
0.09
1.76+
0.33 (a)
5.34+
3.53
1.41+
0.20 (a)
1.65+
0.32
3.48+
0.69 (a)
2.74+
0.44 b
5.54+
3.54
6.84+
0.84 c
2.25+
0.07 a
1.72+
0.35 (a)
9.82+
3.36 b
2.76+
0.10 b
1.54+
0.18 (a)
2.11+
0.39 (a)
1.65 +
0.28 (a)
1.46+
0.15
2.29+
0.28 b
16.96+
8.25 b
1.97+
0.47
0.85+
0.13
2.22+
0.26
2.83+
0.47 (a)
0.30+
0.12
11.28+
6.21 b
1.97+
0.26
2.01+
0.45 (a)
4.76+
3.36
1.76+
0.12
0.94+
0.16
1.62+
0.29
1.73 +
0.39 (a)
2.11+
0.11 b
143

C-MYC
Accession
number
AI010476 RAC2 Ras-related C3 botulinum
toxin substrate 2 (p21-Rac2)
BF397719 PLEKHG2 Pleckstrin homology
domain containing G2
NM_030862 MARCKS Myristoylated alaninerich
protein kinase C substrate
BG663107 AKAP12 A kinase anchor
protein 12 (gravin)
NM_012603 CMYC Myc proto-oncogene (cmyc)
BI275741 EMP1 Epithelial membrane
protein 1 (TMP Tumorassociated
membrane protein)
NM_030847 EMP3 Epithelial membrane
protein 3
Gene title References (Pub Med
ID)
PMID: 18230340
PMID: 10843388
Chapter 6: Manuscript IV
Fold deregulation vs. HT control (mean and p-value of 3 replicate animals per
lesion)
1.34+
0.39
PMID: 18045877 1.52+
0.21 (a)
PMID: 16109477 1.13+
0.13
PMID: 11282019 1.09+
0.40
PMID: 18056446
PMID: 12894220
PMID: 18056446
PMID: 12894220
PMID: 18056446
PMID: 12894220
1.50+
0.23
1.18+
0.19
1.21+
0.40
1.26+
0.36
1.36+
0.12
0.83+
0.29
2.50+
2.16
1.07+
0.36
1.22+
0.53
0.79+
0.32
2.08+
0.57 a
2.13+
1.08
2.04+
0.48 (a)
2. 77+
1.64
1.87+
0.22 (a)
2.62+
1.03 (a)
2.85+
1.17
1.90+
0.50
1.51+
0.20 (a)
1.37+
0.22
6.82+
0.45 b
2.65+
0.21 (a)
2.08+
0.16 b
2.84+
0.56 b
1.73+
0.32
1.35+
0.14
1.23+
0.14
4.88+
0.16 (a)
3.09+
0.40 b
1.89+
0.40
1.62+
0.10
3.27+
0.50 b
2.25+
0.28 b
2.93+
0.35 b
7.62+
6.33 (a)
2.60+
0.90 (a)
3.38+
0.81 b
2.52+
0.28 b
1.99+
0.58 a
1.53+
0.25 (a)
1.64+
0.38
3.84+
0.33 (a)
2.21+
0.32 (a)
1.92+
0.35 (a)
2.30+
0.50 (a)
2.53+
0.78 a
1.55+
0.30
1.35+
0.10
5.65+
1.63 (a)
3.88+
0.95 b
2.52+
0.50 (a)
1.87+
0.24
144

Chapter 7: Manuscript V
High-fat diet exposure is associated with renal carcinogenesis
in rats
Kerstin Stemmer 1* , Diego Perez-Tilve 2 , Daniel R. Dietrich 1 , Matthias H. Tschöp 2 , and Paul T.
Pfluger 2
1
Human and Environmental Toxicology, University of Konstanz, Konstanz, Germany
2
Department of Psychiatry, Obesity Research Centre - Genome Research Institute, University
of Cincinnati, College of Medicine, Cincinnati, Ohio, USA
* Corresponding author: Kerstin Stemmer: kerstin.stemmer@uni-konstanz.de
Manuscript to be submitted
7.1 Abstract
Animal and epidemiologic studies strongly suggest an association of renal cancer with dietinduced
obesity. To date, however, it remains unclear whether the pro-carcinogenic
processes in diet-induced obesity are a direct consequence of dietary lipds, or from an
increase in adiposity with its co-morbidities and metabolic alterations. To elucidate the
effects of high fat diet exposure and body adiposity on renal carcinogenesis, male Wistar
rats were fed for 11 months with high fat diet, or chow. Life-history traits revealed two
different rat subpopulations: one with a morbidly obese phenotype (Diet-Induced Obesity
Sensitive, DIOsens, ca. 1.1kg bw), and one high-fat diet-resistant (DIOres) subgroup with
modestly increased body weight (ca. 650g bw), and local fat depots more reminiscent of
chow-fed controls (ca. 470g bw).
High fat-diet exposure led to a severe nephropathy, with early stages of renal
carcinogenesis, such as atypical regenerative hyperplasia and preneoplasias in kidneys of
DIOsens and DIOres, and absence thereof in control rats. In addition, increased cell
proliferation was found in high-fat diet fed animals, and hyperphosphorylation of the S6
ribosomal protein suggests an activated mTOR pathway in proliferating tubules in DIOsens
and DIOres rats.
145

Chapter 7: Manuscript V
In conclusion, the similar degree of histopathological changes in DIOsens and DIOres rats
indicates that the dietary fat content, rather than the degree of adiposity, is the key
etiological factor for renal non-neoplastic and pre-neoplastic pathology. The here presented
findings of increased mTOR activation in preneoplastic lesions of high fat diet-exposed rats
independently of their degree of adiposity is consistent with a central role for this pathway
in the pathogenesis of obesity induced carcinogenous lesions. With recurring cycles of
tissue damage, inflammation and regeneration are critical hallmarks of kidney cancer,
chronic high-fat diet exposure may propagate the fixation and progression of spontaneous
mutations and pre-neoplastic lesions.
7.2 Introduction
Obesity is defined as abnormal or excessive fat accumulation that presents a risk to health.
It can arise from the interaction of both genetic factors and environmental conditions and
behavior. A high availability of calorie-dense food, paired with a sedentary life style, thereby
leads to a chronically positive energy balance with high caloric intake and low energy
expenditure, and subsequently to the excessive storage of fat. It is assumed that
differences in lifestyle, e.g. a lower spontaneous physical activity, or a lower metabolic rate
(Ravussin and Danforth 1999; Ravussin 2005) are important factors influencing the
relationship between high caloric intake body weight gain. Similar to human populations,
inbreed rats also show varying susceptibilities to weight gain after high fat diet exposure
(Levin et al. 1987), and are therefore useful tools to study the effects of high caloric or high
fat exposure.
In Western societies, the widespread obesity epidemia is accompanied by a concurrent
increase in many accompanying diseases, such as diabetes, cardiovascular diseases and
cancer (McTiernan 2005; Hotamisligil 2006; Van Gaal et al. 2006; Ogden et al. 2007). A
recent survey of all available literature on adiposity and cancer (including epidemiologic,
clinical, and experimental data) by the International Agency for Research on Cancer
(IARC), provided sufficient evidence that excess body weight increases the risk of cancers
of the colon, breast (postmenopausal), endometrium, esophagus and the kidney (renal cell
tumors) (IARC 2002a). Specifically, studies of populations worldwide suggested a 1.5- to
2.5-fold higher relative risk of renal-cell cancer (RCC) for overweight and obese subjects
compared to normal weight controls. Since kidney tumors are often only detected at late
stages due to the absence of early symptoms, overall mortality rates are high. Worldwide,
146

Chapter 7: Manuscript V
kidney cancer with approximately 210.000 cases per year accounts for up to 2% of all
malignancies.
There is convincing pre-clinical and clinical evidence that renal cancer is being promoted or
caused by high fat diet induced obesity (Mellemgaard et al. 1995; Chow et al. 2000;
Bergstrom et al. 2001; Renehan et al. 2008), However, it is not clear whether renal cancer
risk is increased by the high body adiposity itself with its manifold co-morbidities and
disease consequences, such as subchronic inflammation, or non-physiological adipokine
secretory patterns. Instead, the overload of dietary fat could directly elicit a negative effect
on kidney physiology by direct stimulation of cellular signaling pathways through specific
dietary fatty acids.
One prime candidate for such a specific cellular effect could be the mammalian target of
rapamycin (mTOR) pathway, which plays a key role in both kidney cancer (Kenerson et al.
2002; Albanell et al. 2007; Stemmer et al. 2007; Hanna et al. 2008) and obesity (Thomas
2006). A very recent report suggested that high-fat diet exposure induced the activation of
the hypothalamic mTOR-S6K signaling pathway in rodents (Ono et al. 2008). Based on
these findings, it was hypothesized in this study that high-fat diet exposure may induces
renal mTOR-S6K activation, and thus may represent a key step in high-fat diet- induced
renal tumorigenesis.
The development of kidney tumors is frequently associated with chemically induced renal
α2u-globulin accumulation in male rats, resulting in α2u-globulin nephropathy (Swenberg
1993; Hard 1998; Doi et al. 2007). Since an early report identified α2u-globulin as kidney
fatty acid binding protein (Kimura et al. 1989), it was further hypothesized that α2u-globulin
might bind dietary lipids, might thereby get accumulated in rat kidneys after chronic high-fat
diet exposure, and might thus result in renal pathology either directly or through an
increased lipid accumulation in renal tubules.
To elucidate the roles of chronic high-fat diet exposure and body adiposity on renal
carcinogenesis, α2u-globulin accumulation and renal mTOR-S6K signaling, a novel rodent
model of diet-induced obesity was employed. Specifically, diet-induced obesity sensitive
(DIOsens) and diet-induced obesity resistant (DIOres) rats were selected from a large
population of chronically high-fed diet fed Wistar rats, and life-history traits, plasma
parameters, renal histopathology and cell proliferation were recorded and compared to
those from a group of chow-fed animals. Thus, for the first time it was possible to dissect
the direct influence of dietary fat vs. the degree of body adiposity on renal carcinogenesis.
147

7.3 Material and Methods
7.3.1 Animals
Chapter 7: Manuscript V
32 male Wistar rats (initial BW approx. 250g; Harlan, Indianapolis, IN, USA) were allowed
ad libitum access to a customized high fat diet (Ref.: # D03082706, 40% butter fat, 46%
carbohydrates (corn starch), 0.05% cholesterol, Research Diets, New Brunswick, NJ) for 11
months. From the initial cohort, two subpopulations of 1) diet-induced obesity resistant rats
(DR) and 2) diet-induced obesity sensitive rats (DIO) were studied further in comparison to
a group of standard chow-fed rats (6% fat, Harlan Teklad LM-485).
All rats were housed in individual cages and maintained on a 12 hr light – dark cycle in a
temperature controlled environment at 23°C. Ad libitum fed animals were sacrificed by
decapitation, and the kidneys rapidly excised. Kidneys were cross sectioned and sections
were either frozen on dry ice and kept at -80˚C, or fixed in 10% buffered formalin for a total
of 4 months before paraffin embedding. In addition, epididymal fat pads were excised and
weighed. All procedures were approved by the Institutional Animal Care and Use
Committees at the University of Cincinnati Office in accordance with the NIH guide for the
care and use of laboratory animals.
7.3.2 Blood parameters
Two weeks prior to sacrifice, tail blood was collected from overnight fasted rats,
immediately chilled on ice, and centrifuged at 2500g, 4°C for 10min to extract plasma.
Circulating non-esterified fatty acid, triglyceride and cholesterol levels were determined
using commercially available enzymatic assays (NEFA, Wako Germany; Infinity triglyceride
and Infinity cholesterol, Thermo Electron). Circulating adipokine levels were measured by
using the respective multiplex mouse panels from LINCOplex (St. Charles, MO, USA). All
measurements were performed in duplicate according to the manufacturer’s instructions.
Fed and fasting blood glucose levels were measured directly from tail blood by using a
glucometer (TheraSense Freestyle).
148

7.3.3 Renal Pathology
Chapter 7: Manuscript V
H&E stained paraffin sections were randomized for histopathological evaluation, Nonneoplastic
pathology was classified as none (0), mild (1), moderate (2), strong (3), and
severe (4). Total numbers of preneoplastic lesions were counted and depicted as
incidences/section & animal. All pathological examinations were conducted by KS and
independently verified by DRD.
7.3.4 Cell Proliferation analysis
Cell proliferation was evaluated by immunohistochemical staining for proliferating cell
nuclear antigen (PCNA) using monoclonal primary anti-PCNA antibody, in paraffinembedded
kidney sections, as described previously (Stemmer et al. 2007). For details see
table 7.1. PCNA- positive stained S-phase nuclei were quantified on randomized sections.
20 microscopic fields (10x ocular, 40x objective) were randomly chosen within the area of
the renal outer cortex and inner cortex/outer medulla. A minimum of 1000 proximal tubules
were counted separately per field, distinguishing between negative and positive PCNAstained
nuclei. Nuclear labeling indices (LI) were calculated as positive nuclei/total number
of nuclei counted.
Table 7.1: Overview of antibodies and modifications to the manufacture’s protocols
Primary antibody Company Antibody retrival Dilution Incubation
Mouse Anti- PCNA
(PC-10)
Rabbit anti-pS6RP
(Ser235/236)
Mouse anti-alpha2uglobulin
DAKO, Cat No:
M0879
Cell Signaling
Technologies, Cat
No: 2211
Kind gift from Dr. U.
Deschel (Boehringer
Ingelheim, Biberach,
Germany)
7.3.5 Immunohistochemistry
10mM sodium
citrate buffer (pH
6.0), 10min at 98°C
10mM sodium
citrate buffer (pH
6.0), 10min at 98°C
1: 50 in 1x
powerblock:
Biogenex; Cat No.
HK085-5K
1:100 in 5% normal
goat serum
none 1: 200 in 1x
powerblock:
Biogenex; Cat No.
HK085-5K
Over night at
4°C
Over night at
4°C
Over night at
4°C
Immunohistochemistry of phospho-S6 ribosomal protein (pS6RP), PCNA, and α2u-globulin
in paraffin sections was carried out according to the manufacturers’ instructions (for brief
information see table 7.1). Antigen–antibody complexes were visualized using the Super
149

Chapter 7: Manuscript V
SensitiveTM (BioGenex, USA) alkaline phosphatase-labeled, biotin–streptavidin amplified
detection system and Fast Red as chromogen.
7.3.6 Statistics
Significant differences in nuclear labeling indices (LI%), or in the total number of
preneoplastic lesions, were calculated by using Bonferroni's test for multiple comparisons.
Ranked non-neoplastic pathology data were analyzed by using Kruskal-Wallis tests. All
analyses were performed by using GraphPad Prism 5.0 (GraphPad Software, San Diego,
California, USA). All results are given as Means ± SD. Results were considered statistically
significant when p < 0.05 (*p < 0.05; **p < 0.01 and ***p

Chapter 7: Manuscript V
Table 7.2: Life-history traits of chow-fed rats (n=8), and DIOres (n=8) and DIOsens (n=7)
subpopulations exposed to high fat diet.
Body weight [g]
Epididymal fat pad weights
[g]
Fasting glucose [mg/dL]
Fed glucose [mg/dL]
Triglyceride
Free fatty acids
Chow DIOres DIOsens
468.0±10.9 649.6±15.9 1031.1±34.8
20,5±1.3 76.5±7.9 204.4±12.5
72.63±1.7 77.1±1.9 85.1±3.1
99.6±2.4 99.8±3.7 104.5±3.0
192.6±15.8 243.6±72.8 244.6±46.7
0.44±0.030 0.41±0.033 0.37±0.027
Despite the marked changes in body weight and fat mass in DIOsens and DIOres
compared to chow-fed rats, no changes were observed in total fasting triglyceride,
cholesterol or free fatty acid levels between the groups (Table 7.2).
7.4.2 Increased levels of adipokines and insulin in DIOsens and DIOres
rats
Leptin levels were increased in both DIOsens and DIOres rats, compared to chow fed
controls, however, the degree of body adiposity did not influence leptin levels in DIOres vs.
DIOsens rats (Figure 7.1, A). In contrast, only DIOsens rats had higher insulin levels,
compared to chow-fed or DIOres rats (Figure 7.1, B). Plasminogen activator inhibitor 1
(PAI-1) levels correlated to the degree of body adiposity, and were higher in DIOres and
especially in DIOsens rats (Figure 7.1, E). No changes were observed for Interleukin 1β (IL-
1β) or monocyte chemoattractant protein 1 (MCP-1), or in any of the groups tested (Figure
7.1, C and D).
151

Chapter 7: Manuscript V
Figure 7.1: Adipokine, cytokine, and insulin levels in plasma from chow-fed controls (open bars,
n=8), and high-fat diet fed DIOres (striped bars, n=8), and DIOsens (grey bars, n=7)
rats. All rats were fed ad libitum prior to blood sampling. Significant differences
between groups were evaluated by using one-way ANOVA and Bonferroni's Post Test
for multiple comparisons.
7.4.3 High-fat diet exposure causes preneoplasia in DIOsens and DIOres
rats
Chronic high fat diet exposure resulted in an increased non-neoplastic renal pathology only
in DIOsens and DIOres rats, but not in rats fed a control diet (Table 7.3). Most prominent
changes included a marked chronic progressive nephropathy (CPN) of the renal cortex,
including tubular degeneration and regeneration, glomerulosclerosis, interstitial fibrosis and
tubules containing protein casts and a widespread mononuclear cell inflammation (Figure
7.2, A and B). Notably, CPN in DIOsens and DIOres rats was associated with simple
tubular hyperplasia characterized by an increased number of epithelial cells that do not
extend beyond the single cell layer (Figure 7.2, A and B). Importantly, some tubules within
the CPN lesions had a preneoplastic phenotype: partly solid, with basophilic cytoplasm,
irregular shaped nuclei and not associated with a markedly thickened basement membrane
(Figure 7.2, C and D). Notably, no overt changes in any of the observed parameters were
observed between DIOres and DIOsens rats.
152

Chapter 7: Manuscript V
Table 7.3: Histopathology in chow-fed (n=8), DIOres (n=8) and DIOsens (n=7) rats exposed to
high fat diet. Histopathological changes were ranked from none (0) to severe (4)
including intermediate classes. Values are presented as median ± median absolute
deviation.
Glomeruli
Cortex/Medulla
Chow DIOres DIOsens
Glomerulosclerosis 0.0 + 0.0 0.8 + 0.3 1.0 + 0.3*
Fibrosis 0.0 + 0.0 0.8 + 0.3 0.5 + 0.2
Dilated blood vessels 0.0 + 0.0 0.5 + 0.3 0.0 + 0.2
Proteincast in Bowman’s
space
0.0 + 0.0 0.0 + 0.2 0.0 + 0.1
Necrosis 0.0 + 0.1 0.5 + 0.4 1.0 + 0.5
Vacuolisation 0.0 + 0.0 0.0 + 0.5 0.0 + 0.5
Apoptosis 0.0 + 0.0 0.0 + 0.0 0.0 + 0.3
CPN 0.3 + 0.3 1.5 + 0.6* 2.0 + 0.5***
Regeneration 0.3 + 0.3 1.0 + 0.5* 1.5 + 0.3*
Regenerative Hyperplasia 0.0 + 0.0 0.8 + 0.6 1.0 + 0.2
Inflammation 0.0 + 0.2 1.3 + 0.6* 2.0 + 0.6**
Protein Casts 0.0 + 0.1 1.3 + 0.6** 1.5 + 0.7***
Calcium Casts 0.0 + 0.1 0.0 + 0.2 0.5 + 0.2
Immunhistochmenistry alpha2u-globulin 2.5 + 0.1 2.5 + 0.4 2.5 + 0.1
* **
Significantly higher than the respective control group. Kruskal-Wallis test (p< 0.05). Significantly higher
than the respective control group. Kruskal-Wallis test (p< 0.005). *** Significantly higher than the respective
control group. Kruskal-Wallis test (p< 0.001)
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Figure 7.2: Representative images of (A, B) simple tubular hyperplasia with tubules containing a
thickened basal membrane and increased number of epithelial cells that do not
extend beyond the single cell layer (1). Images of atypical hyperplasia (C, D), partly
solid, with basophilic cytoplasm, irregular shaped nuclei and not associated with a
markedly thickened membrane (2). Protein cast (3). Representative alpha 2u stained
protein droplets in DIOsens rats (E, F).
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Chapter 7: Manuscript V
7.4.4 High-fat diet-induced changes in kidney pathology are
independent from α2u-globulin accumulation
Positively stained cytoplasmatic α2u-globulin droplets were localized within the P2 segment
of the proximal convoluted tubule. When classifying α2u-globulin staining intensity as none
(0), mild (1), moderate (2), strong (3), and severe (4), similar intensities and therefore
amounts of α2u-globulin were found in all groups tested, independent of the diet and
severity of obesity (see last row in table 7.3, and Figure 7.2, E and F). In addition, no
difference in the tubular localisation was detected, compared to the control rats. Thus, α2u-
globulin did not accumulate with high-fat diet exposure, and did not seem to be implicated
in the observed changes in renal pathology.
7.4.5 High fat diet increases cell proliferation in proximal tubule of
DIOsens and DIOres rats
Visualization of S-Phase nuclei by immunohistochemical staining of nuclear PCNA
demonstrated a marked increase of proliferating cells within the CPN lesions compared to
the healthy tissue. To determine whether high fat diet targets distinct tubular segments, cell
proliferation was separately analyzed in random fields in specifiable areas of the outer and
inner cortex. This resulted in the detection of a similar and significant increase of cell
proliferation in the p1/p2 segments and p3 segments proximal tubules of DIOsens and
DIOres rats respectively, compared to chow fed control rats (Figure 7.3, A and B).
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Chapter 7: Manuscript V
Figure 7.3: (A) Representative images of PCNA staining in DIOsens rats. Red: PCNA positive
nuclei, blue, negative counterstaining with haematoxilin. (B) Comparison of PCNA
labelling indices (LI%) of Eker rats of chow fed, DIOsens and DIOres rats exposed
with high fat diet. LI%, determined for proximal tubules (PT) within randomly chosen
fields of the outer or inner cortex. Within both regions at least 1000 nuclei were
counted. LI% were tested for significance using one-way ANOVA and Bonferroni's
Post Test for multiple comparisons.
7.4.6 Involvement of the mTOR pathway
To evaluate the potential activation of the mTOR-S6K pathway by high-fat diet exposure,
phosphorylation of Ser235/236 residues of S6RP was measured by immunohistochemical
detection. S6RP Ser235/236 specifically gets phosphorylated by activated S6K1 (p70
ribosomal protein S6 kinase 1) (Flotow and Thomas 1992) and serves as marker for
mTOR-S6K activation. Only single S6RP phosphorylation positive cells were found in
chow-fed control rats, or in unaffected tissue of any group (Figure 7.4, A). In contrast, in
both DIOsens and DIOres rats positive staining was detected in nearly all cells of
regenerating tubules within the CPN lesions, and especially in tubules with an atypical
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Chapter 7: Manuscript V
phenotype (Figure 7.4, B-D). However, no overt changes in S6RP phoshphorylation could
be observed between DIOsens and DIOres rats.
Figure 7.4: Representative images of single cell pS6RP staining (1) of a chow fed control rats,
proliferating pS6RP positive tubules with in DIOsens rat (B-D). pS6RP positive tubular
cell undergoing mitosis (2).
7.5 Discussion
Renal tissue damage, inflammation and regeneration are important factors contributing to
the onset and progession of RCC by propagating the fixation of spontaneous mutations and
progression of pre-neoplastic lesions into solid renal tumors (Dietrich and Swenberg 1990;
Cohen and Ellwein 1991; Cohen and Arnold 2008). Obesity is a known risk factor for kidney
cancer, and chronic exposure to dietary lipids has previously been shown to cause
inflammation, regeneration and renal pathologies in animal models for obesity (Aguila and
Mandarim-De-Lacerda 2003; Armitage et al. 2005; Altunkaynak et al. 2008). However,
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Chapter 7: Manuscript V
none of these previous studies could convincingly distinguish between the direct influence
of dietary fat, and the impact of the high body adiposity.
This study describes for the first time the effect of chronic high fat diet exposure on renal
pathology in DIOsens and DIOres rats. These rats were selected from a large population of
high-fat diet fed inbred Wistar rats, and showed marked differences in their body weight
and fat pad weight despite the highly similar genetic background. High-fat diet exposure
induced marked chronic progressive nephropathy (CPN) and an increased regenerative
cell proliferation of similar severity in both DIOsens and DIOres rats, compared to chow fed
controls. Notably, in DIOsens and DIOres rats, CPN was not only associated with a simple
tubular hyperplasia, but also with preneoplastic lesions. Although neither DIOsens nor
DIOres rats presented with full adenomas or carcinomas after high fat diet exposure, it is
now widely accepted that atypical hyperplasias represent a preneoplastic entity which has
the potential to progress to adenomas and carcinomas (Dietrich and Swenberg 1991; Hard
and Khan 2004). However, it remains unclear whether atypical tubular hyperplasias, or
other renal pathologies, are the result of high adiposity with its direct physiological
consequences, of co-morbidities of obesity such as hypertension or diabetes, or of direct
toxic effects of dietary fat.
7.5.1 Similar renal preneoplasias in DIOsens and DIOres rats suggest a
minor role of high body adiposity or its co-morbidities
The lack of overt differences in non-neoplastic pathology between DIOres and DIOsens
rats, points to a minor role for the level of adiposity in the progression of non-neoplastic
pathology. However, despite significantly higher epididymal fat pad weights, leptin levels in
DIOsens rats were only slightly higher than in DIOres rats. Previously, an excess secretion
of leptin in obese animals was suggested to mediate, at least in part, the effects of high
body adiposity on renal carcinogenesis (Takahashi et al. 1996; Attoub et al. 2000;
Horiguchi et al. 2006). Thus, leptin might in part contribute to the observed renal pathology
in DIOsens and DIOres rats. In obesity, monocyte infiltration of white adipose tissue can
lead to the release of cytokines, and a sub-chronic, systemic inflammation. However,
similar plasma levels of MCP1 and IL-ß in all groups tested do not suggest such an
increased cytokine release, or sub-chronic inflammation. PAI-1 levels were reported to be
elevated in obesity and might enhance fibrinolysis in renal disease by inhibiting plasmindependent
extracellular matrix turnover, thus enhancing renal pathology (Eddy and Fogo
2006). Accordingly, PAI-1 levels increased with the degree of body adiposity in DIOres rats
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Chapter 7: Manuscript V
and DIOsens rats, compared to chow fed controls. Adipokine levels in diet-induced obesity
might therefore contribute in part to the observed effects, however, their exact role in the
etiology of kidney cancer still remains elusive. For instance, A-Zip/F-1 mice, which
completely lack white adipose tissue and therefore have undetectable adipokine levels,
nevertheless displayed higher tumor incidences, tumor multiplicity, and decreased tumor
latency than wild-type mice in two experimental tumor models (Nunez et al. 2006).
Insulin resistance, diabetes type II and associated hyperglycemia itself are well-established
risk factors for the onset of renal cancer (Hjartaker et al. 2008). Chronic hyperinsulinemia
may thereby induce an increased synthesis and bioavailability of the insulin-like growth
factor 1 (IGF1), one of the most potent activators of the oncogenic AKT signaling pathway
(Renehan et al. 2006). Hyperglycemia may further induce the localized production of
reactive oxygen species (ROS) via multiple mechanisms such as advanced glycation or
enhanced glycolysis, and may ultimately lead to diabetic nephropathy (Coughlan et al.
2008; Forbes et al. 2008) and renal DNA damage (Sebekova et al. 2007), therefore
increasing the risk for kidney cancer. However, despite severe adiposity especially in the
DIOS rats, similar blood glucose levels (ad libitum and fasted) in DIOres, DIOsens and
chow fed animals indicated that high fat diet exposure did not induce hyperglycemia, one
major hallmark of type II diabetes. In addition, insulin levels were only increased in
DIOsens, but not in DIOres rats, compared to chow-fed controls. Based on the similar renal
pathology of DIOsens and DIOres rats, hyperglycemia and hyperinsulinemia therefore do
not seem to induce the here observed changes. Thus, the here presented findings suggest
that the influence of body adiposity on renal pathology and renal carcinogenesis is rather
minor.
7.5.2 High-fat diet exposure does not induce α2u-globulin accumulation
Dietary lipids may have a direct effect on renal pathology and early markers of renal
tumorigenesis. It was thus initially hypothesized that an excessive renal accumulation of the
fatty acid binding protein α2u-globulin may contribute to high fat diet-induced CPN, but
immunohistochemical staining of α2u-globulin could not corroborate that hypothesis.
However, glomerusclerosis, and tubular damage mainly within the proximal part of the renal
nephron in DIOsens and DIOres rats might point to a direct toxic effect of lipids. Such
effects were previously observed after chronic high fat diet feeding in leptin-receptor
deficient db/db mice, or diet-induced obese C57BL/6J mice, and were attributed in part
towards a sterol regulatory element binding protein (SREBP)-mediated lipid accumulation
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Chapter 7: Manuscript V
in the kidney (Jiang et al. 2005; Wang et al. 2005). Previous reports suggested a different
capacity for lipid metabolism within different tubular segments, with mitochondrial betaoxidation
of fatty acids being relatively small in the proximal and the distal nephron, but
high in the proximal tubule. Notably, the proximal tubule has a peroxisomal beta-oxidative
capacity of the same order of magnitude as in liver cells of Wistar rats (Le Hir and Dubach
1982). Higher lipid turnover in the glomerulus or proximal tubule may therefore lead to the
release of reactive oxygen species by mitochondria, and regional oxidative stress, one key
player in the pathogenesis of renal pathology.
7.5.3 mTor-S6K signaling: The link between obesity and kidney cancer
Kidney cancer has been linked to an abnormal activation of the mammalian target of
rapamycin (mTOR) pathway (Kenerson et al. 2002; Albanell et al. 2007; Stemmer et al.
2007; Hanna et al. 2008). Activation of the mTOR pathway results in activation of its
downstream target S6-Kinase (S6K) and further to phosphorylation of S6 ribosomal protein
(S6RP) at Ser293. Due to the lack of S6K antibodies suitable for immunohistochemistry,
staining of phosphoSer293- S6RP was used as surrogate marker for an activated mTOR
pathway. The here presented data clearly demonstrate that mTOR pathway activation can
only be observed in DIOsens and DIOres rats. Specifically, mTOR signaling is activated
specifically in proximal tubules that also demonstrate an increased proliferation and
regenerative hyperplasia with atypical nuclear morphology. The functional role of such
mTor/S6K pathway activation in tumor initiation and/or tumor promotion, however, has not
been clearly established. Kenerson and co-workers demonstrated that rapamycin, an
inhibitor of mTOR, diminished renal preneoplastic progression to veritable renal tumors in
Eker rats but not the formation of earliest preneoplastic lesions (Kenerson et al. 2002). In
addition, an activation of the mTOR/S6K pathway might serve as facilitator of tumor
initiation by an induction of cell proliferation, thus elevating the risk for the fixation of DNA
mutations, e.g. induced by increased oxidative stress.
The mTOR pathway is also known to be a central regulator for the nutrient-hormonal
signaling network (Cota et al. 2008; Gulati et al. 2008), and deregulation by high-fat diet
exposure might therefore induce human and rodent cancer. High fat diet exposure was
previously shown to induce hypothalamic S6K activation (Ono et al. 2008). In addition,
Palmitoleic acid was shown to rapidly induce S6K phosphorylation in various hypothalamic
and muscle cell lines in vitro, and chronic exposure of mice to high-fat diet induced the
phosphorylation of skeletal muscle S6K, whereas exposure to a fat-free diet reduced
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Chapter 7: Manuscript V
skeletal muscle S6K phosphorylation (Castaneda et al. 2008). Thus, it seems entirely
possible that fatty acids, derived from high-fat diet, could also activate S6K in renal cells.
Further studies, based on in vitro exposure of primary kidney cells or established kidney
cell lines with various fatty acids, will help to clarify this open question.
7.5.4 Conclusion
The here presented data suggests that dietary lipids can induce renal toxicity. This effect
seems largely independent of the level of adiposity, and can manifest in non-diabetic rats.
The high-fat diet induced activation of the mTOR pathway by dietary lipids with the
increase in cell proliferation, may promote the fixation and progression of spontaneous
mutations and the development of neoplasia and solid tumors, and may causally link
obesity and renal cancer.
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Chapter 8: Additional Data
8.1 Gender Disparity in Early Ochratoxin A and Aristolochic
Acid Mediated Renal Toxicity in Short-term Assays
This chapter summarizes additional data from short-term AA- and OTA-treated female Eker
and wild type rats, respectively, that were not presented in one of the previous manuscripts.
The experiments and analyses in female rats were done together with those from male
rats, which are shown in chapter 3. Therefore, sex-specific effects of AA or OTA treatment
on cell proliferation and renal pathology in female rats can be directly compared to those
derived from male rats. For details on the experimental design, see material and methods
of chapter 3. The results from these gender disparity experiments were partly presented as
poster at the 47 th Annual Meeting of the Society of Toxicology, 2008 in Seattle, WA, USA.
8.2 Ochratoxin A
8.2.1 Cell proliferation (PCNA labeling index)
Treatment of male and female Eker and wild typ rats with 210µg OTA/kg bw significantly
increased cell proliferation in the renal cortex after 7 and 14 days of exposure (Figure 8.1).
Male rats showed a strong tendency towards a higher OTA-dependent increase in cell
proliferation, compared to female rats. Furthermore, the gender difference in cell
proliferation was more pronounced in wild type than in Eker rats.
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Chapter 8: Additional Data
Figure 8.1: Comparison of PCNA labelling indices (LI%) in the renal cortex of OTA-treated Eker
and wild type rats. Data represent the mean + SD of n=3 animals per group.
Significant differences between treated and time-matched control groups: *p < 0.05;
**p < 0.01 and ***p

Chapter 8: Additional Data
Figure 8.2: Comparison of total numbers and incidences of basophilic atypical tubules (bATs) in
male and female Eker and wild type rats treated with OTA. Significant differences
between treated and time-matched control groups: *p < 0.05; **p < 0.01 and ***p

8.3 Aristolochic acid
8.3.1 Cell proliferation (PCNA labeling index)
Chapter 8: Additional Data
Treatment of male and female Eker and wild typ rats with 10mg AA/kg bw significantly
increased cell proliferation in the renal cortex of female but not male rats (Figure 8.3).
Female Eker rats appeared to be more sensitive to AA than corresponding wild type rats,
as an increased cell proliferation rate was already observed at day 7 of exposure.
Figure 8.3: Comparison of PCNA labelling indices (LI%) in the renal cortex of AA-treated Eker
and wild type rats. Data represent the mean + SD of n=3 animals per group.
Significant differences between treated and time-matched control groups: *p < 0.05;
**p < 0.01 and ***p

Chapter 8: Additional Data
significantly increase the number of bATs in comparison to vehicle controls. Higher
background numbers and incidences of bATs were found in TSC2-mutant Eker rats.
Figure 8.4: Comparison of total numbers and incidences of basophilic atypical tubules (bATs) in
male and female Eker and wild type rats treated with AA. Mean + SD. No significant
differences between treated and time-matched control groups were detected by one
way ANOVA with Bonferroni post-test.
8.3.3 Conclusion
Although no sex-differences in total numbers and incidences of preneoplastic lesions could
be detected, the increased cell proliferation in AA-treated females but not in males suggest
a higher sensitivity of female rats towards AA treatment. This is corroborated by previous
findings, demonstrating 2-fold higher levels of dG-AAI and dA-AAII DNA adducts in kidneys
of female than male Wistar rats following treatment with oral doses of 0.15mg/kg body
weight for 3 months (Arlt et al. 2001).
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Chapter 9: Overall Discussion and Future Perspectives
9.1 Short-term In Vivo Tests to Identify Renal Carcinogens
Exposure to renal carcinogens remains one important cause for a vast majority of all
human kidney cancers and identification of potential carcinogens serves as first step in
disease prevention. Classification as carcinogen is mainly based on life-time rodent
bioassays. These tests assume that cancer development is a basic process with a similar
pathogenesis in humans and in experimental animals (Bannasch 1986a; Bannasch 1986b).
However, the scientific value of rodent bioassays has come under criticism (Monro 1993;
Davies et al. 2000; Haseman et al. 2001). The criticisms are: a) that the studies are too
long and should rather be terminated at earlier points of life when the animals still have
essentially normal organ functions and are free from widespread age-related pathology, b)
that the carcinogenic doses are too high and, due to cytotoxicity and regenerative cell
proliferation or dose-dependent differences in metabolism and pharmacokinetics, do not
reflect the true carcinogenic potential, and c) that some organ-specific carcinogenic effects
observed in experimental animals have little or no relevance to humans (e.g. α2u-globulin
nephropathy associated with renal cancer in male rats, or chemically induced peroxisomal
proliferation associated with rodent liver tumors). Other criticisms are that rodent bioassays
require hundreds of animals, are time-consuming, and costly, especially due to the high
amounts of compounds required.
Due to the current limitations of the lifetime rodent bioassay, interest in developing sensitive
short-term, mechanistically based in vivo studies has grown. One promising approach is
the use of microarrays for the identification and characterization of novel mechanistic
biomarkers involved in the early onset of cancer. In addition, since microarrays are highly
sensitive detection tools, gene expression profiling may allow an early detection of adverse
effects of test compounds, even before those effects have manifested in histopathological
changes. However, before short-term assays in combination with gene expression profiling
can be adopted as alternatives for the lifetime rodent bioassay, further research is needed
to establish and validate their sensitivity, accuracy and predictivity to detect carcinogenic
compounds. Some promising studies have been performed where gene expression profiles
from rat livers were used to identify and distinguish known genotoxic and non-genotoxic
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Chapter 9: Overall Discussion and Future Perspectives
hepato-carcinogens after 1 to 14 days of treatment (Ellinger-Ziegelbauer et al. 2005;
Ellinger-Ziegelbauer et al. 2008). However, at the beginning of this thesis no comparable
studies on renal carcinogens had been performed.
The first aim of this thesis was therefore to investigate some of the most important
prerequisites needed for a sensitive, specific and predictive short-term in vivo test to
identify renal carcinogens. Those are:
1. Detectable and compound-specific gene expression changes in kidney
homogenate of short-term treated rats (Sensitivity)
2. Possible differentiation between genotoxic and non-genotoxic renal carcinogens by
these gene expression profiles (Specificity)
3. Manifestation of early genotoxic or non-genotoxic expression changes in renal
preneoplastic and neoplastic lesions (Predictivity)
An in-depth discussion on the respective hypotheses and obtained results can be found in
the respective manuscripts. This chapter will summarize the findings of all short-term and
long-term in vivo experiments, and will discuss them in context to the above named
prerequisites. Thus, a more comprehensive evaluation of all findings presented in this
thesis might help to clarify whether the methods and model systems used for these studies
can help to establish a new standard for renal toxicity testing. Ultimately, such a new
standard test could shorten the duration of the life-time rodent bioassay, and could help to
achieve the goal of the three R’s, to reduce, refine and replace animal experiments.
9.1.1 Prerequisite I: Short term treatment would result in detectable
compound-specific gene expression changes
In the first part of this thesis, gene expression profiles of kidney cortex homogenates of
male Tsc2 mutant Eker- and corresponding wild-type rats were analyzed after 1, 3, 7 and
14 days of treatment with genotoxic (AA and MAMAc) and non-genotoxic (OTA) renal
carcinogens and compared with compound-induced changes in renal pathology and cell
proliferation (for details see chapter 3, 4 and 8). In both Eker- and wild-type rats short-term
treatment with the respective carcinogens resulted in minor but compound-specific changes
in histopathology and cell proliferation that were reflected by early gene expression profiles.
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Chapter 9: Overall Discussion and Future Perspectives
1. AA and OTA resulted in an up-regulation of genes and pathways involved in
inflammatory responses, which was in consistence with the histopathological
finding of an infiltration of monocytes in both groups.
2. OTA induced the deregulation of genes modulated by acute toxic effects (e.g.
genes involved in oxidative stress response, regenerative cell proliferation, and
increased extracellular matrix synthesis). These changes correlated well with the
histopathological findings in OTA-treated rats demonstrating tubular damage and
regeneration with signs of fibrosis.
3. OTA but not AA treatment resulted in an up-regulation of numerous genes involved
in cell cycle progression and cell proliferation, which is in accordance to the OTAspecific
increase in cell proliferation and with signs of regeneration.
4. Short-term treatment with MAMAc only resulted in a small number of deregulated
genes in male Eker and wild-type rats, when compared to AA and OTA treatment,
which was in accordance with the lack of effects on pathology or cell proliferation in
male rats.
5. Carcinogen treatment generally resulted in a higher number of deregulated genes
in Tsc2 mutant Eker rats compared to wild type rats. However, when compared to
the respective controls, similar pathways were affected. Solely OTA-treated Eker
but not wild type rats demonstrated a number of additional genes pointing to an
OTA-mediated ERK-dependent inactivation of the Tsc2 tumor suppressor gene.
This finding corresponded well with the significant manifestation of preneoplastic
lesions, exclusively seen in OTA-treated Eker rats after 14 days of exposure.
From these findings it was concluded that gene expression profiling allows an in-depth
mechanistic insight into earliest cellular alterations after carcinogen exposure. This notion
was corroborated by the finding that deregulated genes reflect the majority of cellular
pathways which are known to be involved in the carcinogenic properties of AA and OTA.
Table 9.1 summarizes these pathways, and compares the here presented findings to the
specific results published elsewhere (for further references see Table 9.1). In conclusion,
the findings from chapter 3 and 4 demonstrate that microarrays are sufficient to identify a
compound-specific mode of action in the kidney already after just 1-14 days of exposure.
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Chapter 9: Overall Discussion and Future Perspectives
Table 9.1: Summary of pathways, suspected to be involved in AA-, OTA- or MAMAc-induced
renal toxicity and carcinogenicity, and of genes that may be involved in the suspected
pathways or downstream responses (for details see chapter 3 and 4 and GEO
repository (http://www.ncbi.nlm.nih.gov/projects/geo; accession number: GSE5923).
AA
OTA
Major pathways previously
described in chronic in vivo
or in vitro
Phase I metabolic activation of
AA (Arlt et al. 2002; Kohara et
al. 2002; Li et al. 2006)
DNA damage (Arlt et al. 2002;
Lord et al. 2004)
Caspase-3 activation
(Balachandran et al. 2005)
Mutations in H-ras and p53
(Schmeiser et al. 1991; Arlt et
al. 2002)
Activation of cyclin D1/cdk4
(Chang et al. 2006)
Transcriptional repression of
Nrf2 target genes (Marin-Kuan
et al. 2006)
Increased histone deacetylase
activity and down regulation of
RNA synthesis (Luhe et al.
2003; Marin-Kuan et al. 2006)
Transcriptional repression of
HNF4alpha target genes
(Marin-Kuan et al. 2006)
Activation of the mitogenic
ERK1/2 pathway (Horvath et
al. 2002; Marin-Kuan et al.
2007)
Activation of the stress-
inducible JNK and p38
pathway (Gekle et al. 2000;
Rached et al. 2006)
Activation of the NFkappa B
pathway (Rached et al. 2006)
Impairment of cellular Ca 2+
and cAMP homeostasis
(Rahimtula and Chong 1991;
Benesic et al. 2000)
Suggested downstream
effects causally related to
deregulated pathways
Deregulated genes found in this
study, supportive for previous
described pathways and
downstream effects
DNA reactivity Up: AKR1B8, AKR7A3, EPHX1,
CYP4A10, CYP51, NQO1, GNMT,
CES2, CES3
Cell cycle arrest, DNA repair Up: MGMT, PHLDA3, CDKN1A,
SNK, CCNG1, MDM2, FTHFD,
PRODH, OXR1
Down: CDCA3, CCNB1, HMMR,
CDC2, CKS2,
Apoptosis, decreased cell
survival and proliferation
Cell survival and proliferation Not detectable
Cell cycle progression and
proliferation
Impaired cellular defense
against oxidative stress,
enhanced oxidative stress,
DNA-damage
Reduced transcription and
protein expression, gene
silencing
Reduced biotransformation,
decreased detoxification and
excretion
Active mitogenic IGF-MAPK
system, cell survival, cell
transformation
Up: TNFAIP8, HSPA5
Down: USP2, SNN, Ki-67, FRZB,
IGF1, CTGF, TGM2, NAB2,
SFRP2, KLK7
Not detectable
Up: KEAP1, SUPT16H, CHEK2,
MDM2, RBBP6, SEPP1, GGTLA1,
TXNRD1
Down: CN1, HSP40-3, MSRA
Down: H2AA, MYST1, RPP25,
POLD4, NR1D2, KLF13, ID1
Down: CES1B, CES3, AADAC,
CYP2T1, CYP2F4, WBSCR21,
ALDH6A1 , CML1, NAT8, GGT6,
MGST1, GNMT, OCTN1, OAT1,
OCT1
Up: PI3CB, AKT2
Apoptosis Up: JNK2, STAT1, CYBB
Down: CFLAR
Suppressed apoptosis, G1/S
cell cycle transition: Cell
proliferation
Disturbance of hormonal Ca 2+
signaling, leading to altered cell
proliferation
Up: GMFB, NFE2L1
Up: CALB, CALR, ITPKB,
PRKAR2A, PPP1R2, CNB, NCX1,
GNAI3, CHP, MPP2
Down: SMP-30
170

MAMAc
Activated TGFß signaling
(Gagliano et al. 2005; Sauvant
et al. 2005)
Spontaneous hydrolysis to the
DNA-reactive
methyldiazonium ion
(Matsumoto and Higa 1966;
Shank and Magee 1967; Sohn
et al. 2001)
Inhibited RNA synthesis
(Zedeck et al. 1970)
Chapter 9: Overall Discussion and Future Perspectives
Altered cell proliferation and
growth control, epithelialmesenchymal-transition,
fibrosis
DNA alkylation, cell cycle arrest,
DNA damage repair, Apoptosis
Up: TGFBR2, SMAD1, SMAD3,
SMAD4, CTNNB1, PDGFC, HAI-1,
NPHS1, TIMP3, DPT, CD44,
NOTCH2
Not detectable
Tumor suppression and others Down: PLAGL1, NR1D1, NR1D2,
NFIX, FKHL18, DBP, BHLHB3,
BAT1A
9.1.2 Prerequisite II: Genotoxic and non-genotoxic renal carcinogens
can be distinguished by early gene expression profiles
As demonstrated in chapter 3, 1 to 14 days of treatment with AA clearly resulted in the upregulation
of numerous genes involved in DNA damage response, cell cycle arrest and
apoptosis, indicative for a compound-induced DNA-damaging (genotoxic) action (Branzei
and Foiani 2008) In contrast, gene expression profiles of OTA-treated rats point to an
indirect genotoxic mode of action due to increased oxidative stress, as indicated by a broad
down-regulation of genes involved in anti-oxidant defense. Compared to the predominant
detection of genes involved in DNA damage response in AA-treated rats, OTA treatment
resulted in a marginal deregulation of these gene groups, which suggests a secondary role
of oxidative DNA damage in OTA-induced kidney cancer. More prominent, OTA treatment
resulted in the additional up-regulation of genes involved in mitogenic processes, such as
cell cycle progression, cell survival and proliferation (for details see chapter 3). Already
these findings indicate that gene expression profiling may allow the prediction of genotoxic
or non-genotoxic/ indirect genotoxic carcinogenic potential for a compound in short-term
studies.
This interpretation is further supported by previous reports showing that similar groups of
genes (indicative either for a genotoxic or and non-genotoxic mode of action) were
deregulated in rat liver after short-term exposure to different known genotoxic or nongenotoxic
compounds, respectively (Ellinger-Ziegelbauer et al. 2004; Ellinger-Ziegelbauer
et al. 2005). Specifically, the genotoxic liver carcinogens 2-nitrofluorene,
dimethylnitrosamine; 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone and aflatoxin B1 all
resulted in the up-regulation of p53 target genes such as CDKN1A, MGMT, CCNG1, or
MDM2. Notably, these genes were also up-regulated in kidneys of short-term AA-treated
rats (see chapter 3). In contrast, gene expression profiles after treatment with non-
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genotoxic liver carcinogens methapyrilene, diethylstilbestrol, Wy-14643 and
piperonylbutoxide appeared more heterogeneous, with a slight emphasis on de-regulated
genes involved in DNA replication and cell cycle progression, cell survival and proliferation
(Ellinger-Ziegelbauer et al. 2005; Ellinger-Ziegelbauer et al. 2008). Consistently, such a
gene expression profile was also found in kidneys of rats after OTA treatment (Chapter 3).
In contrast to the above findings, 1-14 days of treatment with the known genotoxic, DNAalkylating
compound MAMAc did not result in characteristic gene expression profiles
previously found for other genotoxic, or non-genotoxic compounds. In a predictive
approach, this data would imply a non-carcinogenic action of MAMAc, at least at the low
doses used for this study. However, the additional detection of an accumulating amount of
pro-mutagenic O6-methylguanine adducts by LC-MS/MS in the same samples used for
gene expression profiling corroborates the potentially genotoxic, DNA-alkylating
mechanism of MAMAc in Eker rats (see chapter 4). This however would suggest that
microarray analysis might not be sensitive enough to detect the consequences of low but
possibly relevant amounts of DNA adducts. Another explanation for the lack of deregulation
of genes involved in DNA damage repair and apoptosis could be that basal expression of
genes involved in DNA repair and/or apoptosis might be sufficient to deal with low amounts
of DNA adducts, at least until a certain threshold dose or duration of exposure is exceeded.
Together, the findings presented here suggest that gene expression profiling in
combination with the analysis of cell proliferation and histopathology may allow the
distinction of genotoxic from non-genotoxic modes of action in short-term studies. However,
microarray analyses may require a minimum amount of DNA damage, resulting in a
detectable up-regulation of DNA damage response genes. More research on other renal
carcinogens is therefore needed to verify these findings and also to elucidate whether a
carcinogen can be clearly distinguished from nephrotoxic/non-carcinogenic mechanisms in
short term assays.
9.1.3 Prerequisite III: Manifestation of early compound-induced
expression changes in kidney tumors.
Eker rats were chronically exposed with AA, OTA, or MAMAc for either 3 or 6 months.
Prolonged exposure should reveal whether early gene expression changes, indicative for a
genotoxic, non-genotoxic/ indirect genotoxic, or non-carcinogenic mode of action, would
indeed manifest in the onset or absence of renal tumors, respectively. Eker rats were
chosen as the only animal model in these chronic studies out of both ethical and financial
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considerations. Specifically, various studies have demonstrated a substantially higher
susceptibility of Eker rats towards genotoxic and non-genotoxic carcinogens, resulting in an
earlier manifestation and higher number of carcinogen-induced renal pre-neoplastic and
neoplastic lesions compared to wild-type rats (Walker et al. 1992; Wolf et al. 1998; Wolf et
al. 2000). Thus, the duration of the study could be significantly shortened and fewer
animals and less compound could be used.
As demonstrated in chapter 4 and 6, prolonged carcinogen exposure corroborated the
findings of the short-term assay: Both AA and OTA treatment resulted in a significant
increase in total numbers of preneoplastic lesions, and the absence thereof in MAMActreated
male Eker rats. Moreover, in accordance with previous in vivo studies using AA and
OTA, a similar sex-specific susceptibility towards both carcinogens was found; pointing to a
compound-specific carcinogenic effect of AA and OTA in Eker rats (for details see chapter
6 and chapter 8).
A sex-specific susceptibility towards a carcinogenic action of MAMAc has not been
described before. The findings of this thesis point to a higher susceptibility of female rats,
as a significant increase of MAMAc-induced preneoplastic lesions was solely observed in
female rats. In male Eker rats, prolonged treatment with MAMAc did not manifest in a
significant increase of preneoplastic lesions. This was in accordance with the gene
expression profiles derived from short-term treated males that did not point to a genotoxic
mode of action of MAMAc, further corroborating the predictive potential of short-term
assays. The lack of a tumor-initiating action was surprising since MAMAc has been
identified as a potent genotoxic renal carcinogen in male rats (Laqueur 1964; Laqueur and
Matsumoto 1966; Hirono et al. 1968; Fukunishi et al. 1971). However, all previous studies
on the carcinogenic action of MAMAc have used acute high doses (25 to 500 mg/kg bw),
compared to the here shown study using low and chronic doses (250 µg/kg bw). It thus
seems possible that tumor initiation by MAMAc might depend on a threshold dose
ultimately leading to a sufficient amount of DNA adducts which then might result in
transforming mutations in critical genes and tumor initiation.
Importantly, although 6 month treatment with MAMAc did not result in an increased number
of preneoplastic lesions in males, they showed an increased incidence and higher total
number of neoplastic lesions, compared to the respective control rats (for details see
chapter 4). These findings could therefore point to a differential influence of MAMAc on
early and later tumor stages, and may be explained by the here detected MAMAc-induced
up-regulation of the TGF-ß pathway. This pathway is known to function as a tumor
suppressor at early stages of kidney cancer but it can also promote tumor progression and
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metastasis in later stages (Gold 1999; Laping et al. 2007). These findings may therefore
indicate that short-term gene expression profiling could also be a useful tool to predict the
carcinogenic potential of compounds acting on later stages of carcinogenesis.
9.1.4 Summary Part I
In summary, the initial hypothesis of this thesis, that short-term in vivo assays, using
microarrays as detection system, can be used as a sensitive and specific tool to predict the
renal carcinogenic potential of test compounds in the kidney, is corroborated by the here
presented data. However, additional work needs to be done to evaluate gene expression
profiles in response to different dose-regimens, to also elucidate whether one compound, in
a dose-dependent manner, can simultaneously or successively adopt both non-genotoxic
and genotoxic mechanisms.
Furthermore it needs to be established whether short-term gene expression profiles would
indeed allow a reliable detection of carcinogens that target genes and pathways important
for later stages of renal carcinogenesis. This however would require a more detailed
understanding of signaling cascades involved in tumor promotion and progression, and the
impact of renal carcinogens on these processes. This question was further elucidated in the
second part of this thesis and is discussed in detail the following section.
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9.2 Cellular Signaling Cascades in Preneoplastic Lesion
Progression
The two-year rodent bioassay is mainly based on the detection of end-stage adenomas and
carcinomas. Shorter in vivo bioassays will however no longer be based on the detection of
end-stage tumors, but rather have to use specific molecular, predictive endpoints. Clearly,
however, such predictive tests would require a detailed understanding of mechanisms
involved in tumor initiation, promotion and progression.
Currently, mechanisms involved in multistage kidney carcinogenesis are only poorly
understood. Thus, the next aim of this thesis was to identify and characterize signaling
pathways involved in the progression of early preneoplastic renal lesions (for details see
chapter 3 and 6). This should further allow to:
• Analyze the impact of genotoxic and non-genotoxic renal carcinogens on these
pathways
• Determine, whether these genes and pathways could be detected in short-term
assays
Since only prolonged treatment with AA and OTA, but not with MAMAc, resulted in a
compound-specific increase of total numbers of bATs and bAHs in males, gene expression
studies from microdissected lesions were restricted to male AA- and OTA-treated rats and
vehicle controls. For technical reasons, later tumor stages (adenomas and carcinomas)
were not further addressed, since the cryo-conserved tissue designated for laser
microdissection did not comprise enough replicate tumors in each dose group for proper
statistical analysis.
First, a protocol was established that allowed a reproducible and reliable analysis of gene
expression profiles from laser-microdissected preneoplastic lesions (for details see chapter
5). Using this protocol, gene expression profiles of different stages of preneoplastic lesions
(bATs and bAHs) and healthy tubules of AA-, OTA- and vehicle-treated male Eker rats
were analyzed and revealed the following key findings:
1. Consistent with the initial hypothesis, the here presented findings demonstrate for
the first time that large-scale gene expression profiling from microdissected earliest
stages of renal preneoplastic lesions is possible (for details see chapter 5 and 6).
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2. As expected at the beginning of this thesis, preneoplastic lesions showed a
massive deregulation of genes compared to healthy tissue of control rats, clearly
demonstrating that tumor cells are different from their cellular origin (chapter 6).
3. In contrast to the initial hypothesis, different stages of microdissected preneoplastic
lesions (bATs and bAHs) were similar in their transcriptome chapter 6).
4. Unexpectedly, comparisons of gene expression profiles from microdissected
preneoplastic lesions of vehicle-treated with AA- and OTA-treated rats revealed
only marginal differences. Thus, carcinogen treatment does not seem to influence
gene deregulation once a preneoplastic lesion has manifested.
5. Chronic treatment with AA or OTA did not substantially change gene expression in
microdissected healthy tubules, which was in contrast to the overt carcinogeninduced
gene expression changes in short-term treated Eker rats (see chapter 3
and 6).
The above findings are discussed in detail in the respective manuscripts. The next chapter
will summarize all findings and propose a hypothetical model of carcinogen-induced renal
tumorigenesis in Eker rats and potentially also wild-type strains. This model delineates the
pivotal roles of carcinogen-induced tubular damage, regeneration and adaptation
processes for the development of kidney cancer (see chapter 9.2.1), and proposes a
predictive potential of preneoplastic lesions for the carcinogenic outcome of the rodent
bioassays (see chapter 9.2.2).
9.2.1 Pivotal role of carcinogen-induced tubular damage, regeneration
and adaptation processes for the development of kidney cancer
Based on the differing gene expression profiles from kidney homogenates and healthy
tubules of short-term vs. chronically treated rats, respectively, a hypothetical model of
carcinogen-induced renal tumorigenesis is proposed (Figure 9.1, A-E) This model assumes
that proximal tubules of a similar microscopic phenotype generally differ in their sensitivity
towards renal carcinogens (Figure 9.1, A). Such differences in carcinogen sensitivity could
be based on variations in the cellular environment (e.g. amount of blood and carcinogen
supply), cellular polymorphisms in carcinogen uptake, metabolic activation, detoxification,
DNA damage repair or many other variations in intracellular carcinogen binding sites.
Depending on their intrinsic sensitivity, some tubules would remain rather unaffected by
carcinogen treatment, while others are sensitive towards genotoxic, non-genotoxic or
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Chapter 9: Overall Discussion and Future Perspectives
cytotoxic effects. Gene expression profiling from short-term treated rats will therefore reveal
compound-specific deregulations in sensitive tubules, as shown in chapter 3 and 4).
As demonstrated for AA and OTA, prolonged carcinogen treatment can result in
compound-specific cytotoxic or genotoxic effects accompanied with apoptosis or necrosis
and regenerative cell proliferation (Chapter 6). Regeneration might be based on the
replication of less affected or more insensitive neighboring cells (Figure 9.1, B). Thus,
recurring cycles of damage and regeneration might also constitute a selection towards
carcinogen-insensitive cells with a healthy phenotype (Figure 9.1, C). Gene expression
profiles from microdissected healthy tubules of carcinogen-treated rats, when compared
with healthy tubules of control rats, would thus not demonstrate overt compound-specific
effects even though all healthy tubules are still systemically supplied with carcinogens
(Chapter 6, Figure 6.2). However, a qualitative comparison of short-term gene expression
profiles from kidney homogenates of AA- and OTA-treated rats with those derived from
microdissected healthy tubules of AA- and OTA-treated rats, respectively, demonstrated
several similarly deregulated genes (Figure 9.2). This finding may point to a low number of
sensitive healthy tubules remaining in AA- and OTA-treated rats.
Figure 9.1: Overview of the hypothetical model of chemically-induced renal carcinogenesis in
Eker rats
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Chapter 9: Overall Discussion and Future Perspectives
Recurring cycles of compound-induced cell death and regeneration also allow the fixation
of carcinogen-induced or spontaneous mutation and, if critical genes were affected, their
clonal expansion to an atypical tubule (Figure 9.1, D). Thus, the compound-specific amount
of damage and regeneration could be an important driving force for the development of
preneoplastic lesions that determines their total numbers. A correlation between tubular
damage, increased cell proliferation and the total numbers of preneoplastic lesions was
demonstrated in chapter 4 and 6 and is further supported by the findings of Cunningham
and colleagues (Cunningham et al. 1993), who demonstrated that mutagenic compounds
that increased renal cell proliferation also increased renal tumors, whereas mutagens
having no effect on renal cell proliferation did not.
The carcinogen-induced transformation of tubular cells together with the finding that
atypical tubules are insensitive towards carcinogen treatment points to a carcinogen
resistance of clonal expanding cells (Figure 9.1, E). A similar phenomenon is already
known as multidrug resistance, where e.g. cancer cells have the ability to become resistant
to chemotherapeutics. This includes protective mechanisms, e.g. an increased efflux of
drugs or enzymatic deactivation, but could also be the result of decreased uptake or
membrane permeability, or of altered drug binding sites (Szakacs et al. 2006). Indeed, as
demonstrated in chapter 6, the functional analysis of gene expression profiles derived from
preneoplastic lesions demonstrates a broad down-regulation of transporters and metabolic
enzymes previously demonstrated to be involved in AA- and OTA-mediated toxicity and
carcinogenicity (Gekle and Silbernagl 1994; Stiborova et al. 2003; O'Brien and Dietrich
2005), for details see GEO repository, http://www.ncbi.nlm.nih.gov/projects/geo; accession
number: GSE 10608. However, it remains elusive whether the here detected downregulation
of genes is a specific feature of atypical renal tubular cells, or results from an
unspecific dedifferentiation of fast proliferating cells. An additional explanation for the
general insensitivity of preneoplastic lesions towards AA- and OTA-treatment could be that
a temporarily reduced blood supply in fast growing pre-neoplastic foci could reduce the
amount of carcinogen reaching the cells, at least until angiogenesis starts.
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Chapter 9: Overall Discussion and Future Perspectives
Figure 9.2: Heatmap of compound-specific unions of genes found significantly deregulated (red:
up-regulated; green: down-regulated) after carcinogen treatment. Gene expression
profiles are derived from AA- or OTA-treated Eker or wild type rats after 1 or 14 days
of treatment (WT-d1 to EK/d14), and from microdissected healthy tubules of 6 month
treated rats (HT). All genes were compared to their corresponding vehicle controls
(n=3 per time-point). The color scale at the left depicts gene expression ratios. Note
that only a qualitative comparison of genes is possible, since arrays were not
processed at same time points and only 1mg/kg bw instead of 10mg/kg AA were used
for chronic experiments.
The here presented findings suggest that the increase of preneoplastic lesions primarily
depends on the initial DNA damaging or nephrotoxic action of AA and OTA, while lesion
progression is the result of compound-independent clonal expansion (Chapter 3 and 6).
The extent of damage and regeneration may also determine the selection rate of
compound-insensitive cells. This suggests the existence of a specific time window where
healthy tubules are still sensitive towards carcinogen treatment and not yet adapted. Such
a critical period of carcinogen exposure would imply that extended compound exposure
might add little to the formation of additional preneoplastic lesions. Instead, the number of
preneoplastic lesions formed during this critical period can determine the incidence and
number of veritable tumors at later stages.
However, not all carcinogen-induced preneoplastic lesions will progress to neoplastic
lesions. Instead, some preneoplastic lesions may also be self-limiting or even reversible
(Alden and Kanerva 1982; Eustis 1989; Dietrich and Swenberg 1991). The identification of
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Chapter 9: Overall Discussion and Future Perspectives
pathways that distinguish self-limiting or reversible preneoplastic lesions from lesions with
true neoplastic potential would therefore greatly improve the predictive value of
preneoplastic lesions for carcinogenicity testing. Potential genes and pathways are
discussed in the following section.
9.2.2 Predictive potential of preneoplastic lesions as tumor precursors
Tumor progression has been suggested to depend on acquiring six essential "hallmarks of
cancer”, that collectively dictate malignant growth (Hanahan and Weinberg 2000) (Chapter
1.1.3 and Table 9.2). The basic concept of Hanahan and Weinberg is well accepted and
may be shared by the majority, if not by all tumor types. However, to date it is not clear
whether some or all of these acquired characteristics are detectable in preneoplastic
lesions.
Gene expression profiles derived from different progression stages of renal tumors, i.e.
from early basophilic atypical tubules (bAT) were highly similar to later basophilic atypical
hyperplasias (bAHs) (Chapter 6). This raised the hypothesis that early atypical tubules may
already have all prerequisites to develop into neoplastic lesions. Indeed, functional analysis
of gene expression profiles from microdissected renal bATs and bAHs identified groups of
deregulated genes and pathways that were indicative for all six hallmarks of cancer. Table
9.2 summarizes some of the functional groups of genes and pathways that may give rise to
the respective physiological changes, as proposed by Hanahan and Weinberg. Together,
these findings suggest that the earliest microscopically detectable preneoplastic lesions
from Eker rats may have the potential to develop into a malignant phenotype.
Functional analysis of deregulated genes as well as immunohistochemical staining of
pS6RP, pAKT and FOXO1 in bATs and bAHs of control, AA- and OTA-treated Eker rats
further demonstrated an activation of the mTOR pathway when compared to healthy tissue
of control animals (for details see chapter 6). The latter may result from a functional loss of
the TSC2 tumor suppressor gene in preneoplastic lesions by genetic or epigenetic events,
leading to a permanent activation of the TSC2-mTOR pathway.
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Chapter 9: Overall Discussion and Future Perspectives
Table 9.2: Genes and pathways linked to the six hallmarks of cancer, as suggested by Hanahan
and Weinberg (Hanahan and Weinberg 2000). For specific information see chapter 6
and GEO repository (http://www.ncbi.nlm.nih.gov/projects/geo; accession number:
GSE 10608)
Hallmark of cancer Suggested functional gene groups indicative
for the respective hallmarks
Self-sufficiency in
growth signals
Insensitivity to
growth inhibitory
signals
Evasion of
apoptosis
Limitless replicative
potential
Sustained
angiogenesis
Tissue invasion and
metastasis
Up-regulation of growth factors and their
receptors
Significantly deregulated genes, found
in preneoplastic lesions of this study,
supportive for the respective hallmark
Up: CTGF, HDGFRP3, IGFBP1, CNTF
Up-regulation of oncogenes Up: MYC, NIBAN, ELK3, CASC4
Up-regulation of members of the SOS-RAS-RAF-
MAPK pathway
Down-regulation of tumor suppressor genes or
survival factors
Down-regulation of terminal differentiation factors Down: HNF-4A
Up-regulation of anti-apoptotic genes and survival
factors
Down-regulation of pro-apoptotic genes Down: DNASE1
Up-regulation of genes involved in cell cycle
progression
Up: RAB2, RAB3D, RAB31, RAB6, NXN
Down: PINK1, CRYL1, FOXO1A, CHN2
Up: PEA-1, BNIP2, TMBIM1, ARC,
SH3BGRL3, CLU, GAS6, NAP1L1, KITL,
NRTN, EMP1
Up:, CCNB1, CCNB2, CDC2, CDCA3,
CKS2, PCTK2, AURKB, KIF15, KIF22,
PLK4, UBE2C, RMBS2, POLD1, MCM2,
MCM3, PAF
Up-regulation of endothelial growth factors Up: PAI1 CXCR4, GP38, DDL4, DSCR1,
Up-regulation of smooth muscle components Up: CRP1, PSEL,
Up-regulation of proteases or cell contact
inhibition
Up-regulation of genes involved in epithelial-
mesenchymal transition (EMT)
Up: tPA, BMP1, CTSK, CAPN2, ST14,
MEP1A, DPP7, KLK12, FXYD5, CD44
Up: VIM, CTGF, ACVR1, TGFBI, TGFB2,
Down-regulation of protease inhibitors Down: SERPINF2, HRG
Down-regulation of cell adhesion molecules Down: CXN-26, PCLKC, TFF3, TNS
An in-depth description of this pathway is given in the introduction of chapter 6 and is
summarized in Figure 9.4. Briefly, the mammalian target of rapamycin (mTOR) is an
intracellular Ser/Thr kinase that is part of two distinct protein complexes called TORC1 and
TORC2. The raptor-containing mTOR complex TORC1 is inhibited by the TSC1/ TSC2
complex, remains rapamycin-sensitive, and mainly activates ribosomal biogenesis,
translation and nutrient import. TORC2 is rapamycin-insensitive and is required for the
organization of the cytoskeleton (Mak and Yeung 2004; Jozwiak 2006; Wullschleger et al.
2006). Both TORC1 and TORC2 are key regulators of numerous important cellular
processes like cell growth, -survival, -proliferation, -motility and the nutrient-hormonal
signaling network. However, upon loss of the tumor suppressor TSC2, e.g. by carcinogeninduced
mutations, mTORC1 activity is aberrantly increased, leading to pathologies such
as cancer, metabolic disorders and cardiovascular diseases (Thomas 2006).
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Chapter 9: Overall Discussion and Future Perspectives
Under physiological conditions, TSC2 can be phosphorylated and inactivated by AKT in
response to growth factors (e.g. insulin), thus resulting in activation of mTORC1. TORC2 in
turn was demonstrated to directly phosphorylate AKT at Ser 473, resulting in the activation
of several down-stream pathways, including an indirect activation of TORC1 (Wullschleger
et al. 2006). Recent studies added even further complexity by suggesting the existence of a
negative feedback loop from the activated TSC2-TORC1-S6K1 pathway to the upstream
insulin-responsive IRS-PI3K-PDK1-AKT pathway (Figure 9.4) (Harrington et al. 2004; Um
et al. 2004). It was previously demonstrated that the mTORC1-dependent negative
feedback loop is still present in benign and growth-limited hamartomas (Kwiatkowski 2003;
Manning et al. 2005). This was in contrast to the findings of this study, which point to a
concomitant activation of TORC1 and TORC2 signaling and therefore to a disturbance of
this feedback loop in preneoplastic lesions from Eker rats (for details see chapter 6). In this
scenario, AKT activation due to TORC2 dependent Ser473 phosphorylation (Bellacosa et
al. 2005) would not only further ameliorate the AKT-TSC2-TORC1-dependent oxygen and
energy supply of proliferating cells via increased angiogenesis and glycolysis, but would
also reduce AKT-dependent apoptosis and cell cycle progression.
Together with the functional gene expression analysis, pointing to the establishment of all
six hallmarks of cancer, it might be possible that the simultaneous activation of TORC1 and
TORC2 may act as a neoplastic switch in renal preneoplastic lesions. Thus, disturbance of
the negative feedback loop of the AKT-TSC2-mTOR pathway may be indicative of a
malignant outcome. This is consistent with previous findings showing that the suppression
of phosphatase and tensin homolog PTEN in TSC2 mutant cells, which efficiently blocks
the phosphorylation of AKT, reactivates the PI3K-AKT pathway to generate more
aggressive tumors (Ma et al. 2005b). However, further research is needed to verify a direct
mechanistic correlation of these findings, for instance by using specific TORC1 or TORC2
inhibitors and a combination thereof in in vivo carcinogenicity studies. A specific inhibitor of
TORC1, rapamycin, is already used under the trade name ORISEL® (temsirolimus; Wyeth
USA) to treat patients with advanced RCC. However, and in accordance with the here
presented findings, new evidence suggests that mTOR might have a more central
rapamycin-insensitive role in the pathology of some cancers e.g. by hyperactive TORC2
signalling. In Spring 2008, a small molecule dual TORC1/TORC2 kinase inhibitor has
reached clinical trials (OSI-027, OSI Pharmaceuticals, Inc), which might help to further
clarify the role of this pathway in tumorigenesis.
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Chapter 9: Overall Discussion and Future Perspectives
Figure 9.3: Overview of the mTOR pathway and its hypothesized function within a proximal
tubule. Modified from (Wullschleger 2006, Thomas, 2006, Mak, 2004, Jacinto, 2004,
Hannah, 2008).
9.2.3 Summary Part II
For the first time, the findings from Eker rats have demonstrated a possible adaptation of
(damaged and regenerating) healthy tubules and an insensitivity of preneoplastic lesions
towards prolonged carcinogen treatment. Furthermore, these data indicate that the
incidence and number of veritable tumors is primarily driven by the number of preneoplastic
lesions initially formed during a critical period of carcinogen exposure. Clonal expansion of
preneoplastic lesions however seems to be a compound-independent process, and may be
essentially driven by the mTOR pathway. The finding that both, TORC1 and TORC2 are
activated in preneoplastic lesions of Eker rats points to a disturbed negative feedback loop
of the PI3K-AKT-TSC2-mTOR pathway. Together with the establishment of the 6 hallmarks
of (malignant) cancer, this finding suggests that the earliest detectable preneoplastic
lesions of Eker rats have the potential to overcome growth- and proliferation-limiting
barriers, and thus develop into full neoplasms. Molecular characteristics of the earliest
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Chapter 9: Overall Discussion and Future Perspectives
detectable preneoplastic lesions might therefore already be indicative for their later
outcome. In conclusion, the use of preneoplastic lesions as predictive endpoints in
shortened rodent bioassays seems principally possible.
9.3 Obesity as biasing factor for a reliable human risk
assessment from rodent bioassays
A large number of previous reports, as well as findings presented within this thesis, have
demonstrated an important role of the activated mTOR pathway in certain types of rodent
and human cancer (see 9.2.2). Next to its role in tumorigenesis, the mTOR pathway is also
known to be a central regulator for the nutrient-hormonal signaling network and activation
of the TORC1 complex is commonly detected in in vivo and in vitro models of obesity
(Castaneda et al. 2008; Cota et al. 2008; Gulati et al. 2008. Thus, it was hypothesized that
hyperactivation of the mTOR pathway might be a missing link between obesity and kidney
cancer (Thomas, 2006). However, the exact impact of chronic high fat diet exposure on
kidney cancer and the renal mTOR pathway remains widely elusive.
In the final part of this thesis, it was therefore hypothesized that prolonged high fat diet
exposure leads to the manifestation of severe renal pathology with early markers of renal
carcinogenesis. Specifically, this thesis aimed to dissect the impact of high body adiposity
with its known co-morbidities and disease consequences versus the direct impact of dietary
lipids on cellular renal pathways involved in renal carcinogenesis, such as the mTOR-S6K
pathway. Renal pathology in a diet-sensitive subpopulation ((DIOsens) characterized by a
morbidly increased body weight) was examined and compared to a diet-resistant
subpopulation ((DIOres) with moderately increased body weight) of male Wistar rats as well
as to chow fed control rats with normal body weight. This resulted in the following key
findings (for details see chapter 7).
1. DIOsens and DIOres rats but not control rats demonstrated marked tubular
damage, regenerative cell proliferation and chronic progressive nephropathy
(CPN). CPN was not only associated with a simple tubular hyperplasia, but also
with preneoplastic lesions, which might have the potential to manifest into solid
tumors at later stages of life.
2. In both DIOsens and DIOres rats positive staining of phosphorylated ribosomal
protein S6 (P-RPS6), a downstream effecter of activated TORC1, was detected in
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Chapter 9: Overall Discussion and Future Perspectives
nearly all cells of regenerating tubules within the CPN lesions, and especially in
tubules with an atypical phenotype.
3. A similar degree of histopathological changes in DIOsens and DIOres rats
suggested a more prominent role of the dietary fat content, rather than the degree
of adiposity, for the etiology of renal pathology and TORC1 activation.
Together these findings demonstrate a clear adverse effect of dietary lipids on renal
morphology and further implicate that dietary lipids may act via similar mechanism like
nephrotoxic compounds. The findings of chapter 3, 4 and 6 implicate that renal tissue
damage, inflammation and regeneration are important factors contributing to the onset and
progression of RCC. High-fat diet-induced renal damage therefore may further propagate
the fixation of spontaneous mutations and progression of pre-neoplastic lesions into solid
renal tumors. Notably, preneoplastic lesions are frequently found within the CPN lesions
and might be indicative for a cancer promoting action of dietary lipids. However, to date it
cannot be determined whether such preneoplastic lesions would further develop into gross
tumors. Instead, the observed lesions could be self-limiting or even reversible, since no
adenomas or carcinomas could be detected in this study (see chapter 9.2). Nevertheless,
the lack of gross tumors was not surprising and indeed was not expected after 11 month of
high-fat diet exposure, since full adenomas and carcinomas in rodent bioassays are often
only detectable after 15 to 18 months of carcinogen treatment (Haseman et al. 2001).
The findings of chapter 7 have demonstrated an increased amount of phosphorylated
RPS6 in atypical and regenerating tubules of DIOsens and DIOres rats, but not in
unaffected tissue or in control animals. These preliminary findings may point to a role of
TORC1 in dietary lipid-induced renal damage and regeneration. However, it cannot be
concluded whether high fat diet directly results in an activation of TORC1 and RPS6
phosphorylation in renal cells (e.g. via pathways summarized in Figure 9.4). Alternatively,
TORC1 activation could simply be a secondary effect of cell regeneration, e.g. via
stimulation with extracellular growth factors like IGF-1 (Moore et al. 2008). Thus, clearly
more research is needed to clarify whether the nephrotoxic action of high fat diet may be
involved in the onset or progression of spontaneous mutations. This question could be
answered in an in vivo tumor initiation-promotion study, using e.g. aristolochic acid as
kidney specific tumor initiator and high fat diet as possible promoter. In addition, further
studies should be conducted in vitro in primary kidney cells or established kidney cell lines,
to clarify whether direct exposure to various fatty acids might directly stimulate renal
TORC1 or TORC2.
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Chapter 9: Overall Discussion and Future Perspectives
Considering that obesity has reached epidemic proportions, further elucidating the impact
of high fat diet on renal and other types of cancer seems not only important under a
medical aspect, but also regarding carcinogenicity testing in rodents. The choice of diet can
severely affect the results of the rodent bioassay. For instance ad libitum-feeding of a high
caloric diet considerably enhanced weight gain, increased background tumor development
and non-neoplastic lesions, and decreased the life-span of rodents, compared to those fed
with a caloric restricted chow (Keenan et al. 1995; Keenan et al. 1996). Thus, the dosage
and composition of a diet can significantly influence the effects of a test compound,
possibly by enhancing tubular damage and regeneration or by (synergistic) a”ctivation of
the mTOR pathway.
In conclusion, high-fat diet exposure with high body adiposity clearly represents principal
biasing factors for a reliable human risk assessment of compounds in rodent bioassays. It
seems entirely possible that previous carcinogenicity testing in rodents underestimated the
potential impact of a carcinogen in human subpopulations exposed to a high fat/ high
calorie environment. Future studies should address this important issue, and should clarify
whether carcinogen exposure in obese human subpopulations indeed could be linked to an
enhanced number and incidence of renal cancer.
9.4 Synopsis
Evaluating the carcinogenic potential of test compounds by life-time rodent bioassays is
time-consuming and associated with high financial costs, high numbers of animals, and a
high amount of compound is required for continuous dosing over the entire period of the
assay. With respect to the kidney, the findings of this thesis suggest that it could be
possible to shorten rodent bioassays and to increase the specificity of these assays by
using predictive biomarkers in short-term, or intermediate in vivo assays. The key findings
of this study, (a) that microarrays allow the detection and distinction of genotoxic and nongenotoxic
carcinogens in short-term assays and (b) that the incidence and number of
veritable tumors is primarily driven by the number of preneoplastic lesions initially formed
during a critical period of exposure. If the above hypothesis would be transferable to other
organs, then the following possibilities seem likely:
• Predictive biomarkers could serve as early and specific indicators for a genotoxic or
non-genotoxic carcinogenic action of test compounds in short-term (prescreening)
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Chapter 9: Overall Discussion and Future Perspectives
assays. With short term assays the use of carcinogenic compounds could be
reduced.
• The continuous dosage of animals could be limited to the “critical” time window
where cells are not yet adapted to the carcinogen exposure. Thus, much shorter
time-period of exposure with a concomitant reduction of pain and distress for the
animals could be achieved.
• Predictive biomarkers might identify the carcinogenic potential of preneoplastic
lesions by distinguishing between a potential malignant or self-limiting phenotype.
Furthermore, specific markers may help to distinguish carcinogen-induced
preneoplastic lesions from spontaneous background lesions. Such mechanistic
biomarkers involved in rodent and human preneoplastic lesion progression (e.g. the
mTOR pathway) could therefore serve as improved predictors for the neoplastic
outcome in rats and the potential risk in humans.
• By further specifying the carcinogenic potential of preneoplastic lesions, these could
indeed serve as reliable endpoints for carcinogenicity testing and thus shorten the
assay. In addition, reduced mortality in shorter assays would also allow a reduction in
the number of animals. Moreover, residual animals would not suffer from extensive
tumor growth.
In general, higher efficiencies of the current safety testing paradigm (shorter assays with
fewer animals) would lead to the reduction of financial costs for product development. In
conclusion, the here presented findings suggest that the standard rodent bioassay can
indeed be improved, mainly by shortening the duration of the life-time rodent bioassay, and
by using novel methodology such as gene array. Ultimately, this thesis provides
encouraging first results that may one day help to establish a new rodent bioassay that
ultimately reduces and refine refines and even replaces animal experiments.
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Erklärung
Die vorliegende Arbeit wurde ohne unzulässige Hilfe Dritter und ohne Benutzung anderer
als der angegebenen Hilfsmittel angefertigt. Die aus anderen Quellen direkt oder indirekt
übernommenen Daten und Konzepte sind unter Angabe der Quelle gekennzeichnet.
Weitere Personen, insbesondere Promotionsberater, waren an der inhaltlich materiellen
Erstellung dieser Arbeit nicht beteiligt. Die Arbeit wurde weder im In- noch im Ausland in
gleicher oder ähnlicher Form einer anderen Prüfungsbehörde vorgelegt.
Eigenabgrenzung/ Kooperationen
• Die Hybridisierung der Microarrays (siehe Kapitel 3, 4, 5 und 6) erfolgte in der
Abteilung Molecular and Special Toxicology, Bayer Healthcare AG in Wuppertal.
• Sämtliche Paraffinschnitte wurden von Mitarbeitern der Abteilung Non-Clinical Drug
Safety bei Boehringer Ingelheim in Biberach hergestellt.
• LC-MS/MS Analysen zur Detektion von O6MG Addukten (Kapitel 4) wurden von
Mitarbeitern von Prof. Dr. James A. Swenberg am Department of Environmental
Sciences and Engineering, University of North Carolina, Chapel Hill, USA
durchgeführt.
• Die Exposition der Ratten mit fetthaltiger Diät, sowie die Messung der Blutparameter
(Kapitel 7) wurde von Mitarbeitern von Prof. Dr. Matthias Tschöp, im Department of
Psychiatry, Obesity Research Centre in Cincinnati, Ohio, USA durchgeführt.
Alle weiteren Leistungen wurden, sofern nicht explizit angemerkt, von mir selbst
durchgeführt.
Konstanz im Oktober 2008
Kerstin Stemmer
199

Danksagung
Meinen herzlichsten Dank möchte ich all denen aussprechen, die mich auf dem Weg zur
Entstehung dieser Doktorarbeit unterstützt haben. Mein besonderer Dank gilt hierbei:
• Prof. Dr. Daniel Dietrich für die Überlassung des Promotionsthemas, seine stete
wissenschaftliche und menschliche Unterstützung, seine Förderung,
Diskussionsbereitschaft und Offenheit gegenüber neuen Projektideen. Insgesamt für
eine schöne und sehr lehrreiche Zeit in der AG-Dietrich, an die ich immer gerne
zurückdenken werde.
• Prof. Dr. Christof Hauck für die Übernahme des Koreferates und sein Interesse an
dieser Arbeit.
• Dr. Dr. Hans-Jürgen Ahr, Dr. Heidrun-Ellinger Ziegelbauer und Mitarbeitern für eine
offene und nette Projektkooperation, ihre stete Diskussionsbereitschaft auch nach
Projektabschluss, das Einlernen in die komplexe Auswertung von Microarray Analysen,
nicht zuletzt für die herzliche Gastfreundschaft und Unterstützung während vieler
mehrwöchiger Aufenhalte bei der Bayer HealthCare AG in Wuppertal.
• Prof. Dr. Matthias Tschöp, Dr. Paul Pfluger und Dr. Diego Perez-Tilve für Ihre
Unterstützung und Begeisterung, ein neues, gemeinsames Projekt auf den Weg zu
bringen, ihre Gastfreundschaft, und die Überlassung eines Laborplatzes während
mehrer Aufenthalte am Obesity Research Center in Cincinnati, sowie für den Einblick in
die Kunst des Cabrewings. Besonders bei Paul möchte ich mich für die Korrekturen und
die konstruktive Kritik an dieser Arbeit bedanken. Nicht zuletzt für unzählige
wissenschaftliche Diskussionen, die so manch gute Idee und Fortschritt mit sich
brachten. Erin Grant möchte ich herzlichst für die Englisch-Korrekturen danken.
• Dr. Ulrich Deschl, Dr. Thomas Nolte und Mitarbeitern, für die Ermöglichung eines 2wöchigen
Arbeitsaufenthaltes in der Abteilung für Non-Clinical Drug Safety bei
Boehringer Ingelheim in Biberach. Ohne diesen waere mir die Planung und
Durchführung der in vivo Studie für diese Doktorarbeit weitaus schwerer gefallen. Nicht
zuletzt bedanke ich mich für das Anfertigen zahlreicher Paraffinschnitte.
• Prof. Dr. James A. Swenberg und Mitarbeitern vom Department of Environmental
Sciences and Engineering, University of North Carolina, Chapel Hill, danke ich für die
Zusammenarbeit und die Quantifizierung von DNA-Addukten mittels LC-MS/MS.
• Allen ehemaligen und jetzigen Mitarbeiter/-innen der Arbeitsgruppe Dietrich für das
nette und familiäre Arbeitsklima. Besonders Tanja Lampertsdörfer und Gudrun von
Scheven möchte ich für die tatkräftige Unterstützung beim in vivo Versuch und bei der
Verabreichung tausender Schlundsonden danken. Beiden, sowie Dan Dietrich, Alex
Heussner und Evelyn O’Brien gilt mein Dank für die Mithilfe bei den Sektionen.
Und vor allem meiner Familie und meinem Freund Paul für ihre stete Unterstützung in allen
Lebenslagen, ihren stetigen Beistand, und ihre Ruhe während aller Höhen und Tiefen dieser
Doktorarbeit.
200