Transcriptional Characterization of Glioma Neural Stem Cells Diva ...

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7.3 Tumour Expression Correlation Results The PRSS12 gene encodes a protease that can activate tissue plasminogen acti- vator (tPA) [335], an enzyme which is highly expressed by glioma cells and has been suggested to promote invasion [168]. We observe a slight up-regulation in the GNS cell lines and primary GBM of PRSS12 (Fig 7.4a), and a slight down-regulation in grade III astrocytomas (Fig 7.4b). The LYST gene encodes a vesicular transport protein called the "lysosomal trafficking regulator" that so far has not been implicated in any neoplasia but is known to be associated with a rare recessive disorder (Chédiak-Higashi syn- drome) caused by a microtubule polymerisation defect that decreases phago- cytosis ability [87]. In line with the hypothetical increase of cellular activities and rates, and thus of vesicular transport, in GNS cells, we observed LYST to be up-regulated in GNS cell lines and primary GBM (Fig 7.4a), and slightly down-regulated in grade III astrocytomas (Fig 7.4b). Down-regulated in GNS cell lines. The panels c and d of figure 7.4 the core down-regulated genes found through Tag-seq are used to evaluate the comparison of the GBM data to the non-neoplastic tissue data (TCGA dataset), and the comparison of the GBM (grade IV) to the grade III astrocytoma (HGG dataset). In this comparison the genes that were also identified via qRT-PCR as being differentially expressed between GNS cell lines and NS cell lines, are highlighted by the blue colour gradient dots. The trends highlighted in figure 7.4 show matching down-regulation for genes NELL2, TUSC3, ST6GALNAC5, PLCH1, NDN, MAP6 and PTEN in GNS cell lines and primary GBM, and non matching down-regulation in GNS cell lines and up-regulation in primary GBM for genes MAF, MYL9, HMGA2, SDC2, SYNM, IRX2, TES and TAGLN. The MAF gene encodes a transcription factor and oncoprotein that belongs to the same AP-1 super-family of JUN and FOS. MAF has been associated with multiple myeloma whereby its up-regulation is suggested to enhance myeloma proliferation and adhesion to the bone marrow [406]. Although not previously linked to glioma, we find MAF to be down-regulated in GNS cell lines but slightly up-regulated in primary GBM, perhaps as an indicator of its cell type restricted proliferation enhancing functions (Fig 7.4c). Accordingly, we observed a slight down-regulation of MAF in grade III astrocytoma with respect to primary GBM (Fig 7.4d). The protein encoded by the MYL9 gene is a myosin light chain that has previously been associated with the stem cell component of lung adenocar- cinoma [447] and medullary breast cancer [54] in gene expression profiling studies. MYL9 has never been implicated in glioma and we observed down- 178
7.3 Tumour Expression Correlation Results regulation of its expression in GNS cell lines opposed to its up-regulation in primary GBM (Fig 7.4c), and a strong down-regulation in grade III astrocytoma (Fig 7.4d). The HMGA2 gene encodes a transcriptional regulator that belongs to the non- histone family of structural proteins. The members of this family act as chro- matin architectural factors and contain structural DNA-binding domains that allow them to act as transcriptional factors. We find HMGA2 to be down- regulated in GNS lines and up-regulated in primary GBM (Fig 7.4c), and slightly down-regulated in grade III astrocytoma (Fig 7.4d). Low or absent protein expression of HMGA2 has been observed in GBM compared to low grade gliomas [14] and HMGA2 polymorphisms have been associated with survival time in GBM [295]. The SDC2 gene encodes a transmembrane heparan sulfate proteoglycan that participates as an extracellular matrix receptor in the processes of cell proliferation, cell migration and cell-matrix interaction. An altered expression of SDC2 has been detected in esophageal carcinoma [201], colon carcinoma [184], fi- brosarcoma [380], prostate cancer [108,407] and gliomas, where over-expression of SDC2 promotes membrane protrusion, migration, capillary tube formation and cell-cell interactions in microvascular endothelial cells [141]. We found SDC2 to be down-regulated in GNS cell lines and grade III astrocytoma, but slightly up-regulated in primary GBM (Fig 7.4). The SYNM gene is a type IV intermediate filament that has recently been shown to interact with the LIM domain protein Zyxin, thereby possibly mod- ulating cell adhesion and cell motility. Aberrant SYNM promoter methylation has been associated with early breast cancer relapse [362]. In gliomas SYNM has been found to promote AKT-dependent GBM cell proliferation by antago- nising protein phosphatase PP2A, the major regulator of Akt dephosphoryla- tion [396]. We found SYNM to be down-regulated in GNS cell lines and grade III astrocytoma, but slightly up-regulated in primary GBM, although with a relatively high p-value (Fig 7.4). The IRX2 gene is a iroquois-class homeobox genes that has been associated with development of the vertebrate embryo and in humans specifically in the development of brain [322] and breast [274]. Over-expression of IRX2 has been detected in soft tissue sarcomas [7]. IRX2 has been proposed to enhance antitumour immune responses in that ex vivo pre-treatment of CD8 + T cells with IRX-2 provided protection from tumour- induced apoptosis [112]. In line with this suggested role of IRX2, we observed the gene to be strongly down-regulated in GNS cell lines and grade III astro- 179
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Transcriptional Characterization of
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This dissertation is my own work an
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Acknowledgements I would like to th
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5.9 External Dataset Expression Cor
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Introduction 1
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1.1 Glial Cells in the Central Nerv
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1.2 Glioblastoma Multiforme Introdu
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1.3 Primary and Secondary Glioblast
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1.4 Pathways Involved in Glioblasto
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1.5 Pathway Crosstalk Introduction
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Chapter 2 Neurogenesis Contents 2.1
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2.1 Radial Glia Introduction VZ adj
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2.2 Neural Stem Cells Introduction
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Chapter 3 Brain Cancer Stem Cells C
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3.1 The Cancer Stem Cell Hypothesis
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3.1 The Cancer Stem Cell Hypothesis
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3.2 Brain Cancer Stem Cells Introdu
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3.3 Glioma Culture Systems Introduc
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Chapter 4 The Non-Coding RNA World
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4.1 MicroRNA regulation Introductio
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4.1 MicroRNA regulation Introductio
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4.2 Target Prediction and Validatio
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Methods 93
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5.1 Tag-sequencing Data Processing
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5.1 Tag-sequencing Data Processing
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5.2 Array Comparative Genomic Hybri
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5.4 Quantitative Real Time-PCR Vali
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5.5 Literature Mining Methods Figur
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5.5 Literature Mining Methods How m
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5.6 Differential Isoform Expression
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5.9 External Dataset Expression Cor
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5.10 Glioblastoma Pathway Construct
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5.11 MicroRNA Target Prediction Ana
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Results 119
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6.2 Tag mapping Results Table 6.1:
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6.2 Tag mapping Results 123 Figure
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6.3 Copy Number Aberrations Results
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9.1. Digital Profiling of GNS Cell
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9.2. MicroRNA Target Prediction Ana
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9.3. Concluding Remarks Appendix pr
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A.1 Differential Expression Appendi
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A.2 Classified Differential Express
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A.3 Quantitative RT-PCR Appendix Ta
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A.3 Quantitative RT-PCR Appendix We
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A.3 Quantitative RT-PCR Appendix Ta
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A.3 Quantitative RT-PCR Appendix We
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A.4 Tag-seq vs qRT-PCR Correlation
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Appendix "BEX5", "DIAPH2", "GBP3",
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End Select End If End Sub Appendix
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If NameStr.ToLower().Equals("query"
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Appendix C Long ncRNAs We detected
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C. Long ncRNAs Appendix Tag Accessi
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D.1 Pathway Interactions Appendix F
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D.2 Pathway Images Appendix Figure
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D.2 Pathway Images Appendix Figure
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E. Exon Array Data Appendix Average
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F. MicroRNA Array Data Appendix Tab
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F. MicroRNA Array Data Appendix GNS
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F. MicroRNA Array Data Appendix GNS
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Ln Natural logarithm LOH Loss of He
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3.3 Schematisation of cell cycle ph
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8.3 Workflows at the core of the pr
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7.1 Selected Gene Ontology terms an
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