Abstracts of the Scientific Posters, 2013 AACC Annual Meeting ...

Cancer/Tumor Markers
Tuesday, July 30, 9:30 am – 5:00 pm
as identified by MARS. The importance of glycerol and ethanolamine in the HCC
MARS metabolite panel points to a potential cancer-related variation in fatty acid
metabolism.
released using the on-membrane deglycosylation method and labeled and analyzed by
fluorophore-assisted carbohydrate electrophoresis using a capillary electrophoresisbased
ABI3130 sequencer.
A-13
Complete mitochondrial genome sequencing reveals association with
acute myeloid leukemia
J. Zhou, W. Wang, Y. Ye, X. Lu, B. Ying, L. Wang. West China Hospital,
Sichuan University, Chengdu, China
Background: To explore mitochondrial DNA variations in acute myeloid leukemia
(AML) patients.
Methods: Blood or bone marrow samples of 47 AML patients (20 M1 and 27 M2)
who met with WHO diagnostic criteria and 40 age- and sex-matched healthy controls
were collected. The whole mitochondrial genome was directly sequenced in 24
overlapping fragments, then spliced by DNAstar software, and eventually compared
with Cambridge reference sequence (CRS) using CodonCode Aligner software.
Results: A total of 639 variations were found, twenty eight of which have not been
reported at www.mitomap.org and mtDB (www.genpat.uu.se/mtDB/). 224 variations
were found only in patients, two of which were statistical significant, they were
T14200C (6/47, P=0.029) in ND6 region and C14929A (14/47, P=0.000) in CYTB
region. We then compared the frequencies of the rest variations between case and
control groups, C6455T in COI region and T16297C in D-loop region were found
to be associated with the risk of AML. People carrying C6455T mutation had a 5.8-
fold risk of developing AML (95%CI: 1.203-28.0, P=0.016), and people carrying
T16297C mutation had a 4.5-fold risk (95%CI: 0.911-22.21, P=0.048). Furthermore,
we analyzed the relationship between the above four variations and clinical features,
and found that C6455T, T16297C and C14929A occurred more frequently in M1
patients than in M2 patients, and patients with these variations had higher percentage
of myeloblasts in the bone marrow and higher percentage of abnormal cells in blood,
While T14200C showed the opposite results.
Conclusion: C6455T, T16297C, C14929A and T14200C might be used as potential
biomarkers for M1/M2 patients. Further studies are needed to verify these findings in
another large population, and the roles of the variations play in the pathogenesis of
AML remains to be explored.
Table 1 Characteristics of the four positive-association variations from screening the
whole mitochondrial genome
Position Base Case Control P-
change N % N %
OR(95%CI) Region Codon Amino Change
value
6455 C-T 11(4) # 23.40% 2 5.00% 0.016 5.806(1.203-28.0) COI 184 Phe-> Phe
14200 T-C 6(5) # 12.77% 0 0.00% 0.029 / ND6 158 Trp -> Trp
14929 C-A 14(14) # 29.79% 0 0.00% 0.000 / CYTB 61 Thr -> Thr
16297 T-C 9(2) # 19.15% 2 5.00% 0.048 4.5(0.911-22.21) D-loop
#
The number inside the parentheses presented the frequencies of heterozygote
A-14
Prostate proteins glycosylation profile and its potential as a diagnostic
biomarker for prostate cancer
T. Vermassen 1 , N. Lumen 2 , C. Van Praet 2 , D. Vanderschaeghe 3 , N.
Callewaert 3 , P. Hoebeke 2 , S. Van Belle 1 , S. Rottey 1 , J. R. Delanghe 4 .
1
Department of Medical Oncology, University Hospital Ghent, Ghent,
Belgium, 2 Department of Urology, University Hospital Ghent, Ghent,
Belgium, 3 VIB Department of Molecular Biomedical Research - Ghent
University, Ghent, Belgium, 4 Department of Clinical Chemistry, University
Hospital Ghent, Ghent, Belgium
Introduction: Serum Prostate Specific Antigen (sPSA) is widely used for screening
and early diagnosis of prostate cancer (PCa). This analysis is associated with
considerable sensitivity and specificity problems especially in the diagnostic gray
zone (sPSA between 4 and 10ng/ml). In urine, PSA is only detected in its free form
with concentrations largely exceeding the values observed in serum or plasma.
Because of aberrant glycosylation changes in tumorogenesis, we explored the use of
prostate proteins and its glycosylation profile as a new biomarker for PCa.
Materials and Methods: We determined standard biochemical markers (total
urinary protein, albumin in urine, gamma-GT in urine, urinary total PSA, urinary
free PSA and sPSA) in healthy volunteers (HV; n = 16), patients with BPH (n =
39), PCa patients (n = 29) and prostatitis (n = 14). Urinary protein N-glycans were
Results: None of these markers was able to discriminate BPH from prostate
cancer, except for sPSA. N-glycan profile analyses have pointed out differences in
the N-glycosylation patterns between BPH and PCa. The changes were associated
with a decreased fucosylation of bi- and triantennary structures. This isolated test
was not statistically better than sPSA measurement (AUC after ROC curve analysis:
0.805 ± 0.056 and 0.737 ± 0.063 for sPSA screening and the glycosylation marker
respectively). Logistic regression showed that the glycosylation marker gives an
added value to sPSA screening: combining these assays resulted in an AUC of 0.854
± 0.049 for all patients.
Conclusion: We have found a statistical significant difference in the urinary
glycosylation patterns of patients with BPH versus PCa patients. These changes in
N-glycosylation could lead to the discovery of a new biomarker for PCa, particularly
in the diagnostic gray zone.
A-15
Fast Method for Classification Based on Coherent High Resolution
XUV Scatter Images of Biologic Specimen
M. Zürch 1 , S. Foertsch 2 , M. Matzas 2 , K. Pachmann 3 , R. Kuth 2 , C.
Spielmann 1 . 1 Friedrich-Schiller-University Jena, Jena, Germany, 2 Siemens
AG, Healthcare Sector, Erlangen, Germany, 3 University Hospital Jena,
Jena, Germany
Background: In cancer research and diagnostics the cell classification is currently
done by classical PCR analysis. This procedure is time consuming and results will
be often available only within a few days. For several reasons the need for faster
and probably cheaper methods is obvious. Current research for realizing a faster
discrimination concentrates on spectroscopic methods, e.g. Raman spectroscopy. In
this contribution we will present a method relying on high resolution imaging based
on coherent diffraction imaging of biological samples such as a single cell illuminated
with coherent short wavelength light.
Methods: Our experimental apparatus is based on a commercial ultra-short infrared
laser system. With nonlinear methods we convert the visible light into laser-like
light extreme ultraviolet (XUV) radiation in the range from 20 to 70 nanometers,
whilst preserving the high spatial and temporal coherence. This XUV light source is
used to illuminate different biologic specimen. In our recent experiments we choose
four different single cells from the MCF7 and SKBR3 breast-cancer-cell-line cells,
pipetted on a gold-coated fused silica slide. The cells were prepared in a PBS puffer,
which remained on the sample holder after drying. It is worth to mention that no
additional markers or staining is required. The recorded images of scattered XUV
light from the samples contain the full spatial information (“2D fingerprint”) down to
a feature size of roughly half of the XUV wavelength. From these recorded diffraction
patterns it is possible to reconstruct the real space image of the sample with the help of
well-established coherent diffraction imaging algorithms. However, these algorithms
are slow, limiting the throughput of the system. Since only classification is of interest
CLINICAL CHEMISTRY, Vol. 59, No. 10, Supplement, 2013
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