Gene expression analysis in ovarian cancer - faults and hints from DNA microarray study.
The introduction of microarray techniques to cancer research brought great expectations for finding biomarkers that would improve patients' treatment; however, the results of such studies are poorly reproducible and critical analyses of these methods are rare. In this study, we examined global gene expression in 97 ovarian cancer samples. Also, validation of results by quantitative RT-PCR was performed on 30 additional ovarian cancer samples. We carried out a number of systematic analyses in relation to several defined clinicopathological features. The main goal of our study was to delineate the molecular background of ovarian cancer chemoresistance and find biomarkers suitable for prediction of patients' prognosis. We found that histological tumor type was the major source of variability in genes expression, except for serous and undifferentiated tumors that showed nearly identical profiles. Analysis of clinical endpoints [tumor response to chemotherapy, overall survival, disease-free survival (DFS)] brought results that were not confirmed by validation either on the same group or on the independent group of patients. CLASP1 was the only gene that was found to be important for DFS in the independent group, whereas in the preceding experiments it showed associations with other clinical endpoints and with BRCA1 gene mutation; thus, it may be worthy of further testing. Our results confirm that histological tumor type may be a strong confounding factor and we conclude that gene expression studies of ovarian carcinomas should be performed on histologically homogeneous groups. Among the reasons of poor reproducibility of statistical results may be the fact that despite relatively large patients' group, in some analyses one has to compare small and unequal classes of samples. In addition, arbitrarily performed division of samples into classes compared may not always reflect their true biological diversity. And finally, we think that clinical endpoints of the tumor probably depend on subtle changes in many and, possibly, alternative molecular pathways, and such changes may be difficult to demonstrate.
Center for Translational Research and Molecular Biology of Cancer, Maria Skłodowska-Curie Memorial Cancer Center and Institute of Oncology , Gliwice , Poland.
Katarzyna Marta
KM
Lisowska
Center for Translational Research and Molecular Biology of Cancer, Maria Skłodowska-Curie Memorial Cancer Center and Institute of Oncology , Gliwice , Poland.
Magdalena
M
Olbryt
Department of Medical Biology and Genetics, Grodno State Medical University , Grodno , Belarus.
Volha
V
Dudaladava
Center for Translational Research and Molecular Biology of Cancer, Maria Skłodowska-Curie Memorial Cancer Center and Institute of Oncology , Gliwice , Poland.
Jolanta
J
Pamuła-Piłat
Center for Translational Research and Molecular Biology of Cancer, Maria Skłodowska-Curie Memorial Cancer Center and Institute of Oncology , Gliwice , Poland.
Katarzyna
K
Kujawa
Center for Translational Research and Molecular Biology of Cancer, Maria Skłodowska-Curie Memorial Cancer Center and Institute of Oncology , Gliwice , Poland.
Ewa
E
Grzybowska
Center for Translational Research and Molecular Biology of Cancer, Maria Skłodowska-Curie Memorial Cancer Center and Institute of Oncology , Gliwice , Poland.
Michał
M
Jarząb
Faculty of Automated Control, Electronics and Computer Science, Silesian University of Technology , Gliwice , Poland.
Sebastian
S
Student
Department of Pathology, Maria Skłodowska-Curie Memorial Cancer Center and Institute of Oncology , Warsaw , Poland.
Iwona Krystyna
IK
Rzepecka
Department of Nuclear Medicine and Oncological Endocrinology, Maria Skłodowska-Curie Memorial Cancer Center and Institute of Oncology , Gliwice , Poland.
Barbara
B
Jarząb
Department of Pathology, Maria Skłodowska-Curie Memorial Cancer Center and Institute of Oncology , Warsaw , Poland.
Jolanta
J
Kupryjańczyk
CLASP1; epithelial ovarian cancer; gene expression profiling; genomic medicine; molecular markers; oligonucleotide microarrays; survival time; tumor histology