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Title: Analysis of gene expression in stage I serous tumors identifies critical pathways altered in ovarian cancer.
Authors: Chien J,  Fan JB,  Bell DA,  April C,  Klotzle B,  Ota T,  Lingle WL,  Gonzalez Bosquet J,  Shridhar V,  Hartmann LC
Journal: Gynecol Oncol
Date: 2009 Jul
Branches: CGR
PubMed ID: 19410283
PMC ID: not available
Abstract: OBJECTIVE: Despite recent advances in the conceptual understanding of the pathogenesis of ovarian cancer, it remains the foremost cause of death from gynecologic malignancies in developed countries. The main reason for such a high rate of mortality is the lack of sensitive and specific biomarkers and imaging techniques for early detection of ovarian cancer. Additional biological insights into early-stage ovarian carcinogenesis are needed to help speed the development of markers for early detection of ovarian cancer. The objective of this study was to characterize differentially expressed genes in high-grade stage I serous carcinoma of the ovary. METHODS: We analyzed gene expression in macrodissected formalin-fixed, paraffin-embedded samples from 5 high-grade stage I serous carcinomas and 5 stage I borderline tumors of the ovary using the Illumina Whole Genome DASL assay (cDNA-mediated annealing, selection, extension, and ligation) corresponding to 24,000 genes. Significance Analysis of Microarrays was performed to determine differentially expressed genes in stage I serous carcinoma, and class prediction analysis was performed to determine the predictive value of differentially expressed gene sets to correctly classify serous carcinoma from borderline tumors in 3 independent data sets. Altered transcription factor pathways and biological pathways unique to stage I serous carcinoma were identified through class comparison of differentially expressed genes. RESULTS: Unsupervised cluster analysis of gene expression correctly classified stage I serous carcinomas from serous borderline tumors. Supervised analysis identified several known, as well as novel, genes differentially expressed in stage I ovarian cancer. Using a differentially expressed gene set, class comparison prediction analysis correctly identified serous carcinomas from serous borderline tumors in 3 independent data sets at over 80% accuracy, sensitivity, and specificity. Pathway analysis demonstrated the significance of p53 and E2F pathways in serous carcinogenesis and significant involvements of cell cycle and immune response pathways in stage I serous epithelial ovarian cancer. CONCLUSION: We have identified differentially expressed genes associated with the carcinogenesis of high-grade stage I serous EOC. Furthermore, integrative analysis of biological and transcription pathway data contributed to the confirmation of important biological pathways and discovery of additional unique genes and pathways that may have potential importance in ovarian pathogenesis and biomarker development.