Abstract
Ovarian cancer is the fifth leading cause of cancer death for women in the U.S. and the seventh most fatal worldwide. Although ovarian cancer is notable for its initial sensitivity to platinum-based therapies, the vast majority of patients eventually develop recurrent cancer and succumb to increasingly platinum-resistant disease. Modern, targeted cancer drugs intervene in cell signaling, and identifying key disease mechanisms and pathways would greatly advance our treatment abilities. In order to shed light on the molecular diversity of ovarian cancer, we performed comprehensive transcriptional profiling on 129 advanced stage, high grade serous ovarian cancers. We implemented a, re-sampling based version of the ISIS class discovery algorithm (rISIS: robust ISIS) and applied it to the entire set of ovarian cancer transcriptional profiles. rISIS identified a previously undescribed patient stratification, further supported by micro-RNA expression profiles, and gene set enrichment analysis found strong biological support for the stratification by extracellular matrix, cell adhesion, and angiogenesis genes. The corresponding “angiogenesis signature” was validated in ten published independent ovarian cancer gene expression datasets and is significantly associated with overall survival. The subtypes we have defined are of potential translational interest as they may be relevant for identifying patients who may benefit from the addition of anti-angiogenic therapies that are now being tested in clinical trials.
Highlights
Advanced epithelial ovarian cancer is notable for initial sensitivity to platinum- and taxane-based chemotherapy [1,2], but the vast majority of women will develop recurrent ovarian cancer within 12 to 24 months and will eventually die from increasingly platinum- and chemotherapy-resistant disease
Eligible patients had a diagnosis of late stage high grade papillary serous ovarian carcinoma, pathology blocks available for generation of a high-density tissue microarray (HTMA) [13]
We focused on high grade serous tumors as they represent, by far, the most common histologic subtype of ovarian cancer and the one most responsive to chemotherapy
Summary
Advanced epithelial ovarian cancer is notable for initial sensitivity to platinum- and taxane-based chemotherapy [1,2], but the vast majority of women will develop recurrent ovarian cancer within 12 to 24 months and will eventually die from increasingly platinum- and chemotherapy-resistant disease. Gene expression profiling data represents the largest source of genomic data that might be of use in identifying clinically-relevant subtypes in ovarian cancer, and multiple studies have explored its use for finding predictive biomarkers and clinically-relevant subtypes in ovarian cancer [3,4,5,6,7,8,9,10,11]. Tothill et al [10] used an unsupervised clustering of gene expression profiles and proposed the existence of six subtypes in epithelial ovarian cancer (denoted C1–C6) and a seventh group of unclassifiable tumors (NC); the C1 subtype, which had the poorest prognosis, was found to be characterized by expression of a responsive stromal signature. Dressman and colleagues [5] used a supervised statistical approach to predict response to platinum-based treatment from gene expression data; they found evidence linking chemoresistance to Src and Rb/E2F pathway activity.
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