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U.S. National Institutes of Health
Last Updated: 03/05/10

Jeffrey A. Boyd, Sloan-Kettering Institute for Cancer Research
“Molecular Classification of Ovarian Cancers”

Abstract: Epithelial ovarian carcinoma is the leading cause of mortality among all gynecologic cancers. Poor survival rates associated with this malignancy are attributable to a frequently advanced stage at diagnosis and the inability to successively treat most cases of advanced stage disease using current standards of surgery and chemotherapy. While there are a number of clinical, surgical outcome, and histopathological variables that correlate with prognosis for ovarian cancer, there exists wide variation in the length of recurrence-free interval and survival among typical cases, i.e., post-menopausal women with moderately to poorly differentiated serous tumors of advanced surgical stage. This heterogeneity in clinical outcome presumably reflects differences in the underlying molecular genetic characteristics of individual cancers, but the molecular basis of ovarian cancer remains largely obscure. Thus, the long-term goal of this project is to address the hypothesis that a comprehensive molecular genetic classification of ovarian cancer will improve our ability to predict clinical outcome, specifically with regard to duration of recurrence-free interval following chemotherapy, and survival. Furthermore, elucidation of the molecular determinants of these clinical outcome parameters should provide substantial insights into the biological basis of ovarian tumorigenesis, as well as suggest potential new targets or strategies for ovarian cancer therapy. We propose that this goal may be accomplished through the systematic application of new, comprehensive molecular screening methodologies, specifically, use of cDNA microarrays for gene expression analysis and comparative genomic hybridization for genetic analysis, together with a large ovarian cancer tissue resource linked to extensive surgical, histopathological, and clinical data. The specific aims of this project are to: 1) obtain RNA expression profiles of a large number of ovarian cancers using cDNA microarrays to identify subgroups assembled by expression characteristics; 2) obtain comparative genomic hybridizations on the same samples; 3) define distinct molecular and genetic subsets of ovarian cancer that will predict time to recurrence following chemotherapy, and survival, by correlating these molecular and genetic observations with clinical and pathological outcomes; and 4) confirm and refine observations from specific aims one and two using targeted assays and the development of tissue-based approaches. These aims will be accomplished by a National Cooperative Tumor Signature Group with expertise in molecular biology, genetics, cDNA and tissue array technology, bioinformatics, gynecologic oncology and pathology.