Prognostically relevant gene signatures of high-grade serous ovarian carcinoma

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From: Journal of Clinical Investigation(Vol. 123, Issue 1)
Publisher: American Society for Clinical Investigation
Document Type: Report
Length: 7,781 words
Lexile Measure: 1470L

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Because of the high risk of recurrence in high-grade serous ovarian carcinoma (HGS-OvCa), the development of outcome predictors could be valuable for patient stratification. Using the catalog of The Cancer Genome Atlas (TCGA), we developed subtype and survival gene expression signatures, which, when combined, provide a prognostic model of HGS-OvCa classification, named "Classification of Ovarian Cancer" (CLOVAR). We validated CLOVAR on an independent dataset consisting of 879 HGS-OvCa expression profiles. The worst outcome group, accounting for 23% of all cases, was associated with a median survival of 23 months and a platinum resistance rate of 63%, versus a median survival of 46 months and platinum resistance rate of 23% in other cases. Associating the outcome prediction model with BRCA1/BRCA2 mutation status, residual disease after surgery, and disease stage further optimized outcome classification. Ovarian cancer is a disease in urgent need of more effective therapies. The spectrum of outcomes observed here and their association with CLOVAR signatures suggests variations in underlying tumor biology. Prospective validation of the CLOVAR model in the context of additional prognostic variables may provide a rationale for optimal combination of patient and treatment regimens.


High-grade serous ovarian carcinoma (HGS-OvCa) accounts for 60%-80% of the approximately 26,000 women diagnosed with epithelial ovarian carcinoma in the US annually (1), (2). Known risk determinants for the development of ovarian carcinoma include BRCA1/BRCA2 mutations, family history, nulliparity, oral contraceptive use, tubal ligation, pregnancy, and lactation (1), (3). A common treatment regimen consists of tumor debulking, followed by administration of platinum and taxane-based chemotherapy (4). The advanced stage at which most patients present, combined with the high rate of relapse, results in a 5-year survival rate less than 40% (5), (6). Identification of nonresponders and patients with primary platinum resistance (recurrence less than 6 months after last chemotherapy cycle) is an important step toward achieving greater life expectancy for serous ovarian carcinoma patients (7). Gene expression profiles have been established that are associated with overall survival (8), (9), debulking status (10), and response to platinum therapy (11-15). Despite those encouraging developments, no biomarkers for prediction of response to therapy are yet in clinical use.

Gene expression--based outcome predictors have had the greatest impact in breast cancer, where gene signature--based assays of recurrence, chemotherapy efficacy, and metastasis were developed with the potential to guide therapy decisions (16-18). Predictors of prognosis have been developed for other cancers, but have not necessarily led to changes in clinical practice. In addition to predicting survival, the potential of prognostic classifiers lies in the ability to recognize categories of patients that are more likely to respond to particular therapies. For example, the Mesenchymal expression subtype of glioblastoma is being investigated in relation to response to angiogenesis inhibitors such as bevacizumab (19).

In a recent report from The Cancer Genome Atlas (TCGA) Research Network, 489 cases of HGS-OvCa were analyzed using copy number, expression and methylation arrays, and exonic sequencing of more than 18,500 genes (20). The HGS-OvCa genome was shown to harbor more somatic copy number alterations...

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Gale Document Number: GALE|A348997175