Prognostically relevant gene signatures of high-grade serous ovarian carcinoma

Roel G.W. Verhaak(The University of Texas MD Anderson Cancer Center), Pablo Tamayo(Harvard University Press), Ji-Yeon Yang(The University of Texas MD Anderson Cancer Center), Diana Hubbard(Harvard University Press), Hailei Zhang(Dana-Farber Cancer Institute), Chad J. Creighton(Baylor College of Medicine), Sián Fereday(Peter MacCallum Cancer Centre), Michael S. Lawrence(Harvard University Press), Scott L. Carter(Harvard University Press), Craig H. Mermel(Harvard University Press), Aleksandar D. Kostic(Harvard University Press), Dariush Etemadmoghadam(Peter MacCallum Cancer Centre), Gordon Saksena(Harvard University Press), Kristian Cibulskis(Harvard University Press), Sekhar Duraisamy(Dana-Farber Cancer Institute), Keren Levanon(Sheba Medical Center), Carrie Sougnez(Harvard University Press), Aviad Tsherniak(Harvard University Press), Sebastián Martín Gómez(Harvard University Press), Robert C. Onofrio(Harvard University Press), Stacey Gabriel(Harvard University Press), Lynda Chin(Harvard University Press), Nianxiang Zhang(The University of Texas MD Anderson Cancer Center), Paul T. Spellman(Oregon Health & Science University), Yiqun Zhang(Baylor College of Medicine), Rehan Akbani(The University of Texas MD Anderson Cancer Center), Katherine A. Hoadley, A Kahn(SRA International (United States)), Martin Köbel(University of Calgary), David G. Huntsman(University of British Columbia), Robert A. Soslow(Memorial Sloan Kettering Cancer Center), Anna DeFazio(The University of Sydney), Michael J. Birrer(Harvard University Press), Joe W. Gray(Oregon Health & Science University), John N. Weinstein(The University of Texas MD Anderson Cancer Center), David D.L. Bowtell(Peter MacCallum Cancer Centre), Ronny Drapkin(Dana-Farber Cancer Institute), Jill P. Mesirov(Harvard University Press), Gad Getz(Harvard University Press), Douglas A. Levine(Memorial Sloan Kettering Cancer Center), Matthew Meyerson(Harvard University Press)
Journal of Clinical Investigation
December 21, 2012
10.1172/jci65833
Cited by 591

Abstract

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.

Related Papers

No related papers found

Powered by citation graph analysis