domingo, 30 de diciembre de 2012

JCI - Prognostically relevant gene signatures of high-grade serous ovarian carcinoma

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JCI - Prognostically relevant gene signatures of high-grade serous ovarian carcinoma

Research Article

Prognostically relevant gene signatures of high-grade serous ovarian carcinoma

Roel G.W. Verhaak1, Pablo Tamayo2, Ji-Yeon Yang1, Diana Hubbard2,3, Hailei Zhang3, Chad J. Creighton4, Sian Fereday5, Michael Lawrence2, Scott L. Carter2,3, Craig H. Mermel2,3, Aleksandar D. Kostic2,3, Dariush Etemadmoghadam5, Gordon Saksena2, Kristian Cibulskis2, Sekhar Duraisamy3, Keren Levanon3,6, Carrie Sougnez2, Aviad Tsherniak2, Sebastian Gomez2, Robert Onofrio2, Stacey Gabriel2, Lynda Chin2,3, Nianxiang Zhang1, Paul T. Spellman7, Yiqun Zhang4, Rehan Akbani1, Katherine A. Hoadley8, Ari Kahn9, Martin Köbel10, David Huntsman11, Robert A. Soslow12, Anna Defazio13, Michael J. Birrer14, Joe W. Gray7, John N. Weinstein1, David D. Bowtell5, Ronny Drapkin3, Jill P. Mesirov2, Gad Getz2, Douglas A. Levine15, Matthew Meyerson2,3 and The Cancer Genome Atlas Research Network
1Department of Bioinformatics and Computational Biology, MD Anderson Cancer Center, Houston, Texas, USA.
2The Eli and Edythe L. Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, Massachusetts, USA.
3Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA.
4Dan L. Duncan Cancer Center, Baylor College of Medicine, Houston, Texas, USA.
5Cancer Genetics and Genomics Laboratory, Peter MacCallum Cancer Centre, East Melbourne, Victoria, Australia.
6Sheba Cancer Research Center, Chaim Sheba Medical Center, Ramat Gan, Israel.
7Department of Molecular and Medical Genetics, Oregon Health and Science University, Portland, Oregon, USA.
8Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
9SRA International, Fairfax, Virgina, USA.
10Department of Pathology and Laboratory Medicine, University of Calgary, Calgary Laboratory Services, Calgary, Alberta, Canada.
11British Columbia Cancer Agency, Centre for Translational and Applied Genomics, Vancouver, British Columbia, Canada.
12Department of Pathology, Memorial Sloan-Kettering Cancer Center, New York, New York, USA.
13Department of Gynaecological Oncology and Westmead Institute for Cancer Research, University of Sydney at Westmead Millennium Institute, Westmead, New South Wales, Australia.
14Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA.
15Gynecology Service, Department of Surgery, Memorial Sloan-Kettering Cancer Center, New York, New York, USA.
Address correspondence to: Roel G.W. Verhaak, University of Texas MD Anderson Cancer Center, 1400 Pressler Street, Unit 1410, Houston, Texas 77030, USA. Phone: 713.563.2293; Fax: 713.563.4242; E-mail: rverhaak@mdanderson.org.
Published December 21, 2012
Received for publication July 31, 2012, and accepted in revised form October 24, 2012.
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.

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