Usage Information

Prognostically relevant gene signatures of high-grade serous ovarian carcinoma
Roel G.W. Verhaak, … , Matthew Meyerson, The Cancer Genome Atlas Research Network
Roel G.W. Verhaak, … , Matthew Meyerson, The Cancer Genome Atlas Research Network
Published December 21, 2012
Citation Information: J Clin Invest. 2013;123(1):517-525. https://doi.org/10.1172/JCI65833.
View: Text | PDF
Research Article Oncology

Prognostically relevant gene signatures of high-grade serous ovarian carcinoma

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.

Authors

Roel G.W. Verhaak, Pablo Tamayo, Ji-Yeon Yang, Diana Hubbard, Hailei Zhang, Chad J. Creighton, Sian Fereday, Michael Lawrence, Scott L. Carter, Craig H. Mermel, Aleksandar D. Kostic, Dariush Etemadmoghadam, Gordon Saksena, Kristian Cibulskis, Sekhar Duraisamy, Keren Levanon, Carrie Sougnez, Aviad Tsherniak, Sebastian Gomez, Robert Onofrio, Stacey Gabriel, Lynda Chin, Nianxiang Zhang, Paul T. Spellman, Yiqun Zhang, Rehan Akbani, Katherine A. Hoadley, Ari Kahn, Martin Köbel, David Huntsman, Robert A. Soslow, Anna Defazio, Michael J. Birrer, Joe W. Gray, John N. Weinstein, David D. Bowtell, Ronny Drapkin, Jill P. Mesirov, Gad Getz, Douglas A. Levine, Matthew Meyerson

×

Usage data is cumulative from August 2024 through August 2025.

Usage JCI PMC
Text version 1,380 371
PDF 156 80
Figure 234 3
Supplemental data 206 46
Citation downloads 97 0
Totals 2,073 500
Total Views 2,573
(Click and drag on plot area to zoom in. Click legend items above to toggle)

Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.

Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.

Advertisement