Prognostic and therapeutic relevance of molecular subtypes in high-grade serous ovarian cancer

Gottfried E. Konecny, Chen Wang, Habib Hamidi, Boris Winterhoff, Kimberly R. Kalli, Judy Dering, Charles Ginther, Hsiao Wang Chen, Sean Dowdy, William Cliby, Bobbie Gostout, Karl C. Podratz, Gary Keeney, He Jing Wang, Lynn C. Hartmann, Dennis J. Slamon, Ellen L. Goode

Research output: Contribution to journalArticlepeer-review

161 Scopus citations

Abstract

Molecular classification of high-grade serous ovarian cancer (HGSOC) using transcriptional profiling has proven to be complex and difficult to validate across studies. We determined gene expression profiles of 174 well-annotated HGSOCs and demonstrate prognostic significance of the prespecified TCGA Network gene signatures. Furthermore, we confirm the presence of four HGSOC transcriptional subtypes using a de novo classification. Survival differed statistically significantly between de novo subtypes (log rank, P = .006) and was the best for the immunoreactive-like subtype, but statistically significantly worse for the proliferative- or mesenchymal-like subtypes (adjusted hazard ratio = 1.89, 95% confidence interval = 1.18 to 3.02, P = .008, and adjusted hazard ratio = 2.45, 95% confidence interval = 1.43 to 4.18, P = .001, respectively). More prognostic information was provided by the de novo than the TCGA classification (Likelihood Ratio tests, P = .003 and P = .04, respectively). All statistical tests were two-sided. These findings were replicated in an external data set of 185 HGSOCs and confirm the presence of four prognostically relevant molecular subtypes that have the potential to guide therapy decisions.

Original languageEnglish (US)
Article numberdju249
JournalJournal of the National Cancer Institute
Volume106
Issue number10
DOIs
StatePublished - Oct 1 2014

ASJC Scopus subject areas

  • Oncology
  • Cancer Research

Fingerprint Dive into the research topics of 'Prognostic and therapeutic relevance of molecular subtypes in high-grade serous ovarian cancer'. Together they form a unique fingerprint.

Cite this