The Impact of Stroma Admixture on Molecular Subtypes and Prognostic Gene Signatures in Serous Ovarian Cancer

Cancer Epidemiol Biomarkers Prev. 2020 Feb;29(2):509-519. doi: 10.1158/1055-9965.EPI-18-1359. Epub 2019 Dec 23.

Abstract

Background: Recent efforts to improve outcomes for high-grade serous ovarian cancer, a leading cause of cancer death in women, have focused on identifying molecular subtypes and prognostic gene signatures, but existing subtypes have poor cross-study robustness. We tested the contribution of cell admixture in published ovarian cancer molecular subtypes and prognostic gene signatures.

Methods: Gene signatures of tumor and stroma were developed using paired microdissected tissue from two independent studies. Stromal genes were investigated in two molecular subtype classifications and 61 published gene signatures. Prognostic performance of gene signatures of stromal admixture was evaluated in 2,527 ovarian tumors (16 studies). Computational simulations of increasing stromal cell proportion were performed by mixing gene-expression profiles of paired microdissected ovarian tumor and stroma.

Results: Recently described ovarian cancer molecular subtypes are strongly associated with the cell admixture. Tumors were classified as different molecular subtypes in simulations where the percentage of stromal cells increased. Stromal gene expression in bulk tumors was associated with overall survival (hazard ratio, 1.17; 95% confidence interval, 1.11-1.23), and in one data set, increased stroma was associated with anatomic sampling location. Five published prognostic gene signatures were no longer prognostic in a multivariate model that adjusted for stromal content.

Conclusions: Cell admixture affects the interpretation and reproduction of ovarian cancer molecular subtypes and gene signatures derived from bulk tissue. Elucidating the role of stroma in the tumor microenvironment and in prognosis is important.

Impact: Single-cell analyses may be required to refine the molecular subtypes of high-grade serous ovarian cancer.

Publication types

  • Meta-Analysis
  • Research Support, N.I.H., Extramural
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Biomarkers, Tumor / genetics*
  • Cystadenocarcinoma, Serous / genetics
  • Cystadenocarcinoma, Serous / mortality*
  • Cystadenocarcinoma, Serous / pathology
  • Datasets as Topic
  • Female
  • Gene Expression Profiling
  • Humans
  • Microdissection
  • Ovarian Neoplasms / genetics
  • Ovarian Neoplasms / mortality*
  • Ovarian Neoplasms / pathology
  • Ovary / cytology
  • Ovary / pathology*
  • Prognosis
  • Stromal Cells / pathology*
  • Survival Analysis
  • Transcriptome
  • Tumor Microenvironment / genetics

Substances

  • Biomarkers, Tumor