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

Overview

Journal Cancer Epidemiol Biomarkers Prev

Specialties Biochemistry
Oncology
Public Health

Date 2019 Dec 25

PMID 31871106

Citations 26

Authors

Matthew Schwede

Levi Waldron

Samuel C Mok

Wei Wei

Azfar Basunia

Melissa A Merritt

Constantine S Mitsiades

Giovanni Parmigiani

David P Harrington

John Quackenbush

Michael J Birrer

Aedin C Culhane

Affiliations

Soon will be listed here.

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.

Citing Articles

Leveraging Multi-omics to Disentangle the Complexity of Ovarian Cancer.

Lin S, Nguyen L, McMellen A, Leibowitz M, Davidson N, Spinosa D Mol Diagn Ther. 2024; 29(2):145-151.

PMID: 39557776 DOI: 10.1007/s40291-024-00757-3.

Metabolomic Analysis of Histological Composition Variability of High-Grade Serous Ovarian Cancer Using H HR MAS NMR Spectroscopy.

Skorupa A, Klimek M, Ciszek M, Pakulo S, Cichon T, Cichon B Int J Mol Sci. 2024; 25(20).

PMID: 39456684 PMC: 11507550. DOI: 10.3390/ijms252010903.

The Progression and Prospects of the Gene Expression Profiling in Ovarian Epithelial Cancer.

Srinivasamurthy B, Ramamoorthi S Gynecol Minim Invasive Ther. 2024; 13(3):141-145.

PMID: 39184260 PMC: 11343359. DOI: 10.4103/gmit.gmit_13_23.

Spatial transcriptomics reveals discrete tumour microenvironments and autocrine loops within ovarian cancer subclones.

Denisenko E, de Kock L, Tan A, Beasley A, Beilin M, Jones M Nat Commun. 2024; 15(1):2860.

PMID: 38570491 PMC: 10991508. DOI: 10.1038/s41467-024-47271-y.

Proteogenomic analysis of enriched HGSOC tumor epithelium identifies prognostic signatures and therapeutic vulnerabilities.

Bateman N, Abulez T, Soltis A, McPherson A, Choi S, Garsed D NPJ Precis Oncol. 2024; 8(1):68.

PMID: 38480868 PMC: 10937683. DOI: 10.1038/s41698-024-00519-8.

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