Analysis of gene expression signatures identifies prognostic and functionally distinct ovarian clear cell carcinoma subtypes.

ABSTRACT:

Background

Ovarian clear cell carcinoma (OCCC) is a histological subtype of epithelial ovarian cancer (EOC) with distinct pathological, biological, and molecular features. OCCCs are more resistant to conventional treatment regimen of EOC and have the worst stage-adjusted prognosis amongst EOC subtypes. As the OCCC incidence rate in Asian populations has significantly increased in recent decades, it is critical to elucidate its molecular features that could lead to OCCC-tailored therapeutic strategies.

Methods

Gene expression profiles of 222 OCCC were analyzed by hierarchical clustering and statistical analyses.

Findings

We identified two OCCC gene expression subtypes: EpiCC-epithelial-like, which is associated with early-stage disease, with a relatively higher rate of gene mutations in the SWI/SNF complex; and MesCC-mesenchymal-like, associated with late-stage and higher enrichment of immune-related pathway activity. Genetic, copy number and transcriptomic analyses showed that both EpiCC and MesCC carried OCCC-associated aberrations. The EpiCC/MesCC classification was reproducible in validation cohorts and OCCC cell lines. MesCC tumors had a poorer progression-free survival (PFS) than EpiCC tumors (HR: 3·0, p = 0·0006). Functional assays in cell lines showed that the MesCC subtype was more proliferative and more anoikis-resistant than the EpiCC. By applying the EpiCC/MesCC classification to the TCGA renal clear cell carcinoma cohort, our results indicated interoperability of the subtyping scheme, and revealed preferential drug response of MesCC to bevacizumab.

Interpretation

The EpiCC/MesCC classification shows promise for prognostic and therapeutic stratification in OCCC patients and warrants further investigation in the context of OCCC gene expression subtype-tailored treatment strategies.

SUBMITTER: Tan TZ 

PROVIDER: S-EPMC6921362 | biostudies-literature |

REPOSITORIES: biostudies-literature