Expression signature distinguishing two tumour transcriptome classes associated with progression-free survival among rare histological types of epithelial ovarian cancer

Br J Cancer. 2016 Jun 14;114(12):1412-20. doi: 10.1038/bjc.2016.124. Epub 2016 Jun 2.

Abstract

Background: The mechanisms of recurrence have been under-studied in rare histologies of invasive epithelial ovarian cancer (EOC) (endometrioid, clear cell, mucinous, and low-grade serous). We hypothesised the existence of an expression signature predictive of outcome in the rarer histologies.

Methods: In split discovery and validation analysis of 131 Mayo Clinic EOC cases, we used clustering to determine clinically relevant transcriptome classes using microarray gene expression measurements. The signature was validated in 967 EOC tumours (91 rare histological subtypes) with recurrence information.

Results: We found two validated transcriptome classes associated with progression-free survival (PFS) in the Mayo Clinic EOC cases (P=8.24 × 10(-3)). This signature was further validated in the public expression data sets involving the rare EOC histologies, where these two classes were also predictive of PFS (P=1.43 × 10(-3)). In contrast, the signatures were not predictive of PFS in the high-grade serous EOC cases. Moreover, genes upregulated in Class-1 (with better outcome) were showed enrichment in steroid hormone biosynthesis (false discovery rate, FDR=0.005%) and WNT signalling pathway (FDR=1.46%); genes upregulated in Class-2 were enriched in cell cycle (FDR=0.86%) and toll-like receptor pathways (FDR=2.37%).

Conclusions: These findings provide important biological insights into the rarer EOC histologies that may aid in the development of targeted treatment options for the rarer histologies.

MeSH terms

  • Aged
  • Aged, 80 and over
  • Carcinoma, Ovarian Epithelial
  • Disease-Free Survival
  • Gene Expression Regulation, Neoplastic
  • Humans
  • Middle Aged
  • Neoplasms, Glandular and Epithelial / genetics*
  • Neoplasms, Glandular and Epithelial / pathology
  • Ovarian Neoplasms / genetics*
  • Ovarian Neoplasms / pathology
  • Transcriptome