Stem cell-like gene expression in ovarian cancer predicts type II subtype and prognosis

Abstract

Although ovarian cancer is often initially chemotherapy-sensitive, the vast majority of tumors eventually relapse and patients die of increasingly aggressive disease. Cancer stem cells are believed to have properties that allow them to survive therapy and may drive recurrent tumor growth. Cancer stem cells or cancer-initiating cells are a rare cell population and difficult to isolate experimentally. Genes that are expressed by stem cells may characterize a subset of less differentiated tumors and aid in prognostic classification of ovarian cancer. The purpose of this study was the genomic identification and characterization of a subtype of ovarian cancer that has stem cell-like gene expression. Using human and mouse gene signatures of embryonic, adult, or cancer stem cells, we performed an unsupervised bipartition class discovery on expression profiles from 145 serous ovarian tumors to identify a stem-like and more differentiated subgroup. Subtypes were reproducible and were further characterized in four independent, heterogeneous ovarian cancer datasets. We identified a stem-like subtype characterized by a 51-gene signature, which is significantly enriched in tumors with properties of Type II ovarian cancer; high grade, serous tumors, and poor survival. Conversely, the differentiated tumors share properties with Type I, including lower grade and mixed histological subtypes. The stem cell-like signature was prognostic within high-stage serous ovarian cancer, classifying a small subset of high-stage tumors with better prognosis, in the differentiated subtype. In multivariate models that adjusted for common clinical factors (including grade, stage, age), the subtype classification was still a significant predictor of relapse. The prognostic stem-like gene signature yields new insights into prognostic differences in ovarian cancer, provides a genomic context for defining Type I/II subtypes, and potential gene targets which following further validation may be valuable in the clinical management or treatment of ovarian cancer.

Figure 1. Heatmap of gene expression and Kaplan-Meier survival curves for the stemness bipartition.

(A) A heatmap of gene expression profiles of the 24 differentiated (green) and 121 stem-like (blue) tumors from the AOCS dataset . The tumors are ordered by increasing stemness molecular subtype score, and the 51 classifier genes are ordered from top to bottom by increasing over-expression in the stem-like subtype according to a pooled t-test. The Kaplan-Meier curves are with respect to (B) disease-free survival and (C) overall survival and are not significant at p<0.05, but this is possibly due to the small size of the differentiated subtype.

Figure 2. Validation of the stemness bipartition in independent ovarian cancer microarray datasets, as well as in the remaining AOCS dataset.

In the remaining AOCS dataset, the stem-like subtype has strongly worse (A) disease-free survival (p<0.001) and (B) overall survival (p = 0.00127). In the (C) Crijns and (D) Dressman datasets, the stem-like subtype has significantly worse overall survival (p = 0.022 and p = 0.035, respectively).