High-risk ovarian cancer based on 126-gene expression signature is uniquely characterized by down-regulation of antigen presentation pathway
A partir de données portant sur 1 054 patientes atteintes d'un cancer de l'ovaire, cette étude évalue l'intérêt d'une signature basée sur l'expression de 126 gènes pour prédire la survie des patientes
Purpose:High-grade serous ovarian cancers are heterogeneous not only in term of clinical outcome but also at the molecular level. Our aim was to establish a novel risk classification system based on a gene expression signature for predicting overall survival, leading to suggesting novel therapeutic strategies for high-risk patients. Experimental Design:In this large-scale cross-platform study of six microarray datasets consisting of 1,054 ovarian cancer patients, we developed a gene expression signature for predicting overall survival by applying elastic net and 10-fold cross-validation to a Japanese dataset A (n = 260) and evaluated the signature in five other datasets. Subsequently, we investigated differences in the biological characteristics between high- and low-risk ovarian cancer groups. Results:An elastic net analysis identified a 126-gene expression signature for predicting overall survival in patients with ovarian cancer using the Japanese dataset A (multivariate analysis, P = 4×10-20). We validated its predictive ability with five other datasets using multivariate analysis (Tothill's dataset, P = 1×10-5; Bonome's dataset, P = 0.0033; Dressman's dataset, P = 0.0016; TCGA dataset, P = 0.0027; Japanese dataset B, P = 0.021). Through gene ontology and pathway analyses, we identified a significant reduction in expression of immune-response related genes, especially on the antigen presentation pathway, in high-risk ovarian cancer patients. Conclusions:This risk classification based on the 126-gene expression signature is an accurate predictor of clinical outcome in patients with advanced-stage high-grade serous ovarian cancer and has the potential to develop new therapeutic strategies for high-grade serous ovarian cancer patients.
Clinical Cancer Research , résumé, 2012