Identification of Prognostic Groups in High-Grade Serous Ovarian Cancer Treated with Platinum-Taxane Chemotherapy
Menée initialement à partir de données portant sur 180 patientes atteintes d'un cancer séreux de l'ovaire de haut grade traité par une chimiothérapie combinant sels de platine et taxane, puis validée sur plusieurs cohortes complémentaires, cette étude identifie un ensemble de biomarqueurs permettant de classer les patientes en trois sous-groupes de pronostic différent
Disseminated high-grade serous ovarian cancer (HGS-OvCa) is an aggressive disease treated with platinum and taxane combination therapy. While initial response can be favorable, the disease typically relapses with treatment resistance. As genomic alterations in HGS-OvCa are heterogenous, identification of clinically meaningful molecular markers for outcome prediction is challenging. We developed a novel computational approach (PSFinder) that fuses transcriptomics and clinical data to identify HGS-OvCa prognostic subgroups for targeted treatment. Application of PSFinder to transcriptomics data from 180 HGS-OvCa patients treated with platinum-taxane therapy revealed 61 transcript isoforms that characterize two poor and one good survival associated groups (p = 0.007). These groups were validated in eight independent data sets, including a prospectively collected ovarian cancer cohort. Two poor prognostic groups have distinct expression profiles and are characteristic by increased hypermethylation and stroma related genes. Integration of the PSFinder signature and BRCA1/2 mutation status allowed even better stratification of HGS-OvCa patients' prognosis. The herein introduced novel and generally applicable computational approach can identify outcome-related subgroups and facilitate the development of precision medicine to overcome drug resistance. A limited set of biomarkers divides HGS-OvCa into three prognostic groups and predicts patients in need of targeted therapies.
Cancer Research , résumé, 2015