Predicting time to ovarian carcinoma recurrence using protein markers
Menée initialement sur 412 échantillons tumoraux prélevés sur des patientes atteintes d'un cancer de l'ovaire, puis validée sur une cohorte complémentaire de 226 patientes, cette étude évalue l'intérêt d'un indicateur appelé PROVAR, basé sur les profils d'expression de diverses protéines, pour prédire le risque de récidive
Patients with ovarian cancer are at high risk of tumor recurrence. Prediction of therapy outcome may provide therapeutic avenues to improve patient outcomes. Using reverse-phase protein arrays, we generated ovarian carcinoma protein expression profiles on 412 cases from TCGA and constructed a PRotein-driven index of OVARian cancer (PROVAR). PROVAR significantly discriminated an independent cohort of 226 high-grade serous ovarian carcinomas into groups of high risk and low risk of tumor recurrence as well as short-term and long-term survivors. Comparison with gene expression–based outcome classification models showed a significantly improved capacity of the protein-based PROVAR to predict tumor progression. Identification of protein markers linked to disease recurrence may yield insights into tumor biology. When combined with features known to be associated with outcome, such as BRCA mutation, PROVAR may provide clinically useful predictions of time to tumor recurrence.
The Journal of Clinical Investigation , article en libre accès, 2012