Predicting response and survival in chemotherapy-treated triple-negative breast cancer.

BACKGROUND In this study, we evaluated the ability of gene expression profiles to predict chemotherapy response and survival in triple-negative breast cancer (TNBC). METHODS Gene expression and clinical-pathological data were evaluated in five independent cohorts, including three randomised clinical trials for a total of 1055 patients with TNBC, basal-like disease (BLBC) or both. Previously defined intrinsic molecular subtype and a proliferation signature were determined and tested. Each signature was tested using multivariable logistic regression models (for pCR (pathological complete response)) and Cox models (for survival). Within TNBC, interactions between each signature and the basal-like subtype (vs other subtypes) for predicting either pCR or survival were investigated. RESULTS Within TNBC, all intrinsic subtypes were identified but BLBC predominated (55-81%). Significant associations between genomic signatures and response and survival after chemotherapy were only identified within BLBC and not within TNBC as a whole. In particular, high expression of a previously identified proliferation signature, or low expression of the luminal A signature, was found independently associated with pCR and improved survival following chemotherapy across different cohorts. Significant interaction tests were only obtained between each signature and the BLBC subtype for prediction of chemotherapy response or survival. CONCLUSIONS The proliferation signature predicts response and improved survival after chemotherapy, but only within BLBC. This highlights the clinical implications of TNBC heterogeneity, and suggests that future clinical trials focused on this phenotypic subtype should consider stratifying patients as having BLBC or not.

This work was presented, in part, as an oral communication at the ASCO 2012 annual meeting (Abstract #10500). Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't;

This work was supported by funds from the NCI Breast SPORE program Grant No. P50-CA58223-09A1 (CMP), by RO1-CA138255 (CMP), by the Breast Cancer Research Foundation (CMP and MJE), National Cancer Institute (NCI) Strategic Partnering to Evaluate Cancer Signatures Grant No. U01 CA114722-01 (MJE), by the Sociedad Española de Oncología Médica (AP), by FEDER (RETICC-RD12/0036/0051, RD12/0036/0042, RD12/0036/0076, RD12/0036/0070), by Instituto de Salud Carlos III—PI13/01718 (AP), by Banco Bilbao Vizcaya Argentaria (BBVA) Foundation (AP) and by the Alliance Statistics and Data Center (U10-CA33601).