Biological processes associated with breast cancer clinical outcome depend on the molecular subtypes - Desmedt, Christine; Haibe-Kains, Benjamin; Wirapati, Pratyaksha; Buyse, Marc; Larsimont, Denis; Bontempi, Gianluca; Delorenzi, Mauro; Piccart, Martine; Sotiriou, Christos (Clinical cancer research, 2008)
Recently, several prognostic gene expression signatures have been identified; however, their performance has never been evaluated according to the previously described molecular subtypes based on the estrogen receptor (ER) and human epidermal growth factor receptor 2 (HER2), and their biological meaning has remained unclear. Here we aimed to perform a comprehensive meta-analysis integrating both clinicopathologic and gene expression data, focusing on the main molecular subtypes. We developed gene expression modules related to key biological processes in breast cancer such as tumor invasion, immune response, angiogenesis, apoptosis, proliferation, and ER and HER2 signaling, and then analyzed these modules together with clinical variables and several prognostic signatures on publicly available microarray studies (>2,100 patients). Multivariate analysis showed that in the ER+/HER2- subgroup, only the proliferation module and the histologic grade were significantly associated with clinical outcome. In the ER-/HER2- subgroup, only the immune response module was associated with prognosis, whereas in the HER2+ tumors, the tumor invasion and immune response modules displayed significant association with survival. Proliferation was identified as the most important component of several prognostic signatures, and their performance was limited to the ER+/HER2- subgroup. Although proliferation is the strongest parameter predicting clinical outcome in the ER+/HER2- subtype and the common denominator of most prognostic gene signatures, immune response and tumor invasion seem to be the main molecular processes associated with prognosis in the ER-/HER2- and HER2+ subgroups, respectively. These findings may help to define new clinicogenomic models and to identify new therapeutic strategies in the specific molecular subgroups.