Molecular classification of prostate cancer using curated expression signatures

Abstract

High Gleason score is currently the best prognostic indicator for poor prognosis in prostate cancer. However, a significant number of patients with low Gleason scores develop aggressive disease as well. In an effort to understand molecular signatures associated with poor outcome in prostate cancer, we analyzed a microarray dataset characterizing 281 prostate cancers from a Swedish watchful- waiting cohort. Patients were classified on the basis of their mRNA microarray signature profiles indicating embryonic stem cell expression patterns (stemness), inactivation of the tumor suppressors p53 and PTEN, activation of several oncogenic pathways, and the TMPRSS2-ERG fusion. Unsupervised clustering identified a subset of tumors manifesting stem-like signatures together with p53 and PTEN inactivation, which had very poor survival outcome, a second group with intermediate survival outcome, characterized by the TMPRSS2-ERG fusion, and three groups with benign outcome. The stratification was validated on a second independent dataset of 150 tumor and metastatic samples from a clinical cohort at Memorial Sloan-Kettering Cancer Center. This classification is independent of Gleason score and therefore provides useful unique molecular profiles for prostate cancer prognosis, helping to predict poor outcome in patients with low or average Gleason scores.