microRNA-associated progression pathways and potential therapeutic targets identified by integrated mRNA and microRNA expression profiling in breast cancer - Buffa, Francesca M; Camps, Carme; Winchester, Laura; Snell, Cameron E; Gee, Harriet E; Sheldon, Helen; Taylor, Marian; Harris, Adrian L; Ragoussis, Jiannis (Cancer research (Chicago, Ill.), 2011)
microRNA expression profiling plays an emerging role in cancer classification and identification of therapeutic strategies. In this study, we have evaluated the benefits of a joint microRNA-mRNA analysis in breast cancer. Matched mRNA and microRNA global expression profiling was conducted in a well-annotated cohort of 207 cases with complete 10-year follow-up. Penalized Cox regression including microRNA expression, mRNA expression, and clinical covariates was used to identify microRNAs associated with distant relapse-free survival (DRFS) that provide independent prognostic information, and are not simply surrogates of previously identified prognostic covariates. Penalized regression was chosen to prevent overfitting. Furthermore, microRNA-mRNA relationships were explored by global expression analysis, and exploited to validate results in several published cohorts (n = 592 with DRFS, n = 1,050 with recurrence-free survival). Four microRNAs were independently associated with DRFS in estrogen receptor (ER)-positive (3 novel and 1 known; miR-128a) and 6 in ER-negative (5 novel and 1 known; miR-210) cases. Of the latter, miR-342, -27b, and -150 were prognostic also in triple receptor-negative tumors. Coordinated expression of predicted target genes and prognostic microRNAs strengthened these results, most significantly for miR-210, -128a, and -27b, whose targets were prognostic in meta-analysis of several cohorts. In addition, miR-210 and -128a showed coordinated expression with their cognate pri-microRNAs, which were themselves prognostic in independent cohorts. Our integrated microRNA-mRNA global profiling approach has identified microRNAs independently associated with prognosis in breast cancer. Furthermore, it has validated known and predicted microRNA-target interactions, and elucidated their association with key pathways that could represent novel therapeutic targets.