Title: Identification of microRNA clusters cooperatively acting on Epithelial to Mesenchymal Transition in Triple Negative Breast Cancer,
Abstract: MicroRNAs play important roles in many biological processes. Their aberrant
expression can have oncogenic or tumor suppressor function directly
participating to carcinogenesis, malignant transformation, invasiveness and
metastasis. Indeed, miRNA profiles can distinguish not only between normal and
cancerous tissue but they can also successfully classify different subtypes of
a particular cancer. Here, we focus on a particular class of transcripts
encoding polycistronic miRNA genes that yields multiple miRNA components. We
describe clustered MiRNA Master Regulator Analysis (ClustMMRA), a fully
redesigned release of the MMRA computational pipeline (MiRNA Master Regulator
Analysis), developed to search for clustered miRNAs potentially driving cancer
molecular subtyping. Genomically clustered miRNAs are frequently co-expressed
to target different components of pro-tumorigenic signalling pathways. By
applying ClustMMRA to breast cancer patient data, we identified key miRNA
clusters driving the phenotype of different tumor subgroups. The pipeline was
applied to two independent breast cancer datasets, providing statistically
concordant results between the two analysis. We validated in cell lines the
miR-199/miR-214 as a novel cluster of miRNAs promoting the triple negative
subtype phenotype through its control of proliferation and EMT.