Diagnostic and Prognostic Potential of MiR-379/656 MicroRNA Cluster in Molecular Subtypes of Breast Cancer

Introduction: Breast cancer is the most frequently diagnosed cancer globally and is one of the most important contributors to cancer-related deaths. Earlier diagnosis is known to reduce mortality, and better biomarkers are needed. MiRNA clusters often co-express and target mRNAs in a coordinated fashion, perturbing entire pathways; they thus merit further exploration for diagnostic or prognostic use. MiR-379/656, at chromosome 14q32, is the second largest miRNA cluster in the human genome and implicated in various malignancies including glioblastoma, melanoma, gastrointestinal tumors and ovarian cancer highlighting its potential importance. In this study, we focus on the diagnostic and prognostic potentials of MiR-379/656 in breast cancer and its molecular subtypes. Materials and Methods: We analyzed miRNA and mRNA next generation sequencing data from 903 primary tumors and 90 normal controls (source: The Cancer Genome Atlas). The differential expression profile between tumor and normal was analyzed using DeSEQ2. Penalized logistic regression modelling (lasso regression) was used to assess the predictive potential of MiR-379/656 expression for tumor and normal samples. The association between MiR-379/656 expression and overall patient survival was studied using Cox Proportional-Hazard Model. The target mRNAs (validated) of MiR-379/656 were annotated via pathway enrichment analysis to understand the biological significance of the cluster in breast cancer. Results: The differential expression analysis for 1390 miRNAs (miRnome) revealed 310 upregulated (22.3%) and 176 downregulated (12.66%) miRNAs in breast cancer patients compared with controls. For MiR-379/656, 32 miRNAs (32/42; 76%) were downregulated. The MiR-379/656 cluster was found to be the most differentially expressed cluster in the human genome (p < 10(−30)). The Basal and Luminal B subtypes showed at least 83% (35/42) of the miRNAs to be downregulated. The binomial model prioritized 15 miRNAs, which distinguished breast cancer patients from controls with 99.15 ± 0.58% sensitivity and 77.78 ± 5.24% specificity. Overall, the Basal and Luminal B showed the most effective predictive power with respect to the 15 prioritized miRNAs at MiR-379/656 cluster. The decreased expression of MiR-379/656 was found to be associated with poorer clinical outcome in Basal and Luminal B subtypes, increasing tumor stage and tumor size/extent, and overall patient survival. Pathway enrichment for the validated targets of MiR-379/656 was significant for cancer-related pathways, especially DNA repair, transcriptional regulation by p53 and cell cycle checkpoints (adjusted p-value < 0.05). Conclusions: Genome informatics analysis of high throughput data for MiR-379/656 cluster has shown that a subset of 15 miRNAs from MiR-379/656 cluster can be used for the diagnostic and prognostic purpose of breast cancer and its subtypes—especially in Basal and Luminal B.