Identification of core miRNAs and regulatory pathways in breast cancer by integrated bioinformatics analysis

Abstract

Breast cancer (BC) ranks first among malignancies in the female population due to its complicated pathological progression and poor prognosis. Hence, the aim of the present study was to identify potential molecular prognostic biomarkers able to predict the prognosis of BC patients. We integrated two microRNA (miRNA) expression microarrays and three gene microarrays related to BC from the NCBI Gene Expression Comprehensive (GEO) database to screen for differentially expressed miRNAs and identify their regulatory networks. The Kaplan–Meier plotter online analysis tool was used to assess the overall survival value of miRNAs expression in BC patients. The LinkedOmics online tool was used to analyze genes correlated with miRNAs expression. To clarify the upstream regulation mechanism of genes, we used ChIP-Atlas to identify and screen for transcription factors and visually verify them using the Integrative Genomics Viewer. To further analyze the downstream regulatory mechanism of miRNA in BC, we verified differentially expressed genes (DEGs) correlated to miRNAs in three GEO gene microarrays and the gene set predicted by miRWalk. The open access Metascape program allowed analysis of Gene Ontology (GO) processes, KEGG pathways and GO enrichment was performed on the DEGs. To further identify hub genes, Cytoscape software and its plug-in were applied to construct protein–protein interaction networks. In the present study, several possible molecules and related pathways related to miR-483 were identified by bioinformatics analysis. These molecules and pathways might represent key mechanisms involved in BC progression and development. This work provides a novel view and insight in the pathogenesis, treatment and prognosis for BC.