Identification of chemoresistance-associated microRNAs and hub genes in breast cancer using bioinformatics analysis

Breast cancer threatens women's health. Although there are a lot of methods to treat breast cancer, chemotherapy resistance still hinders the effectiveness of treatment. This study attempts to explore the mechanism of chemotherapy resistance from the perspective of miRNA and look for several new targets for developing new drugs. Three datasets (GSE73736, GSE71142 and GSE6434) from Gene Expression Omnibus (GEO) were used for the bioinformatics analysis. Differentially expressed miRNAs (DE-miRNAs) and differentially expressed genes (DE-genes) were obtained by using R package "limma". DAVID tool was used to perform gene ontology annotation analysis (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis for the overlapping genes. Protein-protein interaction (PPI) network was established by STRING database and visualized by software Cytoscape. Hub genes were identified by software Cytoscape. The prognostic value of hub genes was assessed through Kaplan-Meier plotter website. In total, 22 DE-miRNAs, 1932 DE-genes and top 10 hub genes were obtained. The genes were mainly enriched in cell signaling pathways like ErbB signaling pathway and PI3K / AKT/mTOR pathway. These pathways have a significant impact on the proliferation, invasion and drug resistance in cancer. MiRNA-Gene interaction may provide new insight for exploring the mechanism of chemotherapy resistance in breast cancer. Our study ultimately identified effective biomarkers and potential drug targets, which may enhance the effect of chemotherapy in patients with breast cancer.