Differentially expressed genes analysis and target genes prediction of miR-22 in breast cancer*

Abstract

Abstract Objective miR-22 is highly active in breast cancer, especially in the luminal B and HER2 subtypes. However, the detailed potential of the use of target genes for miR-22 in breast cancer are still unclear. In this study, we aimed to discover potential genes and the miRNA-DEGs network of miR-22 in breast cancer using bioinformatics approaches. Methods Analysis of microarray data GSE17508 (including 3 miR-22 knockout samples and 3 controls) obtained from the Gene Expression Omnibus (GEO) database was performed. Differentially expressed genes (DEGs) between the miR-22 knockout samples and the three control samples were detected using GEO2R. The gene ontology (GO) functional enrichment analysis and protein-protein interaction (PPI) network of DEGs were performed using the online tool Metascape and STRING database, separately. The miR-22 and DEG networks were obtained from the miRNet database. Cytoscape software was used to construct and analyze a merged miRNA-DEG network. The online tools database, mirDIP 4.1, was used to predict miR-22 target genes. Results Certain DEGs and miRNAs may be potential targets for predicting and treating miR-22 expressed breast cancer. Conclusion We constructed a prognostic model of rectal adenocarcinomas based on four immune-related lncRNAs by analyzing the data based on TCGA database, with high prediction accuracy. We also identified two biomarkers with poor prognosis (PXN-AS1 and AL158152.2) and one biomarker with good prognosis (LINC01871).