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

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）.