Association of miR-۳۹۱۶ expression with overall survival in breast cancer and identification key pathways and hub genes using bioinformatics analysis

miRNAs are small non-coding RNAs that are important in regulating gene expression using RNA degradation or translational repression . Dysregulation of miRNAs plays a role in the initiation and progression of many cancers, including breast cancer. Also, identification of the main target genes provides a miRNA-related mechanism in cancer and suggests potential treatments. The purpose of this study is to determine the relationship between miR۳۹۱۶ expression and key pathways in breast cancer, based on the real-time PCR data and computational analysis. Methods:The expression of miR-۳۹۱۶ was determined using real-time PCR in breast tumor tissue compare to adjusted normal tissue. multiMiR package in R was used for miRNA target genes prediction . Gene ontology and KEGG pathway analysis were performed to identify the potential function of miR-۳۹۱۶ by the clusterProfiler package in R version ۴.۲.۱ . A PPI network (Protein-protein interaction network) was constructed to display key target genes. For hub genes validation, GEPIA databases were used.Results:miR-۳۹۱۶ was upregulated in breast tumor tissues, and its increase was significantly related to a bad prognosis in breast cancer. GO analysis showed that target genes were mainly enriched in the regulation of gene expression and regulation of transcription, DNA-templated. KEGG pathway analysis suggested that target genes were enriched in the neurotrophin signaling pathway, and Wnt signaling pathway. And finally, the ten hub genes were detected from the PPI network in the following order (KRAS, HSP۹۰AA۱, MAPK۱, FOXO۳, IGF۱, MAPK۸, SMAD۳, STAT۵B, AR, and MAP۲K۷).Conclusion:This study proposed that miR-۳۹۱۶ up-regulation is associated with breast cancer progression and worse survival, and also identified ten genes associated with breast cancer, which can help to provide candidate targets for the treatment.

Keywords:

miR-۳۹۱۶ , hub gene , Breast cancer , Bioinformatics analysis