Akademik Veri Yönetim Sistemi
Genel Tip Dergisi, cilt.34, sa.4, ss.458-464, 2024 (Scopus)
Objective: MicroRNAs(miRNAs) have been demonstrated to contribute to cancer development by playing essential roles in processes including proliferation, migration, invasion, and metastasis. One of the most serious issues in breast cancer (BC) is drug resistance. Recent research suggests that miRNAs may play a role in drug resistance. Using diverse datasets and in silico approaches, we focused on the BC/drug resistance/miRNA link in our study. Material and Methods: GSE73736 and GSE71142 geo datasets (for miRNAs) and GSE162187 geo dataset (for genes) were obtained from the GEO database to detect differently expressed miRNAs and genes using the R software “LIMMA” package. Potential target genes of screened differentially expressed miRNAs (DE-miRNAs) were predicted using miRMap, miRTarbase, and miRNet tools. Differently expressed genes (DE-genes) were filtered and common DE-genes were identified via TCGA data and miRNet. Afterward, Enrichr, and Funrich tools were used to perform GO annotation and KEGG pathway enrichment analysis. KMplot and GEPIA2 web tools were utilized to investigate further hub miRNAs and genes’ expression and prognostic effects. Results: 3 miRNAs that were considerably downregulated and had prognostic significance in BC were identified using the criteria defined in the investigated geo datasets. MiR-586, which is expected to be more closely linked to BC, has been found to have the ability to target 5 genes involved in BC resistance to therapy. GO, KEGG, and survival analysis showed that the probable target genes of miR-586 could be closely connected to BC. Conclusion: In this study, a comprehensive BC-drug resistance-miRNA-gene network was established and new targets for the treatment and prognosis of BC were revealed using bioinformatics data.