Abstract Background: Breast cancer is the most common cancer in women and the second most frequent cancer worldwide. Changes in miRNA levels are associated with various diseases, including cancer, making them ideal non-invasive biomarkers for diagnosis, prognosis, and treatment. Bioinformatics advancements have enabled the prediction of miRNAs and their target genes. This study aimed to analyze the miR-15 family (miR-15a, miR-15b, miR-16-1, miR-16-2, miR-195, and miR-497) to predict their target genes and evaluate their role in breast cancer progression. Materials and Methods: Expression levels of the miR-15 family were evaluated in healthy and cancerous breast tissues using the OncomiR database. Target genes involved in breast cancer-related pathways were identified through the DIANA TOOLS-mirPath v.3 database. Algorithms from online databases such as TargetScan, miRWalk 2.0, and RNAhybrid were used to rank the genes. Genes with the highest scores were analyzed for their functional roles using the DAVID database. Results: Analysis of cell adhesion, TGF-beta, and P53 pathways identified seven genes (IGF1R, PVRL1, SMAD7, CCND2, CCND1, SESN1, and CCNE1) as common targets of miR-15a-5p, miR-15b-5p, miR-195-5p, and miR-497-5p. Additionally, CCNG2 was identified as an exclusive target of miR-16-1-3p. These genes were enriched in pathways associated with cell adhesion, apoptosis, and key cancer-related signaling networks. Conclusion: Members of the miR-15 family may serve as biomarkers for breast cancer by targeting genes involved in cell adhesion, apoptosis, and pathways such as TGF-β and P53. Further clinical and laboratory studies are recommended to validate these findings.
Alizadeh et al. (Sun,) studied this question.