Comprehensive Computational Analysis of Differentially Expressed miRNAs and Their Target Genes in Breast Cancer: Implications for Diagnostic and Prognostic Insights

Abstract Breast cancer, known for its complex and multifaceted nature, presents formidable challenges in both diagnosis and treatment. MicroRNAs (miRNAs) have emerged as promising biomarkers due to their distinctive expression patterns in tumor tissues and their stability in various biological fluids. This stability makes them valuable for early detection and precise prognostication. In this research endeavor, we conducted an exhaustive analysis to pinpoint differentially expressed miRNAs (DE-miRNAs) in breast tumor samples compared to their normal counterparts. To achieve this, we meticulously examined four microarray datasets (GSE45666, GSE2665, GSE44124, and GSE59247) acquired from the Gene Expression Omnibus (GEO) repository. Our analytical approach consistently unveiled eight DE-miRNAs (miR-21, miR-99a, miR-100, miR-125b, miR-130b, miR-195, miR-451, and miR-497) across all datasets. Subsequently, we delved into the interactions between these DE-miRNAs and identified a network of 387 target genes. This comprehensive network offers a visual representation of the intricate miRNA-target interactions. Furthermore, we embarked on a functional enrichment analysis rooted in gene ontology terms. This analysis illuminated several pivotal biological processes, including epithelial to mesenchymal transition, positive regulation of nuclear-transcribed mRNA poly(A) tail shortening, protein K27-linked deubiquitination, peptidyl-threonine phosphorylation, regulation of transcription by RNA polymerase, gene silencing by RNA, phosphorylation, negative regulation of nitrogen compound metabolic processes, and the cellular response to transforming growth factor beta. These processes are characterized by their diverse roles in cancer biology, influencing gene expression, protein activity, cellular signaling, and metabolic pathways. Dysregulation of these processes can indeed lead to uncontrolled cell growth, invasive behavior, and metastasis, all of which are hallmarks of cancer development and progression. In conclusion, our extensive computational analysis provides valuable insights into the potential use of miRNAs as markers for early breast cancer diagnosis and ongoing monitoring. By identifying DE-miRNAs and unraveling their interactions and associated biological processes, this study enhances our comprehension of the molecular intricacies of breast cancer and the potential for improved diagnostic and prognostic approaches.