Integrative Bioinformatics Analysis of microRNA Expression and Genomic Signatures for Early Detection and Survival Prediction in Prostate Cancer

Abstract

Prostate cancer remains the second most common malignancy among men worldwide and a leading cause of cancer-related mortality. MicroRNAs (miRNAs) and genomic signatures are critical regulators of oncogenic processes and represent promising biomarkers for cancer diagnosis and prognosis. In this study, we conducted an integrative analysis of miRNA expression profiles and genomic data from public bioinformatics resources, including The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). Differential expression analysis, Cox proportional hazards modeling, and network-based functional enrichment were applied to identify key miRNAs and gene signatures associated with prostate cancer progression and patient survival. Our findings revealed a panel of dysregulated miRNAs and co-expressed gene modules with significant prognostic value. These biomarkers provide novel insights into the molecular mechanisms underlying prostate cancer and may support non-invasive early detection, survival prediction, and personalized therapeutic strategies in clinical practice.