INTEGRATIVE IDENTIFICATION OF RECURRENT NON-CODING MUTATIONS IN MICRORNAs AND TRANSCRIPTION FACTOR BINDING SITES FOR EARLY DETECTION OF PROSTATE CANCER
DOI:
https://doi.org/10.48165/abr.2026.28.01.33Keywords:
Cell lines, microRNAs, prostate cancer, recurrent non-coding mutations, transcription factor binding sitesAbstract
Prostate cancer remains a major global health challenge, and the largely unexplored non-coding genome—including microRNAs (miRNAs) and transcription factor binding sites (TFBS) — offers critical insights into its early molecular events. This study is distinct in integration of computational analyses of both TFBS and miRNAs to identify highly recurrent mutations within non coding regions of prostate cancer. Point mutations were retrieved from the COSMIC database and then subjected to computational analysis. Recurrent non-coding mutations were identified in MIR100HG, MIR4432, and MIR2054. These statistically significant mutations were mapped to prostate cancer cell-line specific TFBS, revealing their presence within recurrent mutational hotspots. Importantly, a 10,000-bootstrap randomization model (q < 0.05) confirmed that these hotspots are unlikely to be random. The loci identified here represent strong candidate regulatory regions that warrant experimental validation through approaches like luciferase reporter assays, and CRISPR-based editing, aswell as clinical cohort studiesto establish their functional and causalrelevance. Overall,thisframeworkhighlights coordinateddisruptionsacrosstranscriptional and post-transcriptional networks, offering a novel computational strategy to distinguish biologically meaningful regulatory loci from background genetic noise. By doing so, it provides a foundation for future biomarker discovery and the development of targeted interventions in prostate cancer.
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