Urine transcriptomic biomarkers for prostate cancer detection and risk stratification

Early and accurate diagnosis of prostate cancer remains challenging due to its biological heterogeneity and the limitations of current clinical tools. Widely used diagnostic approaches, including serum prostate-specific antigen (PSA) testing and biopsy, are associated with low specificity, invasiveness, and limited assessment of tumour aggressiveness. These limitations have driven increasing interest in non-invasive molecular diagnostics that can provide biologically meaningful insights while reducing unnecessary clinical interventions This review aims to evaluate the biological basis, analytical methodologies, and clinical utility of urine-based gene expression profiling for prostate cancer detection and risk stratification. Tumour-associated transcriptional alterations, persistent androgen receptor signalling, epigenetic dysregulation, metabolic reprogramming, and extracellular vesicle-mediated RNA release enable the detection of clinically relevant gene expression signatures in urine. Key urinary biomarkers include mRNAs, long non-coding RNAs, fusion transcripts, and microRNAs, which are analyzed using platforms ranging from quantitative PCR-based assays to next-generation sequencing and multigene classifier approaches. Evidence from prospective and multicentre clinical studies suggests that urine-based transcriptomic assays may improve the detection of clinically significant disease, reduce unnecessary biopsies, and support risk stratification when compared with PSA and conventional clinical models. However, biological variability, technical complexity, and standardization challenges remain important considerations. This review highlights current limitations and future perspectives, including the integration of urinary transcriptomic profiling with multimodal diagnostic strategies and artificial intelligence-based decision-support systems to advance precision prostate cancer care.