Prostate cancer (PCa) is the second most common malignancy in men worldwide, with rising mortality linked to late-stage diagnoses. While current diagnostic strategies rely heavily on biomarker detection, their limitations highlight the need for comprehensive and integrative biomarker discovery. This review consolidates recent advances in PCa biomarkers, encompassing genetic, proteomic, liquid biopsy, and imaging-based approaches. Genetic mutations inform disease prognosis and therapy selection, while proteomic biomarkers elucidate molecular mechanisms and therapeutic targets. Blood- and urine-based biomarkers, including exosome-derived markers, circulating tumor DNA (ctDNA), PCA3, and SelectMDx, enable minimally invasive risk stratification. Artificial intelligence-assisted analysis of multiparametric MRI and PSMA PET/CT has been explored to support lesion detection and staging, although most AI-based tools remain investigational. Integrating these biomarker-driven strategies into clinical workflows supports precision oncology and improves patient outcomes. Despite challenges in assay standardization, validation, cost, and ethical implementation, the convergence of genomics, liquid biopsy, and AI technologies marks a transformative step toward personalized prostate cancer management. To distinguish clinically validated tools from emerging candidates, biomarkers are discussed according to their level of evidence and clinical readiness.
Ramesh et al. (Tue,) studied this question.