Empowering early detection of prostate cancer: a point-of-care biosensing perspective

Prostate cancer (PCa) is a major oncological burden globally, with disease progression closely linked to the timeliness and accuracy of clinical detection. Despite widespread use, conventional diagnostic approaches, including prostate-specific antigen assays, digital rectal examination, and ultrasound-guided biopsy, suffer from significant limitations such as poor biomarker specificity, invasiveness, and inter-operator variability, contributing to overdiagnosis and overtreatment. Recent advances in biosensor engineering have enabled the development of highly sensitive, selective, and multiplexed point-of-care diagnostic systems that can quantitatively detect PCa-associated biomarkers in noninvasive biological fluids with minimal sample processing. This review critically examines the current landscape of POC biosensing strategies for PCa, focusing on electrochemical, optical, and field-effect transistor (FET)-based platforms functionalized with high-affinity biorecognition elements such as antibodies, aptamers, and synthetic receptors. We highlight clinically validated and emerging molecular targets, including PSA isoforms, PCA3, TMPRSS2–ERG fusion transcripts, exosomal RNAs, and circulating tumor cells, and evaluate their diagnostic performance in integrated sensor systems. Emphasis is placed on the role of nanostructured transducer interfaces such as graphene, MXenes, metal–organic frameworks, and quantum dots in enhancing signal-to-noise ratios, lowering detection limits to the femtomolar range, and enabling multimodal sensing. Moreover, the integration of machine learning (ML) and explainable artificial intelligence (XAI) algorithms into biosensor data workflows is discussed as a means to extract clinically actionable insights from high-dimensional, multi-biomarker datasets. These intelligent systems facilitate individualized risk assessment, improved classification of equivocal cases, and data-driven clinical decision-making. Finally, we address translational challenges related to device reproducibility, regulatory compliance, long-term stability, and deployment in low-resource settings. Collectively, the synergy between advanced materials, real-time analytics, and noninvasive sample access positions next-generation biosensing technologies as a cornerstone in the future of precision diagnostics and global prostate cancer management.