PCA3 (Prostate cancer associated 3)

Despite this wealth of information, significant challenges in standardized isolation techniques and clinical application due to tumor heterogeneity remain. This review also aims to bridge existing gaps and provide future prospectives toward hybrid isolation techniques, cell-specific exosome profiling, and artificial intelligence (AI)-driven multi-omics data integration to leverage exosome biology and address PCa-specific biomarkers and heterogeneity, thereby improving patient outcomes.

This review systematically summarizes progress in biosensor platforms based on immunosensors, aptamer-based sensors, peptide-based sensors, nanopore technologies, and miRNA targeted biosensors by highlighting the nanomaterials such as graphene derivatives, carbon nanotubes, noble metal nanoparticles, and carbon dots in enhancing analytical performance. In this review we critically discussed about various biomarkers in details and multiple nano-materials with LOD, range and limitation for better material selection and current challenges, translational limitations, and future prospects toward point-of-care, and non-invasive prostate cancer diagnostics.

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.

The developed nomogram, integrating initial fPSA/tPSA screening, PHI risk quantification, PCA3 molecular confirmation, and magnetic resonance imaging (MRI) features, provides an effective tool for personalized risk stratification, with direct comparative analyses confirming its advantage over single-modality approaches.

It does not require specialized laboratory UV imaging equipment; results are visible to the naked eye under LED blue light. Following further optimization, it offers a feasible technical solution for rapid molecular screening of prostate cancer.

PCR analysis of KLK3, FOLH1, and PCA3 expression enables the molecular detection of lymph-node metastasis and, when combined with standard histopathological examination, improves the accuracy and sensitivity of lymph-node staging. It also refines risk stratification for postoperative BCR, particularly by identifying pathologically node-negative patients at increased risk. Molecular lymph-node assessment based on these markers may therefore serve as a useful prognostic tool to guide adjuvant treatment decisions, although larger prospective studies are needed to validate these findings.

Additionally, the review addresses key genetic alterations implicated in prostate carcinogenesis, including mutations in BRCA1/2, HOXB13, and PTEN deletions, as well as changes in the androgen receptor pathway. By evaluating recent advancements and applications of these biomarkers, this review aims to enhance understanding of their role in improving early diagnosis, prognosis, and personalised management of prostate cancer.

Furthermore, serum Phi combined with urinary PCA3-T2:ERG outperformed urinary PCA3-T2:ERG in each of the 3 algorithms reflecting different potential clinical workflows: (1) serum Phi and urine PCA3-T2:ERG tested simultaneously, either exceeding its own threshold (P = .04); (2) urine PCA3-T2:ERG first and those in the grey zone resolved by subsequent serum Phi (P = .03); and (3) serum Phi first and those in the grey zone resolved by subsequent urine PCA3-T2:ERG (P = .002). Combining serum Phi with urinary PCA3 RNA alone or together with urinary T2:ERG RNA, simultaneously or sequentially, improves selection of men for initial prostate biopsy and represents an avenue to improve early detection of aggressive PCa.

To validate these findings, we constructed a PCA3 promoter-driven transcriptional reporter system, which exhibited elevated activity in lower-grade PCa, reinforcing the differential expression pattern of PCA3 across pathological grades. Our findings suggest that PCA3 could serve as a robust and clinically valuable biomarker for predicting PCa pathological grade.

Clinically implemented assays, including PCA3, ConfirmMDx, and ExoDx Prostate, along with emerging multi-analyte panels, enhance risk stratification, reduce unnecessary biopsies, and guide therapeutic decisions. Integration of epigenetic and liquid biopsy biomarkers into multimodal diagnostic pathways has the potential to support personalized management of prostate cancer; however, many still require further validation and optimization.

Despite slightly decreased performance, the TR-FRET nanoassay demonstrated reliable quantification of nanomolar PCA3 concentrations also in samples containing up to 50% of serum. These findings underscore the potential of Tb-to-QD FRET assays for rapid clinical prostate cancer diagnostics, offering a promising tool for the early detection of PCA3 in a noninvasive manner.