In this review, we evaluated literature regarding different modalities for multiparametric magnetic resonance imaging (mpMRI) and mpMRI-targeted biopsy (TB) for the detection of prostate cancer (PCa). We identified studies evaluating systematic biopsy (SB) and TB in the same patient, thereby allowing each patient to serve as their own control. Although the evidence supports the accuracy of TB, there is still a proportion of clinically significant PCa (csPCa) that is detected only in SB, indicating the importance of maintaining SB in the diagnostic pathway, albeit with additional cost and morbidity. There is a growing subset of data which supports the role of TB alone, which may allow for increased efficiency and decreased complications. We also compared the literature on transrectal (TR) vs. transperineal (TP) TB. Although further high-level evidence is necessary, current evidence supports similar csPCa detection rate for both approaches. We also evaluated various TB techniques such as cognitive fusion biopsy (COG-TB) and in-bore biopsy (IB-TB). COG-TB has comparable detection rates to software fusion, but is operator-dependent and may have reduced accuracy for smaller lesions. IB-TB may allow for greater precision as lesions are directly targeted; however, this is costly and time-consuming, and does not account for MRI-invisible lesions.

Focal therapy (FT) has emerged as a potential treatment for localized prostate cancer (PCa) with encouraging functional outcomes. According to the compelling evidence based on meta-analyses and recent trials, erectile function (EF) is mostly retained at 6 and 12 months after FT when compared to baseline. These findings are consistent across different energy sources reported to date. However, overall, quality of life, including impotence, was not the endpoint for most studies. Additionally, impotency has not been consistently reported in most of the recent literature. Furthermore, confounding factors such as baseline potency and usage of phosphodiesterase 5 inhibitors (PDE5-I) were also frequently undisclosed. Long-term functional outcomes are awaited. To fully comprehend how FT affects EF, more extensive long-term randomized clinical trials using EF as a primary outcome are needed.

Background/Objectives: Needle biopsy-based molecular assays that are sensitive, cost-effective, and reproducible could improve prostate cancer (PCa) diagnosis and risk stratification. We developed a compact, biologically informed gene expression signature panel (ONECUT2, EZH2, BRCA2) for cancer detection and aggressiveness stratification. Methods: We designed and validated a multiplex real-time RT-qPCR assay for ONECUT2, EZH2, and BRCA2. Biomarker selection was guided by The Cancer Genome Atlas Prostate Adenocarcinoma (TCGA-PRAD) and Gene Expression Omnibus (GEO) cohort analyses. The assay was applied to 979 ex vivo needle biopsy cores from 255 radical prostatectomy specimens; machine-learning models (Random Forest, AdaBoost, Elastic Net) generated an RNA signature. Diagnostic and prognostic performance was assessed by the area under the receiver operating characteristic curve (AUC), model comparisons by DeLong’s test, and biochemical recurrence-free survival (BCR) by Kaplan–Meier and Cox proportional hazards analyses. Reproducibility based on sample pairs was assessed by intraclass correlation coefficients (ICC). Results: The three-gene expression signature (ONECUT2, EZH2, and BRCA2) robustly discriminated malignant from non-malignant tissue (AUC = 0.91) and identified clinically significant cancer (Gleason Grade Group [GG] ≥ 2 vs. GG 0–1, AUC = 0.89) within biopsy cores. However, it had limited performance for advanced patient-level features (e.g., pathological GG3–5, AUC = 0.63). In contrast, ONECUT2 gene-body methylation significantly stratified pathological aggressiveness (pathological GG3–5, AUC = 0.79; aggressive disease, AUC = 0.75) and demonstrated superior assay stability (methylation ICC 0.58–0.70 vs. RNA ICC 0.38–0.61). Furthermore, ONECUT2 DNA methylation significantly stratified BCR-free survival (hazard ratio = 3.90, p = 0.023), whereas the RNA signature showed a modest trend (hazard ratio = 1.88, p = 0.053). Notably, integrating DNA methylation with the three-gene expression signature (combined model) significantly improved predictive accuracy for adverse features (e.g., extraprostatic extension, ΔAUC = 0.20, p = 0.02) compared to the three-gene expression signature alone. Conclusions: While a multiplex RT-qPCR panel (ONECUT2, EZH2, and BRCA2) excels at core-level cancer detection, it lacks the resolution for aggressiveness classification. In contrast, ONECUT2 DNA methylation provides superior analytical reproducibility, robust stratification of cancer aggressiveness, and long-term recurrence risk estimation. These findings suggest that integrating transcriptional and epigenetic markers into a multimodal framework could provide complementary information to refine risk stratification in PCa.