Biomarkers for prostate cancer detection and risk stratification

Driving Knowledge to Action: Building a Better Future With Artificial Intelligence-Enabled Multidisciplinary Oncology

Artificial intelligence (AI) is transforming multidisciplinary oncology at an unprecedented pace, redefining how clinicians detect, classify, and treat cancer. From earlier and more accurate diagnoses to personalized treatment planning, AI's impact is evident across radiology, pathology, radiation oncology, and medical oncology. By leveraging vast and diverse data-including imaging, genomic, clinical, and real-world evidence-AI algorithms can uncover complex patterns, accelerate drug discovery, and help identify optimal treatment regimens for each patient. However, realizing the full potential of AI also necessitates addressing concerns regarding data quality, algorithmic bias, explainability, privacy, and regulatory oversight-especially in low- and middle-income countries (LMICs), where disparities in cancer care are particularly pronounced. This study provides a comprehensive overview of how AI is reshaping cancer care, reviews its benefits and challenges, and outlines ethical and policy implications in line with ASCO's 2025 theme, Driving Knowledge to Action. We offer concrete calls to action for clinicians, researchers, industry stakeholders, and policymakers to ensure that AI-driven, patient-centric oncology is accessible, equitable, and sustainable worldwide.

Transcriptomic signatures of prostate cancer progression: a comprehensive RNA-seq study

Transcriptomics has been entirely transformed by RNA-sequencing (RNA-seq) due to its high sensitivity, accuracy, and precision. This study analyzed RNA-seq data to identify potential biomarkers for prostate cancer (PCa), a serious health issue among aging men. Despite several existing studies, biomarkers that effectively detect PCa or its prognosis have yet to be entirely determined. The differentially expressed genes (DEGs) that are critical and clinically informative were identified in PCa patient samples that had been progression stage categorized into medium risk (MR) and high risk (HR). A total of 174 DEGs were found to be shared between MR and HR samples. Functional enrichment analysis revealed their involvement in crucial biological processes, such as p53 signaling, mitotic nuclear division, and inflammation. To further examine their interactions, a Protein-Protein Interaction (PPI) network was constructed, where key genes, such as KIF20A, TPX2, BUB1, BIRC5, BUB1B, and MKI67, were found in significant modules, hubs, and motifs. Several transcription factors, including STAT5B, MYC, and SOX5 controlled these genes. Heatmap analysis indicates that the expression of the six crucial genes (KIF20A, TPX2, BUB1, BIRC5, BUB1B, and MKI67) increases with progression from benign state to medium-risk and high-risk states. Additionally, a nomogram model was constructed to predict the prognostic value of these biomarkers. Among the studied genes, BIRC5, MKI67, and KIF20A are suggested as potential prognostic biomarkers, while NIFK and PPP1CC are suggested as new therapeutic targets. These findings indicate that these biomarkers show considerable promise in improving early detection and prognosis of PCa.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-025-04297-3.

The effect of flavonoid and subclasses supplementation on prostate specific antigen, hormonal parameters and prostate cancer risk: a systematic review and meta-analysis of randomized controlled trials

INTRODUCTION AND OBJECTIVES

Prostate cancer (PCa) is a significant concern and burden worldwide. Several studies suggest that flavonoids have a significant potential as an anti-cancer agent, but the evidence remains controversial. This study aims to assess the effect of flavonoids and its subclasses supplementation on PCa risk parameters in men with biopsy-proven diagnosis of PCa or clinically determined to have a high risk of PCa.

MATERIALS AND METHODS

This systematic review and meta-analysis adhered to PRISMA guideline. A literature search was conducted across PubMed, ScienceDirect, Scopus and Cochrane utilizing PICO framework. Revised Cochrane's risk of bias tools (RoB2) was used for quality analysis. Review manager 5.4 was used for statistical analysis.

RESULTS

Out of 1.117 articles, nine final studies (involving 420 patients) were included. Regarding total PSA, flavonoid provided a reduction of total PSA (MD: -0.64, p<0.05), and sub-group analysis based on the supplementation duration showed flavonoid administration with a duration of ≥12 weeks significantly reduced total PSA compared to administration of <12 weeks (p<0.05). Meta-analyses of four studies, including men clinically at risk of PCa, revealed that flavonoid supplementation was associated with a significantly lower risk of developing PCa at endpoint (OR 0.41, p<0.05). However, our results indicated no favorable effect on hormonal parameters.

CONCLUSIONS

The results of this meta-analysis suggest there may be a potential role for flavonoid in PCa risk reduction. Flavonoids supplementation also have been proven to be safe. However, further investigation is necessary to gain a clear understanding of the flavonoid impact on PSA and sex hormone parameters.

MRI-detected extranodal extension as a marker of prostate cancer aggressiveness

OBJECTIVE

Extranodal extension (ENE) is a histological marker of aggressiveness for various cancers. We evaluated if clinical ENE, detected by Magnetic Resonance Imaging, can also serve as a biological marker of Prostate Cancer (PCa) aggressiveness.

MATERIALS AND METHODS

This retrospective, single-center study analyzed patients diagnosed with PCa and had MRI on a 3-T scanner from January 2013 to December 2017. After exclusions, 461 patients were included and divided into: Group 1, no lymph node involvement (LNI), Group 2 (LNI without ENE), and Group 3 (LNI and ENE). Two experienced radiologists assessed the MRI scans for primary lesion characteristics, LNI and ENE. Reproducibility assessment was calculated for ENE and PI-RADS. Clinical outcomes, including Overall Survival (OS), Specific Survival Rate (SSR), and Progression-Free Survival (PFS), were analyzed.

RESULTS

Group 1 included 410 patients, Group 2, 32 patients, and Group 3, 19 patients. The prevalence of ENE was 4.1%. Significant differences between groups were observed for age, PSA, dPSA, ISUP scores, clinical risk stratification, and staging (all p < 0.01). The Kappa coefficient for ENE was 0.75 (95% CI: 0.56-0.90), and 0.48 (0.14-1.0) for PI-RADS. Cox proportional hazards model showed PSA (HR: 1.009; 95% CI = 1.003-1.015, p < 0.01) and ENE (HR: 8.50; 1.76-40.98, p < 0.01) were associated with SSR, and both ENE (HR: 8.18; 2.34-28.58, p < 0.01) and LNI (HR: 5.99, 1.97-18.17, p < 0.01) were linked to poor PFS.

CONCLUSION

MRI-detected ENE, despite low prevalence, is a predictor of SSR and PFS in PCa. These findings support ENE as an independent prognostic marker. Further prospective, multi-institutional studies are required to validate these results.

KEY POINTS

Question Pathological extranodal extension (pENE) has been described as a marker of worrisome prognosis in prostate cancer (PCa), but clinical ENE has not been evaluated as a marker of prognosis in PCa. Findings MRI-detected clinical ENE, had a low prevalence in our cohort (4.1%), but it was a predictor of specific survival rate and progression-free survival. Clinical relevance MRI-detected clinical ENE, a reproducible imaging feature, may serve as a non-invasive biomarker for aggressive prostate cancer. It correlates with poorer progression-free survival and specific survival rates, offering valuable prognostic insights for patient management.

The impact of prostate volume on Retzius-sparing robot-assisted laparoscopic radical prostatectomy with retrograde release of the neurovascular bundle

OBJECTIVE

Robot-assisted radical prostatectomy (RARP) has emerged as a primary treatment modality for localized prostate cancer. In this context, we report a novel surgical technique termed Retzius-sparing robot-assisted laparoscopic radical prostatectomy with retrograde release of the neurovascular bundle (RNRS-RARP). This study aims to assess the perioperative, oncological, and functional outcomes of RNRS-RARP across varying prostate volumes.

METHODS

A retrospective analysis was conducted on clinical data retrieved from 298 patients who underwent RNRS-RARP from October 2021 to September 2023. Patients were stratified into three groups based on pathological prostate weight: ≤ 30 g, 30-50 g, and ≥ 50 g. Comparative analyses were performed on perioperative and postoperative oncological and functional outcomes among the three groups to discern variations. Separate analyses were performed for patients who received neoadjuvant therapy and those who did not. Additionally, independent predictors of immediate continence following RNRS-RARP were investigated.

RESULTS

Patients with larger prostate volumes were significantly older and have higher body mass index and prostate-specific antigen (PSA) (all p < 0.05). Larger prostate volumes exhibited prolonged median console time (65 vs. 70 vs. 90 min, p < 0.01) and increased median estimated blood loss (95 vs. 90 vs. 100 ml). There were no significant differences in duration of catheterization, length of stay, postoperative complications, positive surgical margin, PSA recurrence after 6 months, 1 month and 3 months continence. Immediate continence worsened with increasing prostate volume (80.0% vs. 77.5% vs. 64.2%, p = 0.04). Prostate volume (OR = 0.98; 95% Cl: 0.97-0.99; p = 0.03), age (OR = 0.90; 95% Cl: 0.86-0.95; p < 0.01), and clinical T stage (OR = 0.31; 95% Cl: 0.13-0.74; p = 0.01) were independent risk factors for immediate continence, with an area under the curve of 0.75 in the predictive model.

CONCLUSION

RNRS-RARP can be safely performed regardless of prostate volume. As prostate volume increases, both console time and estimated blood loss tend to rise. However, the oncological outcomes and complication rates remained similar. Immediate continence was significantly lower with larger prostate volume, which also emerged as an independent predictor.

CLINICAL TRIAL REGISTRATION

The clinical trial registration number is ChiCTR2200066350 (December1, 2022).

The impact of urine biomarkers for prostate cancer detection-A systematic state of the art review

BACKGROUND

Prostate cancer (PCa) screening primarily relies on Prostate-Specific Antigen (PSA), which has low specificity and therefore leads to unnecessary biopsies. Consequently, there is a growing need for, ideally, non-invasive biomarkers. Liquid biopsy, a diagnostic approach analyzing circulating tumor components in body fluids, has emerged as a promising diagnostic tool for various cancers, including PCa.

METHODS

To evaluate recent evidence on urine-based biomarkers for the detection of PCa, we conducted a systematic review in accordance with the PRISMA guidelines. Our literature search identified a total of 286 studies, of which 66 met our inclusion criteria (men suspected of PCa with no prior history of PCa). After assessing the risk of bias using the QUADAS-2 tool, studies on five distinct urinary biomarker tests were included for further analysis.

RESULTS

Tests that do not rely on digital rectal examination (non-DRE), such as Exosome Dx Prostate IntelliScore (EPI) and Protexam Prostate Status Management (PSM)/Prostate Check-Up (PSU), demonstrated strong performance in detecting PCa, particularly clinically significant PCa. Meanwhile, the MyProstateScore test (MPS) showed the highest efficacy among tests utilizing urine samples collected post-DRE. Unfortunately, the performance of the biomarker test with the most available studies, PCA3 ProGensa® Score, was underwhelming with only moderate sensitivity and specificity.

CONCLUSIONS

Despite promising results from various urine-based biomarker tests, we are currently unable to recommend one specific test for implementation into clinical practice. The broad heterogeneity of the studies conducted hindered the ability to perform a meta-analysis, and prospective randomized trials providing clinical evidence are still lacking.

Investigating Intensity and Percentage of p53 Nuclear Expression in Prostate Cancer: Findings from a Cohort of U.S. Military Veterans

BACKGROUND

Next-generation sequencing has revealed TP53 alterations in localized prostate cancer (PCa), suggesting growing clinical potential for p53 immunohistochemistry (IHC). Prior research supports the use of IHC for the detection of p53 overexpression to predict the presence of TP53 alterations known to be associated with adverse outcomes. However, to reach a consensus definition of p53 overexpression in PCa, further insights are needed. This study aimed to compare two fundamental approaches of evaluating p53 expression across a variety of specimens regarding PCa progression.

METHODS

This study included 84 patients (75% self-identified as African American) diagnosed with PCa between 1996 and 2021 at the DC VA Medical Center. Representative sections of core biopsies, radical prostatectomies, transurethral prostate resections, and metastatic deposits were examined. p53 nuclear expression was scored according to the highest intensity observed (0, 1+, 2+, 3+) and the percentage (0%, <1%, 1-5%, >5%) of tumor cells expressing any level of intensity in the aggregate tumor area. All slides were reviewed by two independent pathologists. Pertinent clinical data were collected.

RESULTS

A total of 34 patients (40%) exhibited p53 nuclear expression, of which 18 (21%) showed the maximum (3+) intensity. The presence of maximum intensity, regardless of percentage, was found to be associated with Grade Group (p < 0.001), higher PSA at biopsy (p < 0.001), BCR (p < 0.001) and metastasis (p < 0.001). Importantly, maximum p53 intensity was identified only in patients who developed metastatic disease.

CONCLUSIONS

Maximum (3+) p53 nuclear intensity of any percentage is highly associated with disease progression in PCa, suggesting that optimal determination of p53 overexpression should incorporate intensity.

Non-DRE Voided Urine Test to Diagnose Prostate Cancer: Updated Results

Background: The standard diagnostic approach for prostate cancer (PCa) diagnosis consists of serum prostate-specific antigen (PSA) testing, digital rectal examination (DRE) and image-guided targeted biopsies. Given the invasive nature, potential adverse events and costs associated with these techniques, alternative approaches have been investigated, specifically with serum and urine assays. The work presented here is intended to further validate a novel noninvasive optical technique for PCa detection, targeting the VPAC genomic receptors that are overexpressed on prostate cancer's malignant cells (MC), in non-DRE voided urine. Methods: Patients (N = 62) who had image-guided biopsy and histologically confirmed localized PCa, and who were scheduled for radical prostatectomy, provided a non-DRE voided urine sample prior to surgery. Urine was cytocentrifuged and cells fixed on a glass slide, incubated with 0.5 μg TP4303 (a receptor-specific fluorophore developed in our laboratory with high affinity for VPAC), excess washed and treated with 4,6-diamidodino-2-phenylindole (DAPI) for nuclear staining. The field of cells on each slide was analyzed using a Zeiss AX10 Observer microscope (20×). The total number of cells and MC were then counted, and the florescent intensity around each MC was measured using Zeiss software. Additionally, non-DRE voided urine samples collected from clinically determined BPH patients (N = 97), were also analyzed similarly. Results: Urine samples from 62 patients were processed and analyzed. Mean PSA levels by Gleason grade (GG) group were 6.5 ± 4.1 ng/mL for GG1 (N = 10), 7.2 ± 3.8 for GG2 (N = 31), 13.2 ± 14.6 for GG3 (N = 13), 6.2 ± 2.2 for GG4 (N = 2) and 50.2 ± 104.9 for GG5 (N = 6). Like the PSA, % MC shed (66.7 ± 27.7) in voided urine and the fluorescent intensity (35.8 ± 5.7) were highest in patients with GG5 prostate cancer. All PCa patients in GG1 to GG5 shed MC in voided urine with increasing % of MC and increasing fluorescence intensity which correlated with the increasing GG for PCa. For BPH, the specificity for the assay was 89.6% (95% CI:81.9-94.9%), PPV was 0.0% and NPV was 100% (95.9% CI, 95.9-100%). Conclusions: These data indicate the following: (i) PCa MC shed in non-DRE voided urine can be detected by targeting VPAC receptors, (ii) MC are shed in non-DRE voided urine with increasing quantity, corresponding to the severity of the disease, and (iii) this non-DRE voided urine optical assay provides a simple, noninvasive, and reliable method for the preliminary detection of PCa with potentially a lower cost than the currently available pre-biopsy detection technologies.

Claudin 18.2 Is Not a Promising Biomarker for Targeted Immunotherapy in Prostatic Cancers

BACKGROUND/AIM

Claudin 18.2 (CLDN18.2) has emerged as a highly selective biomarker and its abnormal expression has been reported in various primary malignant tumors. Recently, CLDN18.2 has gained attention as both a prognostic biomarker and a potential therapeutic target in gastric and gastroesophageal junction cancer. The purpose of this study was to investigate CLDN18.2 expression in a large cohort of 168 prostate cancer (PC) tissues, assess its correlation with clinicopathological factors, and evaluate its potential as a therapeutic target for anti-CLDN18.2 therapy.

MATERIALS AND METHODS

Immunohistochemical staining was conducted using an approved diagnostic CLDN18.2 immunohistochemistry protocol (Ventana, 43-14A clone). Interpretation was carried out following the general rules for staining evaluation.

RESULTS

Non-neoplastic gastric mucosa, used as a positive control for CLDN18.2 immunostaining, exhibited strong membranous staining. In contrast, no CLDN18.2 expression was detected in normal ductal and acinar cells of prostate tissue, nor in any of the 168 variable PC tissues.

CONCLUSION

CLDN18.2 is not expressed in normal prostate tissue or PC, suggesting that it is unlikely to serve as a prognostic marker or a potential target for immunotherapy in PC.

Defining the genetic profile of prostate cancer

Several studies indicated that prostate cancer has a hereditary component. In particular, a significant risk of prostate cancer has been linked to a tight familial lineage. However, to provide insight into how prostate cancer is inherited, characterising its genetic profile is essential. The current body of research on the analysis of genetic mutations in prostate cancer was reviewed to achieve this. This paper reports on the effects and underlying processes of prostate cancer that have been linked to decreased male fertility. Many research approaches used have resulted in the discovery of unique inheritance patterns and manifest traits, the onset and spread of prostate cancer have also been linked to many genes. Studies have specifically examined Androgen Receptor gene variants about prostate cancer risk and disease progression. Research has shown that genetic and environmental variables are important contributors to prostate cancer, even if the true origins of the disease are not fully recognised or established. Researchers studying the genetics of prostate cancer are using genome-wide association studies more and more because of their outstanding effectiveness in revealing susceptibility loci for prostate cancer. Genome-Wide Association Studies provides a detailed method for identifying the distinct sequence of a gene that is associated with cancer risk. Surgical procedures and radiation treatments are 2 of the treatment options for prostate cancer. Notwithstanding the compelling evidence shown in this work, suggests that more research must be done to detect the gene alterations and the use of genetic variants in the treatment of prostate cancer.

Circulating Epithelial Tumor Cells (CETC/CTC) in Prostate Cancer: Potential Prognostic Marker for the Risk of Recurrence During Radiotherapy

Prostate cancer is a leading cause of cancer-related mortality in men, with radiotherapy (RT) playing a pivotal role in treatment. However, reliable biomarkers for assessing relapse risk following RT remain scarce. This study aimed to evaluate circulating epithelial tumor cells (CETC/CTC) as potential biomarkers for assessing relapse risk in prostate cancer patients undergoing RT. Peripheral blood samples were collected from 52 prostate cancer patients, and CETC/CTC were detected using the EpCAM surface marker. Patients received definitive, adjuvant, or salvage RT, and CETC/CTC counts were measured before, at mid-treatment, and at the end of RT. The association between changes in CETC/CTC counts and relapse risk was examined. CETC/CTC were detected in 96% of patients prior to RT. A significant reduction in CETC/CTC counts during RT, particularly in patients who had undergone surgery, was associated with a lower relapse risk. In contrast, an increase in CETC/CTC counts during or after RT was associated with a higher relapse risk (hazard ratio = 8.8; p = 0.002). Furthermore, 36% of patients receiving adjuvant RT and 14% of those receiving definitive RT relapsed, with a higher risk observed in patients showing increasing CETC/CTC counts during RT. Among patients receiving salvage RT, 18% relapsed, though changes in CETC/CTC counts were less significantly associated with relapse. Monitoring CETC/CTC levels during RT offers important prognostic insights into relapse risk in prostate cancer patients. While changes in CETC/CTC counts correlated with relapse, PSA levels measured during the study did not reliably reflect relapse risk in this cohort. CETC/CTC shows promise as a prognostic marker, though further studies are required to validate its clinical superiority over PSA.

Prostate cancer risk biomarkers from large cohort and prospective metabolomics studies: A systematic review

Prostate cancer (PCa) is one of the leading causes of cancer-related deaths among men. The heterogeneous nature of this disease presents challenges in its diagnosis, prognosis, and treatment. Numerous potential predictive, diagnostic, prognostic, and risk assessment biomarkers have been proposed through various population studies. However, to date, no metabolite biomarker has been approved or validated for the diagnosis, prognosis, or risk assessment of PCa. Recognizing that systematic reviews of case reports or heterogenous studies cannot reliably establish causality, this review analyzed 29 large prospective metabolomics studies that utilized harmonized criteria for patient selection, consistent methodologies for blood sample collection and storage, data analysis, and that are available in public repositories. By focusing on these large prospective studies, we identified 42 metabolites that were consistently replicated by different authors and across cohort studies. These metabolites have the potential to serve as PCa risk-assessment or predictive biomarkers. A discussion on their associations with dietary sources or dietary patterns is also provided. Further detailed exploration of the relationship with diet, supplement intake, nutrition patterns, contaminants, lifestyle factors, and pre-existing comorbidities that may predispose individuals to PCa is warranted for future research and validation.

Validation of a Urine-Based Proteomics Test to Predict Clinically Significant Prostate Cancer: Complementing mpMRI Pathway

INTRODUCTION

Prostate cancer (PCa) is the most frequently diagnosed cancer among men. A major clinical need is to accurately predict clinically significant PCa (csPCa). A proteomics-based 19-biomarker model (19-BM) was previously developed using capillary electrophoresis-mass spectrometry (CE-MS) and validated in close to 1,000 patients at risk for PCa. This study aimed to validate 19-BM in a multicenter prospective cohort of 101 biopsy-naive patients using current diagnostic pathways.

METHODS

Urine samples from 101 patients with suspicious of PCa were analyzed using CE-MS. All patients underwent multiparametric or magnetic resonance imaging (mpMRI) using a 3-T system. The 19-BM score was estimated using support vector machine-based software (MosaCluster v1.7.0), employing the previously published cut-off criterion of -0.07. Diagnostic nomograms were investigated along with mpMRI.

RESULTS

Independent validation of 19-BM yielded a sensitivity of 77% and a specificity of 85% (AUC:0.81). This performance surpassed those of prostate-specific antigen (PSA; AUC:0.56) and PSA density (AUC:0.69). For PI-RADS≤ 3 patients, 19-BM showed a sensitivity of 86% and a specificity of 88%. Integrating 19-BM with mpMRI resulted in significantly better accuracy (AUC:0.90) compared to individual investigations alone (AUC19BM = 0.81; p = 0.004 and AUCmpMRI: 0.79; p = 0.001). Examining the decision curve analysis, 19-BM with mpMRI surpassed other approaches for the prevailing risk interval from a 30% cut-off.

CONCLUSIONS

19-BM exhibited favorable reproducibility for the prediction of csPCa. In patients with PI-RADS ≤3, 19-BM correctly classified 88% of the patients with insignificant PCa at the cost of 1 missed csPCa patient. Utilizing the 19-BM test could prove valuable in complementing mpMRI and reducing the need for unnecessary biopsies.

The efficacy of different biomarkers and endpoints to refine referrals for suspected prostate cancer: the TARGET study (Tiered integrAted tests for eaRly diaGnosis of clinically significant ProstatE Tumours)

BACKGROUND

The majority of men referred with a raised PSA for suspected prostate cancer will receive unnecessary tertiary investigations including MRI and biopsy. Here, we compared different types of biomarkers to refine tertiary referrals and when different definitions of clinically significant cancer were used.

METHODS

Data and samples from 798 men referred for a raised PSA (≥ 3 ng/mL) and investigated through an MRI-guided biopsy pathway were accessed for this study. Bloods were acquired pre-biopsy for liquid biomarkers and germline DNA. Variables explored included PSA + Age (base model), free/total PSA (FTPSA), Prostate Health Index (phi), PSA density (PSAd), polygenic risk score (PRS) and MRI (≥ LIKERT 3). Different diagnostic endpoints for significant cancer (≥ grade group 2 [GG2], ≥ GG3, ≥ Cambridge Prognostic Group 2 [CPG2], ≥ CPG3) were tested. The added value of each biomarker to the base model was evaluated using logistic regression models, AUC and decision curve analysis (DCA) plots.

RESULTS

The median age and PSA was 65 years and 7.13 ng/mL respectively. Depending on definition of clinical significance, ≥ grade group 2 (GG2) was detected in 57.0% (455/798), ≥ GG3 in 27.5% (220/798), ≥ CPG2 in 61.6% (492/798) and ≥ CPG3 in 42.6% (340/798). In the pre-MRI context, the PSA + Age (base model) AUC for prediction of ≥ GG2, ≥ GG3, ≥ CPG2 and ≥ CPG3 was 0.66, 0.68, 0.70 and 0.75 respectively. Adding phi and PSAd to base model improved performance across all diagnostic endpoints but was notably better when the composite CPG prognostic score was used: AUC 0.82, 0.82, 0.83, 0.82 and AUC 0.74, 0.73, 0.79, 0.79 respectively. In contrast, neither FTPSA or PRS scores improved performance especially in detection of ≥ GG3 and ≥ CPG3 disease. Combining biomarkers did not alter results. Models using phi and PSAd post-MRI also improved performances but again benefit varied with diagnostic endpoint. In DCA analysis, models which incorporated PSAd and phi in particular were effective at reducing use of MRI and/or biopsies especially for ≥ CPG3 disease.

CONCLUSION

Incorporating phi or PSAd can refine and tier who is referred for tertiary imaging and/or biopsy after a raised PSA test. Incremental value however varied depending on the definition of clinical significance and was particularly useful when composite prognostic endpoints are used.

External Validation of a Digital Pathology-based Multimodal Artificial Intelligence Architecture in the NRG/RTOG 9902 Phase 3 Trial

BACKGROUND

Accurate risk stratification is critical to guide management decisions in localized prostate cancer (PCa). Previously, we had developed and validated a multimodal artificial intelligence (MMAI) model generated from digital histopathology and clinical features. Here, we externally validate this model on men with high-risk or locally advanced PCa treated and followed as part of a phase 3 randomized control trial.

OBJECTIVE

To externally validate the MMAI model on men with high-risk or locally advanced PCa treated and followed as part of a phase 3 randomized control trial.

DESIGN, SETTING, AND PARTICIPANTS

Our validation cohort included 318 localized high-risk PCa patients from NRG/RTOG 9902 with available histopathology (337 [85%] of the 397 patients enrolled into the trial had available slides, of which 19 [5.6%] failed due to poor image quality).

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Two previously locked prognostic MMAI models were validated for their intended endpoint: distant metastasis (DM) and PCa-specific mortality (PCSM). Individual clinical factors and the number of National Comprehensive Cancer Network (NCCN) high-risk features served as comparators. Subdistribution hazard ratio (sHR) was reported per standard deviation increase of the score with corresponding 95% confidence interval (CI) using Fine-Gray or Cox proportional hazards models.

RESULTS AND LIMITATIONS

The DM and PCSM MMAI algorithms were significantly and independently associated with the risk of DM (sHR [95% CI] = 2.33 [1.60-3.38], p < 0.001) and PCSM, respectively (sHR [95% CI] = 3.54 [2.38-5.28], p < 0.001) when compared against other prognostic clinical factors and NCCN high-risk features. The lower 75% of patients by DM MMAI had estimated 5- and 10-yr DM rates of 4% and 7%, and the highest quartile had average 5- and 10-yr DM rates of 19% and 32%, respectively (p < 0.001). Similar results were observed for the PCSM MMAI algorithm.

CONCLUSIONS

We externally validated the prognostic ability of MMAI models previously developed among men with localized high-risk disease. MMAI prognostic models further risk stratify beyond the clinical and pathological variables for DM and PCSM in a population of men already at a high risk for disease progression. This study provides evidence for consistent validation of our deep learning MMAI models to improve prognostication and enable more informed decision-making for patient care.

PATIENT SUMMARY

This paper presents a novel approach using images from pathology slides along with clinical variables to validate artificial intelligence (computer-generated) prognostic models. When implemented, clinicians can offer a more personalized and tailored prognostic discussion for men with localized prostate cancer.

Genomics in active surveillance and post-prostatectomy patients: A review of when and how to use effectively

PURPOSE OF REVIEW

Prostate cancer (PCa) represents a significant health burden globally, ranking as the most diagnosed cancer among men and a leading cause of cancer-related mortality. Conventional treatment methods such as radiation therapy or radical prostatectomy have significant side effects which often impact quality of life. As our understanding of the natural history and progression of PCa has evolved, so has the evolution of management options.

RECENT FINDINGS

Active surveillance (AS) has become an increasingly favored approach to the management of very low, low, and properly selected favorable intermediate risk PCa. AS permits ongoing observation and postpones intervention until definitive treatment is required. There are, however, challenges with selecting patients for AS, which further emphasizes the need for more precise tools to better risk stratify patients and choose candidates more accurately. Tissue-based biomarkers, such as ProMark, Prolaris, GPS (formerly Oncotype DX), and Decipher, are valuable because they improve the accuracy of patient selection for AS and offer important information on the prognosis and severity of disease. By enabling patients to be categorized according to their risk profiles, these biomarkers help physicians and patients make better informed treatment choices and lower the possibility of overtreatment. Even with their potential, further standardization and validation of these biomarkers is required to guarantee their broad clinical utility. Active surveillance has emerged as a preferred strategy for managing low-risk prostate cancer, and tissue-based biomarkers play a crucial role in refining patient selection and risk stratification. Standardization and validation of these biomarkers are essential to ensure their widespread clinical use and optimize patient outcomes.

Microfluidic Applications in Prostate Cancer Research

Prostate cancer is a disease in which cells in the prostate, a gland in the male reproductive system below the bladder, grow out of control and, among men, it is the second-most frequently diagnosed cancer (other than skin cancer). In recent years, prostate cancer death rate has stabilized and, currently, it is the second-most frequent cause of cancer death in men (after lung cancer). Most deaths occur due to metastasis, as cancer cells from the original tumor establish secondary tumors in distant organs. For a long time, classical cell cultures and animal models have been utilized in basic and applied scientific research, including clinical applications for many diseases, such as prostate cancer, since no better alternatives were available. Although helpful in dissecting cellular mechanisms, these models are poor predictors of physiological behavior mainly because of the lack of appropriate microenvironments. Microfluidics has emerged in the last two decades as a technology that could lead to a paradigm shift in life sciences and, in particular, controlling cancer. Microfluidic systems, such as organ-on-chips, have been assembled to mimic the critical functions of human organs. These microphysiological systems enable the long-term maintenance of cellular co-cultures in vitro to reconstitute in vivo tissue-level microenvironments, bridging the gap between traditional cell cultures and animal models. Several reviews on microfluidics for prostate cancer studies have been published focusing on technology advancement and disease progression. As metastatic castration-resistant prostate cancer remains a clinically challenging late-stage cancer, with no curative treatments, we expanded this review to cover recent microfluidic applications related to prostate cancer research. The review includes discussions of the roles of microfluidics in modeling the human prostate, prostate cancer initiation and development, as well as prostate cancer detection and therapy, highlighting potentially major contributions of microfluidics in the continuous march toward eradicating prostate cancer.

Revisiting HER2 in Prostate Cancer from an Inclusive Perspective: From Biomarkers to Omics

Human epidermal growth factor receptor 2 (HER2) is a major driver of disease progression, treatment resistance, and worse survival for patients with various types of cancers, including prostate cancer. However, key bench studies and clinical trials have failed to evaluate the role of HER2 in prostate cancer using racially diverse experimental designs and protocols. This lack of diversity represents what has been the status quo of cancer research in the United States for decades. In the case of prostate cancer, homogenic study designs are problematic as Black men are much more likely to be diagnosed and die from aggressive and incurable forms of the disease. Therefore, the strategic inclusion of biospecimens collected from Black patients as well as the recruitment and enrollment of Black men into prostate cancer clinical trials is necessary to comprehensively evaluate genetic and molecular factors that contribute to variable outcomes in this high-risk population. Additionally, a higher prevalence of HER2 expression in Black men was recently reported in a small cohort of prostate cancer patients and may contribute to worsened prognosis. In this review, we carefully consider the role of HER2 in prostate cancer while, for the first time, taking into account the influences of race and genetic ancestry.

Contemporary Update on Clinical and Experimental Prostate Cancer Biomarkers: A Multi-Omics-Focused Approach to Detection and Risk Stratification

Prostate cancer remains a significant health challenge, being the most prevalent non-cutaneous cancer in men worldwide. This review discusses the critical advancements in biomarker discovery using single-omics and multi-omics approaches. Multi-omics, integrating genomic, transcriptomic, proteomic, metabolomic, and epigenomic data, offers a comprehensive understanding of the molecular heterogeneity of prostate cancer, leading to the identification of novel biomarkers and therapeutic targets. This holistic approach not only enhances the specificity and sensitivity of prostate cancer detection but also supports the development of personalized treatment strategies. Key studies highlighted include the identification of novel genes, genetic mutations, peptides, metabolites, and potential biomarkers through multi-omics analyses, which have shown promise in improving prostate cancer management. The integration of multi-omics in clinical practice can potentially revolutionize prostate cancer prognosis and treatment, paving the way for precision medicine. This review underscores the importance of continued research and the application of multi-omics to overcome current challenges in prostate cancer diagnosis and therapy.

Redefining prostate cancer risk stratification: a pioneering strategy to estimate outcome based on Ki67 immunoscoring

Accurate prostate cancer (PCa) patient diagnosis and risk assessment are key to ensure the best outcome. Currently, low- and favorable intermediate-risk PCa patients may be offered AS due to the indolent nature of the disease. Nonetheless, deciding between active surveillance and curative-intent treatment remains an intricate task, as a subset of these patients may eventually progress, enduring poorer prognosis. Herein, we sought to construct risk calculators based on cancer biomarkers, enabling more accurate discrimination among patients which may benefit from active interventions.Ki67 immunoscore, GSTP1 and KLF8 promoter methylation levels (me) were assessed in PCa tissues. Study endpoints included overall and biochemical recurrence-free (BCR) survival. Combination with relevant clinicopathological parameters allowed for construction of graphical calculating tools (nomograms).Higher Ki67 index correlated with worse BCR-free survival, whereas higher KLF8me levels were associated with improved overall survival, especially in patients with lower-grade tumors. GSTP1me levels had no prognostic value. Among prognostic models tested, a BCR-risk calculator - ProstARK (including Ki67 and clinicopathologic parameters) - disclosed 79.17% specificity, 66.67% sensitivity, 55% positive predictive value, 86% negative predictive value, and 75.76% accuracy. Similar results were found using an independent PCa biopsy cohort, validating its prognostication ability.Combining clinicopathologic features and Ki67 index into a risk calculator enables easy and accurate implementation of a novel PCa prognostication tool. This nomogram may be useful for a more accurate selection of patients for active surveillance protocols. Nonetheless, validation in a larger, multicentric, set of diagnostic PCa biopsies is mandatory for further confirmation of these results.

Induced pluripotent stem cell models as a tool to investigate and test fluid biomarkers in Alzheimer's disease and frontotemporal dementia

Neurodegenerative diseases are increasing in prevalence and comprise a large socioeconomic burden on patients and their caretakers. The need for effective therapies and avenues for disease prevention and monitoring is of paramount importance. Fluid biomarkers for neurodegenerative diseases have gained a variety of uses, including informing participant selection for clinical trials, lending confidence to clinical diagnosis and disease staging, determining prognosis, and monitoring therapeutic response. Their role is expected to grow as disease-modifying therapies start to be available to a broader range of patients and as prevention strategies become established. Many of the underlying molecular mechanisms of currently used biomarkers are incompletely understood. Animal models and in vitro systems using cell lines have been extensively employed but face important translatability limitations. Induced pluripotent stem cell (iPSC) technology, where a theoretically unlimited range of cell types can be reprogrammed from peripheral cells sampled from patients or healthy individuals, has gained prominence over the last decade. It is a promising avenue to study physiological and pathological biomarker function and response to experimental therapeutics. Such systems are amenable to high-throughput drug screening or multiomics readouts such as transcriptomics, lipidomics, and proteomics for biomarker discovery, investigation, and validation. The present review describes the current state of biomarkers in the clinical context of neurodegenerative diseases, with a focus on Alzheimer's disease and frontotemporal dementia. We include a discussion of how iPSC models have been used to investigate and test biomarkers such as amyloid-β, phosphorylated tau, neurofilament light chain or complement proteins, and even nominate novel biomarkers. We discuss the limitations of current iPSC methods, mentioning alternatives such as coculture systems and three-dimensional organoids which address some of these concerns. Finally, we propose exciting prospects for stem cell transplantation paradigms using animal models as a preclinical tool to study biomarkers in the in vivo context.

Prognostic value of 17-Gene genomic prostate score in patients with clinically localized prostate cancer: a meta-analysis

BACKGROUND

The 17-gene Genomic Prostate Score (GPS) test has been clinically employed to predict adverse prognosis in prostate cancer. In this meta-analysis, we aimed to evaluate the prognostic value of the 17-gene GPS in patients with prostate cancer.

METHODS

Potentially relevant studies were obtained by searching PubMed, Web of Science, Embase databases from their inception to December 1, 2023. Studies were considered eligible if they evaluated the association of the 17-gene GPS with distant metastases, biochemical recurrence, or prostate cancer-specific mortality (PCSM) in prostate cancer patients. To estimate the prognostic value, we pooled the adjusted hazard ratio (HR) with 95% confidence intervals (CI) for the high versus low GPS group or per 20-unit increase in GPS.

RESULTS

Seven cohort studies that reported on 8 articles comprising 1,962 patients satisfied the eligibility criteria. Meta-analysis showed that per 20-unit increase in GPS was significantly associated with distant metastases (HR 2.99; 95% CI 1.97-4.53), biochemical recurrence (HR 2.18; 95% CI 1.64-2.89), and PCSM (HR 3.14; 95% CI 1.86-5.30). Moreover, patients with high GPS (> 40 points) had an increased risk of distant metastases (HR 5.22; 95% CI 3.72-7.31), biochemical recurrence (HR 4.41; 95% CI 2.29-8.49), and PCSM (HR 3.81; 95% CI 1.74-8.33) than those with low GPS (≤ 40 points).

CONCLUSIONS

A higher 17-gene GPS significantly predicts distant metastases, biochemical recurrence, and PCSM in men with clinically localized prostate cancer. However, large-scale multicenter prospective studies are necessary to further validate these findings.

Biomarkers for Pre-Treatment Risk Stratification of Prostate Cancer Patients: A Systematic Review

BACKGROUND

Prostate cancer (PCa) is one of the most frequently occurring malignancies. Although most cases are not life-threatening, approximately 20% endure an unfavorable outcome. PSA-based screening reduced mortality but at the cost of an increased overdiagnosis/overtreatment of low-risk (lrPCa) and favorable intermediate-risk (firPCa) PCa. PCa risk-groups are usually identified based on serum Prostate-Specific Antigen (PSA), the Gleason score, and clinical T stage, which have consistent although variable specificity or subjectivity. Thus, more effective and specific tools for risk assessment are needed, ideally making use of minimally invasive methods such as liquid biopsies. In this systematic review we assessed the clinical potential and analytical performance of liquid biopsy-based biomarkers for pre-treatment risk stratification of PCa patients.

METHODS

Studies that assessed PCa pre-treatment risk were retrieved from PubMed, Scopus, and MedLine. PCa risk biomarkers were analyzed, and the studies' quality was assessed using the QUADAS-2 tool.

RESULTS

The final analysis comprised 24 full-text articles, in which case-control studies predominated, mostly reporting urine-based biomarkers (54.2%) and biomarker quantification by qPCR (41.7%). Categorization into risk groups was heterogeneous, predominantly making use of the Gleason score.

CONCLUSION

This systematic review unveils the substantial clinical promise of using circulating biomarkers in assessing the risk for prostate cancer patients. However, the standardization of groups, categories, and biomarker validation are mandatory before this technique can be implemented. Circulating biomarkers might represent a viable alternative to currently available tools, obviating the need for tissue biopsies, and allowing for faster and more cost-effective testing, with superior analytical performance, specificity, and reproducibility.

Association Between Pretreatment Blood 25-Hydroxyvitamin D Level and Survival Outcomes in Patients With Clinically Localized Prostate Cancer: An Updated Meta-Analysis

Studies on the prognostic value of the blood 25-hydroxyvitamin D level have yielded controversial results in prostate cancer (PCa) patients. This updated meta-analysis aimed to evaluate the association between pretreatment 25-hydroxyvitamin D level with survival outcomes among patients with clinically localized PCa. PubMed, Web of Science, and Embase databases were searched to identify studies evaluating the association of pretreatment 25-hydroxyvitamin D level with PCSM and all-cause mortality among clinically localized PCa patients. Ten cohort studies with 10,394 patients were identified. The meta-analysis revealed that PCa patients with the lowest 25-hydroxyvitamin D levels had an increased risk of PCSM (adjusted hazard ratio [HR] 1.52; 95% confidence interval [CI] 1.26-1.83; p < 0.001) and all-cause mortality (adjusted HR 1.31; 95% CI 1.00-1.90; p = 0.047) compared to those with higher reference 25-hydroxyvitamin D level. Subgroup analyses based on different sample sizes, follow-up duration, and adjusted times of blood draw also exhibited a significant association of vitamin D deficiency with the risk of PCSM. Lower pretreatment level of 25-hydroxyvitamin D may be an independent predictor of reduced survival in patients with clinically localized PCa. Measuring the pretreatment blood 25-hydroxyvitamin D level can provide valuable information for risk stratification of survival outcomes in these patients.

Based on PI-RADS v2.1 combining PHI and ADC values to guide prostate biopsy in patients with PSA 4-20 ng/mL

PURPOSE

The study aimed to investigate the diagnostic accuracy of prostate health index (PHI) and apparent diffusion coefficient (ADC) values in predicting prostate cancer (PCa) and construct a nomogram for the prediction of PCa and clinically significant PCa (CSPCa) in Prostate Imaging-Reporting and Data System (PI-RADS) three lesions cohort.

METHODS

This study prospectively enrolled 301 patients who underwent multiparametric magnetic resonance (mpMRI) and were scheduled for prostate biopsy. The receiver operating characteristic curve (ROC) was performed to estimate the diagnostic accuracy of each predictor. Univariable and multivariable logistic regression analysis was conducted to ascertain hidden risk factors and constructed nomograms in PI-RADS three lesions cohort.

RESULTS

In the whole cohort, the area under the ROC curve (AUC) of PHI is relatively high, which is 0.779. As radiographic parameters, the AUC of PI-RADS and ADC values was 0.702 and 0.756, respectively. The utilization of PHI and ADC values either individually or in combination significantly improved the diagnostic accuracy of the basic model. In PI-RADS three lesions cohort, the AUC for PCa was 0.817 in the training cohort and 0.904 in the validation cohort. The AUC for CSPCa was 0.856 in the training cohort and 0.871 in the validation cohort. When applying the nomogram for predicting PCa, 50.0% of biopsies could be saved, supplemented by 6.9% of CSPCa being missed.

CONCLUSION

PHI and ADC values can be used as predictors of CSPCa. The nomogram included PHI, ADC values and other clinical predictors demonstrated an enhanced capability in detecting PCa and CSPCa within PI-RADS three lesions cohort.

Prostate cancer screening in African American men: a review of the evidence

BACKGROUND

Prostate cancer is the most diagnosed cancer in African American men, yet prostate cancer screening regimens in this group are poorly guided by existing evidence, given underrepresentation of African American men in prostate cancer screening trials. It is critical to optimize prostate cancer screening and early detection in this high-risk group because underdiagnosis may lead to later-stage cancers at diagnosis and higher mortality while overdiagnosis may lead to unnecessary treatment.

METHODS

We performed a review of the literature related to prostate cancer screening and early detection specific to African American men to summarize the existing evidence available to guide health-care practice.

RESULTS

Limited evidence from observational and modeling studies suggests that African American men should be screened for prostate cancer. Consideration should be given to initiating screening of African American men at younger ages (eg, 45-50 years) and at more frequent intervals relative to other racial groups in the United States. Screening intervals can be optimized by using a baseline prostate-specific antigen measurement in midlife. Finally, no evidence has indicated that African American men would benefit from screening beyond 75 years of age; in fact, this group may experience higher rates of overdiagnosis at older ages.

CONCLUSIONS

The evidence base for prostate cancer screening in African American men is limited by the lack of large, randomized studies. Our literature search supported the need for African American men to be screened for prostate cancer, for initiating screening at younger ages (45-50 years), and perhaps screening at more frequent intervals relative to men of other racial groups in the United States.

miRNA Expression Patterns in Early- and Late-Stage Prostate Cancer Patients: High-Throughput Analysis

Prostate cancer (PCa) is one of the most common types of cancer among men. To date, there have been no specific markers identified for the diagnosis and prognosis or response to treatment of this disease. Thus, there is an urgent need for promising markers, which may be fulfilled by small non-coding RNAs known as microRNAs (miRNAs). Therefore, the present study aimed to investigate the miRNA profile in tissue samples obtained from patients with PCa using microarrays, followed by reverse transcriptase quantitative PCRs (RT-qPCRs). In the discovery phase, 754 miRNAs were screened in tissues obtained from patients (n = 46) with PCa in early and late stages. Expression levels of miRNA-324-3p, miRNA-429, miRNA-570, and miRNA-616 were found to be downregulated, and miRNA-423-5p expression was upregulated in patients with early-stage cancer compared to the late-stage ones. These five miRNAs were further validated in an independent cohort of samples (n = 39) collected from patients with PCa using RT-qPCR-based assays. MiRNA-324-3p, miRNA-429, miRNA-570, and miRNA-616 expression levels remained significantly downregulated in early-stage cancer tissues compared to late-stage tissues. Remarkably, for a combination of three miRNAs, PSA levels and Gleason scores were able to discriminate between patients with early-stage PCa and late-stage PCa, with an AUC of 95%, a sensitivity of 86%, and a specificity close to 94%. Thus, the data obtained in this study suggest a possible involvement of the identified miRNAs in the pathogenesis of PCa, and they may also have the potential to be developed into diagnostic and prognostic tools for PCa. However, further studies with a larger cohort are needed.

Role of radiomic analysis of [18F]fluoromethylcholine PET/CT in predicting biochemical recurrence in a cohort of intermediate and high risk prostate cancer patients at initial staging

AIM

To study the feasibility of radiomic analysis of baseline [18F]fluoromethylcholine positron emission tomography/computed tomography (PET/CT) for the prediction of biochemical recurrence (BCR) in a cohort of intermediate and high-risk prostate cancer (PCa) patients.

MATERIAL AND METHODS

Seventy-four patients were prospectively collected. We analyzed three prostate gland (PG) segmentations (i.e., PGwhole: whole PG; PG41%: prostate having standardized uptake value - SUV > 0.41*SUVmax; PG2.5: prostate having SUV > 2.5) together with three SUV discretization steps (i.e., 0.2, 0.4, and 0.6). For each segmentation/discretization step, we trained a logistic regression model to predict BCR using radiomic and/or clinical features.

RESULTS

The median baseline prostate-specific antigen was 11 ng/mL, the Gleason score was > 7 for 54% of patients, and the clinical stage was T1/T2 for 89% and T3 for 9% of patients. The baseline clinical model achieved an area under the receiver operating characteristic curve (AUC) of 0.73. Performances improved when clinical data were combined with radiomic features, in particular for PG2.5 and 0.4 discretization, for which the median test AUC was 0.78.

CONCLUSION

Radiomics reinforces clinical parameters in predicting BCR in intermediate and high-risk PCa patients. These first data strongly encourage further investigations on the use of radiomic analysis to identify patients at risk of BCR.

CLINICAL RELEVANCE STATEMENT

The application of AI combined with radiomic analysis of [18F]fluoromethylcholine PET/CT images has proven to be a promising tool to stratify patients with intermediate or high-risk PCa in order to predict biochemical recurrence and tailor the best treatment options.

KEY POINTS

• Stratification of patients with intermediate and high-risk prostate cancer at risk of biochemical recurrence before initial treatment would help determine the optimal curative strategy. • Artificial intelligence combined with radiomic analysis of [18F]fluorocholine PET/CT images allows prediction of biochemical recurrence, especially when radiomic features are complemented with patients' clinical information (highest median AUC of 0.78). • Radiomics reinforces the information of conventional clinical parameters (i.e., Gleason score and initial prostate-specific antigen level) in predicting biochemical recurrence.

Active surveillance should be considered for select men with Grade Group 2 prostate cancer

BACKGROUND

Treatment decisions for localized prostate cancer must balance patient preferences, oncologic risk, and preservation of sexual, urinary and bowel function. While Active Surveillance (AS) is the recommended option for men with Grade Group 1 (Gleason Score 3 + 3 = 6) prostate cancer without other intermediate-risk features, men with Grade Group 2 (Gleason Score 3 + 4 = 7) are typically recommended active treatment. For select patients, AS can be a possible initial management strategy for men with Grade Group 2. Herein, we review current urology guidelines and the urologic literature regarding recommendations and evidence for AS for this patient group.

MAIN BODY

AS benefits men with prostate cancer by maintaining their current quality of life and avoiding treatment side effects. AS protocols with close follow up always allow for an option to change course and pursue curative treatment. All the major guideline organizations now include Grade Group 2 disease with slightly differing definitions of eligibility based on risk using prostate-specific antigen (PSA) level, Gleason score, clinical stage, and other factors. Selected men with Grade Group 2 on AS have similar rates of deferred treatment and metastasis to men with Grade Group 1 on AS. There is a growing body of evidence from randomized controlled trials, large observational (prospective and retrospective) cohorts that confirm the oncologic safety of AS for these men. While some men will inevitably conclude AS at some point due to clinical reclassification with biopsy or imaging, some men may be able to stay on AS until transition to watchful waiting (WW). Magnetic resonance imaging is an important tool to confirm AS eligibility, to monitor progression and guide prostate biopsy.

CONCLUSION

AS is a viable initial management option for well-informed and select men with Grade Group 2 prostate cancer, low volume of pattern 4, and no other adverse clinicopathologic findings following a well-defined monitoring protocol. In the modern era of AS, urologists have tools at their disposal to better stage patients at initial diagnosis, risk stratify patients, and gain information on the biologic potential of a patient's prostate cancer.

Molecular Insight into Prostate Cancer: Preventive Role of Selective Bioactive Molecules

Prostate cancer (CaP) is one of the most prevalent male malignancies, accounting for a considerable number of annual mortalities. However, the prompt identification of early-stage CaP often faces delays due to diverse factors, including socioeconomic inequalities. The androgen receptor (AR), in conjunction with various other signaling pathways, exerts a central influence on the genesis, progression, and metastasis of CaP, with androgen deprivation therapy (ADT) serving as the primary therapeutic strategy. Therapeutic modalities encompassing surgery, chemotherapy, hormonal intervention, and radiotherapy have been formulated for addressing early and metastatic CaP. Nonetheless, the heterogeneous tumor microenvironment frequently triggers the activation of signaling pathways, culminating in the emergence of chemoresistance, an aspect to which cancer stem cells (CSCs) notably contribute. Phytochemicals emerge as reservoirs of bioactive agents conferring manifold advantages against human morbidity. Several of these phytochemicals demonstrate potential chemoprotective and chemosensitizing properties against CaP, with selectivity exhibited towards malignant cells while sparing their normal counterparts. In this context, the present review aims to elucidate the intricate molecular underpinnings associated with metastatic CaP development and the acquisition of chemoresistance. Moreover, the contributions of phytochemicals to ameliorating CaP initiation, progression, and chemoresistance are also discussed.

Exosome Analysis in Prostate Cancer: How They Can Improve Biomarkers' Performance

Exosomes are extracellular nanovesicles (EV), that is, carriers of different biomolecules such as lipids, proteins, nucleic acids. Their composition and the fact that their release dramatically increases in cases of tumorigenesis open up different scenarios on their possible application to research into new biomarkers. The first purpose of the present review was to specifically analyze and compare different methodologies available for the use of exosomes in prostate cancer (PC). The most widely applied methodologies include ultracentrifugation techniques, size-based techniques, immunoaffinity capture-based techniques (mainly ELISA), and precipitation. To optimize the acquisition of exosomes from the reference sample, more techniques can be applied in sequence for a single extraction, thereby determining an increase in labor time and costs. The second purpose was to describe clinical results obtained with the analysis of PSA-expressing exosomes in PC; this provides an incredibly accurate method of discriminating between healthy patients and those with prostate disease. Specifically, the IC-ELISA alone method achieved 98.57% sensitivity and 80.28% specificity in discriminating prostate cancer (PC) from benign prostatic hyperplasia (BPH). An immunocapture-based ELISA assay was performed to quantify and characterize carbonic anhydrase (CA) IX expression in exosomes. The results revealed that CA IX positive exosomes were 25-fold higher in plasma samples from PC patients than in those from healthy controls. The analysis of PC-linked exosomes represents a promising diagnostic model that can effectively distinguish patients with PC from those with non-malignant prostatic disease. However, the use of exosome analysis in clinical practice is currently limited by several issues, including a lack of standardization in the analytical process and high costs, which are still too high for large-scale use.

Deregulated microRNAs Involved in Prostate Cancer Aggressiveness and Treatment Resistance Mechanisms

Prostate cancer (PCa) is the most frequently diagnosed cancer and the second leading cause of cancer deaths among American men. Complex genetic and epigenetic mechanisms are involved in the development and progression of PCa. MicroRNAs (miRNAs) are short noncoding RNAs that regulate protein expression at the post-transcriptional level by targeting mRNAs for degradation or inhibiting protein translation. In the past two decades, the field of miRNA research has rapidly expanded, and emerging evidence has revealed miRNA dysfunction to be an important epigenetic mechanism underlying a wide range of diseases, including cancers. This review article focuses on understanding the functional roles and molecular mechanisms of deregulated miRNAs in PCa aggressiveness and drug resistance based on the existing literature. Specifically, the miRNAs differentially expressed (upregulated or downregulated) in PCa vs. normal tissues, advanced vs. low-grade PCa, and treatment-responsive vs. non-responsive PCa are discussed. In particular, the oncogenic and tumor-suppressive miRNAs involved in the regulation of (1) the synthesis of the androgen receptor (AR) and its AR-V7 splice variant, (2) PTEN expression and PTEN-mediated signaling, (3) RNA splicing mechanisms, (4) chemo- and hormone-therapy resistance, and (5) racial disparities in PCa are discussed and summarized. We further provide an overview of the current advances and challenges of miRNA-based biomarkers and therapeutics in clinical practice for PCa diagnosis/prognosis and treatment.

Association of Statin Use with the Risk of Incident Prostate Cancer: A Meta-Analysis and Systematic Review

Background

With the growth and aging of population, the incidence of prostate cancer will increase year by year, which is bound to bring greater economic burden to the society. There has been greater interest in the anticancer effects of statin in recent years. It is controversial whether statin use is associated with the risk of prostate cancer (PCa). Thus, we conducted a meta-analysis and systematic review to explore the effects of statin use and their duration and cumulative dose on the overall incidence of PCa.

Method

The study was conducted according to the latest guidelines for PRISMA 2020. We searched PubMed and other databases for studies about the association of statin use with the risk of incident prostate cancer between January 1, 1990, and April 11, 2022. Two independent researchers extracted data and evaluated the quality of the studies. R x64 4.1.2 and random-effects model were used for data statistics. Relative risk (RR) and odds ratio (OR) effective values with a 95% confidence interval (95% CI) were used to assess the main results.

Results

The results of 6 RCT and 26 cohort studies showed that statins did not significantly associate with the incidence of PCa (RR = 0.94, 95% CI: 0.82-1.08). The similar results were obtained from 9 case-control studies (OR = 1.03, 95% CI: 0.99-1.07). However, statins were associated with a lower risk of Pca (RR = 0.44, 95% CI: 0.28-0.70) when the cumulative defined daily dose (cDDD) was high. Using statins for more than five years could be associated with a reduced incidence of Pca (RR = 0.47, 95% CI: 0.23-0.97). There was a significant heterogeneity in these studies (RCT and cohort study: I ² = 98%, P < 0.01; case-control study: I ² = 72%, P < 0.01).

Conclusion

We concluded that statins had a neutral association with the overall risk of PCa. High cDDD and long duration were associated with a lower risk of PCa.