The Prostate

BackgroundHomozygous biallelic inactivation of CDKN1B is thought to be rare in cancer. Herein we evaluate the prevalence of intratumoral (subclonal) complete p27 protein loss (IPPL) in primary prostate cancer. Experimental DesignWe used immunohistochemistry (IHC) for p27 in a large cohort of whole tissue sections from radical prostatectomy (n=412) and metastases from self-identified African American (AA) and European American (EA) individuals. IPPL was evaluated alongside CDKN1B mRNA in-situ hybridization and next generation sequencing of laser captured cancer regions. Cox proportional hazards analyses assessed the association of IPPL with biochemical recurrence and development of metastases after radical prostatectomy. ResultsIPPL was detected in 18.1% of AA versus 12.2% of EA cases and was tightly correlated with CDKN1B mRNA loss and biallelic genomic loss. IPPL was associated with [≥]pT3 pathologic stage and pN1 disease, however these associations were only significant among AA participants. IPPL was further associated in both univariate and multivariate analyses with the development of biochemical recurrence and metastasis after primary treatment, specifically in AA individuals. The prevalence of p27 genomic alterations in metastatic disease is higher than that of primary prostate cancer in publicly available datasets as well as our analysis of autopsy cases via IHC, indicating that complete p27 loss may be selected for in metastatic disease. ConclusionsSubclonal biallelic loss of CDKN1B resulting in complete p27 protein loss is one of the most commonly occurring biallelic tumor suppressor genomic alterations in primary prostate cancer, and could contribute to worse prostate cancer outcomes, specifically in AA males.

BackgroundIdentifying metabolites associated with prostate cancer (PC) aggressiveness may elucidate mechanisms underlying disease severity. Doing so for plasma and formalin-fixed, paraffin-embedded (FFPE) tissue could accelerate discovery. In this cross-sectional pilot study, we generated hypotheses for further exploration by assessing associations between plasma metabolites and Gleason score in individuals with PC and evaluating correlations between plasma and FFPE metabolite levels. MethodsWe examined plasma and FFPE samples from 10 individuals with Gleason score 7 (six 3+4, four 4+3) and nine individuals with Gleason score 9 (six 4+5, three 5+4) tumors from a convenience sample of 19 men with PC. We measured the relative abundance of polar metabolites at the time of radical prostatectomy. We used linear models of log2 fold changes to examine plasma metabolite levels relative to pathologic tumor grade. Relationships among metabolite levels measured in plasma and FFPE tumor tissue within individuals across metabolites were examined using Pearson correlations. ResultsAmong 18 plasma metabolites selected a priori because of prior associations with PC aggressiveness, serine (p=0.0051) and ornithine (p=0.036) levels were higher in individuals with Gleason 9 than Gleason 7 PC. After multiple testing correction, however, no associations were statistically significant. The median correlation between levels in plasma and FFPE tumor tissue was 0.45 (range: 0.40-0.53) for the 94 metabolites measured in both biospecimens. ConclusionsPlasma serine and ornithine demonstrated the largest differences between individuals with Gleason 7 and Gleason 9 PC. Metabolite levels in FFPE prostate tissue samples were moderately correlated with plasma levels. Future studies in larger samples are needed to further explore the hypotheses generated by this study.

Background and ObjectiveRisk stratification in localized prostate cancer relies primarily on Grade group (GG). In GG2-4 disease, risk assignment depends on the proportions of pattern 3 and pattern 4. We hypothesized that total pattern 4 length on biopsy would better predict oncologic outcome than GG, percent pattern 4, and multivariable models ("nomograms") based on clinical variables. MethodsWe identified 2499 patients with GG2-4 prostate cancer on biopsy who underwent radical prostatectomy. Discrimination for predictors was calculated for adverse pathologic stage (seminal vesicle invasion or lymph node invasion) and biochemical recurrence (BCR). Key Findings and LimitationsTotal pattern 4 length for the case demonstrated the highest discrimination for adverse pathologic stage in comparison with GG (AUC 0.779 vs 0.658; p<0.0001), percent pattern 4 (0.719), and a model including prostate-specific antigen level, clinical stage, GG, PI-RADS score, and number of positive cores (0.762). Results were similar for BCR, with total pattern 4 length outperforming GG (C-index 0.716 vs 0.662), percent pattern 4 (0.695), and the clinical model (0.699). Neither mm of pattern 3 nor the clinical model added discrimination to total mm of pattern 4. Conclusions and Clinical ImplicationsTotal length of Gleason pattern 4 on biopsy best predicts oncologic outcome in GG2-4 prostate cancer. Other common clinicopathologic variables do not further aid discrimination. Further research is warranted to determine the optimal method for quantifying pattern 4 before incorporation into risk stratification algorithms. O_LIWhat does the study add?: Patients with Grade group 2-4 prostate cancer constitute both the largest group and the one in which treatment decision-making is most difficult. For such patients, total length of Gleason pattern 4 on biopsy predicted oncologic outcomes better than Grade group or multivariable models including the standard predictors of stage, grade, PSA, PI-RADS and number of positive cores. Neither mm of pattern 3 nor the standard predictors add discrimination once total length of pattern 4 is known. C_LIO_LIPatient Summary: Treatment decisions in prostate cancer are often determined by the ratio of pattern 4 to pattern 3 disease. We showed that, in GG2-4 disease, using the total amount of pattern 4 for the case better predicts risk and therefore provides a better basis for treatment decisions. C_LI Take Home MessageIn Grade group 2-4 prostate cancer, total Gleason pattern 4 length for the case is a stronger predictor of adverse pathologic stage and biochemical recurrence than Grade group and other standard clinical variables. Further research is warranted to determine the optimal method for quantifying pattern 4 before incorporation into risk stratification algorithms.

BackgroundNeuroendocrine Prostate Cancer (NEPC) is an incurable malignancy, originating from the trans-differentiation of prostate adenocarcinoma (PRAD). Compared to PRAD, NEPC shows over-activation of Polycomb Repressive complex-1(PRC1) and-2 (PRC2), which are multiprotein epigenetic writers that drive cancer progression via tumour suppressor gene silencing. Tazemetostat is a PRC2 inhibitor approved for the treatment of sarcomas and lymphomas. ORIC-944 is a novel EED (Embryonic Ectoderm Development) inhibitor, which is being tested in clinical trials. EED is an attractive target as it functions as a key component of both PRC1 and PRC2. Objective and MethodsWe compared the anticancer effects of tazemetostat and ORIC-944 in NEPC and PRAD cells. Cells were exposed to various concentrations of the two compounds to measure effects on cell viability (IC50) and apoptosis (flow cytometry). PRC2 inhibition was confirmed by measuring histone H3 Lys 27 trimethylation (H3K27me3) via ELISA and Western Blot. RNA Sequencing and pathway analysis was conducted to study modes of actions of tazemetostat vs ORIC-944. ResultsUnlike tazemetostat, ORIC-944 causes dose-dependent growth inhibition in both NEPC and PRAD cells. In this context, EED targeting achieves IC50 values that are comparable to those of compounds used for the clinical treatment of advanced prostate cancer. Moreover, ORIC-944 (but not tazemetostat) causes significant apoptosis in NEPC cells. Both tazemetostat and ORIC-944 reduce H3K27me3. Mechanistically, both compounds reactivate the expression of known PRC2 targets, such as genes that control neural differentiation. However, the EED inhibitor also reactivates PRC1 targets, including pro-apoptotic and anti-proliferating genes (e.g. metallothionines). This evidence suggests that EED inhibition is a promising therapeutic strategy for NEPC.

BackgroundCyclin-dependent kinases drive the progression through the cell cycle and thereby form classical targets for cancer therapy. In prostate cancer (PC), the first line of therapy typically targets androgen receptor (AR), but it frequently leads to development of incurable form of the disease, castration-resistant PC (CRPC). Here, we sought to understand if CRPC cells are selectively addicted to a specific cell cycle kinase. MethodsWe used PC and CRPC patient data to evaluate transcriptional changes and modeled the responses in vitro using multiple models of PC, CRPC and normal cells. Development of a CDK2 inhibitor-resistant CRPC cell line, and a compound screen were used to identify chronic and acute vulnerabilities to augment the efficacy of our candidate therapy in multiple PC, CRPC and also normal cells, to assure selectivity. ResultsWe show that the emergence of CRPC is associated with significant upregulation of cyclins that positively regulate cyclin-dependent kinase 2 (CDK2) and downregulation of CDK4 cyclins. Accordingly, CDK2-specific inhibitors and its knock down efficiently reduce proliferation of PC and CRPC cells. CDK2 inhibitor-resistant CRPC model displayed transcriptional rewiring of cell cycle regulators, characterized by a shift towards CDK4/6-dependency and increased AR-signaling. Combinatorial drug screen discovered both antagonistic and additive combinations, and we show that AR inhibitors selectively augment the efficacy of CDK2 inhibitors against PC and CRPC cells, but the combination is not toxic to normal cells. ConclusionWe discovered that CRPC cells are addicted to high CDK2 activity and show that combination of CDK2 inhibitors with the currently used anti-CRPC therapies selectively augment their efficacy.

ImportanceMetastatic prostate cancer (PCa) incidence has increased in U.S. men, partly due to changes in prostate-specific antigen (PSA) screening recommendations. However, few studies have examined contemporary PSA screening practices in large U.S. healthcare systems. ObjectiveDescribe and examine contemporary PSA testing practices associated with metastatic PCa incidence. DesignCohort study. SettingVeterans Health Administration. ParticipantsVeterans diagnosed with prostate needle biopsy (PNBx) between 2015 and 2023 with follow-up through 2024, excluding those with a history of PCa. ExposuresPSA tests were retrieved from the VA corporate data warehouse and categorized by age at first VA PSA (<50, 50-59, [&ge;]60 years) and by longest interval between consecutive VA PSA tests in the 5 years before PNBx ([&le;]24 , >24 months). Clinical, laboratory, pathological, demographic, and Census Block Group-level socioeconomic status data were obtained from the VA Multi-OMICS Analysis Platform for Prostate Cancer (VA-MAPP) database. Main Outcomes and MeasuresMultivariable Cox models estimated hazard ratios (HR) from time of first VA PSA to first PNBx, evaluated risk of metastatic (regional or distant) versus localized PCa, or benign diagnosis, adjusted for sociodemographic and clinical covariates. Data were analyzed between July 1, 2023 and November 6, 2025. ResultsThere were 103,067 participants of whom 20% were <50 years old at first PSA, 31% non-Hispanic Black, 57% non-Hispanic White, and 13% other racial and ethnic groups. Of these, 22% had first PSA value [&le;]1, 51% had a screening interval [&le;]24 months, and 4% were diagnosed with metastatic PCa at time of PNBx. Compared to men aged <50 years at first PSA, those 50-59 (aHR 1.08, 95% CI: 1.06-1.11) and [&ge;]60 years (aHR 1.79, 95% CI: 1.74-1.84) had higher metastatic PCa. Men with longer screening intervals had higher metastatic PCa (aHR 1.09, 95% CI: 1.07-1.11). Men aged <50 years with shorter screening intervals had lower metastatic PCa (aHR: 0.10, 95% CI: 0.09-0.12) compared to men aged [&ge;]60 years with longer screening intervals. Conclusions and RelevanceFew male veterans were observed to have the most favorable combinations of age, PSA value, and PSA screening interval in relation to metastatic PCa, suggesting potential for further screening optimization.

IntroductionBRCA1/2 alterations are increasingly recognized as biologically and clinically relevant features in prostate cancer, yet the prognostic and therapeutic significance of zygosity status remains uncertain. Understanding differences between monoallelic and biallelic inactivation may refine risk stratification and guide therapeutic decision-making. Materials and MethodsA retrospective, desk-based observational analysis was performed using publicly accessible datasets from TCGA-PRAD (primary disease) and SU2C/PCF (metastatic disease). BRCA1/2 status was categorized as wild-type, monoallelic, or biallelic based on mutation, copy-number, and loss-of-heterozygosity profiles. Overall survival was evaluated using Kaplan-Meier estimates and Cox models. Systemic therapy outcomes were assessed by treatment class, incorporating exploratory interaction tests. ResultsIn TCGA-PRAD (n=300), OS did not significantly differ by zygosity (global log-rank p=0.45), with median OS of 80.0 months (wild-type), 78.0 months (monoallelic), and 55.0 months (biallelic). In SU2C/PCF (n=200), zygosity stratified outcomes significantly (global log-rank p=0.04): median OS was 22.0 months (wild-type), 14.0 months (monoallelic), and 16.0 months (biallelic). Treatment analyses showed ARSI exposure improved OS in wild-type disease (HR 0.60; 95% CI 0.38-0.95), while interaction testing suggested potential heterogeneity without statistical confirmation (interaction p=0.092). PARP inhibitor exposure showed directionally favorable HRs in wild-type and monoallelic groups but no significant interaction (interaction p=0.757). No therapy class demonstrated consistent effect modification by zygosity. ConclusionBRCA1/2 zygosity shows prognostic relevance in metastatic prostate cancer but not clearly in primary disease. While zygosity did not consistently modify systemic therapy associations in this dataset, findings support zygosity-aware reporting as a practical tool for molecular stratification and future research design.

Here, we examined the consequences of biologically relevant vitamin D deficiency, a known risk factor for aggressive prostate cancer, using ex vivo and in vivo models. Phenotypic and single-cell RNA sequencing of mouse prostate organoids showed that vitamin D deficiency stunted luminal cell differentiation more than androgen deficiency, which is a known driver of prostate development. Mice fed a vitamin D-deficient diet showed significantly altered expression of androgen-responsive genes in their prostate luminal cells, as determined by single-cell RNA sequencing. MDA-PCa-2b human prostate cancer cells, when maintained for 6 months in 1,25-dihydroxyvitamin D, lost the ability to form xenografts, despite normal proliferation in vitro. RNA sequencing showed that these cells also had disruptions in androgen signaling and multiple cancer-related pathways. This study offers new insights and validation of vitamin Ds role in both benign and malignant prostate biology, underscoring its essential hormonal functions and supporting strategies for vitamin D supplementation to reduce prostate cancer risk in vulnerable populations. STATEMENT OF SIGNIFICANCEVitamin D is an essential hormone, however, the non-calcemic consequences of vitamin D deficiency remain poorly defined, despite its high prevalence in the population. This study demonstrates significant biological consequences of vitamin D deficiency on prostate cells at biologically relevant levels in multiple systems.

Reinke crystals are a defining histological feature of human adult Leydig cells, the testosterone producing cells of the testis. These structures are present in the cytoplasm and the nucleus and display quantitative alterations in a variety of physiological and pathological contexts. The functional significance and protein composition of Reinke crystals have remained elusive for over a century. Here, we demonstrate that Reinke crystals are intensely immunoreactive for inosine monophosphate dehydrogenase (IMPDH), and phosphoribosyl pyrophosphate synthetase (PRPS), two key rate-limiting enzymes in the de novo synthesis of purine nucleotides. IMPDH and PRPS are two of several metabolic enzymes that are capable of forming mesoscale filamentous aggregates as a mechanism to regulate enzyme activity. IMPDH is also able to form crystals in cellulo. Our observations link Reinke crystal formation to purine nucleotide metabolism in Leydig cells. We discuss how this novel finding may relate to the unique dependence of Leydig cells on guanyl-based purine nucleotides for testosterone synthesis. The results of this study may have important implications for understanding metabolic contributions to male reproductive disorders as well as offering a novel diagnostic and theranostic tool applicable to Leydig cell neoplasms.

BackgroundNo randomized clinical trial comparing the most established new modalities of treatment for patients with localized prostate cancer has been published, and there is scarce comparative effectiveness research assessing Patient-Reported Outcome Measures (PROMs). Objectiveto compare the impact of active surveillance, robot-assisted radical prostatectomy (RARP), Intensity-modulated radiotherapy (IMRT), and real-time brachytherapy on patients, through PROMs, from pre-treatment to five years after diagnosis of localized prostate cancer. MethodsProspective observational study (ClinicalTrials.gov, NCT05523856) of 566 male patients diagnosed in 2014 to 2021 with clinically localized prostate cancer (50-75 years old; stage cT1 or cT2, N0/Nx and M0/Mx; Gleason [&le;] 6 or 7 (if 3 + 4 with T1c); and PSA [&le;] 10 ng/ml) and followed until 2019-2026. The Expanded Prostate Cancer Index Composite (EPIC-26) measures urinary incontinence, urinary irritative/obstructive symptoms, sexual, bowel and hormonal domains. EPIC-26 was centrally administered via telephone interviews before treatment and then annually after treatment. Generalized estimating equation (GEE) models were constructed with overlap propensity score-based weights and adjusted by age and clinical tumor stage. ResultsWeighted results of adjusted GEE models showed significant declines for sexual health during the 5yr in all treatment groups (ranging from -19.8 to -27.6), but this worsening appeared earlier in those of active treatment (RARP, IMRT and brachytherapy) than in active surveillance. The RARP group presented the greatest deterioration in urinary incontinence (-28.5 vs -11.7 in active surveillance), while the greatest impairment in bowel symptoms was observed in both radiotherapy groups (around -3 vs +0.3 in active surveillance). ConclusionOur findings provide detailed novel evidence, measured over 5 yr, on the long-term impact of disease and treatment on patients with localized prostate cancer. While all treatment groups showed large sexual deterioration overtime, important differences in urinary incontinence (highest after RARP) and bowel symptoms (after IMRT and brachytherapy) persisted. These findings can inform patients during shared decision-making on the alignment between localized prostate cancer treatment choices and their priorities.

The insulin receptor (IR) is markedly overexpressed in both human and mouse prostate cancer, with a significant elevation in the IR-A/IR-B ratio across patient tissues, cell lines, and Hi-Myc mouse prostates. To elucidate the role of IR-B in prostate tumorigenesis, we generated a prostate-specific IR-B knockout (KO) mouse model using Pbsn-Cre-driven recombination. Prostate-restricted loss of IR-B was confirmed at the transcript level and did not affect other tissues. Crossing these mice with Hi-Myc transgenics revealed that IR-B deficiency promotes accelerated progression to invasive adenocarcinoma, characterized by enhanced cellular proliferation and atypical histopathology. Transcriptomic and metabolomic profiling of dorsolateral prostate lobes demonstrated activation of PI3K/AKT and mTOR signaling, along with upregulation of IRS1/2/4 and IGF2. Metabolite analyses indicated elevated fatty acid levels and enhanced lipolysis pathways, implicating metabolic reprogramming in tumor progression. Notably, glucose and lipid metabolism genes, including GLUT1, GLUT12, FASN, and GPR120, were upregulated, accompanied by an increased BCL2/BAX ratio, suggesting apoptosis inhibition. Functional studies further revealed opposing roles of dietary fatty acids: {omega}-3 polyunsaturated fatty acids (EPA, DHA) suppressed prostate cancer cell survival, proliferation, and PI3K/AKT signaling while promoting apoptosis, whereas {omega}-6 fatty acid (arachidonic acid) exerted pro-tumorigenic, anti-apoptotic effects. Collectively, these findings identify IR-B loss as a driver of metabolic and signaling reprogramming that accelerates prostate tumorigenesis, while highlighting {omega}-3 fatty acids as potential modulators counteracting IR-B-deficient prostate cancer progression.

Prostate cancer resembles differentiated secretory luminal cells and shows cell-autonomous dependence on androgen receptor (AR) signaling, yet normal luminal cells are often considered dependent on paracrine stromal AR signaling. To resolve this, we conditionally deleted Ar in luminal acinar cells in vivo. Ar-deleted luminal cells persisted short-term, in contrast to the rapid regression observed after castration, but were impaired in regeneration and progressively lost. Their depletion was accompanied by replacement through basal-to-luminal differentiation of AR intact basal cells. Transcriptomic and chromatin profiling showed cell-autonomous suppression of the secretory program with induction of stemness, inflammatory, and epithelial-to-mesenchymal transition signatures after AR loss. Mechanistically, the MAP kinase pathway and downstream AP-1 transcription factors were activated and functionally validated, and MAP kinase inhibition selectively depleted AR-deleted luminal cells, indicating a compensatory survival pathway. These findings define intrinsic roles for luminal AR in maintaining differentiation, restraining plasticity, and sustaining regeneration and homeostatic turnover, providing a mechanistic basis for AR dependence in prostate cancer.

Background: Previous recommendations on screening for prostate cancer relied on ongoing trials of screening with prostate-specific antigen (PSA), which may have lacked sufficient follow-up duration to fully examine effects on mortality and overdiagnosis. Findings which consider absolute effects by age and screening intensity, along with newer guidance for assessing evidence certainty, may lead to different interpretations. Adding magnetic resonance imaging (MRI) to PSA-based screening has been raised as a way to reduce false positives (FPs) and overdiagnosis. Methods: We systematically searched MEDLINE, Embase, and Central from 2014 to January 28, 2026, for randomized controlled trials (RCTs) and prospective observational studies of: (i) screening versus no screening and (ii) sequential screening with MRI for those with a positive PSA test versus PSA alone among men not known to be at high risk for prostate cancer. Studies on screening with PSA or digital rectal examination (DRE) published pre-2014 were identified from existing systematic reviews and reference lists. Studies on FPs and complications from biopsies after PSA screening did not require a control group. Paired reviewers screened titles/abstracts (assisted with artificial intelligence) and full texts, assessed risk of bias, and extracted data, by age when available. We pooled data when suitable using random-effects models, investigated heterogeneity, and assessed the certainty of evidence using GRADE with conclusions of effects based on decision thresholds based on absolute effect sizes. Results: Across both questions, we included 15 RCTs (N=856,000; 8 sites of ERSPC considered separate trials) and 8 observational studies (N=56,122). At 20 years, among 1000 men who underwent repeated PSA-based screening every 2-4 years starting from age 55-69 (mean 62), there is likely a reduction in prostate-cancer mortality ([&ge;]2 fewer) and metastatic cancer incidence ([&ge;]6 fewer), at the expense of prostate-cancer overdiagnosis ([&ge;]24 cases) and FPs ([&ge;]150 cases) (all moderate certainty). If screening starts at age 50-54 or age 55, the benefits are probably smaller (e.g., 1 vs. 2 fewer prostate-cancer related deaths) with similar harms. Adding DRE or screening with PSA annually does not add benefit. One round of PSA screening or starting screening later at age 70-74 may not offer any important benefit or harm (low to moderate certainty), and any benefit from screening primarily with DRE was not shown. Compared with PSA alone, sequential screening with PSA followed by MRI reduces FPs ([&ge;]33 fewer) and overdiagnosis (via [&ge;]10 fewer diagnoses of clinically insignificant [e.g., Gleason 6] cancers without impacting detection of clinically significant cancers) (moderate to high certainty), though findings were limited to one round of screening without long-term follow-up or measurement of mortality. Interpretation: This review provides clinicians and other interest holders with anticipated absolute effects by age, and assessments of certainty across critical and important outcomes and with approximately two decades of follow-up. Findings apply to a general population and may differ for specific groups. Results for most critical outcomes, both benefits and harms, exceeded thresholds for clinically important effect sizes, thereby demonstrating the complexity of guideline developers' and patients' decision-making regarding screening trade-offs. Findings about adding MRI for those with a positive PSA test were limited and would require additional consideration of costs, infrastructure, expertise, and equity. Protocol registration: PROSPERO - CRD420250651056.

Few studies with pre-diagnostic samples have estimated associations between circulating metabolites and risk of advanced prostate cancer. We performed untargeted metabolomic profiling of pre-diagnostic blood samples from 212 advanced prostate cancer cases (stage [&ge;]T3b or lethal during follow-up) and 212 matched controls from the Health Professionals Follow-up Study. 243 metabolites were assayed using liquid chromatography-tandem mass spectrometry (Broad Institute) and met quality control standards. We used multivariable conditional logistic regression to generate odds ratios (OR) and 95% confidence intervals (95%CI) for associations between individual metabolites and risk of advanced prostate cancer, and conducted metabolite set enrichment tests to identify metabolite classes enriched in advanced prostate cancer. Subgroup analyses were conducted by body mass index (BMI) and time between blood draw and diagnosis. Levels of 16 lipid species were nominally associated with advanced prostate cancer at p<0.05, though none were statistically significant after multiple testing correction. The strongest signals were for C56:1 triacylglycerol (TAG; OR: 1.34, 95%CI: 1.07-1.67) and C38:4 diacylglycerol (DAG; OR: 1.27, 95%CI: 1.04-1.55). Enrichment analyses revealed six metabolite classes associated with advanced prostate cancer after multiple testing adjustment, the top four of which were DAGs and TAGs: DAGs overall (P=3.4E-07), unsaturated DAGs (P=5.9E-07), unsaturated TAGs (P=2.3E-06), and TAGs overall (P=2.4E-06). 43 metabolites were nominally associated with advanced prostate cancer among individuals with BMI <25 kg/m2; only three demonstrated nominal associations in individuals with BMI [&ge;]25 kg/m2. These findings suggest associations between circulating pre-diagnostic lipid levels and aggressive prostate cancer risk, particularly in lean individuals.

Prostate cancer overdiagnosis is detection of prostate cancer through PSA testing that otherwise would not have been diagnosed within the patients lifetime. It is a major concern to policymakers due to its impact on quality of life. We used long-term followup data from the CAP randomised trial of a one-off screen, and English male competing mortality rates (2021-23), to estimate the impact of age on excess prostate cancer incidence within 15 years ( overdiagnosis) using competing risks methods. In total, 2249 (1.19%) of 189,386 men invited for a PSA test in CAP had cancer detected at the one-off screen. Prostate cancer cumulative incidence at 15 years was 7.08% (95%CI 6.95 to 7.21%) in those invited to screening, compared with 6.94% (95%CI 6.82 to 7.06%) in the control arm; an absolute excess incidence difference of 0.14% (95%CI -0.04% to 0.37%). Excess net incidence to 15 years was 0.14/1.19 = 11.7% (95%CI 0.0% to 26.7%) of cases detected at a single prevalent screen. Accounting for competing mortality, English men diagnosed aged 50 years were projected to have a 16% chance the cancer would not have been detected within 15 years, rising to 32% aged 70 years and 58% aged 80 years. Thus, prostate cancer overdiagnosis rises substantially with age due to competing mortality, and is relatively low for younger men. Accordingly, opportunistic testing policies should be re-examined in settings where they have led to high rates of screening in older men.

PurposeCastration-resistant prostate cancer (CRPC) is characterized by marked clinical heterogeneity and poor long-term survival, underscoring the need for tools that can rapidly and reliably individualize patient risk. While several prognostic models exist, their complexity has limited routine clinical use. Here, we developed and validated PROGRESS (PROstate cancer Global Risk Evaluation and Stratification Score), a simplified prognostic score, derived through machine learning-guided feature selection, to enhance risk stratification and support individualized, risk-informed clinical decision-making. MethodsPROGRESS was developed using baseline data from 2,035 metastatic CRPC patients enrolled in four different phase III trials. An unsupervised machine-learning approach was applied to identify latent patient subgroups with distinct survival outcomes irrespectively of allocated treatment arm, followed by classical multivariable modelling to derive a simple and straight-forward prognostic score based on routinely available objective laboratory variables. External validation was performed in three independent datasets comprising metastatic CRPC patients treated across different therapeutic settings (n=1,239) and non-metastatic CRPC patients managed with standard care (n=660). Overall survival was assessed using Kaplan-Meier and Cox regression analyses. ResultsUnsupervised modelling identified two patient risk subpopulations with significantly different overall survival rates (median 27.4 vs 17.7 months; hazard ratio [HR] 2.20, 95% CI 1.91-2.54; p<.00001). Feature contribution analysis yielded three independent predictors -PSA, ALP, and AST-used to build PROGRESS. In the training cohort, PROGRESS demonstrated strong discrimination (AUC 0.89). Using a prespecified cut-off, patients classified as increased risk had significantly shorter survival than low-risk patients (median 18.3 vs 25.6 months; HR 1.72, 95% CI 1.50-1.97; p<.0001). PROGRESS prognostic performance was consistent across all validation cohorts, including metastatic and non-metastatic disease, with HRs ranging from 1.74 to 3.46 (all p<.0001). ConclusionsBy integrating machine-learning-based pattern discovery with classical statistical modelling, PROGRESS provides a simple, objective, and clinically accessible approach for individual risk stratification in CRPC. Its reliance on three inexpensive, routinely measured laboratory parameters would facilitate practical implementation in clinical settings, enhancing visibility of underlying disease aggressiveness for individual clinical decision-making. PROGRESS could represent a pragmatic first step toward improving patient selection for clinical trials while identifying regulatory meaningful endpoints achievable in a sizeable patient population; further validation in prospective clinical studies and real-world datasets would allow to confirm its clinical utility and generalizability. PROGRESS can be freely accessed for research use only at the following link: https://dev.ai.topazium.com.

While the prostate-specific antigen (PSA) test is a widely used prostate cancer screening tool, its application remains controversial. Opportunistic PSA testing generates complex data in which testing intensities, PSA levels, and prostate cancer diagnosis are interdependent. Conventional analyses rarely model these processes jointly. The objective of this study was to develop a population-based joint model to analyse PSA dynamics, retesting patterns, and prostate cancer risk. We used the Stockholm Prostate Cancer Diagnostics Register to identify 506,761 men with at least one PSA test between 2003 and 2020. We fitted a joint model linking three components: a linear mixed-effects submodel for PSA over age, and two proportional hazards submodels for time to next PSA test and time to prostate cancer diagnosis. PSA increased nonlinearly with age, with substantial between-person heterogeneity and increasing unexplained variation with increasing age. In the joint model, doubling of the total PSA values was associated with a hazard ratio (HR) of 2.01 (95% CI: 1.99-2.02; P < .001) for diagnosis and 1.163 (95% CI: 1.161-1.165; P < .001) for retesting. These hazard ratios were significantly stronger than estimates obtained when modelling these processes separately. As a limitation, the study is primarily limited by its observational nature and a lack of data on non-cancer factors that can elevate PSA, such as urinary tract infections or lower urinary tract symptoms. Furthermore, the model does not explicitly account for PSA trajectory changes after cancer onset. In conclusion, jointly modelling PSA dynamics and testing behaviour corrects for the informative observation bias inherent in opportunistic testing. This approach yields more accurate population estimates and personalised risk predictions compared to traditional isolated models. Our findings suggest that PSA dynamics may be clinically informative and that screening models should jointly incorporate testing history and PSA trajectories to improve precision.

BackgroundDespite extensive cataloging of carcinogenic exposures by the International Agency for Research on Cancer (IARC) and pharmacogenomic variation by resources such as PharmVar and CPIC, few platforms unify exposure, metabolic activation and detoxification, DNA damage, and genetic annotation within a single interactive visualization framework. This gap limits systematic evaluation of gene-environment interactions in cancer risk assessment. MethodsWe developed the Carcino-Genomic Knowledge Graph, ExposoGraph, an interactive knowledge-graph platform for carcinogen metabolism and DNA damage pathways. The reference graph integrates curated data and annotations from IARC, KEGG, PharmVar, CPIC, CTD, and supporting literature/resources. The current reference graph contains 96 nodes across 5 entity types (Carcinogens, Enzymes, Metabolites, DNA Adducts, and Pathways) and 102 edges across 6 relationship types (activates, detoxifies, transports, forms adduct, repairs, and pathway). ResultsThe first-generation reference graph captures metabolic activation and detoxification pathways for 9 carcinogen classes spanning 15 index carcinogens. It represents 36 enzymes across Phase I activation (n=14), Phase II conjugation and detoxification (n=14), Phase III transport (n=3), and DNA repair (n=5). Interactive exploration supports carcinogen-class filtering, node- and edge-type filtering, metadata-based search, and detailed hover/detail views with provenance and pharmacogenomic annotations. The androgen branch highlights cross-pathway connectivity by linking androgen metabolism to estrogen quinone formation and DNA adduct generation through CYP19A1-mediated aromatization and downstream catechol estrogen chemistry. In the optional androgen-focused extension, additional receptor, tissue, and variant context further connects this branch to androgen receptor signaling and genotype-specific annotations. ConclusionsExposoGraph provides a first-generation integrated, interactive framework linking carcinogenic exposures to metabolic fates and genetic modulators. The platform supports hypothesis generation for gene-environment interaction studies and may inform future individualized risk modeling, while remaining a research-use framework rather than a clinically validated risk-assessment tool.

Whole-genome sequencing (WGS) enables comprehensive analysis of tumour genomes, but its use in formalin-fixed paraffin-embedded (FFPE) samples is limited by DNA fragmentation and low yields. Whole-genome amplification (WGA) methods such as multiple displacement amplification (MDA) can boost DNA availability but distort copy-number alteration (CNA) profiles. DNA ligation-mediated MDA (DLMDA) mitigates this bias by reconstituting fragmented templates, yet its performance in FFPE-derived DNA remains uncertain. We compared paired DLMDA pre-amplified (2h, 8h) and non-pre-amplified FFPE prostate tumour samples from 22 archival blocks (5, 15 and 20 years old). DLMDA increased DNA yield by 42- to 86-fold, with global CNA patterns largely preserved. However, DLMDA significantly reduced the number of detected CNA deletions and amplifications. These effects were independent of both block age and reaction time. CNA dropouts were randomly distributed across the genome, indicating that DLMDA does not introduce regional bias. Our results show that DLMDA enables robust DNA yield recovery and avoids false-positive CNA artefacts, but at the cost of reduced CNA sensitivity. While suitable for CNA screening pipelines through WGS, further improvements are required to minimise the false-negative risk and improve the techniques sensitivity for FFPE-based genomics.

Prostate cancer is the second most common malignancy among men, with androgen deprivation therapy (ADT) serving as the standard treatment due to the hormone sensitivity of prostate tumors. However, therapeutic resistance frequently develops, leading to castration-resistant prostate cancer (CRPC), an aggressive and lethal disease. A recently defined subtype, stem cell-like CRPC (CRPC-SCL), accounts for approximately 25% of CRPC cases and demonstrates poor responsiveness to ADT. CRPC-SCL is characterized by the expression of Cluster of Differentiation 44 (CD44), a glycoprotein that promotes hyaluronic acid binding and uptake. Within CRPC-SCL patient-derived xenograft (PDX) model, CD44 high (CD44hi) cells exhibit enhanced tumorigenicity and proliferative capacity. Importantly, iron metabolism emerges as a critical regulator of this population: CD44hi cells maintain elevated intracellular iron, which sustains CD44 expression and stem cell-like properties by modulating H3K9me2 modification. Leveraging this vulnerability, inhibition of the iron-regulatory factor NRF2 was shown to increase intracellular free iron and selectively induce ferroptosis in CD44hi cells. These findings highlight the therapeutic potential of targeting iron metabolism to induce ferroptosis as a novel treatment strategy for CRPC-SCL.