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PURPOSE Precision medicine has revolutionized oncology; however, tumor biomarkers are not reflective of the heterogeneous cancer population. We evaluated NRG Oncology prostate cancer (PCa) clinical trials for demographic differences among patients with optional biospecimen collection (BC) consent and biospecimen submission (BSub). METHODS Data from 19 NRG PCa clinical trials closed before 2015 were analyzed. Patients who consented to BC and completed BSub were evaluated by race, ethnicity, median income, area deprivation index (ADI; categorized as highest v lowest three quartiles), age at enrollment, site, and year of enrollment. T/chi-square tests were used for continuous/categorical variables, respectively, followed by logistic regression. RESULTS Of the 15,648 randomized patients eligible for BC, 11,796 (75%) had specimens submitted. In all, 4,598 (82.2%) of 5,597 eligible patients consented for optional BC in nine clinical trials with a separate BC consent process (consent rates by race/ethnicity: 74.1% Black, 72.8% Hispanic/Latino, 83.8% White). A smaller proportion of Black and Hispanic/Latino patients consented to optional BC compared with those who did not (12.1% v 19.5% Black, P < .0001; 3.5% v 5.8% Hispanic, P = .0006). In univariable logistic regression models, high ADI (more socioeconomic disadvantage) was associated with a decreased likelihood for optional BC consent (odds ratio [OR], 0.67 [95% CI, 0.55 to 0.82]; P = .02), but not a decreased likelihood for BSub (OR, 0.74 [95% CI, 0.53 to 1.04]; P = .08). Multivariable models demonstrated that Black/Hispanic/Latino patients were less likely to consent to optional BC, and Black patients were less likely to have BSub ( P < .05 for all). CONCLUSION White/non-Hispanic patients and those with less socioeconomic disadvantage were more likely to consent to optional BC, whereas Black patients were less likely to have BSub. Targeted solutions are needed to improve biorepository representation so that precision medicine approaches better reflect the cancer population.

ABSTRACT Background Inflammation plays a critical role in cancer cell proliferation; however, the specific role of inflammasomes, multiprotein complexes that regulate inflammation‐associated signaling pathways, in prostate cancer (PCa) remains insufficiently explored. This study aims to characterize the expression of inflammasome‐related genes in PCa and evaluate their association with clinical outcomes. Methods De‐identified transcriptome data from the Decipher GRID RP, a cohort of 52,266 radical prostatectomy (RP) samples tested (2016–2024) with the Decipher prostate genomic classifier (Veracyte, San Diego, CA), were retrieved from the GRID registry (NCT02609269). Expression analysis of 34 genes involved in inflammatory pathways was conducted to associate their expression with clinical and genomic variables. Outcomes analyses were conducted on a retrospective cohort of 855 patients treated with RP (META855). Results Analysis of inflammasome gene expression in the GRID RP cohort revealed that most genes exhibit low baseline expression, whereas HSP90AB1, APP, TXN, and TXNIP demonstrate strong expression signals. Additionally, higher expression of most genes was associated with Gleason Grade Group 4–5 and very high Decipher scores. On survival analysis of the META855 cohort, higher expressions of AIM2 and HSP90AB1 were significantly associated with worse metastasis‐free survival. Conversely, both high and low expression levels of NLRP3 were associated with better metastasis‐free survival outcomes following RP compared to average expression. On multivariable Cox regression analysis, higher expressions of AIM2 (HR 1.75) and HSP90AB1 (HR 1.60) were significantly associated with shorter time to metastasis following RP. Conclusions There is molecular heterogeneity within pro‐inflammatory genes among patients with PCa. Our findings showed there is a potential association between the expression levels of certain inflammasomes, such as AIM2, HSP90AB1, and NLRP3, and oncological outcomes following RP.

The NCCN Guidelines for Prostate Cancer include recommendations for staging and risk assessment after a prostate cancer diagnosis and for the care of patients with localized, regional, recurrent, and metastatic disease. These NCCN Guidelines Insights summarize the panel’s discussions on select 2026 updates to the guidelines regarding nonmetastatic disease: the elimination of the very-low-risk group, updates to the Principles of Active Surveillance, and caution in the use of focal therapy in newly diagnosed patients.

PURPOSE Although outcomes for nonmetastatic cancers have improved since the 1970s, it remains uncertain whether long-term survival has improved among patients presenting with de novo metastatic disease, defined as cancer presenting with distant metastases at the time of initial diagnosis. This study evaluated changes in 5-year survival among patients with de novo metastatic cancer diagnosed in 1976 versus 2015, with a minimum 5-year follow-up through 1981 and 2020, respectively. METHODS Population-based data were obtained from the SEER database. Patients diagnosed with de novo metastatic cancer in 1976 (n = 11,864) and 2015 (n = 26,324) were included. Five-year overall survival (OS) was compared between cohorts, and multivariable logistic regression identified demographic and clinical factors associated with survival. RESULTS The 5-year OS increased significantly from 10.6% in 1976-1981 to 23.6% in 2015-2020 ( P < .001). Survival gains were largest in breast cancer (12.6%-34.2%; P < .001), ovarian cancer (14.4%-32.5%; P < .001), colorectal cancer (3.7%-15.0%; P < .001), and hematologic malignancies (24.3%-53.9%; P < .001). Minimal improvement occurred in pancreatic cancer (0.25%-1.6%; P = .007) and small cell lung cancer (0.8%-3.1%; P = .008). Multivariable analysis demonstrated that older age, male sex, and Black race were associated with lower odds of 5-year survival (all P < .01) CONCLUSION Over the past four decades, long-term survival among patients with de novo metastatic cancer has more than doubled; however, progress remains uneven across cancer types. Gains appear concentrated in malignancies with substantial therapeutic advances, whereas others show persistently poor outcomes. Continued efforts are needed to address disparities and improve survival in resistant cancer types.

392 Background: Cancer-associated fibroblasts (CAFs) are a major component of the tumor microenvironment, exerting both tumor-promoting and tumor-restrictive effects, and in some cases, dual roles. CAFs are heterogeneous and have been implicated in tumor progression, metastasis, and therapeutic resistance. Recent translational evidence suggests the existence of at least two CAF subtypes: CAV1+ CAFs and FAP+FN1+ CAFs. The clinical utility of subclassifying CAFs in prostate cancer remains undefined. In this study, we aimed to examine the correlation of CAF subtypes in localized prostate cancer with Decipher genomic classifier (GC) scores, Grade Group (GG), and the presence of adverse pathological features (APF). Methods: We retrieved de-identified transcriptomic and pathological data from 55,329 radical prostatectomy (RP) samples tested with the Decipher prostate genomic classifier (Veracyte, San Diego, CA) between 2016 and 2024, available through the GRID registry (NCT02609269). A subset of 855 patients (META855 cohort) treated with RP was utilized for outcomes analyses. CAF subtypes were defined based on the expression of key biomarkers (FN1, FAP, and CAV1), normalized to total CAF estimates. Correlation analyses and multivariable Cox regression models were performed to evaluate the association of CAF subtypes with GC scores, GG, APF. Metastasis-free survival (MFS) estimates were generated using Kaplan–Meier methodology. Results: FAP and FN1 normalized expressions were highly correlated (r=0.61) and weakly correlated with CAV1 suggesting that they represent two distinct subtypes of CAF. Samples with high expression (top 25%) of FN1 (FN1+) and FAP (FAP+) were enriched with very high Decipher (> 0.85, VHD) and GG4-5. As such, 37% and 32% of FAP+ were VHD and GG4-5 respectively compared to ~18% for low FAP(low 25%). While for FN+ 33.9% were VHD, and 31.5% GG4-5. Patients with FAP+FN1+, 42.5% and 37.1% were VHD, and had GG4-5. Samples with high CAV1 (CAV1+) were associated with lower rate of VHD (15.5%) or GG4-5 (20.8%) compared to low CAV1 (35.4% for VHD and 24.5% for GG4-5). When evaluating VHD in FAP+FN1+CAV1- subgroup, 58% were VHD compared to 6.4% in FAP-FN1-CAV1+. The 5-year MFS was 78% in FAP+FN1+CAV- compared to 96% in FAP-FN1-CAV1+ (p<0.01). When evaluating the biological implications of FAP+FN1+, we found that FAP and FN1 expression is highly correlated to angiogenesis and EMT pathways, radiation sensitivity signature (PORTOS). Conclusions: FAP+FN1+CAV- is a unique subset of CAFs that is associated with aggressive prostate cancer behavior. Our findings may lay the foundation for future efforts to modulate CAFs in localized prostate cancer with existing therapeutics targeting FAP or FN1.

382 Background: Androgen receptor signaling drives prostate cancer (PC) progression, and genes involved in androgen production, uptake, and conversion (APUC) are key therapeutic targets. We previously defined a 6-APUC gene set ( HSD3B1, HSD3B2, CYP3A43, CYP11A1, CYP11B1, and CYP17A1 ), that identified metastatic PC with favorable prognosis and predict docetaxel benefit. However, the expression landscape and clinical relevance of APUC genes have not been interrogated in localized PC. Methods: We analyzed the expression of 21 APUC genes in 55,329 radical prostatectomy tumor samples that underwent Decipher prostate genomic classifier (GC) testing (Veracyte Inc) between 2016-2024. Baseline clinical/pathologic factors were retrieved from Decipher GRID database (NCT02609269). Associations between gene expression quartiles with PathoGenomic Risk Factors (PGRF) including Very High Decipher score >0.85 (VHD), Grade Group (GG) 4-5, LNI and SVI were examined. Associations with distant metastatic (DM) outcomes and metastasis free survival (MFS) were evaluated using logistic regression in Mayo545 and Cox regression in Meta855 RP cohorts, respectively. Results: High expression of SRD5A2 was associated with favorable PGRF (lower odds ratio (OR), p<0.0001), lower rate of development of DM (OR 0.36, p<0.05), and longer MFS (Hazard ratio (HR) 0.51, p<0.05). HSD17B6 showed similar results for PGRF (lower OR, p<0.0001), DM (OR 0.58, p<0.05) and longer MFS (HR 0.39, p<0.05) despite being associated with GG4-5 and SVI+ in samples with VHD. In contrast, high expression of SRD5A3 and HSD17B10 had high OR for PGRFs (p<0.0001). High expression of SLCO2B1 , an androgen uptake gene, had the strongest association with GG4-5 and SVI/LNI (p<0.001 for both). We noted that SRD5A2 lacked correlation with SRD5A1 and SRD5A3 , which instead correlated with each other. Compared to all APUC genes, SRD5A2 had limited correlations with almost all APUC genes, including ones that exhibited robust cross correlation with each other . Similar to our prior finding, most APUC genes demonstrated negative correlation with AR expression and AR activity signatures. Key outcomes were validated based on transcriptomic data from 492 samples from TCGA database. Conclusions: Comprehensive analysis of 21 APUC genes in over 55,000 PC identified distinct, context-dependent associations with metastatic outcomes and clinical and molecular risk factors. Notably, high SRD5A2 expression was associated with lower odds of high-risk features and metastatic outcomes, whereas SRD5A1 and SRD5A3 linked to adverse outcomes, suggesting critical yet divergent roles among 5-alpha-reductase family members. These findings underscoring androgen-metabolic heterogeneity and highlighting SRD5A2 as a potential biomarker of indolent biology in localized prostate cancer.

Importance The ideal duration of androgen deprivation therapy (ADT) for treating localized prostate cancer is unknown due to variable adherence and treatment durations tested in clinical trials. Objective To determine the ideal duration of ADT for patients with prostate cancer treated with radiotherapy. Data Sources This individual patient data meta-analysis of 13 randomized phase 3 clinical trials evaluated the use of radiotherapy alone or with ADT. It included patients with a median follow-up of 11.3 (IQR, 9.5-14.5) years and ADT duration of 0 to 36 months. Most patients (7392 [72%]) included had National Comprehensive Cancer Network high-risk or very high-risk disease. Study Selection For this meta-analysis, a systematic literature search from 1980 to 2020 was performed in trial registries (Cochrane Central Register of Controlled Trials and ClinicalTrials.gov), MEDLINE (1966-2020), Embase (1982-2020), Web of Science, and Scopus to identify trials. Data Extraction and Synthesis Intention-to-treat and as-treated analyses were performed. The number needed to treat to prevent 1 distant metastasis at 10 years was calculated based on prognostic risk group. The analyses were conducted from January 5 to August 15, 2023. Main Outcomes and Measures The primary end point for this study was overall survival, defined as time to death or last follow-up from randomization. Secondary end points included biochemical recurrence, distant metastasis (DM), prostate cancer–specific mortality, and other-cause mortality. Results The median (IQR) age among the 10 266 male patients was 70 (65-74) years. Longer durations of ADT were associated with nonlinear improvement in relative benefits of DM, prostate cancer–specific mortality, and overall survival, with reduced estimated benefits beyond 9 to 12 months of ADT based on the end point. There was a near-linear increase in other-cause mortality associated with long-term ADT use (hazard ratio, 1.28; 95% CI, 1.09-1.50; P = .002 for 28 vs 0 months of ADT). The optimal ADT duration based on 10-year DM was 0, 6, 12 months, and undefined for patients with 1 intermediate-risk factor, 2 or more intermediate-risk factors, and National Comprehensive Cancer Network high-risk and very high-risk disease, respectively. Conclusions and Relevance The results of this meta-analysis suggest that, for men with localized prostate cancer treated with definitive radiotherapy and ADT, there are relative and absolute benefits from increasing durations of ADT that help provide individualized risk estimates.

The NCCN Guidelines for Prostate Cancer provide a framework on which to base decisions for patients with prostate cancer across the disease spectrum. The Guidelines sections included in this article focus on metastatic castration-sensitive prostate cancer (mCSPC), nonmetastatic castration-resistant prostate cancer (CRPC), and metastatic CRPC (mCRPC). For patients with mCSPC, disease characteristics, such as whether metastases arose synchronously or metachronously and the degree of metastatic burden, impact therapy decisions, including how much treatment intensification is appropriate and when prostate-directed and/or metastasis-directed therapy should be considered. In the mCRPC setting, androgen deprivation therapy is continued with the sequential or concurrent addition of certain androgen receptor pathway inhibitors, chemotherapies, immunotherapies, radiopharmaceuticals, and/or targeted therapies. The NCCN Prostate Cancer Panel emphasizes a shared decision-making approach in all disease settings based on patient preferences, prior treatment exposures, biomarkers, the extent and location of metastases, symptoms, and potential side effects.

PURPOSE Long-term androgen deprivation therapy (ADT) improves survival in men with high-risk localized prostate cancer (PCa) receiving radiotherapy (RT). Predictive biomarkers are needed to guide ADT duration. METHODS A multimodal artificial intelligence (MMAI)–derived predictive biomarker was trained for long-term (LT) versus short-term (ST) ADT using pretreatment digital prostate biopsy images and clinical data (age, prostate-specific antigen, Gleason, and T stage) from six NRG Oncology phase III randomized radiotherapy trials. The novel MMAI-derived biomarker was developed to predict the differential benefit of LT-ADT on the primary end point, distant metastasis (DM). MMAI predictive utility was validated on a seventh randomized trial, RTOG 9202 (N = 1,192), which randomly assigned men to RT + ST-ADT (4 months) versus RT + LT-ADT (28 months). Fine-Gray and cumulative incidence analyses for DM, and secondarily, death with DM, were performed. Deaths without DM were treated as competing risks. RESULTS In the validation cohort (median follow-up, 17.2 years), LT-ADT significantly improved DM from 26% to 17% (subdistribution hazard ratio [sHR], 0.64 [95% CI, 0.50 to 0.82], P < .001). A significant biomarker-treatment predictive interaction was observed ( P = .04) for DM, whereby MMAI biomarker–positive men (n = 785, 66%) had reduced DM with LT-ADT versus ST-ADT (sHR, 0.55 [95% CI, 0.41 to 0.73], P < .001), whereas no treatment benefit was observed for MMAI biomarker–negative men (n = 407; sHR, 1.06 [95% CI, 0.61 to 1.84], P = .84). The estimated 15-year DM risk difference between RT + LT-ADT and RT + ST-ADT was 14% in MMAI biomarker–positive men and 0% in MMAI biomarker–negative men. The MMAI biomarker was also prognostic for DM, irrespective of treatment (sHR, 2.35 [95% CI, 1.72 to 3.19], P < .001). CONCLUSION To our knowledge, the MMAI model is the first validated predictive biomarker to guide ADT duration with RT in localized/locally advanced PCa. Approximately one third of men with high-risk PCa could safely be spared the additional 24 months of ADT and the associated morbidity.

Objectives: Early identification of patients living with cancer at higher risk of death from an infection is critical in infection mortality prevention. We characterize patients living with cancer at the highest risk of dying from an infection. Methods: 7,529,481 US cancer survivors (1992 to 2015) were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Standardized mortality ratios (SMRs) and 95% CIs were calculated. Fine-gray survival analysis was performed to calculate hazard ratios by adjusting for the effects of competing risks (eg, deaths due to causes other than infection). Results: Among 7,529,481 patients living with cancer (1992 to 2015), 101,167 (1.3%) died of infection. The rate of infection-specific mortality was 27.19/10,000 person-years, with an SMR of 3.29 (95% CI: 3.26-3.32, P <0.001). Patients who were older, male, black, and unmarried were at a greater risk of fatal infection. Overall, the risk of infection-specific mortality for patients living with cancer is greatest 1 year after diagnosis compared with the general population (SMR: 8.68, 95% CI: 8.53-8.84; P< 0.0001), and this risk decreases with follow-up time (SMR at >10 y after diagnosis: 2.93, 95% CI: 2.87-3.00; P< 0.0001). Among patients with Hodgkin Lymphoma, Non-Hodgkin Lymphoma, and Kaposi Sarcoma, 9.2%, 11.5%, and 82.2% of all deaths within the first year after cancer diagnosis occurred due to acute infectious disease. In contrast, for patients with liver cancer, the relative percentage of infection-specific mortality increases with follow-up time from 3.5% at <1 year after cancer diagnosis and 10.4% at 10+ years of follow-up. Conclusion: The results of this study characterize infection mortality in patients living with cancer, which can guide more targeted research and interventions in this population.