Tran, Phuoc T.

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.

160 Background: To our knowledge, no tools are available to guide care in oligometastatic prostate cancer (omPC). Here, we leveraged individual patient-level data pooled from 8 randomized trials in the X-Met collaboration to construct CEREBRO, a tool for predicting patient-specific responses to various treatment scenarios. Methods: Patients with omPC from the STOMP, ORIOLE, SABR COMET, EXTEND continuous ADT, EXTEND intermittent ADT, ARTO, RADIOSA, and RAVENS trials were included. 6 patients (1%) with missing data were excluded. Treatment scenarios were defined as active surveillance (AS), metastasis-directed therapy (MDT), systemic therapy (ST), or MDT+ST. To account for varying baseline hazards, Weibull models were fit for overall survival (OS); progression-free survival (PFS); and castration-resistance free survival (CRFS) for patients with hormone-sensitive disease. Endpoint definitions were harmonized per X-Met framework. Results: Of 600 patients included (treatment scenarios: AS=50; MDT=153; ST=172; MDT+ST=225), 405 (67%) had hormone-sensitive omPC. With median follow-up of 38 months, median PFS, CRFS, and OS of all patients were 18, 70, and 84 months. In order of relative contribution, inputs for predicting outcomes were: treatment scenario, stage, prostate-specific antigen annotated by ADT status, metachronous vs synchronous presentation, imaging type, number of metastases, hormone sensitivity, and age. The model for each endpoint showed robust fit, calibration, superiority against the null model (per the likelihood ratio test), and risk stratification (Table). Median PFS times for model-defined low-, intermediate-, and high-risk strata were 46 months, 18 months, and 7 months ( p <0.0001). In addition, the PFS and OS models also showed strong discrimination via c index and a large interval of risk probabilities with additive clinical utility per decision-curve analysis (Table). A public webpage will be made available to facilitate prospective trial stratification, patient counseling for patient-specific outcome predictions for each potential treatment scenario, and forecasts comparing outcomes between treatment scenarios. Conclusions: CEREBRO is a high-performance tool, trained on robust prospective data from 8 randomized trials with routinely collected clinical variables, for predicting risk and treatment outcomes in omPC. Given the uncertainties in optimal timing of MDT and combination with ST, this tool has been built to facilitate current decision making. External validation is planned. Model summary. Endpoint C index (95% CI) Calibration Likelihood ratio p Risk strata p Net clinical utility observed between thresholds PFS 0.72 (0.70-0.75) 1.04 <0.0001 <0.0001 0.2-1.0 CRFS 0.63 (0.60-0.70) 1.01 0.02 0.004 0.2-0.5 OS 0.81 (0.76-0.86) 1.01 <0.0001 <0.0001 0.05-1.0