BACKGROUND:Docetaxel remains a standard treatment for metastatic castration-resistant prostate cancer (mCRPC), yet reliable prognostic markers are lacking. TP53 and RB1, key tumor suppressor genes regulating cell-cycle control and genomic stability, have been linked to aggressive disease and lineage plasticity in advanced prostate cancer. We evaluated the prognostic impact of TP53 and/or RB1 alterations in mCRPC patients treated with docetaxel. METHODS:We retrospectively analyzed 125 mCRPC patients treated with docetaxel. Genetic alterations were assessed using the TruSight Oncology 500 v2 panel. Progression-free survival (PFS) and overall survival (OS) were analyzed according to TP53 and RB1 alteration status. RESULTS:TP53 alterations were present in 45 patients (36.0%) and RB1 alterations in 16 (12.8%). Patients with alterations in either TP53 or RB1 had significantly shorter OS (median OS = 18.10 vs. 32.23 months; HR = 1.83, 95% CI = 1.19-2.84; p = .006). Co-altered patients showed the poorest OS (median OS = 11.40 months; HR = 5.09, 95% CI = 1.97-13.19; p < .001). PFS was also shorter in patients with TP53 or RB1 alterations. CONCLUSION:TP53 and RB1 alterations, particularly TP53/RB1 co-alteration, are associated with poor prognosis in mCRPC treated with docetaxel.

5057 Background: mCRPC with high neoantigen burden due to DNA mismatch repair deficiency (MMRd) and somatic hypermutation, or CDK12 mutations, may respond best to immune checkpoint inhibition (ICI). CCTG IND.232 suggested that combination ICI with DT has efficacy in a subset of mCRPC but should be biomarker-directed. In this sub-study (SS) of the PC-BETS master protocol, we explored DT in ARPI-resistant mCRPC stratified by circulating tumor DNA (ctDNA) analysis. Methods: Pts had ECOG PS 0–1, evaluable disease, biochemical or radiographic progression, prior ARPI ± cytotoxic chemotherapy (max 1 in castrate resistant setting). Genomic screening tested plasma ctDNA and matched leukocyte DNA via deep targeted sequencing with a prostate cancer-specific panel including coding regions and introns of selected mismatch repair genes and estimating tumor mutational burden. Only pts with evidence of ctDNA ≥1% were eligible. Pts with a positive biomarker (BM+) on ctDNA were assigned to a specific SS by a molecular tumor board (MTB); BM- pts were randomized between SS. SS- F tested DT in 2 cohorts of pts: cohort 1: BM+ pts had either somatic hypermutation (HM) ± concomitant MMR gene alterations, or CDK12 mutations, cohort 2: BM- pts without these alterations, in a 2-stage design. Primary endpoint was clinical benefit rate (CBR), defined by PSA50 response, RECIST CR/PR, or SD ≥12 weeks. Pts received T 225mg IV once on cycle 1, day 1 and D 1500mg IV day 1 every 4 weeks. Results: From January 2020 to February 2024, 25 pts were enrolled: 15 and 10 to cohort 1 and 2, respectively. Median age was 69y (63-84). Five pts had liver mets, 15 pts had had prior cytotoxics. 9 pts in cohort 1 had HM and the remainder had CDK12 mutations only. Median N cycles given was 4 (1-45). 12 pts had a delayed or interruption of DT dosing. The most common related AEs were fatigue (36%), rash (36%), and diarrhea (32%). CBR was seen in 53% of BM+ pts: all also had PSA response and significantly higher median ctDNA% (34% vs 5%; 5-69%); no patient selected as BM+ due to CDK12 mutations had CBR, while 8 of 9 pts selected based on HM had CBR. Conclusions: Liquid biopsy biomarker-informed treatment with DT demonstrated very promising efficacy in mCRPC pts with HM and merits further evaluation. CDK12 mutations were not predictive of CBR. Toxicities experienced were characteristic of ICI. Clinical trial information: NCT03385655 . BM + BM - CBR 8 (53%) 0 Median ctDNA% 25% 12.5% TTP-PSA* (mo; 95% CI) 6.7 (1-NR) 1.9 (1.1-NR) mOS** (mo; 95% CI) 15.2 (11.8-NR) 7.5 (2.1-NR) *PSA time to progression; **median overall survival.

5066 Background: PC-BETS registered patients (pts) with metastatic castration-resistant prostate cancer (mCRPC) for circulating tumour (ct)DNA-based genomic screening to biomarker select and stratify pts for enrolment in a multi-arm platform trial testing clinical activity of investigational therapies. Methods: Pts (≥ 18 years old, ECOG PS 0-1, life expectancy ≥ 6 months) had mCRPC, disease progression (PD), no CNS involvement or serious illnesses and had received AR pathway inhibitor therapy +/- chemotherapy. Eligible pts were registered and screened using plasma ctDNA and enrolled to a substudy (SS) based on the presence (or absence) of a prespecified biomarker (BM), using a prespecified algorithm and a virtual web-based Molecular Tumour Board (MTB). ctDNA testing used an established targeted sequencing approach customised for mCRPC. Pts without BM positive genomic alteration(s) for an open SS were randomized to a BM negative SS cohort; pts who were never enrolled were followed for outcomes. Pts without detected ctDNA were not eligible for enrolment but could be rescreened after >8 weeks. Pts who discontinued a SS could be rescreened. Primary endpoint was clinical benefit rate (CBR; PSA50 response, RECIST CR/PR, or SD ≥12 weeks). Eight SS opened between 2017-2020. Results: From 2017-2024, 568 pts were screened from 11 centres across Canada. Pts: median age 71.5 (range 47.7-94.7), prior chemotherapy in 47.0%, and median ctDNA fraction was 7%. 216 pts were enrolled to 1 or more SS (3 pts enrolled to >1). See Table for summary of results. For all SS, toxicities were as expected. In SS-E, 1 pt had CBR and 1 pt received 25 cycles but did not meet CBR (both pts had AKT mutations). Clinical and genomic correlations will be presented. SS C, F and G are reported separately. Conclusions: Biomarker selected platform designs are an efficient way to screen potential new therapeutics, are well suited to multi-centre cooperative group settings and are strongly supported by patients advocates. CBRs were not reported for SS 223, B and D while modest clinical activity was seen for SS A (in the BM- cohort only) and E. Clinical trial information: NCT03385655 . Total Screens / N pts 606 / 565 ctDNA+ screen / pts 443 / 426 N pts enrolled to SS 216 SS 223 A B C D E F G Drug/s Palbociclib Adavosertib Savolitinib Darolutamide CFI-40095 Ipatasertib Durvalumab / tremelimumab Carboplatin Target/pathway CDK 1 BRCA/ATM 2 MET AR PTEN PIK3CA/AKT TMB high BRCA/ATM 2 Drug supplied by Pfizer AstraZeneca Bayer 3 Treadwell Hoffman-La Roche 3 AstraZeneca 3 - Enrolled to SS(BM+/-) 19 (9/10) 25 (11/14) 16 (6/10) 72 (53/19) 18 (9/9) 8(BM+) 25 (15/10) 35(18/17) CBR (BM+) 0 0 0 0 1 CBR (BM-) 0 3 0 0 1 CDK4/6/CCND1 amplification or CDK12 mutations; 2 or other HRR-related defects; 3 Plus partial funding to support SS.

Clonal hematopoiesis (CH) is an age-related expansion of white blood cell (WBC) progenitors linked to risk of hematological malignancy. Patients with cancer have increased CH prevalence compared to healthy populations, but the characteristics and relevance of CH in advanced urological cancers are unknown. We interrogated CH and circulating tumor DNA (ctDNA) in 299 patients with metastatic urothelial or renal cell carcinoma using error-corrected targeted sequencing of matched WBC DNA and plasma cell-free DNA (cfDNA). 73% of patients carried CH variants at ≥0.25% allele frequency, with 13% exhibiting large CH populations marked by variants ≥10%. CH presence, clone size, and genotype did not impact patient survival. However, CH variants frequently affected solid cancer driver genes and were not individually discriminable from ctDNA variants based on cfDNA features including fragment length. In contrast, matched WBC DNA sequencing to ≥25% of cfDNA depth sufficiently resolved CH from ctDNA variants. Serial profiling revealed ctDNA and CH temporal dynamics including treatment-related expansion of PPM1D-mutated CH clones following platinum chemotherapy. Our data reveal the molecular landscape of CH in urological cancers and suggest that CH interferes in clinical ctDNA genotyping. We urge test providers to comprehensively filter CH from ctDNA results using matched WBC sequencing and propose a cost-effective framework for its integration into existing plasma-only assays.

No consensus strategies exist for prognosticating metastatic castration-resistant prostate cancer (mCRPC). Circulating tumor DNA fraction (ctDNA%) is increasingly reported by commercial and laboratory tests but its utility for risk stratification is unclear. Here, we intersect ctDNA%, treatment outcomes, and clinical characteristics across 738 plasma samples from 491 male mCRPC patients from two randomized multicentre phase II trials and a prospective province-wide blood biobanking program. ctDNA% correlates with serum and radiographic metrics of disease burden and is highest in patients with liver metastases. ctDNA% strongly predicts overall survival, progression-free survival, and treatment response independent of therapeutic context and outperformed established prognostic clinical factors. Recognizing that ctDNA-based biomarker genotyping is limited by low ctDNA% in some patients, we leverage the relationship between clinical prognostic factors and ctDNA% to develop a clinically-interpretable machine-learning tool that predicts whether a patient has sufficient ctDNA% for informative ctDNA genotyping (available online: https://www.ctDNA.org ). Our results affirm ctDNA% as an actionable tool for patient risk stratification and provide a practical framework for optimized biomarker testing.

Supplementary Figure 2. Mutations in selected genes.

Supplementary Figure S1 shows independent estimation of circulating tumor DNA fraction using whole exome sequencing.

Supplementary Table 1: Somatic mutation count across all samples within meta-cohort. Counts of mutations in all ctDNA positive samples. 95th and 90th percentile are highlighted. Samples are named as a function of their relative mutation count. Supplementary Table 2: Evidence for mismatch repair deficiency by patient. See also Figure 2 Supplementary Table 3: Somatic mismatch repair gene alterations detected in patients with hypermutation. The status of key mismatch repair genes with respect to mutations and copynumber events. ClinVar version 20180603 annotations are included. *Clinvar annotation absent; **Diploid or lack of evidence for deviation from diploid ploidy; blue colour indicates the patients without MMRd etiology Supplementary Table 4: Whole exome sequencing summary statistics. Read depth and subsequent frequency calculations are based on unique read depth, post duplicate removal. Supplementary Table 5: Frequency of mutation and copy number changes in key genes. Comparison of gene and copy number frequencies in mimsatch repair cohort compared to control. P value and odds ratio generated using scipy.stats.fisher_exact verion 1.2.1 Supplementary Table 6: Somatic coding region altering mutations detected through targeted DNA sequencing (all cases in 95th percentile). Mutation annotation format with refseq protein change annotation. Supplementary Table 7: AR and other oncogene mutations detected across serial cfDNA collections. Protein changes are annotated with all refseq isoform amino acid changes. Variant allele frequency (VAF) is provided for each mutation. Supplementary Table 8: Distribution of variant allele frequencies for somatic mutations in each sample. Column D indicates the proportion of mutations in each sample that are considered subclonal. Predicted ctDNA fractions are calculated on max allele frequency of mutations in gene panel. Other columns contain descriptive statistics that summarize the central tendency, dispersion and shape of the distribution of variant allele frequencies per sample. Supplementary Table 9: CtDNA fraction by sample. The highest allele frequency mutation from each sample which does not belong to copy altered segment of the genome is used in the calculation of ctDNA fraction. Supplementary Table 10: Comparison of variant allele frequencies between tissue and ctDNA samples from patients P04 and P10. Supplementary Table 11: Clinical characteristics and PSA response to first-line AR-pathway inhibitor in the MMRd and control (MMR intact) cohort.

Supplementary Figures S1 - S18

INTRODUCTION:In patients with prostate cancer (PCa), the identification of an alteration in genes associated with homologous recombination repair (HRR) has implications for prognostication, optimization of therapy, and familial risk mitigation. The aim of this study was to assess the genomic testing landscape of PCa in Canada and to recommend an approach to offering germline and tumor testing for HRR-associated genes.METHODS:The Canadian Genitourinary Research Consortium (GURC) administered a cross-sectional survey to a largely academic, multidisciplinary group of investigators across 22 GURC sites between January and June 2022.RESULTS:Thirty-eight investigators from all 22 sites responded to the survey. Germline genetic testing was initiated by 34%, while 45% required a referral to a genetic specialist. Most investigators (82%) reported that both germline and tumor testing were needed, with 92% currently offering germline and 72% offering tissue testing to patients with advanced PCa. The most cited reasons for not offering testing were an access gap (50%), uncertainties around who to test and which genes to test, (33%) and interpreting results (17%). A majority reported that patients with advanced PCa (74-80%) should be tested, with few investigators testing patients with localized disease except when there is a family history of PCa (45-55%).CONCLUSIONS:Canadian physicians with academic subspecialist backgrounds in genitourinary malignancies recognize the benefits of both germline and somatic testing in PCa; however, there are challenges in accessing testing across practices and specialties. An algorithm to reduce uncertainty for providers when ordering genetic testing for patients with PCa is proposed.

Supplementary Figure S7 shows the concordance of gene coverage logratios between 72-gene targeted sequencing and whole exome sequencing

Abstract Background: There is a need to identify patients with advanced prostate cancer harboring an inherited mutation in selected DNA damage repair (DDR) genes, as there are prognostic, treatment, and familial risk implications. We aimed to develop a model to predict an individual risk of harbouring a germline DDR gene mutation in patients with metastatic and/or castration resistant prostate cancer (CRPC) disease. Patients and Methods: A retrospective multicenter cohort study was performed on 499 patients with metastatic and/or CRPC, who were tested for germline DDR gene mutations. Clinical and pathologic characteristics were compared between patients with and without a germline DDR mutation. Multivariable logistic regression was employed to develop a prediction model, which was internally validated using a bootstrapping method. Results: Eight predictors (age at diagnosis, time to CRPC, Gleason score, intraductal/cribriform histology, family history, visceral, bone, and lymph node metastases) were included in a logistic model to predict the probability of a germline DDR mutation. A formula to calculate an individual patient’s mutation risk is provided. Two optimal risk cut-offs were explored. Conclusion: We provide a predictive model of germline DDR gene mutation status in patients with metastatic and/or CRPC, using eight clinical-pathologic parameters. Predictive models such as this could be used to estimate a patient’s risk of harbouring a germline DDR mutation to determine prioritization for germline testing.

Supplementary Figure 5. Somatic mutation trinucleotide contexts.

<p>Supplementary Figure S17 provides whole exome somatic mutation profiles in patients that did not show temporal changes in 72-gene panel mutation profiles</p>

Supplementary Figure 12. Swimmer plot showing overall patient survival from initial cancer diagnosis.

Supplementary Figure S8 shows that exome-wide sequencing supports ctDNA fraction estimates inferred with the 72-gene panel

Supplementary Figure S13 shows temporal changes in copy number profiles detected via 72-gene targeted sequencing

Supplementary Figure 3. Representative copy number profiles of samples harboring MSH2 and MSH6 deletions.

Supplementary Figure 9. Comparison of tumor mutation burden between primary tissue and cfDNA collections.