Background: The genomic underpinning of clinical phenotypes and outcomes in metastatic castration-sensitive prostate cancer is unclear.Methods: In patients with metastatic castration-sensitive prostate cancer at a tertiary referral center, clinical-grade targeted tumor sequencing was performed to quantify tumor DNA copy number alterations and alterations in predefined oncogenic signaling pathways. Disease volume was classified as high-volume (4 bone metastases or visceral metastases) vs. low-volume.Results: Among 424 patients (88% white), 213 (50%) had high-volume disease and 211 (50%) had low-volume disease; 275 (65%) had de-novo metastatic disease and 149 (35%) had metastatic recurrence of non-metastatic disease. Rates of castration resistance (adjusted hazard ratio, 1.84; 95% CI, 1.40-2.41) and death (adjusted hazard ratio, 3.71; 95% CI, 2.28-6.02) were higher in high-volume disease. Tumors from high-volume disease had more copy number alterations. The NOTCH, cell cycle, and epigenetic modifiers pathways were the highest-ranking pathways enriched in high-volume disease. De-novo metastatic disease differed from metastatic recurrences in the prevalence of CDK12 alterations but had similar prognosis. Rates of castration resistance differed 1.5-fold to 5-fold according to alterations in AR, SPOP (inverse), and TP53, and the cell cycle, WNT (inverse), and MYC pathways, adjusting for disease volume and other genomic pathways. Overall survival rates differed 2-fold to 4-fold according to AR, SPOP (inverse), WNT (inverse), and cell cycle alterations. PI3K pathway alterations were not associated with prognosis once adjusted for other factors. Conclusion:This study identified genomic features associated with prognosis in metastatic castration-sensitive disease that may aid in molecular classification and treatment selection. Translational RelevanceThe genomic landscape of metastatic castration-sensitive prostate cancer is not well defined, and disease stratification for the purpose of initial treatment selection has primarily relied on clinical phenotypes, including volume of disease at the time of metastasis. Here, we describe tumor genomics in a large cohort of patients with metastatic castrationsensitive prostate cancer and show genomic features that are associated with clinical phenotypes, including with disease volume. We identify genomic alterations that are associated with prognosis in metastatic castration-sensitive disease (overall survival and time to castration resistance), demonstrating that alterations in AR, TP53 and the cell cycle and MYC pathways occur in tumors with worse prognosis, while alterations in SPOP and the WNT pathway occur in tumors with better prognosis. Our findings may aid in molecular classification of metastatic castrationsensitive prostate cancer, and pathways that are prognostically relevant could be targeted in studies of intensified upfront therapy.

Purpose: Black men die from prostate cancer twice as often as White men, a disparity likely due to inherited genetics, modifiable cancer risk factors, and healthcare access. It is incompletely understood how and why tumor genomes differ by self-reported race and genetic ancestry. Experimental Design: Among 2,069 men with prostate cancer (1,841 self-reported White, 63 Asian, 165 Black) with access to clinical-grade sequencing at the same cancer center, prevalence of tumor and germline alterations was assessed in cancer driver genes reported to have different alteration prevalence by race. Results: Clinical characteristics such as prostate-specific antigen and age at diagnosis as well as cancer stage at sample procurement differed by self-reported race. However, most genomic differences persisted when adjusting for clinical characteristics. Tumors from Black men harbored fewer PTEN mutations and more AR alterations than those from White men. Tumors from Asian men had more FOXA1 mutations and more ZFHX3 alterations than White men. Despite fewer TP53 mutations, tumors from Black men had more aneuploidy, particularly chromosome arm 8q gains, an adverse prognostic factor. Genetic ancestry was associated with similar tumor alterations as self-reported race, but also with modifiable cancer risk factors. Community-level average income was associated with chr8q gains after adjusting for race and ancestry. Conclusions: Tumor genomics differed by race even after accounting for clinical characteristics. Equalizing access to care may not fully eliminate such differences. Therapies for alterations more common in racial minorities are needed. Tumor genomic differences should not be assumed to be entirely due to germline genetics.

5029 Background: The incidence of transformation to neuroendocrine prostate cancer (NEPC) has increased in castration resistant prostate cancer (CRPC) in parallel with treatment advances inhibiting androgen receptor signaling. The current understanding is that this occurs in ̃10-20% of CRPC cases. Missing is a determination of the timing of molecular events that drive the process. Methods: Under an IRB-approved protocol, retrospective annotation of all MSK-reviewed pathology reports was conducted for 1447 prostate cancer patients with MSK-IMPACT sequencing data. For patients with pathologically confirmed NEPC, the date of the first sample with unequivocally reported NEPC (described as “neuroendocrine carcinoma” or as having “neuroendocrine differentiation” or “neuroendocrine features”) was recorded. Patients with early signs of histologic transformation not specifically reported as NEPC (double negative prostate cancer or rare/focal staining for NE markers) were analyzed separately. Sequencing results were described by castration-status at collection (CRPC vs castration-sensitive) and, if applicable, the relationship to NEPC diagnosis (i.e. pre- vs post-NEPC). Genomic enrichment analysis was used to identify differentially altered genes between groups. Results: In total, 95 (6.6%) patients had pathologically confirmed NEPC during their disease course, from whom 150 samples with sequencing results were available: including 18 patients with matched pre- and post-NEPC samples. CRPC samples from patients with NEPC (n = 70) were significantly enriched for RB1 alterations (50% vs 12%, p < 10-10, q < 10-10). AR alterations were significantly enriched in CRPC samples from patients without NEPC (n = 380) (63% vs 21%, p < 10-10, q < 1.27*10-8). Further, alterations in numerous genes including TP53, AMER1, ARID5B, YAP1, SOX2, and NKX2.1 were enriched in NEPC patients at the 95% confidence interval (CI) without correction for repeat testing. Matched pre- and post-NEPC samples demonstrated that TP53 alterations in post-NEPC samples are detected in the majority of pre-NEPC samples (8 of 10 patients), but RB1 alterations in post-NEPC samples are detected in a minority of pre-NEPC samples (1 of 8 patients). 54 (3.7%) patients had evidence of early histologic transformation. CRPC samples from these patients (n = 29) were enriched for mutations in RB1, MAP2K2, MUTYH, and CTNNB1 at the 95% CI without correction. FOXA1 mutations were enriched in patients without transformation. Conclusions: RB1, consistent with previous findings, is enriched in NEPC. The inability to detect RB1 alterations in pre-NEPC samples supports divergent evolution, although technical limits of tissue panel sequencing make it difficult to rule out the presence of sub-clonal alterations. Further study of additional genes which contribute to histologic transformation and the development of NEPC is warranted.

Background: Routine clinical data from clinical charts are indispensable for retrospective and prospective observational studies and clinical trials. Their reproducibility is often not assessed. We developed a prostate cancer-specific database for clinical annotations and evaluated data reproducibility. Methods: For men with prostate cancer who had clinical-grade paired tumor-normal sequencing at a comprehensive cancer center, we performed team-based retrospective data collection from the electronic medical record using a defined source hierarchy. We developed an open-source R package for data processing. With blinded repeat annotation by a reference medical oncologist, we assessed data completeness, reproducibility of team-based annotations, and impact of measurement error on bias in survival analyses. Results: Data elements on demographics, diagnosis and staging, disease state at the time of procuring a genomically characterized sample, and clinical outcomes were piloted and then abstracted for 2261 patients (with 2631 samples). Completeness of data elements was generally high. Comparing to the repeat annotation by a medical oncologist blinded to the database (100 patients/samples), reproducibility of annotations was high; T stage, metastasis date, and presence and date of castration resistance had lower reproducibility. Impact of measurement error on estimates for strong prognostic factors was modest.Conclusions: With a prostate cancer-specific data dictionary and quality control measures, manual clinical annotations by a multidisciplinary team can be scalable and reproducible. The data dictionary and the R package for reproducible data processing are freely available to increase data quality and efficiency in clinical prostate cancer research.

Background: Large repositories of biospecimens collected from patients at cancer centers can provide a valuable resource in the development and validation of new biomarker assays to guide therapeutic decision-making. In order to utilize such repositories for biomarker studies, biospecimens must be annotated with the clinical context of each sample. The main source of clinical data is typically an unstructured electronic medical record, which can require a significant amount of time and resources to manually curate. Methods: We developed a database comprised of disease-specific clinical data elements for a large repository of prostate cancer blood samples collected between 2006 – 2022 at a comprehensive cancer center. To provide clinical context for these samples, we contracted and trained a data abstraction company on entry practices with strict adherence to our standardized data dictionary and source hierarchy. After data abstraction and review of an initial training set, we performed a formal evaluation of data quality (completeness and accuracy) through a 100-patient blinded comparison to gold-standard abstraction by a medical oncologist using all available data sources. Subsequently, data entry was completed for an additional 2500 patients and included in longitudinal analysis. Results: Comparison to medical oncologist reference determined that the commercial annotations demonstrated similar completeness for most data elements. For some elements such as stage at diagnosis (M1 vs. M0), commercial abstraction achieved lower completeness (80%) than a medical oncologist (100%). Overall, the accuracy of the commercial annotations varied by element but was suitable for the purpose of identifying samples for use in context-specific biomarker studies. Data regarding disease-related events showed low median variance in the timing of first metastasis (0 months) and castration-resistance (-2.1 months), with substantial observed variance trending towards earlier event calling. Longitudinal analysis of 2500 abstractions showed relatively stable completeness in staging data over time, suggesting that missing data is at least partially attributable to imposed restrictions in data source hierarchy rather than inexperience. Targeted retraining mid-way after 1300 annotations considerably increased the speed of data entry without noticeable changes in data completeness. Conclusions: Commercial data abstraction can be effectively utilized to perform clinical data annotation for large biospecimen repositories with acceptable levels of completeness and accuracy. With appropriate training and direct oversight by an experienced on-site research team, this represents a scalable method for extracting valuable clinical data from largely unstructured patient medical records. Citation Format: Emily A. Carbone, Ethan S. Barnett, Niamh M. Keegan, Samantha E. Vasselman, Barbara Nweji, Ria N. Gajar, Karen A. Autio, Wassim Abida, Howard I. Scher, Konrad H. Stopsack. Assessment of the completeness, accuracy, and scalability of commercial abstraction for a large prostate cancer biospecimen repository [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 941.