Abstract Background The Prosigna Breast Risk of Recurrence test is based on the PAM50 classifier and was originally validated as an in vitro diagnostic (IVD) test on the Dx enabled nCounter ® Analysis System. The Prosigna test is intended for early-stage, hormone receptor+ (HR+) breast cancer and provides the risk of recurrence (ROR) score (0-100), intrinsic subtype (Luminal A, Luminal B, HER2-enriched, and Basal-like), and the 10-year probability of distant recurrence. We describe the performance of the Prosigna test as a whole transcriptome RNA sequencing laboratory developed test (LDT) for measuring the Prosigna ROR score and intrinsic subtypes on tissue from surgical resection and core needle biopsy as compared to the Prosigna test on the nCounter system. Methods We evaluated three separate breast cancer cohorts to 1) bridge the IVD test on the nCounter system and NGS LDT test (n = 245), 2) validate the bridged algorithm on an independent biobank sample set (n = 187), and 3) retrospectively test performance on long-term archival samples from a previous study (n = 109). Results Bridging analysis showed minimal score variability and robust correlation of Prosigna ROR scoring in surgical resections (SR) (2.459, SD; 0.981, R 2 ) and core needle biopsy (CNB) (2.338, SD; 0.970, R 2 ) samples. In the validation set, the Prosigna NGS LDT ROR scores maintained high correlation to the scores of the nCounter system (SR = 0.968, CNB = 0.966, R 2 ), exhibited minimal score variability (SR = 2.488, CNB = 2.558, SD), and demonstrated high concordance in subtype classifications (SR = 92.3% CNB = 92.8%). Further testing demonstrated comparable performance across tumor fractions, a lower limit of detection (LLOD) of 5 ng, and robustness to exogenous ethanol or genomic DNA contamination. When testing previously extracted RNA from the clinical cohort, we observed high correlation (0.974, R 2 ) and low variance (3.078, SD) of ROR scores with original values on the nCounter system, along with strong risk group (95.4%) and subtype (94.5%) concordance. Conclusions This study describes the analytical validation of the Prosigna NGS-based LDT measuring the Prosigna ROR score and intrinsic subtypes with robust analytical performance on SR and CNB specimens, providing confidence for clinicians utilizing the NGS-based version of this well-established test.

BACKGROUND AND OBJECTIVE:Systemic therapies that have shown a benefit in advanced prostate cancer are being evaluated in earlier disease stages. We sought to determine the prevalence of transcriptomic changes in signatures related to treatment susceptibilities in patients with nonmetastatic prostate cancer. METHODS:Patients with nonmetastatic prostate cancer with Decipher genomic classifier and whole-transcriptome profiling data for biopsy specimens from October 2016 to February 2024 were included (n = 140 548). Predefined treatment-related signatures of androgen receptor activity (AR-A), PTEN loss, homologous recombination deficiency (HRD), RB loss, immune activity, and prostate-specific membrane antigen (PSMA; FOLH1) expression, along with Decipher scores and prostate cancer subtypes, were assessed. KEY FINDINGS AND LIMITATIONS:The prevalence of low AR-A scores and the basal subtype, which are associated with lower responsiveness to androgen deprivation therapy (ADT), increased with American Joint Committee on Cancer (AJCC) stage and Decipher genomic risk. The prevalence of cancers with a potential response to PI3K inhibitors, according to PTEN loss, and a response to PARP inhibitors, according to HRD status, also increased with AJCC stage and Decipher genomic risk score (all p < 0.001). The prevalence of high PSMA expression was greater in AJCC grade IIC-IIIC disease, so these patients would be potential candidates for PSMA radioligand therapies. More than 60% of patients with AJCC grade IIC-IIIC disease and very high Decipher scores (>0.85) are potential candidates for targeted therapies. CONCLUSIONS AND CLINICAL IMPLICATIONS:Treatment-related signature scores vary by AJCC stage and Decipher score and may be useful in guiding trials and selecting targeted therapies for nonmetastatic prostate cancer. Higher-stage prostate cancers appear to be more basal and androgen-independent, and thus may be more susceptible to intensified ADT + androgen receptor pathway inhibitors or therapies targeting PARP or PSMA.

Abstract Purpose: Prostate cancer is a heterogeneous disease ranging from indolent localized to metastatic castration-resistance. Efforts to generate prognostic and predictive biomarkers to understand disease trajectory beyond clinical variables alone include the Decipher Prostate Genomic Classifier (GC) and Artera Multimodal AI (MMAI). Both are validated prognostic biomarkers within localized prostate cancer and are currently being evaluated in the metastatic setting. It is unknown if these biomarkers are reporting on similar biology through different means (gene expression vs digital pathology) or if they are complementary and provide orthogonal insights. Herein, we aim to correlate GC and MMAI scores in patients with metastatic prostate cancer. Methods: We conducted a retrospective review of patients with oligometastatic castration-sensitive prostate cancer (omCSPC) with available transcriptome and digital H&E images from prostate biopsy tissue. GC scores were calculated from RNA sequencing data using the same coefficients but scores were re-scaled to a reference cohort from GRID registry while missing features were imputed as 0. Following digitization of H&E slides, an AI-detected, 128 image feature vector (IFV) was generated per patient which was subsequently combined with Gleason score, PSA, and T stage for final MMAI scoring (Artera, Inc). The primary endpoint was to assess correlations between these biomarkers as continuous variables with linear regression. Given the MMAI score is composed of both AI-detected digital pathology features and clinical features, we evaluated any associations between the GC and AI-detected image features. Uniform Manifold Approximation and Projection (UMAP) was performed on the 128 IFV to generate digital pathology clusters which were then associated with GC both as a continuous and categorical variable using ANOVA and chi-square test, respectively. Results: 85 patients (Metachronous n=74; Synchronous n=11) were included in the analysis. The median GC and MMAI scores were 0.60 and 0.52, respectively. Linear regression identified a very weak positive association between scores (R2=0.08, 95%CI 0.00-0.20). UMAP identified 4 digital pathology clusters. No cluster was found to be enriched with higher GC scores with median scores of 0.64, 0.67, 0.58, and 0.5 for clusters 1-4 respectively (p=0.138). Additionally, no cluster was enriched with either low (GC <.45, p=0.87), intermediate (GC ≥ 0.45-<0.6, p=0.73), or high (GC≥0.6, p=0.12) GC risk groups. Conclusions: We demonstrate for the first time that Decipher GC and Artera MMAI scores do not strongly correlate in a population of patients with omCSPC. This suggests these biomarkers may be complementary, identifying independently prognostic disease biology. Further work validating these findings is warranted. Citation Format: Philip A. Sutera, Yang Song, Amol Shetty, Jarey Wang, Kim Van der Eecken, Alex Hakansson, Yang Liu, Adrianna Mendes, Xiaolei Shi, Elai Davicioni, Emmalyn Chen, Rikiya Yamashita, Timothy Showalter, Tamara Lotan, Theodore DeWeese, Ana Kiess, Daniel Song, Matthew Deek, Piet Ost, Phuoc Tran.Evaluating associations between genomic classifier and digital pathology based mutli-modal AI biomarkers in oligometastatic castration-sensitive prostate cancer.[abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Targeted Therapies in Combination with Radiotherapy; 2025 Jan 26-29; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2025;31(2_Suppl):Abstract nr P008

Background and objective: Although the prognostic significance of the Decipher prostate cancer genomic classifier (GC) has been established largely from analyses of archival tissue, less is known about the associations between the results of Decipher testing and oncologic outcomes among patients receiving contemporaneous testing and treatment in the real-world practice setting. Our objective was to assess the associations between the Decipher GC and risks of metastasis and biochemical recurrence (BCR) following prostate biopsy and radical prostatectomy (RP) among patients tested and treated in the real-world setting. Methods: A retrospective cohort study was conducted using a novel longitudinal linkage of transcriptomic data from the Decipher GC and real-world clinical data (RWD) aggregated from insurance claims, pharmacy records, and electronic health record data across payors and sites of care. Kaplan-Meier and Cox proportional hazards regressions were used to examine the associations between the GC and study outcomes, adjusting for clinical and pathologic factors. Key findings and limitations: Metastasis from prostate cancer and BCR after radical prostatectomy, Decipher GC continuous score, and risk categories were evaluated. We identified 58 935 participants who underwent Decipher testing, including 33 379 on a biopsy specimen and 25 556 on an RP specimen. The median age was 67 yr (interquartile range [IQR] 62-72) at biopsy testing and 65 yr (IQR 59-69) at RP. The median GC score was 0.43 (IQR 0.27-0.66) among biopsy-tested patients and 0.54 (0.32-0.79) among RP-tested patients. The GC was independently associated with the risk of metastasis among biopsy-tested (hazard ratio [HR] per 0.1 unit increase in GC 1.21 [95% confidence interval {CI} 1.16-1.27], p < 0.001) and RP-tested (HR 1.20 [95% CI 1.17-1.24], p < 0.001) patients after adjusting for baseline clinical and pathologic risk factors. In addition, the GC was associated with the risk of BCR among RP-tested patients (HR 1.12 [95% CI 1.10-1.14], p < 0.001) in models adjusted for age and Cancer of the Prostate Risk Assessment postsurgical score. Conclusions and clinical implications: This real-world study of a novel transcriptomic linkage conducted at a national scale supports the external prognostic validity of the Decipher GC among patients managed in contemporary practice. Patient summary: This study looked at the use of the Decipher genomic classifier, a test used to help understand the aggressiveness of a patient's prostate cancer. Looking at the results of 58 935 participants who underwent testing, we found that the Decipher test helped estimate the risk of cancer recurrence and metastasis. (c) 2024 The Author(s). Published by Elsevier B.V. on behalf of European Association of Urology. This is an open access article under the CC BY license (http://creativecommons. org/licenses/by/4.0/).

The androgen receptor (AR) is central in prostate tissue identity and differentiation, and controls normal growth-suppressive, prostate-specific gene expression. It also drives prostate tumorigenesis when hijacked for oncogenic transcription. The execution of growth-suppressive AR transcriptional programs in prostate cancer (PCa) and the potential for reactivation remain unclear. Here, we use a genome-wide approach to modulate canonical androgen response element (ARE) motifs-the classic DNA binding elements for AR-to delineate distinct AR transcriptional programs. We find that activating these AREs promotes differentiation and growth-suppressive transcription, potentially leading to AR+ PCa cell death, while ARE repression is tolerated by PCa cells but deleterious to normal prostate cells. Gene signatures driven by ARE activity correlate with improved prognosis and luminal phenotypes in PCa patients. Canonical AREs maintain a normal, lineage-specific transcriptional program that can be reengaged in PCa cells, offering therapeutic potential and clinical relevance.

You have accessJournal of UrologyBladder Cancer: Basic Research & Pathophysiology II (PD14)1 May 2024PD14-05 THE STROMA-RICH CONSENSUS BLADDER CANCER SUBTYPE CORRELATES WITH IMPROVED PROGNOSIS AFTER NEOADJUVANT IMMUNOTHERAPY AND RADICAL CYSTECTOMY Joep J. de Jong, Moritz Reike, Bernadett Szabados, Alex Hakansson, Andrea Necchi, Tom Powles, and Ewan Gibb Joep J. de JongJoep J. de Jong , Moritz ReikeMoritz Reike , Bernadett SzabadosBernadett Szabados , Alex HakanssonAlex Hakansson , Andrea NecchiAndrea Necchi , Tom PowlesTom Powles , and Ewan GibbEwan Gibb View All Author Informationhttps://doi.org/10.1097/01.JU.0001009472.76470.8c.05AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: In patients with muscle-invasive bladder cancer (MIBC), molecular alterations that predict benefit from neoadjuvant immunotherapy remain largely unstudied. This study aims to evaluate the ability of molecular signatures to predict outcomes after neoadjuvant atezolizumab plus radical cystectomy (RC) and to explore the biology of atezolizumab-resistant tumors. METHODS: RNA-seq data from TURBT samples from the ABACUS trial were available for gene expression analyses from N=84 patients treated with neoadjuvant atezolizumab of whom N=50 had matched residual bladder cancer RC samples (post-atezolizumab; PMID 31686036). RC samples were also profiled for N=14 patients that showed a complete pathologic response. Pre- and post-atezolizumab tumor gene expression (RNA-seq) data was classified into molecular subtypes using the consensus subtyping model. Unsupervised consensus clustering (CC) was performed to categorize the RC samples and each cluster was characterized using gene expression signatures. The PURE-01 RC cohort (N=26 post-pembrolizumab; PMID 34301456), was also characterized using the consensus model. The Kaplan-Meier method was used to estimate differences in patient outcomes. RESULTS: Unsupervised CC revealed three distinct post-atezolizumab clusters (scar-like, luminal & basal). The scar-like cluster was present in 38% (19/50) of the post-atezolizumab tumors and expressed genes associated with wound healing/scarring. Survival analyses for different classifications revealed 11 out of 12 residual stroma-rich tumors by the consensus subtyping classifier were among the scar-like cluster at RC, showing improved survival - even comparable with complete responders at RC. The stroma-rich subtype showed favorable prognosis with only one relapse event (median follow-up 13.1 months). In the PURE-01 RC cohort, 12 out of 13 cases from the scar-like cluster (also reported for pembrolizumab-treated tumors) were classified as stroma-rich by the consensus subtype, representing a subgroup with improved recurrence-free survival outcomes. CONCLUSIONS: This study expands our understanding of the biology of atezolizumab resistant MIBC and contributes to the framework for defining molecular subtypes at RC. These results further support the hypothesis that residual bladder cancer with a scar-like / stroma-rich profile may predict improved patient prognosis after neoadjuvant immunotherapy treatment and RC. Source of Funding: None © 2024 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 211Issue 5SMay 2024Page: e355 Advertisement Copyright & Permissions© 2024 by American Urological Association Education and Research, Inc.Metrics Author Information Joep J. de Jong More articles by this author Moritz Reike More articles by this author Bernadett Szabados More articles by this author Alex Hakansson More articles by this author Andrea Necchi More articles by this author Tom Powles More articles by this author Ewan Gibb More articles by this author Expand All Advertisement PDF downloadLoading ...

The androgen receptor (AR) is the central determinant of prostate tissue identity and differentiation, controlling normal, growth-suppressive prostate-specific gene expression 1 . It is also a key driver of prostate tumorigenesis, becoming "hijacked" to drive oncogenic transcription 2-5 . However, the regulatory elements determining the execution of the growth suppressive AR transcriptional program, and whether this can be reactivated in prostate cancer (PCa) cells remains unclear. Canonical androgen response element (ARE) motifs are the classic DNA binding element for AR 6 . Here, we used a genome-wide strategy to modulate regulatory elements containing AREs to define distinct AR transcriptional programs. We find that activation of these AREs is specifically associated with differentiation and growth suppressive transcription, and this can be reactivated to cause death in AR + PCa cells. In contrast, repression of AREs is well tolerated by PCa cells, but deleterious to normal prostate cells. Finally, gene expression signatures driven by ARE activity are associated with improved prognosis and luminal phenotypes in human PCa patients. This study demonstrates that canonical AREs are responsible for a normal, growth-suppressive, lineage-specific transcriptional program, that this can be reengaged in PCa cells for potential therapeutic benefit, and genes controlled by this mechanism are clinically relevant in human PCa patients.

PURPOSE:Men with high-risk prostate cancer (PCa) are treated with androgen deprivation therapy (ADT) and radiation therapy, but the disease reoccurs in 30% of patients. Biochemical recurrence of PCa after treatment is influenced by tumor hypoxia. Tumors with high levels of hypoxia are aggressive, resistant to treatment, and have increased metastatic capacity. Gene expression signatures derived from diagnostic biopsies can predict tumor hypoxia and radiosensitivity, but none are in routine clinical use, due to concerns about the applicability of these biomarkers to new patient cohorts. There has been no or limited testing in cohorts of high-risk PCa. METHODS AND MATERIALS:We generated transcriptomic data for cohorts of patients with high-risk PCa. Patients were treated with ADT followed by external beam radiation therapy with or without a brachytherapy boost. Biomarkers curated from the literature were calculated from pretreatment biopsy gene expression data. The primary endpoint for survival analyses was biochemical recurrence-free survival and the secondary endpoints were distant metastasis-free survival and overall survival. RESULTS:The performance of the selected biomarkers was poor, with none achieving prognostic significance for biochemical recurrence-free survival or distant metastasis-free survival in any cohort. The brachytherapy boost cohort received shorter durations of ADT than the conventionally fractionated or hypofractionated cohorts (Wilcoxon rank sum test, P = 2.1 × 10-18 and 2.3 × 10-10, respectively) and had increased risk of distant metastasis (log-rank test, P = 8 × 10-4). There were no consistent relationships between biomarker score and outcome for any of the endpoints. CONCLUSIONS:Hypoxia and radiosensitivity biomarkers were not prognostic in patients with high-risk PCa treated with ADT plus radiation therapy. We speculate that the lack of prognostic capability could be caused by the variable hypoxia-modifying effects of the ADT that these high-risk patients received before and during definitive treatment with radiation therapy. A deeper understanding of biomarker construction, performance, and inter-cohort transferability in relation to patient characteristics, sample handling, and treatment modalities is required before hypoxia biomarkers can be recommended for routine clinical use in the pretreatment setting.

Purpose/Objective(s) Oligometastatic castration-sensitive prostate cancer (omCSPC) is a state of limited metastatic disease that may behave more akin to locoregional rather than systemic disease. Several randomized studies have demonstrated metastasis-directed therapy (MDT) alone improves progression-free survival (PFS) over observation, but androgen deprivation therapy (ADT) represents a standard of care for metastatic CSPC. How to best integrate combinations of MDT and ADT remain unknown. Here we attempt to evaluate whether a high-risk (HiRi) mutational signature can provide discriminative information regarding the added benefit of ADT to MDT. Materials/Methods We performed a multi-institutional retrospective analysis of patients with omCSPC who underwent DNA panel sequencing treated with SABR with or without a defined course of ADT. Our primary endpoints included time to biochemical progression (ttBP) and distant metastasis free survival (DMFS) calculated from the end of treatment. Patients were classified according to the presence of a HiRi mutational signature defined as pathogenic alterations in either TP53, BRCA1/2, ATM, and Rb1. Survival analysis was performed using the Kaplan Meier method, stratified by treatment type or HiRi mutation status, and compared using the log-rank test. Interaction terms were calculated for endpoints of interest. All analyses were conducted using R. Results 144 patients were included (91 treated with MDT alone and 53 with MDT + ADT). Median ADT length was 6 months (range, 1 – 24.3 months). The use of concurrent ADT was associated with improved median ttBP of 23.3 months (95% CI, 18 months – not reached) vs 13.9 months (95% CI, 11 – 17.2 months, p = 0.03) and DMFS of 25.8 months (95% CI, 21.4 months – NR) vs 19 months (95% CI, 14.7 – 26.3 months, p = 0.05). In patients with a HiRi mutation (n=45), the addition of ADT was associated with significantly longer median ttBP of 23.3 months (95% CI, 20.9 months – NR) vs 8.8 months (95% CI, 6.8 – 12.1 months, p = <0.001) but not in patients without a HiRi mutation 18.4 months (95% CI, 16.8 – NR) vs 17.2 months (95% CI, 14.1 – 26.6 months, p = 0.48). Concurrent ADT was similarly associated with improved DMFS in patients with a HiRi mutation with median of 25.8 months (95% CI, 21.4 months – NR) vs 10.7 months (95% CI 5.6 – 19.0 months, p = 0.003) but not patients without a HiRi mutation with median NR (95% CI, 18 months – NR) vs 24.2 months (95% CI, 17.1 – 30.8 months, p = 0.31). The p-interaction value was significant for ttBP (0.02) but not DMFS (0.24). Conclusion The addition of ADT to MDT improves outcomes in unselected patients with omCSPC however appears to provide the greatest benefit to patients with a genetic alteration in TP53, BRCA1/2, ATM, or Rb1. These results may be used to provide predicative information for treatment intensification in omCSPC and should be validated in a prospective randomized setting.

ImportanceAlthough tissue-based gene expression testing has become widely used for prostate cancer risk stratification, its prognostic performance in the setting of clinical care is not well understood.ObjectiveTo develop a linkage between a prostate genomic classifier (GC) and clinical data across payers and sites of care in the US.Design, Setting, and ParticipantsIn this cohort study, clinical and transcriptomic data from clinical use of a prostate GC between 2016 and 2022 were linked with data aggregated from insurance claims, pharmacy records, and electronic health record (EHR) data. Participants were anonymously linked between datasets by deterministic methods through a deidentification engine using encrypted tokens. Algorithms were developed and refined for identifying prostate cancer diagnoses, treatment timing, and clinical outcomes using diagnosis codes, Common Procedural Terminology codes, pharmacy codes, Systematized Medical Nomenclature for Medicine clinical terms, and unstructured text in the EHR. Data analysis was performed from January 2023 to January 2024.ExposureDiagnosis of prostate cancer.Main Outcomes and MeasuresThe primary outcomes were biochemical recurrence and development of prostate cancer metastases after diagnosis or radical prostatectomy (RP). The sensitivity of the linkage and identification algorithms for clinical and administrative data were calculated relative to clinical and pathological information obtained during the GC testing process as the reference standard.ResultsA total of 92 976 of 95 578 (97.2%) participants who underwent prostate GC testing were successfully linked to administrative and clinical data, including 53 871 who underwent biopsy testing and 39 105 who underwent RP testing. The median (IQR) age at GC testing was 66.4 (61.0-71.0) years. The sensitivity of the EHR linkage data for prostate cancer diagnoses was 85.0% (95% CI, 84.7%-85.2%), including 80.8% (95% CI, 80.4%-81.1%) for biopsy-tested participants and 90.8% (95% CI, 90.5%-91.0%) for RP-tested participants. Year of treatment was concordant in 97.9% (95% CI, 97.7%-98.1%) of those undergoing GC testing at RP, and 86.0% (95% CI, 85.6%-86.4%) among participants undergoing biopsy testing. The sensitivity of the linkage was 48.6% (95% CI, 48.1%-49.1%) for identifying RP and 50.1% (95% CI, 49.7%-50.5%) for identifying prostate biopsy.Conclusions and RelevanceThis study established a national-scale linkage of transcriptomic and longitudinal clinical data yielding high accuracy for identifying key clinical junctures, including diagnosis, treatment, and early cancer outcome. This resource can be leveraged to enhance understandings of disease biology, patterns of care, and treatment effectiveness.

Abstract PURPOSE To test the safety of sequential intratumoral plus systemic intramuscular injection of poly-ICLC, and its efficacy in priming antitumor immune responses in patients with prostate cancer (PCa). EXPERIMENTAL PROCEDURES This is an open-label dose-escalating phase 1 neoadjuvant clinical trial of poly-ICLC (NCT03262103) in 12 patients diagnosed with clinically localized PCa with plans to undergo radical prostatectomy (RP). Poly-ICLC was administered intratumorally (Artemis MRI-TRUS-guided) and intramuscularly (e.g., deltoid muscle). Comprehensive transcriptional profiling of tissues, phenotypic and transcriptional analysis of longitudinally collected peripheral blood, and analysis of the prostate tumor microenvironment (TME) were performed before and after poly-ICLC treatment in order to identify innate and adaptive antitumor immune responses within the tumor and in peripheral blood. This trial is the first to use human intratumoral immunotherapy instead of systemic immunomodulation for high-risk PCa patients. RESULTS Poly-ICLC was well tolerated (safe) in all 12 patients. There were no dose-limiting toxicities or TEAE (treatment-emergent adverse events) withdrawals during treatment. Eight of 10 evaluable patients (80%) had undetectable PSA (<0.1 ng/ml) at 1 year of follow-up post-RP. Eight of 12 evaluable patients (66.7%) and 7 of 10 patients (70%) with biopsy Gleason 8-10 had a lower Gleason score in the post-treatment RP specimen. Transcriptome profiling of paired biopsy and RP specimens showed significant upregulation of gene signatures associated with immune cell infiltration and TP53-associated metabolic genes, but downregulation of gene signatures associated with metastasis and DNA replication. Genes upregulated by poly-ICLC were associated with a good prognosis. Treatment with poly-ICLC increased systemic immune responses, as demonstrated by an increase in cytolytic signatures, T- and NK-cell signatures, and NK-cell subsets in the blood. Multiplex immunohistochemistry analysis revealed a significant increase in the densities of CD4- and CD8-T cells and B cells, as well as evidence of tertiary lymphoid structures (TLS) within the TME of post-treatment RP specimens compared to baseline. CONCLUSIONS Poly-ICLC treatment can reliably transform the cold TME of PCa into a hot, immune-enhanced ecosystem. The identified baseline and response biomarkers, tertiary lymphoid structures, potential clinical benefit, and immunologic correlates require validation in larger studies. Citation Format: Sujit S. Nair, Dimple Chakravarty, Sreekumar Balan, Alexander Hakansson, Manuel Duval, Elai Davicioni, Yang Liu, Swati Bhardwaj, Tin Htwe Thin, Monica Garcia-barros, Kenneth Haines, Majd Al Shaarani, Rachel Weil, Marcia Meseck, Parita Ratnani, Monali Fatterpekar, Ivan Jambor, Elena Gonzalez-Gugel, Adam Farkas, Vinayak Wagaskar, Kacie Schlussel, Cristina Pasat-karasik, Kamala Bhatt, Zachary Dovey, Adriana Pedraza, Akriti Gupta, Dara Lundon, Ante Peros, Sneha Parekh, Lily Davenport, Xiangfu Zhang, Raghav Gupta, Macy Robison, Cynthia Knauer, Ethan Ellis, Dmitry Rykunov, Boris Reva, Babu Padanilam, Matthew D. Galsky, Rachel Brody, Mani Menon, Andres Salazar, Nina Bhardwaj, Ashutosh K. Tewari. Prostate cancer in situ autovaccination with the intratumoral viral mimic poly-ICLC: Making a cold tumor hot [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr CT023.

OBJECTIVE:To morphologically describe tertiary lymphoid structures (TLS) in prostatectomy specimens and correlate them with clinical and transcriptomic features. METHODOLOGY:A total of 72 consecutive cases of entirely submitted radical prostatectomy (RP) patients tested with the Decipher Genomic Classifier were included in the study. Images were manually annotated using QuPath tools to denote tumor regions and each cluster of TLS. Clusters of lymphocytes that were surrounded on all four sides by tumor were defined as intra-tumor TLS (IT-TLS). Clusters of lymphocytes at the leading edge of carcinoma with either the prostatic pseudocapsule or benign parenchyma at one end were defined as peri-tumor TLS (PT-TLS). A classification algorithm to distinguish lymphocytes from non-lymphocytic cells using a supervised machine learning model was used. The associations between TLS formation and 265 gene expression-based signatures were examined. RESULTS:The magnitude of total TLS correlations with primary tumor gene expression signatures was moderate (~0.35-0.5) with several HLA, T-cell and B-cell Cluster signatures, showing positive correlation with various metrics for quantification of TLS. On the other hand, immune suppressive signatures (Treg, MDSC) were negatively correlated. While signatures for macrophages, NK cells and other immune cell types were uncorrelated for the most part. PT-TLS was associated with MHC signatures while IT TLS correlated with MHC and T-cell signatures. CONCLUSIONS:Clusters of inflammatory cells in the RP specimen can be divided spatially into PT TLS and IT-TLS, each with its unique molecular correlates of tumor immune microenvironment. The presence of TLS is positively correlated with MHC signatures, T- cell and B-cell cluster signatures but, negatively correlated with immune suppressive signatures. A subset of prostate cancer demonstrate a robust inflammatory response, and warrant further characterization in larger cohorts.

A majority of subjects demonstrate a post-SBRT increase in GC score with reclassification of genomic-prognostic risk group in 58%. An enrichment of the basal-immune molecular subtype was observed following SBRT suggesting a convergence towards this biology in irradiated tumors.

375 Background: Pre-Prostatectomy MRI-Guided Stereotactic Body Radiotherapy for High-Risk Prostate Cancer Trial (PREPARE SBRT; NCT03663218) is an ongoing clinical trial testing the safety of preoperative MRI-guided SBRT for men with clinically localized high-risk prostate cancer. We sought to compare transcriptomic profiles of biopsy (Bx) specimens to acutely irradiated radical prostatectomy (RP) specimens. Methods: Biopsy and post-irradiated RP specimens from 10 subjects were examined. The median interval between the end of RT and the date of RP was 5 days. Transcriptomic profiles were generated using Decipher GRID (Veracyte, Inc). Differences in transcriptional signatures were assessed between Bx samples taken before irradiation and RP samples post-irradiation using a paired T-Test. A control cohort of transcriptomic profiles of 803 untreated Bx samples and matching RP samples from the same patients were used to account for effects in tissue preservation from the procedure different of Bx vs RP. Linear regression model with the interaction effect of cohort (SBRT vs control) by procedure (Bx vs RP) to select signatures impacted by radiation treatment. Results: Transcriptomic signatures associated with Androgen Receptor (AR) activity were significantly downregulated (p=0.002) in irradiated RP specimens compared with pre-treatment biopsies. Analysis of DNA damage repair (DDR) pathways demonstrated that nucleotide excision repair (NER) and non-homologous end joining (NHEJ) signatures were increased (p=0.002 and p=0.02, respectively) after pre-operative RT whereas homologous recombination (p=0.06) and mismatch repair (p=0.08) were not significantly different between pre-treatment and irradiated tissues. Several metabolic-associated pathways were impacted by pre-operative RT including increased glycogen metabolism (p=0.008) and a NADH-NADPH conversion (p=0.001) signature indicative of RT-induced oxidative damage. Consistent upregulation of transcriptomic features associated with increased angiogenesis (p=0.0012) and stromal remodeling (p=0.0008) was observed in irradiated samples. Conclusions: Paired transcriptomic analysis following pre-operative RT demonstrated differential upregulation of specific DDR pathways including NHEJ and NER and metabolic alterations related to oxidative stress and glycogen metabolism. AR activity signatures were decreased in response to pre-operative RT.

Background: Prostate cancer (PCa) is a clinically heterogeneous disease. The creation of an expression-based subtyping model based on prostate-specific biological processes was sought.Methods: Unsupervised machine learning of gene expression profiles from prospectively collected primary prostate tumors (training, n = 32,000; evaluation, n = 68,547) was used to create a prostate subtyping classifier (PSC) based on basal versus luminal cell expression patterns and other gene signatures relevant to PCa biology. Subtype molecular pathways and clinical characteristics were explored in five other clinical cohorts.Results: Clustering derived four subtypes: luminal differentiated (LD), luminal proliferating (LP), basal immune (BI), and basal neuroendocrine (BN). LP and LD tumors both had higher androgen receptor activity. LP tumors also had a higher expression of cell proliferation genes, MYC activity, and characteristics of homologous recombination deficiency. BI tumors possessed significant interferon ?activity and immune infiltration on immunohistochemistry. BN tumors were characterized by lower androgen receptor activity expression, lower immune infiltration, and enrichment with neuroendocrine expression patterns. Patients with LD tumors had less aggressive tumor characteristics and the longest time to metastasis after surgery. Only patients with BI tumors derived benefit from radiotherapy after surgery in terms of time to metastasis (hazard ratio [HR], 0.09; 95% CI, 0.01-0.71; n = 855). In a phase 3 trial that randomized patients with metastatic PCa to androgen deprivation with or without docetaxel (n = 108), only patients with LP tumors derived survival benefit from docetaxel (HR, 0.21; 95% CI, 0.09-0.51).Conclusions: With the use of expression profiles from over 100,000 tumors, a PSC was developed that identified four subtypes with distinct biological and clinical features.

0.95. Rates of Rb loss remained low across all Decipher subgroups, and there was no signi fi cant difference in FOLH1 expression comparing men with Decipher 0.6-0.95 and Decipher (cid:1) 0.95. CONCLUSIONS: Patients with very high Decipher (cid:1) 0.95 localized prostate cancer have a distinct molecular pro fi le, and may bene fi t from PARP inhibitors. Further investigation is required to un-derstand how these molecular signatures may drive progression and metastasis in patients who are identi fi ed as very high risk on genomic classi fi er testing.

371 Background: SBRT is a treatment option for men with prostate cancer. PREPARE-SBRT (NCT03663218) is a clinical trial testing the safety of neoadjuvant MRI-guided SBRT for men with high-risk localized prostate cancer. We leveraged paired samples from pre-treatment biopsy (Bx) and irradiated prostatectomy (RP) specimens to evaluate immune-related transcriptomic changes in irradiated tumors at acute timepoints following neoadjuvant SBRT. Methods: Transcriptomic profiles were generated using Decipher GRID (Veracyte, Inc). Differences in transcriptional signatures were assessed between Bx samples taken before treatment and RP samples post-treatment using a paired T-Test. A control cohort of transcriptomic profiles of 803 untreated Bx samples and matching RP samples from the same patients were used to account for differential effects in tissue preservation between Bx and RP. Linear regression model with the interaction effect of cohort (SBRT vs control) and by treatment status (Bx vs RP) to select signatures significantly impacted by neoadjuvant SBRT. Signatures with interaction p-value <0.01 and paired T-test value <0.05 were considered statistically significant. Results: 10 patients with paired pre-treatment Bx and post-SBRT RP specimens (n=20 samples) were analyzed with a median interval from completion of SBRT to RP of 5 days. Neoadjuvant SBRT was associated with upregulation of the T-cell inflamed signature (p=0.028) and immune190 signature (p=0.0031) supported by enrichment of transcriptomic features associated with IFN-gamma response (p=0.022), TCR signaling (p=0.0052) and antigen presentation (p=0.0048). Increased gene expression associated with effector memory/activated CD4 T-cells (p=0.0005 and p=0.0013, respectively) and effector memory/activated CD8 T-cells (p=0.0015 and p=0.013, respectively) were paralleled by a significant reduction in immunosuppressive regulatory T-cell (Treg; p=0.0015) and myeloid derived suppressor cell (MDSC; p=0.005) signatures. Additionally, macrophage-specific signatures were significantly enriched among SBRT-irradiated samples including CD68 and CSF1 gene clusters (both p=0.0041) as well as a decreased expression of the M2-to-M1 ratio signature (p=0.0052). Interestingly, WNT/β-catenin signaling, a putative oncogenic mediator of immune exclusion, was significantly downregulated in irradiated RP samples relative to pre-treatment Bx (p=2.6x10-5). Conclusions: Neoadjuvant SBRT was associated with significant immune remodeling of the irradiated prostate microenvironment. Collectively, immune-related transcriptional signatures skewed towards immune activation, increased effector T-cell and macrophage signatures and a reduction in immunosuppressive transcriptomic features.

Rationale 177Lu-PSMA ([177Lu]Lutetium-PSMA-617) therapy is an effective treatment option for patients with prostate specific membrane antigen (PSMA)-positive metastatic castration-resistant prostate cancer, but still shows a non-responder rate of approximately 30%. Combination regimes of programmed death-ligand 1 (PD-L1) inhibition and concomitant 177Lu-PSMA therapy have been proposed to increase the response rate. However, the interplay of immune landscape and 177Lu-PSMA therapy efficacy is poorly understood.Methods Between March 2018 and December 2021, a total of 168 patients were referred to 177Lu-PSMA therapy in our department and received a mean total dose of 21.9 GBq (three cycles in mean). All patients received baseline PSMA positron emission tomography to assess the PSMA uptake. The histopathological specimen of the primary prostate tumor was available with sufficient RNA passing quality control steps for genomic analysis in n=23 patients. In this subset of patients, tumor RNA transcriptomic analyses assessed 74 immune-related features in total, out of which n=24 signatures were not co-correlated and investigated further for outcome prognostication.Results In the subset of patients who received 177Lu-PSMA therapy, PD-L1 was not significantly associated with OS (HR per SD change (95% CI) 0.74 (0.42 to 1.30); SD: 0.18; p=0.29). In contrast, PD-L2 signature was positively associated with longer OS (HR per SD change 0.46 (95% CI 0.29 to 0.74); SD: 0.24; p=0.001; median OS 17.2 vs 5.7 months in higher vs lower PD-L2 patients). In addition, PD-L2 signature correlated with PSA-response (ϱ=−0.46; p=0.04). The PD-L2 signature association with OS was significantly moderated by L-Lactatdehydrogenase (LDH) levels (Cox model interaction p=0.01).Conclusion Higher PD-L2 signature might be associated with a better response to 177Lu-PSMA therapy and warrants further studies investigating additional immunotherapy. In contrast, PD-L1 was not associated with outcome. The protective effect of PD-L2 signature might be present only in men with lower LDH levels.

Dear editor, Prostate cancer (PCa) remains a major healthcare burden in men globally [1]. Most patients present with localized disease, and treatment is recommended based on risk classification systems like the National Comprehensive Cancer Network (NCCN) [2]. However, these methods are imprecise for estimating metastasis-free survival and prostate cancer-specific mortality and thus biomarkers that can predict tumor aggression are needed [3-5]. Several studies have since characterized the molecular landscape of localized PCa in White [4, 5] and Black/African-American men [6], but data is lacking in Asian men. The Chinese Prostate Cancer Genome and Epigenome Atlas (CPGEA) reported on the genomic and epigenomic landscape of 208 PCa of men from China [7]. Comparative analyses between the CPGEA cohort and data from The Cancer Genome Atlas (TCGA) revealed higher frequencies of Forkhead box A1 (FOXA1) and chromodomain-helicase DNA-binding 1 (CHD1) mutations, and lower frequencies of phosphatase and tensin homolog (PTEN) mutations and transmembrane protease serine 2-E26 transformation-specific related gene (TMPRSS2-ERG) fusion in Chinese compared with White men [7]. These preliminary findings highlight the presence of race-specific differences in molecular phenotypes of PCa. Here, we conducted a study to compare the gene expression profiles across 75 signatures between an East Asian PCa cohort of 181 patients against a propensity score-matched (PSM) cohort of 905 North American PCa patients, who were identified from a 100,529 North American PCa Genomics Resource for Intelligent Discovery database (GRID, https://decipherbio.com/grid; ClinicalTrials.gov, NCT02609269). PSM was performed at a 1:5 ratio between East Asian and North American patients using 4 factors: NCCN risk-group, clinical-stage, prostate-specific antigen (PSA), and microarray quality control scores (see Supplementary Materials and Methods). Tumors were profiled using the Decipher Genomic Classifier between 2013 and 2022 (Veracyte, San Francisco, CA, USA) [8]. Treatment details of the East Asian cohort are provided in Supplementary Materials and Methods and Supplementary Table S1. Ethics approval was obtained from the SingHealth institutional review board (IRB protocol no. 2019/2177), and written informed consent was obtained from all patients. Proportional differences of selected gene expression signatures between the East Asian and PSM-North American cohorts are summarized in Figure 1A and Supplementary Table S2. We observed fewer PCa with ERG-positivity (16.0% vs. 30.4%, P < 0.001), average androgen receptor (AR) activity scores (61.9% vs. 76.9%, P < 0.001), and PTEN loss (7.7% vs. 20.2%, P < 0.001) in East Asian than in North American patients. The Prediction Analysis of Microarray 50 (PAM50) classifier, which was first developed in breast cancer, bins PCa into luminal A or B, and basal subtypes, which may be predictive of sensitivity to androgen deprivation therapy [9]. We did not observe differences in the distribution of PAM50 luminal-basal subtypes between our East Asian and North American cohorts (luminal A: 8.3% vs. 14.0%; luminal B: 39.2% vs. 39.0%; basal: 52.5% vs. 47.0%; P = 0.092). Interestingly, when we compared the distribution of luminal-basal PCa based on the Prostate Subtyping Classifier, which revised the luminal-basal classification of PCa into luminal differentiated, luminal proliferating, basal immune, and basal neuroendocrine [10], we observed significantly higher proportions of luminal proliferating (25.4% vs. 14.0%, P < 0.001) and basal neuroendocrine subtypes (33.7% vs. 27.9%, P < 0.001) in East Asian than in North American patients. Gene expression signatures relating to angiogenesis and the immune microenvironment also differed between PCa of East Asian and North American patients (Figure 1B). We observed lower angiogenesis scores (median: -0.38 vs. -0.10, P < 0.001) and higher median scores of immune suppression signatures (myeloid-derived suppressor cells: 0.07 vs. -0.04, P < 0.001; regulatory T cells: 0.13 vs. 0.09, P < 0.001; programmed death 1 ligand 2: 0.18 vs. 0.15, P = 0.004) in East Asian than in North American patients. These corresponded to a lower median activated CD8 signature score in the former than in the latter (0.06 vs. 0.12, P < 0.001). To better understand the significance of these differences, we tested for associations between the PAM50 and Prostate Subtyping Classifier luminal-basal status and selected gene signatures of ERG positivity, PTEN loss, and AR activity. When stratified by PAM50 status, we observed that basal tumors were strongly associated with a low rate of ERG positivity, a high rate of PTEN loss, and low AR activity in both East Asian and PSM-North American cohorts (Supplementary Figure S1). By the Prostate Subtyping Classifier model, luminal differentiated and luminal proliferating tumors had lower rates of PTEN loss compared with basal immune and basal neuroendocrine tumors, and basal neuroendocrine PCa had the lowest AR activity in both cohorts (Supplementary Figure S2). Next, we generated a heatmap of hallmark signatures ordered by the Prostate Subtyping Classifier subtypes and cohorts (Figure 1C). Similar trends in hallmarks associated with the Prostate Subtyping Classifier subtypes were observed in both East Asian and North American cohorts, with basal tumors having higher expression of p53 and hypoxia-related genes, while luminal proliferating tumors had higher expression of DNA repair genes. Finally, we investigated if the different molecular subtypes were prognostic for distant metastasis-free survival (DMFS) in the East Asian cohort. Patients with luminal A and luminal differentiated tumors had the most favorable DMFS among the luminal-basal subtypes (Supplementary Figure S3A-B). Among the microenvironment-related signatures, we observed that patients with high angiogenesis signature scores had an inferior DMFS in our cohort (Hazard Ratio [HR] 3.79, 95% CI = 1.00-14.41, P = 0.036, Supplementary Figure S3C). Interestingly, angiogenesis was able to sub-stratify luminal B tumors for DMFS. Patients with luminal B PCa and high angiogenesis scores had the worst DMFS, compared with the other 3 subgroups (HRref non-luminal B + angiogenesis low = 6.56, 95% CI = 1.25-34.51, P = 0.025, Figure 1D). Several limitations of the present study deserve mention. First, these findings in our limited East Asian cohort, which was comprised of mostly NCCN high-risk PCa patients, ought to be validated in other Asian cohorts, with balanced composition of the different NCCN risk groups. Second, while we recruited subjects from different geographical regions, we could not control for race effects; while 90.1% of subjects in the East Asian cohort were Chinese, we lacked curated physician-reported race data in the North American cohort. Third, there is a need to determine the corresponding therapeutic implications of the race-specific phenotypic and microenvironmental differences. Such analyses can only be done using well-curated cohorts from prospective registries or clinical trials, for which archival tissues are available for molecular profiling. To summarize, we uncovered fewer ERG-positive, PTEN-loss, and high AR activity tumors in East Asian than in North American PCa patients. Additionally, there was a higher proportion of luminal proliferating and basal neuroendocrine PCa in East Asian than in North American patients based on the Prostate Subtyping Classifier model. Interrogation of the tumor microenvironment revealed lower levels of angiogenesis and an overall immune suppressive state in East Asian than in North American PCa patients. Of clinical relevance, high angiogenesis and luminal B tumors had the worst DMFS in our East Asian cohort. Taken together, our results showcased race-specific differences in gene expression profiles of PCa from East Asian and North American patients, adding to the literature on genomic and epigenomic inter-racial heterogeneity of localized PCa. These data posit the concept that demographic host factors are highly relevant in PCa tumorigenesis, and support a larger pan-race meta-analysis. Preliminary results of this study were presented at the ASCO GU symposium 2022, San Francisco and the 2022 ESMO Congress, Paris. Study conception and design: MLKC, ED Patient recruitment and data acquisition: All authors Data analysis and interpretation: All authors Statistical analyses: MLKC, AH, EHWO, BHH, YL, ED Obtained funding: MLKC Administrative, technical, or material support: MLKC, EHWO, ED, LYK Study supervision: MLKC, ED Drafting of manuscript: MLKC, AH, EHWO, BHH, JJM, YL, ED, LYK Approval of final manuscript: All authors The authors thank the patients and their families for their participation in this study. Melvin L.K. Chua reports personal fees from Astellas, Bayer, Pfizer, MSD, AstraZeneca, Varian, Janssen, IQVIA, Telix Pharmaceuticals; non-financial support from AstraZeneca; non-financial support from Veracyte Inc; grants from Ferring; consults for immunoSCAPE Inc.; and is a co-inventor of the patent of a High Sensitivity Lateral Flow Immunoassay For Detection of Analyte in Sample (10202107837T), Singapore, and serves on the Board of Directors of Digital Life Line Pte Ltd that owns the licensing agreement of the patent, outside the submitted work. Ravindran Kanesvaran received personal fees from Astella, BMS, Ipsen, J&J, Merck, Novartis, Amgen, and Eisai. Alexander Hakansson, Julian Ho, Xin Zhao, Elai Davicioni and Yang Liu are employees of Veracyte, Inc. All other authors do not declare any conflicts of interests. The article does not contain any person's identifiable data. This study was approved by the SingHealth Institutional Review Board (IRB protocol no. 2019/2177), and all patients provided written informed consent. Melvin L.K. Chua is supported by the National Medical Research Council Singapore Clinician Scientist Award (NMRC/CSA-INV/0027/2018, CSAINV20nov-0021), the Duke-NUS Oncology Academic Program Goh Foundation Proton Research Program, NCCS Cancer Fund, and the Kua Hong Pak Head and Neck Cancer Research Program. The funding organizations had no role in the design and conduct of this trial; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. Data can be made available for bona fide researchers who request it from the authors. The data used in this manuscript will be deposited in the institutional repository at the National Cancer Centre Singapore. 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