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Abstract Background Genomic biomarkers that predict response to anti-PD1 therapy in prostate cancer are needed. Frameshift mutations are predicted to generate more neoantigens than missense mutations; therefore, we hypothesized that the number or proportion of tumor frameshift mutations would correlate with response to anti-PD1 therapy in prostate cancer. Methods To enrich for response to anti-PD1 therapy, we assembled a multicenter cohort of 65 men with mismatch repair-deficient (dMMR) prostate cancer. Patient characteristics and outcomes were determined by retrospective chart review. Clinical somatic DNA sequencing was used to determine tumor mutational burden (TMB), frameshift mutation burden, and frameshift mutation proportion (FSP), which were correlated to outcomes on anti-PD1 treatment. We subsequently used data from a clinical trial of pembrolizumab in patients with nonprostatic dMMR cancers of various histologies as a biomarker validation cohort. Results Nineteen of 65 patients with dMMR metastatic castration-resistant prostate cancer were treated with anti-PD1 therapy. The PSA50 response rate was 65%, and the median progression-free survival (PFS) was 24 (95% confidence interval 16–54) weeks. Tumor FSP, more than overall TMB, correlated most strongly with prolonged PFS and overall survival (OS) on anti-PD1 treatment and with density of CD8+ tumor-infiltrating lymphocytes. High FSP similarly identified patients with longer PFS as well as OS on anti-PD1 therapy in a validation cohort. Conclusion Tumor FSP correlated with prolonged efficacy of anti-PD1 treatment among patients with dMMR cancers and may represent a new biomarker of immune checkpoint inhibitor sensitivity. Implications for Practice Given the modest efficacy of immune checkpoint inhibition (ICI) in unselected patients with advanced prostate cancer, biomarkers of ICI sensitivity are needed. To facilitate biomarker discovery, a cohort of patients with DNA mismatch repair-deficient (dMMR) prostate cancer was assembled, as these patients are enriched for responses to ICI. A high response rate to anti-PD1 therapy in these patients was observed; however, these responses were not durable in most patients. Notably, tumor frameshift mutation proportion (FSP) was identified as a novel biomarker that was associated with prolonged response to anti-PD1 therapy in this cohort. This finding was validated in a separate cohort of patients with nonprostatic dMMR cancers of various primary histologies. This works suggests that FSP predicts response to anti-PD1 therapy in dMMR cancers, which should be validated prospectively in larger independent cohorts.

PURPOSE In prostate cancer, inactivating CDK12 mutations lead to gene fusion–induced neoantigens and possibly sensitivity to immunotherapy. We aimed to clinically, pathologically, and molecularly characterize CDK12-aberrant prostate cancers. METHODS We conducted a retrospective multicenter study to identify patients with advanced prostate cancer who harbored somatic loss-of-function CDK12 mutations. We used descriptive statistics to characterize their clinical features and therapeutic outcomes (prostate-specific antigen [PSA] responses, progression-free survival [PFS]) to various systemic therapies, including sensitivity to poly (ADP-ribose) polymerase and PD-1 inhibitors. RESULTS Sixty men with at least monoallelic (51.7% biallelic) CDK12 alterations were identified across nine centers. Median age at diagnosis was 60.5 years; 71.7% and 28.3% were white and nonwhite, respectively; 93.3% had Gleason grade group 4-5; 15.4% had ductal/intraductal histology; 53.3% had metastases at diagnosis; and median PSA was 24.0 ng/mL. Of those who underwent primary androgen deprivation therapy for metastatic hormone-sensitive disease (n = 59), 79.7% had a PSA response, and median PFS was 12.3 months. Of those who received first-line abiraterone and enzalutamide for metastatic castration-resistant prostate cancer (mCRPC; n = 34), 41.2% had a PSA response, and median PFS was 5.3 months. Of those who received a first taxane chemotherapy for mCRPC (n = 22), 31.8% had a PSA response, and median PFS was 3.8 months. Eleven men received a PARP inhibitor (olaparib [n = 10], rucaparib [n = 1]), and none had a PSA response (median PFS, 3.6 months). Nine men received a PD-1 inhibitor as fourth- to sixth-line systemic therapy (pembrolizumab [n = 5], nivolumab [n = 4]); 33.3% had a PSA response, and median PFS was 5.4 months. CONCLUSION CDK12-altered prostate cancer is an aggressive subtype with poor outcomes to hormonal and taxane therapies as well as to PARP inhibitors. A proportion of these patients may respond favorably to PD-1 inhibitors, which implicates CDK12 deficiency in immunotherapy sensitivity.

BackgroundThe progression of prostate cancer is a complex, multistep process that involves molecular alterations in cells of the tumor and the microenvironment, with associated interactions between the stroma and epithelium. Genomic expression analyses of stromal infiltration markers were performed to determine the significance thereof in prostate cancer.MethodsGenome‐wide expression profiles of formalin‐fixed, paraffin‐embedded radical prostatectomy samples were evaluated from a prospective registry cohort (n = 5239) and 3 retrospective institutional cohorts (n = 1135). Two independent stromal gene expression signatures implied stromal infiltration. Cox proportional hazards regression defined the association between stromal infiltration expression and metastasis‐free survival (MFS).ResultsStromal expression scores were correlated with stromal signature genes and with other key stromal markers (CAV1, VIM, and TAGLN), basal activity, and CD3 and CD4 immune biomarkers (r > 0.5 for all). The top decile of stromal expression was associated with high genomic risk scores (Decipher ≥ 0.6) , high Cancer of the Prostate Risk Assessment–Postsurgical scores, Gleason 9 to 10 disease, and a higher risk for metastasis (hazard ratio, 2.35; 95% CI, 1.37‐4.02; P = .001). A higher stromal infiltration score was also associated with decreased expression of DNA repair genes and higher radiation sensitivity genomic scores. Postoperative radiation therapy (RT) was associated with an MFS benefit for patients with high stromal scores, but not for patients with low stromal scores (Pinteraction = .02).ConclusionsExpression of stromal infiltration markers is correlated with prostate cancer aggressiveness/progression and may be predictive of a response to RT. Stromal infiltration markers should be studied and considered for incorporation into clinical prognostication and decision making.

Abstract Purpose: The heterogeneity of androgen receptor (AR)-activity (AR-A) is well-characterized in heavily treated metastatic castration-resistant prostate cancer (mCRPC). However, the diversity and clinical implications of AR-A in treatment-naïve primary prostate cancer is largely unknown. We sought to characterize AR-A in localized prostate cancer and understand its molecular and clinical implications. Experimental Design: Genome-wide expression profiles from prostatectomy or biopsy samples from 19,470 patients were used, all with independent pathology review. This was comprised of prospective discovery (n = 5,239) and validation (n = 12,728) cohorts, six retrospective institutional cohorts with long-term clinical outcomes data (n = 1,170), and The Cancer Genome Atlas (n = 333). Results: A low AR-active subclass was identified, which comprised 9%–11% of each cohort, and was characterized by increased immune signaling, neuroendocrine expression, and decreased DNA repair. These tumors were predominantly ERG and basal subtype. Low AR-active tumors had significantly more rapid development of recurrence or metastatic disease across cohorts, which was maintained on multivariable analysis [HR, 2.61; 95% confidence interval (CI), 1.22–5.60; P = 0.014]. Low AR-active tumors were predicted to be more sensitive to PARP inhibition, platinum chemotherapy, and radiotherapy, and less sensitive to docetaxel and androgen-deprivation therapy. This was validated clinically, in that low AR-active tumors were less sensitive to androgen-deprivation therapy (OR, 0.41; 95% CI, 0.21–0.80; P = 0.008). Conclusions: Leveraging large-scale transcriptomic data allowed the identification of an aggressive subtype of treatment-naïve primary prostate cancer that harbors molecular features more analogous to mCRPC. This suggests that a preexisting subgroup of patients may have tumors that are predisposed to fail multiple current standard-of-care therapies and warrant dedicated therapeutic investigation.

PURPOSE Multiparametric magnetic resonance imaging (mpMRI) is used widely for prostate cancer (PCa) evaluation. Approximately 35% of aggressive tumors, however, are not visible on mpMRI. We sought to identify the molecular alterations associated with mpMRI-invisible tumors and determine whether mpMRI visibility is associated with PCa prognosis. METHODS Discovery and validation cohorts included patients who underwent mpMRI before radical prostatectomy and were found to harbor both mpMRI-visible (Prostate Imaging and Reporting Data System 3 to 5) and -invisible (Prostate Imaging and Reporting Data System 1 or 2) foci on surgical pathology. Next-generation sequencing was performed to determine differential gene expression between mpMRI-visible and -invisible foci. A genetic signature for tumor mpMRI visibility was derived in the discovery cohort and assessed in an independent validation cohort. Its association with long-term oncologic outcomes was evaluated in a separate testing cohort. RESULTS The discovery cohort included 10 patients with 26 distinct PCa foci on surgical pathology, of which 12 (46%) were visible and 14 (54%) were invisible on preoperative mpMRI. Next-generation sequencing detected prioritized genetic mutations in 14 (54%) tumor foci (n = 8 mpMRI visible, n = 6 mpMRI invisible). A nine-gene signature (composed largely of cell organization/structure genes) associated with mpMRI visibility was derived (area under the curve = 0.89), and the signature predicted MRI visibility with 75% sensitivity and 100% specificity (area under the curve = 0.88) in the validation cohort. In the testing cohort (n = 375, median follow-up 8 years) there was no significant difference in biochemical recurrence, distant metastasis, or cancer-specific mortality in patients with predicted mpMRI-visible versus -invisible tumors (all P > .05). CONCLUSION Compared with mpMRI-invisible disease, mpMRI-visible tumors are associated with underexpression of cellular organization genes. mpMRI visibility does not seem to be predictive of long-term cancer outcomes, highlighting the need for biopsy strategies that detect mpMRI-invisible tumors.

Abstract Purpose: Currently, no genomic signature exists to distinguish men most likely to progress on adjuvant androgen deprivation therapy (ADT) after radical prostatectomy for high-risk prostate cancer. Here we develop and validate a gene expression signature to predict response to postoperative ADT. Experimental Design: A training set consisting of 284 radical prostatectomy patients was established after 1:1 propensity score matching metastasis between adjuvant-ADT (a-ADT)-treated and no ADT–treated groups. An ADT Response Signature (ADT-RS) was identified from neuroendocrine and AR signaling–related genes. Two independent cohorts were used to form three separate data sets for validation (set I, n = 232; set II, n = 435; set III, n = 612). The primary endpoint of the analysis was postoperative metastasis. Results: Increases in ADT-RS score were associated with a reduction in risk of metastasis only in a-ADT patients. On multivariable analysis, ADT-RS by ADT treatment interaction term remained associated with metastasis in both validation sets (set I: HR = 0.18, Pinteraction = 0.009; set II: HR = 0.25, Pinteraction = 0.019). In a matched validation set III, patients with Low ADT-RS scores had similar 10-year metastasis rates in the a-ADT and no-ADT groups (30.1% vs. 31.0%, P = 0.989). Among High ADT-RS patients, 10-year metastasis rates were significantly lower for a-ADT versus no-ADT patients (9.4% vs. 29.2%, P = 0.021). The marginal ADT-RS by ADT interaction remained significant in the matched dataset (Pinteraction = 0.035). Conclusions: Patients with High ADT-RS benefited from a-ADT. In combination with prognostic risk factors, use of ADT-RS may thus allow for identification of ADT-responsive tumors that may benefit most from early androgen blockade after radical prostatectomy. We discovered a gene signature that when present in primary prostate tumors may be useful to predict patients who may respond to early ADT after surgery. Clin Cancer Res; 24(16); 3908–16. ©2018 AACR.

Abstract Background Treatment-induced neuroendocrine prostate cancer (tNEPC) is an aggressive variant of late-stage metastatic castrate-resistant prostate cancer that commonly arises through neuroendocrine transdifferentiation (NEtD). Treatment options are limited, ineffective, and, for most patients, result in death in less than a year. We previously developed a first-in-field patient-derived xenograft (PDX) model of NEtD. Longitudinal deep transcriptome profiling of this model enabled monitoring of dynamic transcriptional changes during NEtD and in the context of androgen deprivation. Long non-coding RNA (lncRNA) are implicated in cancer where they can control gene regulation. Until now, the expression of lncRNAs during NEtD and their clinical associations were unexplored. Results We implemented a next-generation sequence analysis pipeline that can detect transcripts at low expression levels and built a genome-wide catalogue (n = 37,749) of lncRNAs. We applied this pipeline to 927 clinical samples and our high-fidelity NEtD model LTL331 and identified 821 lncRNAs in NEPC. Among these are 122 lncRNAs that robustly distinguish NEPC from prostate adenocarcinoma (AD) patient tumours. The highest expressed lncRNAs within this signature are H19, LINC00617, and SSTR5-AS1. Another 742 are associated with the NEtD process and fall into four distinct patterns of expression (NEtD lncRNA Class I, II, III, and IV) in our PDX model and clinical samples. Each class has significant (z-scores >2) and unique enrichment for transcription factor binding site (TFBS) motifs in their sequences. Enriched TFBS include (1) TP53 and BRN1 in Class I, (2) ELF5, SPIC, and HOXD1 in Class II, (3) SPDEF in Class III, (4) HSF1 and FOXA1 in Class IV, and (5) TWIST1 when merging Class III with IV. Common TFBS in all NEtD lncRNA were also identified and include E2F, REST, PAX5, PAX9, and STAF. Interrogation of the top deregulated candidates (n = 100) in radical prostatectomy adenocarcinoma samples with long-term follow-up (median 18 years) revealed significant clinicopathological associations. Specifically, we identified 25 that are associated with rapid metastasis following androgen deprivation therapy (ADT). Two of these lncRNAs (SSTR5-AS1 and LINC00514) stratified patients undergoing ADT based on patient outcome. Discussion To date, a comprehensive characterization of the dynamic landscape of lncRNAs during the NEtD process has not been performed. A temporal analysis of the PDX-based NEtD model has for the first time provided this dynamic landscape. TFBS analysis identified NEPC-related TF motifs present within the NEtD lncRNA sequences, suggesting functional roles for these lncRNAs in NEPC pathogenesis. Furthermore, select NEtD lncRNAs appear to be associated with metastasis and patients receiving ADT. Treatment-related metastasis is a clinical consequence of NEPC tumours. Top candidate lncRNAs FENDRR, H19, LINC00514, LINC00617, and SSTR5-AS1 identified in this study are implicated in the development of NEPC. We present here for the first time a genome-wide catalogue of NEtD lncRNAs that characterize the transdifferentiation process and a robust NEPC lncRNA patient expression signature. To accomplish this, we carried out the largest integrative study that applied a PDX NEtD model to clinical samples. These NEtD and NEPC lncRNAs are strong candidates for clinical biomarkers and therapeutic targets and warrant further investigation.

93 Background: A key eligibility criterion in many active surveillance (AS) programs is that the biopsy exhibit only Gleason pattern 3 (G3) for a Gleason score of 6 or less. However, 25 to 35% of biopsy Gleason 6 is upgraded to Gleason 7 or higher in the prostatectomy (RP) specimen. Thus, there is a great need for biomarkers that, when measured on G3 tissue in a Gleason 6 biopsy, can predict the presence of unsampled higher grade tumor in the whole prostate. We evaluated PTEN loss by immunohistochemistry (IHC), and PTEN deletion, chromosome 8q (MYC) gain and 8p (LPL) loss by fluorescence in situ hybridization (FISH) for their ability to predict unsampled G4 tumor. Methods: A tissue microarray (TMA) was constructed of RP tissue from three groups of patients (n=50 per group) whose prostates exhibited only Gleason 3+3, only 3+4, or only 4+3 tumor, matched on age, year of RP, and race. In each patient, multiple cores sampled only from areas of G3 were evaluated for PTEN deletion by FISH, PTEN loss by IHC, and chromosome 8p/8q alterations by FISH. Biomarker results were compared between Gleason 6 versus 7 tumors using conditional logistic regression. Results: Patients underwent RP in 2001 to 2009, had median age 60, and median prostate-specific antigen 5.2; 63% of tumors were organ confined. In univariate analyses 8q gain (odds ratio OR=8.9, p<.0001), 8p loss (OR=6.9, p<.0001), PTEN loss by IHC (OR=5.7, p=.025), but not PTEN deletion by FISH (OR=1.5, p=.477) were significantly more common in G3 cores from Gleason 7 tumors than G3 cores from Gleason 6 tumors. In multivariable analyses, 8q gain (OR=6.2, p=.002) and 8p loss (OR=5.2, p=.0002) remained highly significant. At least one high risk biomarker (8q gain, 8p loss, PTEN loss, or PTEN deletion) was found in 35.7% of Gleason 3+3 versus 77.1% of Gleason 3+4 versus 91.3% of Gleason 4+3 tumors, p<.0001. Adjustment for confounding factors did not change the results. Conclusions: Chromosomal 8q gains (MYC), 8p loss (LPL), and PTEN loss measured in Gleason G3 TMA cores strongly differentiate whether the core comes from Gleason 6 or Gleason 7 tumor. If validated in biopsy Gleason 6 cores to predict prostatectomy Gleason 7 tumor these biomarkers could facilitate safe selection of men for active surveillance.