Davicioni, Elai

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.

2 Background: Significant genomic diversity exists in the androgen receptor ( AR) and its activity (AR-A) in mCRPC. In localized prostate cancer, the biologic, prognostic, and therapeutic clinical implications of AR-A heterogeneity have yet to be interrogated Methods: Genome-wide expression profiles of FFPE RP or biopsy tumor samples were evaluated from a prospective registry cohort (n = 5,239, NCT02609269) and six retrospective institutional cohorts (n = 1,170). AR-A was calculated based on expression of 9 targets of AR.. Results: Utilizing 6,409 localized prostate adenocarcinomas with full transcriptomic data, we found there was marked inter-individual transcriptomic diversity in AR and AR-A expression, and weak correlation between them (r = 0.08 to 0.36 based on cohort), in contrast to mCRPC that has a strong correlation between AR and AR-A expression (r = 0.76). Additionally, serum PSA had no correlation to intratumoral AR-A (r = 0.06). Unsupervised hierarchical clustering identified a distinct subclass of low AR-A prostate tumors, which had increased markers of immunogenicity (decreased T-regs and MDSCs, and increased CD3 effector T-cells), increased neuroendocrine marker expression ( NCAM1, ENO2, and SCG2), and decreased DNA repair pathway expression (all p < 0.001). Clinically, low AR-A tumors had more rapid development of metastatic disease in three independent cohorts, were more prone to develop resistance to hormonal therapy and develop CRPC, and were found at an increased frequency in African-American men. Interrogating in vitro drug sensitivity analyses utilizing the NCI-60 panel, low AR-A tumors appear more sensitive to platinum chemotherapy and PARP inhibition, and less sensitive to hormone therapy and taxanes. Conclusions: The diversity in AR-signaling in localized prostate cancer represents important biological heterogeneity that is both prognostic and predictive of treatment response. These findings are provocative in that low AR-A tumors may be more susceptible to immunotherapy, PARP inhibition, platinum chemotherapy, and/or radiotherapy. Patients with low AR-A tumors warrant dedicated biomarker enhanced clinical trials.

125 Background: Men with lymph node involvement (LNI) at prostatectomy (RP) are at high risk of dying from prostate cancer. However, survival following RP is highly variable, with some men apparently cured. Nomograms developed for men with LNI have been based on series where all or the vast majority of men received adjuvant treatment. Because administration of adjuvant treatment is not universal, even for LNI, we evaluated whether the Decipher genomic classifier (GC) can improve upon clinical models to predict metastasis within 5 years (MET5) and prostate cancer specific mortality within 10 years (PCSM10) in a cohort of LNI patients, the majority of whom did not receive adjuvant treatment. Methods: 141 patients from 4 institutions (Johns Hopkins, Mayo Clinic, Leuven, MD Anderson) had LNI at RP, had adequate tissue and clinical data for analysis of MET5, and 86 were analyzed for PCSM10. 43% of men received adjuvant therapy. RP tumor tissue was analyzed by Affymetrix Human Exon 1.0 ST GeneChip; the GC was calculated based on 22 genes in the previously trained and validated algorithm. Logistic regression evaluated whether the GC, dichotomized as high risk (GC score > 0.6) vs low-intermediate risk (≤0.6), improved prediction of MET5 and PCSM10 beyond that achieved with established clinical prognostic factors. Results: 62 men (43%) developed MET5, and 35 (41%) developed PCSM10. For both MET5 and PCSM10 CAPRA-S, number of positive lymph nodes, and age were significant; adjuvant therapy was not significant. GC was a significant independent strong prognostic factor when added to the clinical model for prediction of MET5, odds ratio = 4.04 (95% CI: 1.48, 11.02), p = 0.006, and prediction of PCSM10, odds ratio = 6.71 (95% CI: 2.01, 22.38), p = 0.002. Addition of GC to the clinical model improved the AUC from 0.77 to 0.79 for MET5, and from 0.65 to 0.74 for PCSM10. Conclusions: The Decipher GC significantly improves upon clinical variables to predict metastasis and prostate cancer specific mortality in men at high risk due to LNI. This is the first study to show a genomic classifier predicts outcomes in men with LNI; validation is needed to determine if Decipher can improve treatment decisions in men with LNI.

Abstract Androgen receptor (AR) signaling is a key driver of prostate cancer, and androgen-deprivation therapy (ADT) is a standard treatment for patients with advanced and metastatic disease. However, patients receiving ADT eventually develop incurable castration-resistant prostate cancer (CRPC). Here, we report that the chromatin modifier LSD1, an important regulator of AR transcriptional activity, undergoes epigenetic reprogramming in CRPC. LSD1 reprogramming in this setting activated a subset of cell-cycle genes, including CENPE, a centromere binding protein and mitotic kinesin. CENPE was regulated by the co-binding of LSD1 and AR to its promoter, which was associated with loss of RB1 in CRPC. Notably, genetic deletion or pharmacological inhibition of CENPE significantly decreases tumor growth. Our findings show how LSD1-mediated epigenetic reprogramming drives CRPC, and they offer a mechanistic rationale for its therapeutic targeting in this disease. Cancer Res; 77(20); 5479–90. ©2017 AACR.

Abstract Purpose: Current clinical parameters do not stratify indolent from aggressive prostate cancer. Aggressive prostate cancer, defined by the progression from localized disease to metastasis, is responsible for the majority of prostate cancer–associated mortality. Recent gene expression profiling has proven successful in predicting the outcome of prostate cancer patients; however, they have yet to provide targeted therapy approaches that could inhibit a patient's progression to metastatic disease. Experimental Design: We have interrogated a total of seven primary prostate cancer cohorts (n = 1,900), two metastatic castration-resistant prostate cancer datasets (n = 293), and one prospective cohort (n = 1,385) to assess the impact of TOP2A and EZH2 expression on prostate cancer cellular program and patient outcomes. We also performed IHC staining for TOP2A and EZH2 in a cohort of primary prostate cancer patients (n = 89) with known outcome. Finally, we explored the therapeutic potential of a combination therapy targeting both TOP2A and EZH2 using novel prostate cancer–derived murine cell lines. Results: We demonstrate by genome-wide analysis of independent primary and metastatic prostate cancer datasets that concurrent TOP2A and EZH2 mRNA and protein upregulation selected for a subgroup of primary and metastatic patients with more aggressive disease and notable overlap of genes involved in mitotic regulation. Importantly, TOP2A and EZH2 in prostate cancer cells act as key driving oncogenes, a fact highlighted by sensitivity to combination-targeted therapy. Conclusions: Overall, our data support further assessment of TOP2A and EZH2 as biomarkers for early identification of patients with increased metastatic potential that may benefit from adjuvant or neoadjuvant targeted therapy approaches. Clin Cancer Res; 23(22); 7072–83. ©2017 AACR.

Abstract Aims: Androgen-targeted therapies (ATTs) are the mainstay treatment for metastatic prostate cancer (PCa). However, ATTs promote adaptation of tumour cells and lead to castration resistant disease (CRPC). We have recently identified the cell surface receptor, Neuropilin-1 (NRP1) as increased during EMT and in CRPC. However, the role of NRP1 in the prostate epithelium is poorly understood. This study aims to determine whether the inhibition of NRP1 will be a feasible therapeutic strategy for blocking PCa metastasis and therapy resistance. Methods: qPCR and western blotting were used to assess NRP1 expression in PCa cell lines. NRP1 expression in CRPC was assessed using a murine LNCaP xenograft model of castration. NRP1 was knocked down with shRNA sequences from the pLKO.1 lentiviral construct. For metastasis assays, PC3 cells were microinjected into the zebrafish yolk sac and metastatic dissemination imaged 5 days later. NRP1 expression in radical prostatectomy (RP) samples from Mayo Clinic (545 patients) and Johns Hopkins Medical Institutions (JHMI; 188 patients) cohorts was quantified by Affymetrix exon arrays and multivariable analysis performed. Wound scratch migration and invasion assays were performed with the WoundMaker™ tool and IncuCyte™ FLR imaging systems. Results: NRP1 levels were elevated in humanCRPC xenografts, metastatic and castrate resistant clinical PCa samples (p &lt;0.0001), and PCa cell lines. NRP1 suppression significantly reduced metastasis of human xenografts in zebrafish and the migratory and invasive behaviour of metastatic PCa cells (p=0.0002). Multivariable analysis identified NRP1 as a significant independent prognostic indicator of metastasis and prostate cancer specific mortality in two large clinical cohorts (Mayo Clinic and JHMI; p=0.008/0.048 and 0.013/0,034 respectively). We show that NRP1 knockdown promotes E-Cadherin expression and loss of vimentin in mesenchymal PCa cells. Conclusion: These results will provide the preclinical data necessary to rationalise the use of anti-NRP1 directed adjuvant therapies for clinical use in PCa patients receiving ATTs, and will pave the way for larger scale preclinical and clinical trials in the PCa setting. Citation Format: Marianna Volpert, Brian Tse, Ellca Ratther, Nataly Stylianou, Mannan Nouri, Melanie Lehman, Stephen McPherson, Mani Roshan-Moniri, Mandeep Takhar, Nicholas Erho, Mohamed Alshalafa, Elai Davicioni, Robert Jenkins, Ashley Ross, Jeffrey Karnes, Robert Den, Ladan Fazli, Martin Gleave, Elizabeth Williams, Paul Rennie, Ralph Buttyan, Pamela Russell, Colleen Nelson, Brett Hollier. Neuropilin-1 is up-regulated in the adaptive response of prostate tumors to androgen targeted therapies and is prognostic of metastatic progression and patient mortality [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 4908. doi:10.1158/1538-7445.AM2017-4908

3 Background: There is a clear need to develop a clinically relevant molecular subtyping approach for prostate cancer. We hypothesized that prostate cancer can be subtyped based on luminal versus basal lineage. Methods: We applied the PAM50 classifier, which is used clinically to identify luminal and basal cancers in breast cancer, to subtype a total of 3,782 prostate cancer samples using a high-density microarray platform run in a CLIA-certified laboratory. We examined the associations of these subtypes and clinical outcomes. Results: We demonstrate that PAM50 segregates prostate cancer into three reproducible subtypes in both retrospective cohorts and on prospective validation: luminal A (33.3%-34.3%), luminal B (28.5%-32.6%), and basal (34.1%-37.1%). Luminal B prostate cancers exhibited the worst clinical prognoses, followed by basal and luminal A subtypes (10-year biochemical recurrence-free survival: 29/39/41%; distant metastasis-free survival: 53/73/73%; prostate cancer-specific survival: 78/86/89%; overall survival: 69/80/82% respectively) on both univariable and multivariable analyses accounting for standard clinicopathologic prognostic factors. Known luminal lineage markers, such as NKX3.1 and KRT18, and the basal lineage CD49f signature, were enriched in luminal- and basal-like cancers respectively, demonstrating the connection between these subtypes and established prostate cancer biology. While both luminal-like subtypes were associated with increased AR expression and signaling, only luminal B prostate cancers were significantly associated with post-operative response to androgen deprivation therapy (ADT) in a subset analysis matching patients based on clinicopathologic variables (interaction p = 0.006, luminal B 10-year metastasis: 33% (treated) vs. 55% (untreated), non-luminal B: 37% (treated) vs. 21% (untreated)). Conclusions: These findings contribute novel insight into the biology of prostate cancer, and provide translatable clinical tools for personalizing post-operative ADT for patients with prostate cancer. Similar to breast cancer, these findings suggest that luminal/basal subtyping may be useful in treatment selection in prostate cancer.

142 Background: Despite documented oncological benefit, postoperative adjuvant radiotherapy (aRT) utilization in prostate cancer (PCa) patients is still limited in the US. We aimed to develop and internally validate a risk stratification tool incorporating the Decipher score, along with routinely available clinicopathologic features, to identify patients who would benefit the most from aRT. Methods: Our cohort included a total of 512 PCa patients treated with RP at one of four US academic centers between 1990-2010. All patients had ≥ pT3a disease, positive margins, and/or pathologic lymph node invasion (LNI). Multivariable Cox regression analysis (MVA) tested the relationship between available predictors (including Decipher score) and clinical recurrence (CR), which were then used to develop a novel risk stratification tool. Our study adhered to the TRIPOD guidelines for development of prognostic models. Results: Overall, 21.9% patients received aRT. Median follow-up in censored patients was 8.3 years. The 10-year CR rate was 4.9% vs. 17.4% in patients treated with aRT vs. initial observation (p < 0.001). Pathological T3b/T4 stage, Gleason score 8-10, LNI and Decipher score > 0.6 were independent predictors of CR (all p < 0.01) Cumulative number of risk factors was 0, 1, 2, and 3-4 in respectively 46.5, 28.9, 17.2, and 7.4% of patients. Adjuvant RT was associated with decreased CR rate in patients with ≥ 2 risk factors (10-year CR rate 10.1% in aRT vs. 42.1% in initial observation, p = 0.008), but not in those with < 2 risk factors (p = 0.23). Conclusions: Utilizing the novel model to indicate aRT might reduce overtreatment, decrease unnecessary side effects, and reduce risk of CR in the subset of patients (~25% of all patients with aggressive pathological disease) who really benefit from this therapy.