Weiner, Adam B.

AbstractBackgroundProstate cancer (PCa) is a clinically heterogeneous disease. The creation of an expression‐based subtyping model based on prostate‐specific biological processes was sought.MethodsUnsupervised 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.ResultsClustering 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 γactivity 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).ConclusionsWith the use of expression profiles from over 100,000 tumors, a PSC was developed that identified four subtypes with distinct biological and clinical features.Plain language summary Prostate cancer can behave in an indolent or aggressive manner and vary in how it responds to certain treatments. To differentiate prostate cancer on the basis of biological features, we developed a novel RNA signature by using data from over 100,000 prostate tumors—the largest data set of its kind. This signature can inform patients and physicians on tumor aggressiveness and susceptibilities to treatments to help personalize cancer management.

241 Background: We previously reported on the use of gene expression profiling to characterize four primary subtypes in an analysis of over 100,000 prostate cancer primary tumors. Here we examine these subtypes and response to radiation (RT) after prostatectomy or chemotherapy in addition to androgen deprivation therapy (ADT) in hormone-sensitive metastatic prostate cancer (mHSPC). Methods: We examined a 215-gene prostate subtyping classifier (PSC) which groups luminal and basal gene expression profiles into one of four subtypes; luminal differentiated (LD), luminal proliferating (LP), basal immune (BI) and basal neuroendocrine-like (BN). The log-rank method was used to compare (i) metastasis-free survival between patients who did and did not receive salvage RT in the META855 cohort of localized disease patients treated with radical prostatectomy (n=855) and the (ii) overall survival of patients on the Phase III mHSPC EA3805 CHAARTED trial of ADT or ADT + docetaxel chemotherapy (n=160). Results: After radical prostatectomy, patients with BI tumors derived benefit from RT in terms of metastasis-free survival ( P=9.23e-4) while those with other subtype tumors did not (Each Log-rank P≥0.5). Patients with metastatic disease and LP tumors derived benefit from docetaxel (Log-rank P=0.002) while those with other subtypes tumors did not (Log-rank P=0.2). Conclusions: Basal-luminal subtyping segments tumors by relevant biological processes with potential implications for identifying patients who benefit from salvage radiation post prostatectomy and addition of docetaxel to ADT in mHSPC.

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.

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.