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BackgroundProstate 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 summaryProstate 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.

The most common somatic event in primary prostate cancer is a fusion between the androgen-related TMPRSS2 gene and the ERG oncogene. Tumors with these fusions, which occur early in carcinogenesis, have a distinctive etiology. A smaller subset of other tumors harbor fusions between TMPRSS2 and members of the ETS transcription factor family other than ERG. To assess the genomic similarity of tumors with non-ERG ETS fusions and those with fusions involving ERG, this study derived a transcriptomic signature of non-ERG ETS fusions and assessed this signature and ERG-related gene expression in 1,050 men with primary prostate cancer from three independent population-based and hospital-based studies. Although non-ERG ETS fusions involving ETV1, ETV4, ETV5, or FLI1 were individually rare, they jointly accounted for one in seven prostate tumors. Genes differentially regulated between non-ERG ETS tumors and tumors without ETS fusions showed similar differential expression when ERG tumors and tumors without ETS fusions were compared (differences explained: R2 = 69-77%), including ETS-related androgen receptor (AR) target genes. Differences appeared to result from similarities among ETS tumors rather than similarities among non-ETS tumors. Gene sets associated with ERG fusions were consistent with gene sets associated with non-ERG ETS fusions, including fatty acid and amino acid metabolism, an observation that was robust across cohorts.ImplicationsConsidering ETS fusions jointly may be useful for etiologic studies on prostate cancer, given that the transcriptome is profoundly impacted by ERG and non-ERG ETS fusions in a largely similar fashion, most notably genes regulating metabolic pathways.

BackgroundEmerging data suggest that metastasis is a spectrum of disease burden rather than a binary state, and local therapies, such as radiation, might improve outcomes in oligometastasis. However, current definitions of oligometastasis are solely numerical.ObjectiveTo characterize the somatic mutational landscape across the disease spectrum of metastatic castration-sensitive prostate cancer (mCSPC) to elucidate a biological definition of oligometastatic CSPC.Design, setting, and participantsThis was a retrospective study of men with mCSPC who underwent clinical-grade sequencing of their tumors (269 primary tumor, 25 metastatic sites). Patients were classified as having biochemically recurrent (ie, micrometastatic), metachronous oligometastatic (≤5 lesions), metachronous polymetastatic (>5 lesions), or de novo metastatic (metastasis at diagnosis) disease.Outcome measurements and statistical analysisWe measured the frequency of driver mutations across metastatic classifications and the genomic associations with radiographic progression-free survival (rPFS) and time to castrate-resistant prostate cancer (CRPC).Results and limitationsThe frequency of driver mutations in TP53 (p =  0.01), WNT (p =  0.08), and cell cycle (p =  0.04) genes increased across the mCSPC spectrum. TP53 mutation was associated with shorter rPFS (26.7 vs 48.6 mo; p =  0.002), and time to CRPC (95.6 vs 155.8 mo; p =  0.02) in men with oligometastasis, and identified men with polymetastasis with better rPFS (TP53 wild-type, 42.7 mo; TP53 mutated, 18.5 mo; p =  0.01). Mutations in TP53 (incidence rate ratio [IRR] 1.45; p =  0.004) and DNA double-strand break repair (IRR 1.61; p

Gleason grade group (GG) 5 prostate cancer has been associated with an aggressive natural history, and retrospective data support a role for treatment intensification. However, clinical outcomes remain heterogeneous in this cohort, and intensified treatments carry an increased risk of adverse events. We sought to explore the transcriptomic heterogeneity of GG 5 tumors by querying transcriptomic data from the tumors of 2138 patients with GG 5 disease who underwent prostatectomy. Four distinct consensus clusters were identified with respect to differential transcriptional activation of hallmark pathways, with distinct molecular subtyping profiles and different average genomic risks (AGRs). One cluster, accounting for 325 tumors (15.2% of the population), was enriched for genes related to the cell cycle/proliferation, metabolic pathways, androgen response pathways, and DNA repair, and had a higher AGR than the other clusters (p

Objectives: To evaluate the utility of the 17‐gene Genomic Prostate Score® (GPS; MDxHealth, Irvine, CA, USA) performed on prostate cancer at the positive margin of the radical prostatectomy (RP) for its association with risk of subsequent biochemical recurrence (BCR). Patients and Methods: We designed a case‐cohort for the outcome of BCR, selecting 223 from a cohort of 813 RP patients treated at Johns Hopkins from 2008 to 2017 with positive margins and available clinical data; of these, 213 had available tissue and clinical data. RNA was isolated from formalin‐fixed paraffin‐embedded tumour tissue adjacent to the positive surgical margin and the GPS was evaluable in 203 of these patients with a score ranging from 0 to 100, with higher scores indicating higher risk. All patients underwent RP with or without adjuvant radiation therapy (ART). The statistical analysis employed Cox proportional hazards regression models for outcome of BCR weighted for case‐cohort design. Results: In univariable analysis, every 20‐unit increase in the GPS was associated with a nearly threefold increase in risk of BCR (hazard ratio [HR] per 20 units 2.82, P < 0.001). In a multivariable Cox model adjusted for age, race, Cancer of the Prostate Risk Assessment Postsurgical score, Grade Group at the positive margin, and ART, the GPS was significantly associated with BCR (HR 1.56 per 20 units; 95% confidence interval 1.11–2.19; P = 0.011). The study is limited by its retrospective and single institution design. Conclusions: The GPS at the positive surgical margin could help stratify prognosis and inform clinical decision‐making regarding adjuvant therapy after RP. [ABSTRACT FROM AUTHOR]

The mammalian target of Rapamycin complex 1 (mTORC1) is a serine/threonine kinase that couples nutrient and growth factor signaling to the cellular control of metabolism and plays a fundamental role in aberrant proliferation in cancer. mTORC1 has previously been considered an "on/off" switch, capable of phosphorylating the entire pool of its substrates when activated. However, recent studies have indicated that mTORC1 may be active toward its canonical substrates, eukaryotic translation initiation factor 4E-binding protein 1 (4EBP1) and S6 kinase (S6K), involved in mRNA translation and protein synthesis, and inactive toward TFEB and TFE3, transcription factors involved in the regulation of lysosome biogenesis, in several pathological contexts. Among these conditions are Birt–Hogg–Dubé syndrome (BHD) and, recently, tuberous sclerosis complex (TSC). Furthermore, increased TFEB and TFE3 nuclear localization in these syndromes, and in translocation renal cell carcinomas (tRCC), drives mTORC1 activity toward the canonical substrates, through the transcriptional activation of the Rag GTPases, thereby positioning TFEB and TFE3 upstream of mTORC1 activity toward 4EBP1 and S6K. The expanding importance of TFEB and TFE3 in the pathogenesis of these renal diseases warrants a novel clinical grouping that we term "TFEopathies." Currently, there are no therapeutic options directly targeting TFEB and TFE3, which represents a challenging and critically required avenue for cancer research. [ABSTRACT FROM AUTHOR]

Deep learning (DL)–based algorithms to determine prostate cancer (PCa) Grade Group (GG) on biopsy slides have not been validated by comparison to clinical outcomes. We used a DL-based algorithm, AIRAProstate, to regrade initial prostate biopsies in 2 independent PCa active surveillance (AS) cohorts. In a cohort initially diagnosed with GG1 PCa using only systematic biopsies (n = 138), upgrading of the initial biopsy to ≥GG2 by AIRAProstate was associated with rapid or extreme grade reclassification on AS (odds ratio = 3.3, P  =  .04), whereas upgrading of the initial biopsy by contemporary uropathologist reviews was not associated with this outcome. In a contemporary validation cohort that underwent prostate magnetic resonance imaging before initial biopsy (n = 169), upgrading of the initial biopsy (all contemporary GG1 by uropathologist grading) by AIRAProstate was associated with grade reclassification on AS (hazard ratio = 1.7, P  =  .03). These results demonstrate the utility of a DL-based grading algorithm in PCa risk stratification for AS. [ABSTRACT FROM AUTHOR]

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.