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Immune checkpoint blockade (ICB) has shown immense promise for treating patients with various cancer types, but its effectiveness relies on our ability to identify likely responders. Here, we examined the association between mutations in 25 core DNA repair genes and ICB outcomes in 6619 patients across 9 cancer types with advanced disease and MSK-IMPACT tumor sequencing. Notably, we observed that mutations in 7 of the DNA repair genes (ATM, ATR, POLE, ERCC4, NBN, RAD50, PARP1) were significantly associated with improved overall survival in ICB-treated patients (p0.05 for all) and had significant interaction with treatment (p

The genes in the collection of pathway signatures used in this study.

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Purpose:Rb-pathway disruption is of great clinical interest, as it has been shown to predict outcomes in multiple cancers. We sought to develop a transcriptomic signature for detecting biallelic RB1 loss (RBS) that could be used to assess the clinical implications of RB1 loss on a pan-cancer scale.Experimental Design:We utilized data from the Cancer Cell Line Encyclopedia (N = 995) to develop the first pan-cancer transcriptomic signature for predicting biallelic RB1 loss (RBS). Model accuracy was validated using The Cancer Genome Atlas (TCGA) Pan-Cancer dataset (N = 11,007). RBS was then used to assess the clinical relevance of biallelic RB1 loss in TCGA Pan-Cancer and in an additional metastatic castration-resistant prostate cancer (mCRPC) cohort.Results:RBS outperformed the leading existing signature for detecting RB1 biallelic loss across all cancer types in TCGA Pan-Cancer (AUC, 0.89 vs. 0.66). High RBS (RB1 biallelic loss) was associated with promoter hypermethylation (P = 0.008) and gene body hypomethylation (P = 0.002), suggesting RBS could detect epigenetic gene silencing. TCGA Pan-Cancer clinical analyses revealed that high RBS was associated with short progression-free (P < 0.00001), overall (P = 0.0004), and disease-specific (P < 0.00001) survival. On multivariable analyses, high RBS was predictive of shorter progression-free survival in TCGA Pan-Cancer (P = 0.03) and of shorter overall survival in mCRPC (P = 0.004) independently of the number of DNA alterations in RB1.Conclusions:Our study provides the first validated tool to assess RB1 biallelic loss across cancer types based on gene expression. RBS can be useful for analyzing datasets with or without DNA-sequencing results to investigate the emerging prognostic and treatment implications of Rb-pathway disruption.See related commentary by Choudhury and Beltran, p. 4199

Supplemental Tables

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.

Supplementary Figure S2: The ratio of CDKN2A/CCND1 is not as tightly correlated with Rb functional and genetic status in publicly available data from castate resistant prostate cancer (CRPC) metastases in rapid autopsy cohort.

Correlation of the PCS categories with clinical outcomes in individual cohorts displayed by Kaplan-Meier survival curves.

Table S1-3

Legends for Supplementary Figures.

Genes differentially expressed in RB1 loss tumors with two or more RB1 mutations

Figure S1: Functional network of the 84 ADT-RS genes, with significant interaction with ADT, revealing high degree of connectivity for some ADT-RS genes like REST and EZH2, and several pathways potentially involved in ADT resistance mechanism. SOX2 and NANOG are key transcription factors regulating many ADT-RS genes.

Purpose: Small-cell neuroendocrine differentiation in prostatic carcinoma is an increasingly common resistance mechanism to potent androgen deprivation therapy (ADT), but can be difficult to identify morphologically. We investigated whether cyclin D1 and p16 expression can inform on Rb functional status and distinguish small-cell carcinoma from adenocarcinoma.Experimental Design: We used gene expression data and immunohistochemistry to examine cyclin D1 and p16 levels in patient-derived xenografts (PDX), and prostatic small-cell carcinoma and adenocarcinoma specimens.Results: Using PDX, we show proof-of-concept that a high ratio of p16 to cyclin D1 gene expression reflects underlying Rb functional loss and distinguishes morphologically identified small-cell carcinoma from prostatic adenocarcinoma in patient specimens (n = 13 and 9, respectively). At the protein level, cyclin D1, but not p16, was useful to distinguish small-cell carcinoma from adenocarcinoma. Overall, 88% (36/41) of small-cell carcinomas showed cyclin D1 loss by immunostaining compared with 2% (2/94) of Gleason score 7–10 primary adenocarcinomas at radical prostatectomy, 9% (4/44) of Gleason score 9–10 primary adenocarcinomas at needle biopsy, and 7% (8/115) of individual metastases from 39 patients at autopsy. Though rare adenocarcinomas showed cyclin D1 loss, many of these were associated with clinical features of small-cell carcinoma, and in a cohort of men treated with adjuvant ADT who developed metastasis, lower cyclin D1 gene expression was associated with more rapid onset of metastasis and death.Conclusions: Cyclin D1 loss identifies prostate tumors with small-cell differentiation and may identify a small subset of adenocarcinomas with poor prognosis. Clin Cancer Res; 21(24); 5619–29. ©2015 AACR.

Purpose:Perineural invasion (PNI) is associated with aggressive tumor behavior, recurrence, and metastasis, and can influence the administration of adjuvant treatment. However, standard histopathologic examination has limited sensitivity in detecting PNI and does not provide insights into its mechanistic underpinnings.Experimental Design:A multivariate Cox regression was performed to validate associations between PNI and survival in 2,029 patients across 12 cancer types. Differential expression and gene set enrichment analysis were used to learn PNI-associated programs. Machine learning models were applied to build a PNI gene expression classifier. A blinded re-review of hematoxylin and eosin (H&E) slides by a board-certified pathologist helped determine whether the classifier could improve occult histopathologic detection of PNI.Results:PNI associated with both poor overall survival [HR, 1.73; 95% confidence interval (CI), 1.27–2.36; P < 0.001] and disease-free survival (HR, 1.79; 95% CI, 1.38–2.32; P < 0.001). Neural-like, prosurvival, and invasive programs were enriched in PNI-positive tumors (Padj < 0.001). Although PNI-associated features likely reflect in part the increased presence of nerves, many differentially expressed genes mapped specifically to malignant cells from single-cell atlases. A PNI gene expression classifier was derived using random forest and evaluated as a tool for occult histopathologic detection. On a blinded H&E re-review of sections initially described as PNI negative, more specimens were reannotated as PNI positive in the high classifier score cohort compared with the low-scoring cohort (P = 0.03, Fisher exact test).Conclusions:This study provides salient biological insights regarding PNI and demonstrates a role for gene expression classifiers to augment detection of histopathologic features.

Selection of the 37-gene panel.

Supplement Table 1: Prostate cancer cohorts used for genome wide expression profiling Supplement Table 2: GSEA Hallmark - Significant enrichments Supplement Table 3: GSEA Oncogenic Signatures - Significant enrichments Supplement Table 4: Dana Farber Cancer Institute tissue microarray (TMA) sample information Supplement Table 5: Differentially expressed genes (DEG) Supplement Table 6: Overlapping differentially expressed genes (DEG) Supplement Table 7: Univariate survival analysis including TOP2A/EZH2 expression together with other variables and their association on clinical outcomes (Meta Cohort, N = 631) Supplement Table 8: Multivariate survival analysis including TOP2A/EZH2 expression together with standard clinical variables and their association on clinical outcomes (meta cohort, N = 631) Supplement Table 9: Multivariate survival analysis including TOP2A/EZH2 expression together with Decipher and standard clinical variables and their association on clinical outcomes (Meta Cohort, N = 631)

Supplementary Data Legends

Supplemental figures and box plots

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.

Figure S2: Associations between PAM50 groups and ADT-RS signature

supplemental figure legend and Materials and Methods

Supplementary Figure S1

Supplement Materials and Methods and Figures S1-S6 Supplement Figure 1: Taylor et al. (2010) data indicate that concurrent TOP2A and EZH2 expression identify primary PCa patients with a more aggressive disease. Supplement Figure 2: GSEA for oncogenic signatures in primary human PCa revealed statistically significant overlapping for gene signatures involving VEGF and E2F1 signaling from the TCGA (2015) and Taylor et al. (2010) datasets. (P < 0.05 and FDR < 0.15; Supplement Table 3). Supplement Figure 3: Genes that have been demonstrated to be up-regulated in indolent primary PCa are down regulated in TCGA (2015) patients with concurrent up-regulation of TOP2A and EZH2 (TOP2A+/EZH2+) (Mann-Whitney; * P < 0.05; *** P < 0.001). Supplement Figure 4: Concurrent high TOP2A and EZH2 expression in primary prostatic tumors (TOP2A+/EZH2+) is not associated to a shorter time to biochemical recurrence when compared to TOP2A-/EZH2- patients included in the (A) Mayo Clinic Validation study, (B) Thomas Jefferson University dataset or the (C) Johns Hopkins University post-RP dataset. Supplement Figure 5: (A) Combination therapy induces loss of clonogenicity specific to dKO cells (top: representative experiment; unpaired t test; ** P < 0.01, triplicate, mean {plus minus}SEM). (B) Cell cycle analysis indicates that combination therapy targeting both EZH2 (GSK126 or EPZ6438, 5 μM) and TOP2A (Etoposide, 1 μM) induces G2M arrest in both sKO and dKO cell lines but results in a significant increase in apoptosis as indicated by SubG1 accumulation only in dKO (unpaired t test; ** P < 0.01, triplicate, mean {plus minus}SEM). Supplement Figure 6: TOP2A and EZH2 co-expression can select for metastatic disease progression and shorter regression-free survival in the TCGA's (A) Clear Renal Cell Carcinoma and the (B) Papillary Kidney Carcinoma datasets. (Abbreviations: no distant metastasis, M0; distant metastasis, M1)

Boxplots depict distinct pathway activities between the subtypes.

Differential enrichment of a benign prostate specific gene signature.

Supplemental legend

Tumor suppressors selected for methylation analysis null model

Purpose:Neuroendocrine (NE) bladder carcinoma is a rare and aggressive variant. Molecular subtyping studies have found that 5% to 15% of muscle-invasive bladder cancer (MIBC) have transcriptomic patterns consistent with NE bladder cancer in the absence of NE histology. The clinical implications of this NE-like subtype have not been explored in depth.Experimental Design:Transcriptome-wide expression profiles were generated for MIBC collected from 7 institutions and clinical-use of Decipher Bladder. Using unsupervised clustering, we generated a clustering solution on a prospective training cohort (PTC; n = 175), developed single-sample classifiers to predict NE tumors, and evaluated the resultant models on a testing radical cystectomy (RC) cohort (n = 225). A random forest model was finalized and applied to 5 validation cohorts (n = 1302). Uni- and multivariable survival analyses were used to characterize clinical outcomes.Results:In the training cohort (PTC), hierarchical clustering using an 84-gene panel showed a cluster of 8 patients (4.6%) with highly heterogeneous expression of NE markers in the absence of basal or luminal marker expression. NE-like tumors were identified in 1% to 6.6% of cases in validation cohorts. Patients with NE-like tumors had significantly worse 1-year progression-free survival (65% NE-like vs. 82% overall; P = 0.046) and, after adjusting for clinical and pathologic factors, had a 6.4-fold increased risk of all-cause mortality (P = 0.001). IHC confirmed the neuronal character of these tumors.Conclusions:A single-patient classifier was developed that identifies patients with histologic urothelial cancer harboring a NE transcriptomic profile. These tumors represent a high-risk subgroup of MIBC, which may require different treatment.

Supplementary Table 1

Macrophages in the tumor microenvironment are causally linked with prostate cancer development and progression, yet little is known about their composition in neoplastic human tissue. By performing single cell transcriptomic analysis of human prostate cancer resident macrophages, three distinct populations were identified in the diseased prostate. Unexpectedly, no differences were observed between macrophages isolated from the tumorous and nontumorous portions of the prostatectomy specimens. Markers associated with canonical M1 and M2 macrophage phenotypes were identifiable, however these were not the main factors defining unique subtypes. The genes selectively associated with each macrophage cluster were used to develop a gene signature which was highly associated with both recurrence-free and metastasis-free survival. These results highlight the relevance of tissue-specific macrophage subtypes in the tumor microenvironment for prostate cancer progression and demonstrates the utility of profiling single-cell transcriptomics in human tumor samples as a strategy to design gene classifiers for patient prognostication. Implications: The specific macrophage subtypes present in a diseased human prostate have prognostic value, suggesting that the relative proportions of these populations are related to patient outcome. Understanding the relative contributions of these subtypes will not only inform patient prognostication, but will enable personalized immunotherapeutic strategies to increase beneficial populations or reduce detrimental populations.

Racial disparities in prostate cancer have not been well characterized on a genomic level. Here we show the results of a multi-institutional retrospective analysis of 1,152 patients (596 African-American men (AAM) and 556 European-American men (EAM)) who underwent radical prostatectomy. Comparative analyses between the race groups were conducted at the clinical, genomic, pathway, molecular subtype, and prognostic levels. The EAM group had increased ERG (P, Walter Rayford, Alp Tuna Beksac et al. investigated gene expression alterations in African-American and European-American men who underwent radical prostatectomy for prostate cancer. The observed differences include higher expression of inflammation genes and lower expression of mismatch repair genes in African-American men.

Chromosome 8q arm (chr8q) is the most amplified chromosomal segment in advanced metastatic castration-resistant prostate cancer after chXq12. These regions harbor important oncogenes driving prostate cancer progression, including MYC that plays a role in various hallmarks of cancer, including cell cycle progression and immune surveillance. Herein we characterize the co-expression patterns of chr8q genes and their clinical utility in more than 7,000 radical prostatectomy samples.Copy Number alterations of 336 genes on chr8q21 to chr8q24 were extracted from 2 primary prostate cancer cohorts (TCGA, n = 492; MSK-primary, n = 856) and 3 metastatic prostate cancer cohorts (MSK-met, N = 432; MSK-mCSPC, N = 424; SU2CPNAS, n = 444) from cBioPortal. Expression data for the 336 genes was extracted from 6,135 radical prostatectomy samples from Decipher GRID registry. For survival analysis, patients were grouped into top 10% and top 25% by band expression and were compared with the remaining cohort. Hazard ratios were calculated using Cox proportional hazards models.Genes on chr8q were highly co-amplified and co-expressed. Copy number alterations and overexpression of chr8q genes in primary disease were associated with higher Gleason scores, increased risk of metastases, and increased prostate cancer specific mortality. Additionally, our data demonstrated high expression of MYC alone was not associated with differences in metastases free survival while high expression of other chr8q bands was associated with decreased metastases free survival. By combining chr8q data with an established genomic classifier like Decipher, we were able to develop a new model that was better at predicting metastases than Decipher alone.Our findings highlight the clinical utility of chr8q data, which can be used to improve prognostication and risk prediction in localized prostate cancer.

Background Metastatic prostate cancer (CaP) treatments are evolving rapidly but without evidence-based biomarkers to predict responses, and to maximize remissions and survival. Objective To determine the activity of androgen receptor (AR), the target for default first-line systemic treatment, in localized treatment-naive CaP and its association with clinical risk factors, molecular markers, CaP subtypes, and predictors of treatment response. Design, setting, and participants We examined 452 bona fide AR target genes in clinical-grade expression profiles from 6532 such CaPs collected between 2013 and 2017 by US physicians ordering the Decipher RP test. Results were validated in three independent smaller cohorts (n = 73, 90, and 127) and clinical CaP AR ChIP-Seq data. Association with CaP differentiation and progression was analyzed in independent datasets. Outcome measurements and statistical analysis Unsupervised clustering of CaPs based on AR target gene expression was aligned with clinical variables, differentiation scores, molecular subtypes, and predictors of response to hormonal therapy, radiotherapy, and chemotherapy. AR target gene sets were analyzed via Gene Set Enrichment Analysis for differentiation and treatment resistance, Ingenuity Pathway Analysis for associated biology, and Cistrome for genomic AR binding site (ARBS) composition. Results and limitations Expression of eight AR target gene subsignatures gave rise to five CaP clusters, which were preferentially associated with CaP molecular subtypes, differentiation, and predictors of treatment response rather than with clinical variables. Subsignatures differed in contribution to CaP progression, luminal/basal differentiation, CaP biology, and ARBS composition. Validation in prospective trials and optimized quantitation are needed for clinical implementation. Conclusions Measurement of AR activity patterns in treatment-naive CaP may serve as a first branch of an evidence-based decision tree to optimize personalized treatment plans. Patient summary Treatment options for metastatic prostate cancer are increasing without information needed to choose the right treatment for the right patient. We found variation in the behavior of the target for the default first-line therapy before treatment, which may help optimize treatment plans.

Understanding the intricacies of lethal prostate cancer poses specific challenges due to difficulties in accurate modeling of metastasis in vivo. Here we show that NPKEYFP mice (for Nkx3.1CreERT2/+; Ptenflox/flox; KrasLSL-G12D/+; R26R-CAG-LSL-EYFP/+) develop prostate cancer with a high penetrance of metastasis to bone, thereby enabling detection and tracking of bone metastasis in vivo and ex vivo. Transcriptomic and whole-exome analyses of bone metastasis from these mice revealed distinct molecular profiles conserved between human and mouse and specific patterns of subclonal branching from the primary tumor. Integrating bulk and single-cell transcriptomic data from mouse and human datasets with functional studies in vivo unravels a unique MYC/RAS co-activation signature associated with prostate cancer metastasis. Finally, we identify a gene signature with prognostic value for time to metastasis and predictive of treatment response in human patients undergoing androgen receptor therapy across clinical cohorts, thus uncovering conserved mechanisms of metastasis with potential translational significance. Using lineage tracing and molecular profiling, Abate-Shen and colleagues identify a Ras and Myc co-activation signature that predicts metastasis and castration resistance in localized prostate cancer.

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

BACKGROUND The 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. METHODS Genome-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). RESULTS Stromal 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). CONCLUSIONS Expression 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.