What are the genomic mechanisms underpinning resistance to the androgen receptor (AR) antagonist enzalutamide in metastatic castration-resistant prostate cancer (mCRPC)?
In this study, genomic profiling was performed on serially collected cell-free DNA (cfDNA) from 65 patients with mCRPC treated with enzalutamide and performed integrated genomic profiling. Aberrations associated with both primary resistance (AR amplification, multiple AR mutations, RB1 loss) and acquired resistance (AR-L702H and AR-T878A mutations, PI3K pathway alterations, CTNNB1 mutations) were identified.
Clinically informative genomic profiling of cfDNA was feasible in nearly all patients with mCRPC and provided important insights into enzalutamide resistance.
The molecular landscape underpinning response to the androgen receptor (AR) antagonist enzalutamide in patients with metastatic castration-resistant prostate cancer (mCRPC) is undefined. Consequently, there is an urgent need for practical biomarkers to guide therapy selection and elucidate resistance. Although tissue biopsies are impractical to perform routinely in the majority of patients with mCRPC, the analysis of plasma cell-free DNA (cfDNA) has recently emerged as a minimally invasive method to explore tumor characteristics.
To reveal genomic characteristics from cfDNA associated with clinical outcomes during enzalutamide treatment.
Design, Setting, and Participants
Plasma samples were obtained from August 4, 2013, to July 31, 2015, at a single academic institution (British Columbia Cancer Agency) from 65 patients with mCRPC. We collected temporal plasma samples (at baseline, 12 weeks, end of treatment) for circulating cfDNA and performed array comparative genomic hybridization copy number profiling and deep AR gene sequencing. Samples collected at end of treatment were also subjected to targeted sequencing of 19 prostate cancer–associated genes.
Enzalutamide, 160 mg, daily orally.
Main Outcomes and Measures
Prostate-specific antigen response rate (decline ≥50% from baseline confirmed ≥3 weeks later). Radiographic (as per Prostate Cancer Working Group 2 Criteria) and/or clinical progression (defined as worsening disease-related symptoms necessitating a change in anticancer therapy and/or deterioration in Eastern Cooperative Group performance status ≥2 levels).
The 65 patients had a median (interquartile range) age of 74 (68-79) years. Prostate-specific antigen response rate to enzalutamide treatment was 38% (25 of 65), while median clinical/radiographic progression-free survival was 3.5 (95% CI, 2.1-5.0) months. Cell-free DNA was isolated from 122 of 125 plasma samples, and targeted sequencing was successful in 119 of 122. AR mutations and/or copy number alterations were robustly detected in 48% (31 of 65) and 60% (18 of 30) of baseline and progression samples, respectively. Detection of AR amplification, heavily mutated AR (≥2 mutations), and RB1 loss were associated with worse progression-free survival, with hazard ratios of 2.92 (95% CI, 1.59-5.37), 3.94 (95% CI, 1.46-10.64), and 4.46 (95% CI, 2.28-8.74), respectively. AR mutations exhibited clonal selection during treatment, including an increase in glucocorticoid-sensitive AR L702H and promiscuous AR T878A in patients with prior abiraterone treatment. At the time of progression, cfDNA sequencing revealed mutations or copy number changes in all patients tested, including clinically actionable alterations in DNA damage repair genes and PI3K pathway genes, and a high frequency (4 of 14) of activating CTNNB1 mutations.
Conclusions and Relevance
Clinically informative genomic profiling of cfDNA was feasible in nearly all patients with mCRPC and can provide important insights into enzalutamide response and resistance.
Prostate cancer cells are initially reliant on circulating androgens binding and activating the endogenous androgen receptor (AR). Although androgen deprivation therapy elicits a response in most patients, progression to castration-resistant prostate cancer (CRPC), driven frequently by AR reactivation, is inevitable.1 However, in recent years, continued targeting of the AR signaling axis with abiraterone acetate and enzalutamide has changed clinical practice and improved the overall survival of patients with CRPC.2-5 Multiple other AR axis inhibitors are in clinical trials, promising to expand the arsenal available to patients.6
Despite the efficacy of abiraterone and enzalutamide therapy, substantial challenges persist. Resistance is inevitable, including primary resistance in 10% of chemotherapy-naive patients.2 Although abiraterone and enzalutamide act on different aspects of AR signaling (abiraterone is an androgen synthesis inhibitor; enzalutamide is an AR ligand-binding domain antagonist), cross-resistance is common,7,8 and likely to be further compounded by the introduction of additional analogous agents. Resistance mechanisms are emerging, and although some tumors evolve to become “non-AR driven,” the majority seem to yet again reactivate the AR through heterogeneous genomic and transcriptomic alterations, similar to front-line CRPC.6,9
There is an urgent need for practical biomarkers to guide therapy selection and elucidate resistance. Although tissue biopsies have proved informative, they are impractical to perform routinely in clinical practice because of the bone-predominant metastatic landscape of CRPC, and focus has turned to the development of minimally invasive biomarkers from blood or urine.10-13 Already, the profiling of circulating tumor cells (CTCs) and cell-free DNA (cfDNA) has revealed that truncated AR splice variants, AR copy number gain, and point mutations of AR are linked to resistance to abiraterone.12-15 The genomics of enzalutamide response is less well studied, although AR splice variants are associated with resistance,12 and we recently demonstrated that the presence of certain AR alterations in baseline cfDNA was a poor prognostic factor.14 However, we did not profile the full spectrum of AR mutations, nor did we examine temporal samples to determine changes at disease progression. Therefore, we hypothesized that comprehensive genomic profiling of sequential cfDNA samples from a larger cohort of patients with CRPC treated with enzalutamide would reveal novel molecular characteristics associated with clinical outcomes.
Plasma samples were collected at baseline, 12 weeks, and end of treatment from 65 patients with metastatic CRPC (mCRPC) who received enzalutamide (see study design in eFigure 1 in Supplement 1). All patients were recruited from British Columbia Cancer Agency, Vancouver, Canada (with the approval of the University of British Columbia Research Ethics Board) and continued receiving enzalutamide until clinical or radiographic progression. Written informed consent was obtained from all participants prior to enrollment. Baseline patient characteristics are presented in Table 1 and eSpreadsheet 1 in Supplement 2. Progression was classified as radiological (as defined by Prostate Cancer Working Group 2 criteria)16 or clinical (defined as worsening disease-related symptoms necessitating a change in anticancer therapy and/or deterioration in Eastern Cooperative Group performance status ≥2 levels).17 Cell-free DNA extraction, processing, and array comparative genomic hybridization (aCGH) were performed as previously described although formalin was not added at blood sample collection.14
For deep AR sequencing, we used polymerase chain reaction (PCR) to amplify 15 roughly 150-bp fragments coding for AR exons 2 through 8, in 3 pools of PCR reactions each using 1 ng of cfDNA. Universal adapters and bar codes were added by PCR and libraries were sequenced using an Illumina MiSeq. For targeted sequencing of prostate cancer genes, we used an Ion Ampliseq Custom DNA panel (Life Technologies) to capture the exons of 19 genes (AR, ASXL1, BRCA1, BRCA2, CHD1, CHEK2, CTNNB1, FOXA1, HSDB31, KDM6A, MED12, KMT2A, MYC, OR5A1, PIK3CA, PTEN, SCN11A, SPOP, and TP53). For detailed protocols and description of data analysis see eMethods in Supplement 1. All patient cfDNA sequencing reads are available at the European Nucleotide Archive, accession No. PRJEB11659.
Univariate analysis was performed to identify variables associated with prostate-specific antigen (PSA) response (χ2 for categorical variables or logistic regression for continuous variables) and clinical and/or radiographic progression-free survival (PFS) (Cox proportional-hazards modeling). Survival functions were estimated using the Kaplan-Meier method and compared using the log-rank test.
Patient Cohort and Approach for Deriving AR Mutation Status From cfDNA
In the 65 patients with mCRPC recruited to our study, PSA50 (PSA decline ≥50% from baseline confirmed ≥3 weeks later) and PSA30 response rates to enzalutamide treatment were 38% (25 of 65) and 50% (31 of 62), respectively, while median clinical/radiographic PFS was 3.5 (95% CI, 2.1-5.0) months. Baseline plasma samples were collected for all patients, and for 30 of 65 patients we collected a second plasma sample at 12 weeks postbaseline, prior to progression. Finally, we collected an end-of-treatment plasma sample from 30 of 65 patients at the time of progression during enzalutamide treatment. Extraction of cfDNA was successful from 122 of 125 samples; the median DNA concentration was 1.39 ng/µL (20-60 µL elution) (eFigure 2 in Supplement 1).
Each cfDNA sample was split, with half undergoing aCGH,14 and the remaining unamplified cfDNA reserved for next-generation sequencing (NGS). Tumor-derived cfDNA (known as circulating tumor DNA [ctDNA]) is typically highly degraded, diluted (with cfDNA from noncancerous cells), and present in low amounts. Therefore, mutational profiling of all patients with CRPC necessitates a sensitive approach that can resolve low proportions of ctDNA among the total cfDNA burden. Given the importance of the AR gene in CRPC, we designed an assay to sequence the AR gene exons 2 through 8 (including the commonly mutated ligand-binding domain) from 1 to 3 ng of cfDNA (eFigure 3 in Supplement 1). In a calibration experiment with prostate cancer cell lines 22RV1 and LNCaP, endogenous AR H875Y and T878A mutations were robustly detected at frequencies as low as 1% to 2% (eFigure 4 in Supplement 1). Deep AR sequencing was successful in 119 of 122 patient samples (98%), with an average median coverage more than 31 000×.
Association of Genomic Changes in Baseline cfDNA With Disease Progression
By aCGH, 27 of 63 (43%) baseline cfDNA samples harbored detectable changes in genome copy number (eSpreadsheet 2 in Supplement 2). The remaining 36 samples with no detected changes likely harbor a ctDNA proportion below the detection limit of aCGH. Aberrations were typical of prostate cancer, including chromosome 8p loss (15 of 63), chromosome 8q gain (21 of 63), and RB1 loss (13 of 63) (Figure 1A and eFigure 5 in Supplement 1). AR copy number gain was detected in 19 patients, with 10 of 19 demonstrating evidence of amplification (log2 ratio, >1.2).
We detected AR mutations in 14 of 62 (23%) patients at baseline during enzalutamide treatment, with a surprising 5 of 14 having 2 or more mutations (Figure 1A and eSpreadsheet 2 in Supplement 2). Seven of these 14 patients had no copy number changes detected by aCGH, reflecting the higher sensitivity of the sequencing assay in detecting ctDNA. Notably, no AR mutations were detected in any samples harboring AR amplification (log2 ratio, >1.2). This is consistent with recent data that indicated a tendency toward mutual exclusivity18 and suggests that amplifications and mutations are independent drivers of CRPC progression. The most common mutations at baseline were L702H (6 patients), H875Y (6), T878A (5), and W742L/C (2) (Figure 1B), all known to confer broadened ligand specificity.19 No novel mutations were recurrent. The median allelic frequency of AR mutations at baseline was remarkably high at 8.74% (Figure 1C). Indeed, the allelic frequency of AR mutation was more than 25% in several samples, suggesting that in some patients with CRPC the tumor-derived component of cfDNA is in line with that normally expected of tissue biopsies. Repeating the AR sequencing assay on more than 30 samples that tested positive for mutations (including those detected at end of treatment) demonstrated a high correlation between the original and validation mutation frequency (r2 = 0.90) (Figure 1D). Finally, because the reported incidence of AR mutations in mCRPC tissue biopsies is 10% to 20%,20,21 our assay likely captured most clinically relevant mutations.
The detection of AR gain and/or amplification, multiple AR mutations, RB1 loss, MET gain, and MYC gain was linked to adverse outcomes during enzalutamide treatment (Figure 2 and Table 2). A potential confounding factor is that these aberrations may simply be surrogate markers for ctDNA detection, which itself was linked to poor outcomes during enzalutamide treatment (Table 2). Nevertheless, after adjustment for the presence of ctDNA, detection of RB1 loss (P = .01) and MET gain (P = .02) remained significantly associated with worse PFS (Cox proportional-hazards modeling). In addition, there was nonsignificantly shorter PFS for patients with multiple AR mutations (P = .09). Furthermore, among patients with AR aberrations, those with a “heavily aberrant AR” (amplification or ≥2 mutations) had median PFS of only 1.9 (95% CI, 1.1-2.6) months compared with 4.4 (95% CI, 2.4-6.3) months for patients with a single AR mutation (P = .04, log-rank). Importantly, patients with a single AR mutation did not seem to exhibit primary resistance to enzalutamide (Figure 2).
Dynamic cfDNA Changes and Acquired Enzalutamide Resistance
Plasma sample collection from patients at 12 weeks and at end of treatment allowed an exploration of factors linked to acquired enzalutamide resistance. While patients were undergoing treatment, only 8 of 29 (28%) samples had evidence of ctDNA (eSpreadsheet 2 in Supplement 2), consistent with a lower tumor burden in patients prior to the onset of resistance. However, at progression this was reversed, with 21 of 30 (70%) samples demonstrating ctDNA evidence by aCGH or AR sequencing, including 9 of 30 (30%) with AR copy number gain and 13 of 30 (43%) with AR mutation (Figure 3A and eSpreadsheet 2 in Supplement 2). Compared with baseline samples, we detected emergence and/or regression of particular copy number changes and AR mutations in more than half the cohort (Figure 3A), suggesting tumor clonal population changes and consistent with complex and dynamic intrapatient heterogeneity.22-24 While this could be explained in some cases by absence of ctDNA in 1 time point, the majority of such patients had ctDNA evident at both baseline and progression. Furthermore, the median allelic frequency of AR mutations at baseline and progression was comparable (Figure 1A and eFigure 6 in Supplement 1), implying that the ctDNA burden was not significantly higher at progression than at baseline.
Consistent with the original description of enzalutamide activity, we saw complete regression of clones bearing the bicalutamide-associated W742L/C mutations.25 Indeed, in an independent case we detected emergence of W742L/C in cfDNA during bicalutamide treatment, which dramatically regressed at therapy switch to enzalutamide and abiraterone (eFigure 7 in Supplement 1). Other mutations did not consistently regress; in fact, in patients with the same mutation detected at baseline and progression, 7 of 9 had an increase in detection frequency. Interestingly, we observed emergence of L702H-positive clones in 5 patients (Figure 3A), and an increase in L702H frequency in 3 patients who were positive at baseline. Additionally, we did not see L702H regress in any patients with ctDNA evidence at progression. L702H has been linked to abiraterone resistance13,15 but should be less relevant in the context of enzalutamide. Interestingly, all 11 patients with L702H at either baseline or progression had received prior abiraterone (11 of 40 vs 0 of 22; P = .03, Fisher exact test). Similarly, T878A was only detected in patients who had received prior abiraterone (n = 6) (6 of 40 vs 0 of 22; P = .08, Fisher exact test). In contrast, detection of AR copy number alterations was not associated with prior abiraterone treatment. We detected only 1 instance of F877L (converts enzalutamide from antagonist to agonist26) at progression, although the longest duration of response in patients with progression samples was 7 months.
Four patients with 2 or more AR mutations at baseline had a paired progression sample. Remarkably, 3 of these patients demonstrated regression or emergence of at least 1 (but never all) AR mutation(s) at progression, further suggesting intrapatient clonal heterogeneity. These patients experienced rapid disease progression during enzalutamide treatment, with PFS of 1.7, 2.3, and 2.9 months.
Clinically Actionable Aberration in the cfDNA of Patients With Progressing Disease
A recent landmark study of mCRPC tissue biopsies suggests that a large proportion of patients harbor specific genomic aberrations that potentially confer sensitivity to novel investigative agents.18 We performed deep targeted sequencing of 19 frequently mutated or clinically actionable prostate cancer genes in our progression samples with sufficient remaining cfDNA (n = 14). Somatic mutations and/or copy number changes were detected in all samples, at a remarkably high allelic frequency (median mutation frequency excluding AR, 19.7%) (Figure 3A and eSpreadsheets 3 and 4 in Supplement 2). Mutations were consistent with prostate cancer, including TP53 mutations (patient IDs 19, 85, 93), a deleterious PTEN mutation (patient 57), and a missense mutation within the forkhead domain of FOXA1 (patient 56). Typical copy number changes, including deep deletions of PTEN (n = 4 of 13), were robustly detected, with log ratios that approach that expected of tissue biopsies (eSpreadsheet 4 in Supplement 2). One patient (No. 85) with deep deletion of PTEN also harbored focal amplification of another PI3K pathway gene, PIK3CB (eFigure 6 in Supplement 1), which may confer sensitivity to PIK3CB-specific inhibitors.27 Another patient (No. 19) with PTEN deletion had an activating p.E545K mutation in PIK3CA. We observed strong cross-platform validation for AR mutation, with all except 1 (low frequency) mutation redetected (eFigure 8 in Supplement 1).
We identified 4 patients with activating mutations in the serine phosphorylation domain of CTNNB1 (Figure 3B), including a patient with 2 different mutations at the same amino acid, suggesting a strong selective pressure. CTNNB1 mutations have been reported in primary prostate cancer (1%; The Cancer Genome Atlas28) and front-line CRPC (3%18), but the elevated frequency in patients experiencing rapid disease progression during enzalutamide therapy warrants follow-up and further clinical development of WNT pathway inhibitors.29
Given the high frequency of germline DNA repair defects recently observed in advanced prostate cancer, we screened all patients at progression for germline BRCA1 and BRCA2 mutations (supplemented with additional DNA repair genes in 4 patients). Two patients harbored germline BRCA2 frameshift/nonsense mutations, and a third patient had a germline PALB2 frameshift mutation (Figure 3C, eFigure 9 in Supplement 1, eSpreadsheet 5 in Supplement 2). One patient (No. 22) with a BRCA2 mutation had matched cfDNA sequenced, and loss of heterozygosity was evident in cfDNA (Figure 3C). These patients would be candidates for PARP inhibition or platinum chemotherapy,30,31 and our data suggest that cfDNA could serve as a powerful biomarker to identify biallelic BRCA2 loss.
Liquid biopsies are a promising tool to develop predictive molecular biomarkers, but questions remain over applicability because CTC studies require purification equipment, and study of cfDNA can necessitate sensitive assays such as digital PCR. However, here we show that simple techniques including aCGH and single-gene NGS can robustly detect ctDNA in more than 75% of patients with mCRPC treated with enzalutamide. Furthermore, the median allelic frequency of AR mutation at baseline was greater than 5%, suggesting that most second-line patients with mCRPC have a ctDNA burden well above detection threshold for NGS approaches. Importantly, these results passed rigorous intraplatform and interplatform validation.
AR copy number gain can drive CRPC progression, and its detection in cfDNA is linked to progression during abiraterone treatment.13,15 Although our aCGH analysis was unlikely to capture all samples with AR copy gain, we observed an association between AR amplification detection and poor outcomes during enzalutamide treatment. This suggests that elevated AR expression levels (from gene amplification) are sufficient to overcome the potent inhibition of enzalutamide.25 It is also likely that elevated gene transcription (or rearrangements accrued during amplification) results in increased generation of constitutively active truncated AR variants.32,33 This raises the possibility that in addition to AR amplification, patients with rapidly progressive disease during enzalutamide treatment may have AR variants identified through CTC analysis.12,34
Most patients with AR mutations did not exhibit primary resistance to enzalutamide therapy. However, the persistence and emergence of clones harboring L702H and T878A mutations at progression suggests their continuing fitness during enzalutamide administration. This is surprising because AR-L702H has lower androgen affinity than wild-type AR,35 and both L702H and T878A are associated primarily with abiraterone resistance due to agonism by glucocorticoids and progesterones, respectively.13,15,36 Because patients whose disease progressed during abiraterone therapy who are commencing enzalutamide treatment will frequently continue to receive prednisone (at least temporarily), the most parsimonious explanation is that the persistence of prednisone in circulation, together with endogenous adrenal androgens, continues to stimulate L702H- and T878A-positive clones. The implication that prednisone may contribute to both abiraterone and enzalutamide resistance means that a switch to dexamethasone treatment may prove efficacious,37 and that clinical development of new synthetic oral glucocorticoids (especially those without the 17α-OH group that increases affinity to L702H35) is warranted.38,39
Tumor heterogeneity is increasingly recognized as a confounding factor for the treatment of prostate cancer.22-24 We observed multiple AR mutations in approximately 8% of patients, and temporal AR mutation heterogeneity in several more, possibly reflecting tumor clones with distinct evolutionary niches. Furthermore, patients with multiple AR mutations at baseline obtained poor results from enzalutamide treatment. Given the demonstrated feasibility of AR mutation detection in cfDNA, analogues of our AR NSG assay, or digital PCR assays to detect specific mutations, could be easily implemented in future clinical trials (eg, to prioritize patients for AR BF3 or DBD inhibitor treatment40,41). MYC gain, MET gain, and RB1 loss were also associated with adverse outcomes. Although detection of these aberrations may simply reflect higher tumor burden in some patients, or indicate general genomic instability,42 the association of RB1 loss with poor outcomes from enzalutamide treatment is particularly interesting in light of preclinical data implicating RB1 loss in sensitivity to taxane chemotherapy.43
We detected high allelic frequency mutations in CTNNB1 in 4 of 13 patients at disease progression. They mutate serine phosphorylation sites, preventing ubiquitination and degradation of CTNNB1. CTNNB1 mutations leading to WNT pathway activation are well documented in several cancers but are relatively rare in primary prostate cancer and even first-line CRPC (1% and 3%, respectively).18,28 However, WNT signaling is increasingly linked to therapy resistance in CRPC,44 and it is conceivable that CTNNB1 mutations confer increased cancer cell plasticity in the context of enzalutamide treatment. If validated as a resistance mechanism, cfDNA profiling could allow prospective identification of patients with CRPC most likely to respond to porcupine inhibition.29 We also observed a high frequency of germline DNA repair defects in patients who experienced rapid disease progression during enzalutamide therapy, with somatic loss of heterozygosity detectable in cfDNA. The readiness of detection in cfDNA suggests a simple and practical method for prioritization of patients for PARP inhibition or DNA-damaging agents.30
Limitations of this study include relatively small sample size and inability to detect AR splice variants using cfDNA. In the future, it will also be important to examine resistance mechanisms in patients experiencing durable responses. Twenty of 65 patients in our study continue to receive treatment and are the most likely to develop enzalutamide-specific resistance mechanisms, including the F877L mutation that confers agonist activity to enzalutamide.26,45 Although multigene sequencing was not possible in all our samples (due to insufficient cfDNA after aCGH), our study demonstrates a series of robust assays that could be easily implemented in larger multicenter cohorts to validate our findings and further develop cfDNA as a biomarker for improved clinical management of mCRPC.
Overall, this study demonstrates that clinically informative genomic profiling from minimally invasive blood sampling is feasible in nearly all patients with mCRPC. Beyond the molecular landscape and clinical associations reported herein in the context of enzalutamide treatment, cfDNA therefore holds remarkable promise for the practical implementation of precision medicine programs in advanced prostate cancer.
Accepted for Publication: February 12, 2016.
Corresponding Author: Kim N. Chi, MD, Vancouver Prostate Centre, Department of Urologic Sciences, University of British Columbia, 2660 Oak St, Vancouver, BC V6H 3Z6, Canada (email@example.com).
Published Online: May 5, 2016. doi:10.1001/jamaoncol.2016.0494
Author Contributions: Drs Wyatt and Chi had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Drs Wyatt, Azad, and Volik served as co–first authors, each with equal contribution to the manuscript. Drs Collins and Chi served as co–senior authors, each with equal contribution to the manuscript.
Study concept and design: Wyatt, Azad, Volik, Shukin, Gleave, Collins, Chi.
Acquisition, analysis, or interpretation of data: Wyatt, Azad, Volik, Annala, Beja, McConeghy, Haeger, Warner, Mo, Brahmbhatt, Le Bihan, Gleave, Nykter, Collins, Chi.
Drafting of the manuscript: Wyatt, Azad, Nykter, Collins, Chi.
Critical revision of the manuscript for important intellectual content: Wyatt, Azad, Volik, Annala, Beja, McConeghy, Haeger, Warner, Mo, Brahmbhatt, Shukin, Le Bihan, Gleave, Collins, Chi.
Statistical analysis: Azad, Annala.
Obtained funding: Wyatt, Azad, Volik, Gleave, Nykter, Collins, Chi.
Administrative, technical, or material support: Azad, Haeger, Warner, Brahmbhatt, Shukin, Le Bihan, Collins, Chi.
Study supervision: Wyatt, Volik, Beja, McConeghy, Gleave, Nykter, Collins, Chi.
Conflict of Interest Disclosures: Dr Azad receives honoraria, consultancy, and/or research funding from Astellas and Janssen. Dr Gleave receives consultancy and research funding from Astellas, Janssen, Bayer, and OncoGenex. Dr Chi receives honoraria, consultancy, and/or research funding from Astellas, Amgen, Bayer, Eli Lilly, Janssen, Novartis, and Sanofi. No other disclosures are reported.
Funding/Support: This study was supported by a Pacific Northwest Prostate Cancer Specialized Program of Research Excellence (P50CA097186) Pilot Project Award from the National Cancer Institute (A.W.W., K.N.C.), Canadian Cancer Society Research Institute Innovation Grant 702837 (K.N.C.), Terry Fox New Frontiers Program Project Grant TFF116129 (M.E.G., C.C.C., K.N.C.), Prostate Cancer Canada Movember Discovery Grants D2014-13 (K.N.C.) and D2015-06 (A.W.W., K.N.C.), a National Health and Medical Research Council CJ Martin Overseas Biomedical Fellowship (A.A.A.), Canadian Urologic Oncology Research Awards (A.A.A., A.W.W., K.N.C.), and the Emil Aaltonen Foundation (M.A.).
Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
Additional Contributions: Jun Wang, PhD, and Yingrui Li, BSc, iCarbonX and BGI-Shenzhen, facilitated access to sequencing machinery. Neither received compensation for their contributions beyond that received during the normal course of their employment.
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