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The Selenium and Vitamin E Cancer Prevention Trial (SELECT) showed higher prostate cancer incidence in men supplemented with high-dose α-tocopherol. We, therefore, examined whether presupplementation plasma α-tocopherol or γ-tocopherol was associated with overall or high-grade prostate cancer. A stratified case–cohort sample that included 1,746 incident prostate cancer cases diagnosed through June 2009 and a subcohort of 3,211 men was derived from the SELECT trial of 35,533 men. Plasma was collected at entry from 2001 to 2004, and median follow-up was 5.5 years (range, 0–7.9 years). Incidence of prostate cancer as a function of plasma α-tocopherol, γ-tocopherol, and supplementation with α-tocopherol or selenomethionine was estimated by the hazard ratio (HR). Plasma γ-tocopherol was not associated with prostate cancer. Men with higher α-tocopherol concentrations seemed to have risk similar to that of men with lower concentrations [overall HR for fifth (Q5) vs. first quintile (Q1), 1.21; 95 % confidence interval (CI), 0.88–1.66; P-trend = 0.24; in the trial placebo arm, Q5 HR, 0.85; 95% CI, 0.44–1.62; P-trend = 0.66]. We found a strong positive plasma α-tocopherol association among men receiving the trial selenomethionine supplement [Q5 HR, 2.04; 95% CI, 1.29–3.22; P-trend = 0.005]. A positive plasma α-tocopherol–prostate cancer association also seemed limited to high-grade disease (Gleason grade, 7–10; overall Q5 HR, 1.59; 95% CI, 1.13–2.24; P-trend = 0.001; among men receiving selenomethionine, Q5 HR, 2.12; 95% CI, 1.32–3.40; P-trend = 0.0002). Our findings indicate that higher plasma α-tocopherol concentrations may interact with selenomethionine supplements to increase high-grade prostate cancer risk, suggesting a biologic interaction between α-tocopherol and selenium itself or selenomethionine. Cancer Prev Res; 7(9); 886–95. ©2014 AACR.

Supplementary Table S1: Case-cohort stratified sample, SELECT case-cohort study Supplementary Table S2: Baseline demographic and health related characteristics by quintiles of plasma α-tocopherol and γ-tocopherol, SELECT case-cohort study Supplementary Table S3. Association between quintiles of plasma α-tocopherol and prostate cancer risk - joint effects model by intervention group, SELECT case-cohort study Supplementary Table S4. Association between quintiles of plasma γ-tocopherol and prostate cancer risk stratified by Gleason grade, smoking status, and follow-up time, SELECT case-cohort study

Supplementary Figure 3. Intratumoral dihydrotestosterone (DHT): Histogram representing intratumoral DHT from each patient in the degarelix arm. (ONLINE ONLY) Supplementary Figure 4. Intratumoral dihydrotestosterone (DHT): Histogram representing intratumoral DHT from each patient in the degarelix and bicalutamide arm. (ONLINE ONLY) Supplementary Figure 5. Intratumoral dihydrotestosterone (DHT): Histogram representing intratumoral DHT from each patient in the LHRH agonist and bicalutamide arm. (ONLINE ONLY)

Supplementary Figure 6. Comparison of intratumoral dihydrotestosterone (DHT) levels after treatment with degarelix, degarelix and bicalutamide, or LHRH agonist and bicalutamide. (ONLINE ONLY) Supplementary Figure 7. Comparison of intratumoral testosterone levels after treatment with degarelix, degarelix and bicalutamide, or LHRH agonist and bicalutamide. (ONLINE ONLY)

Purpose: Degarelix, a new gonadotropin-releasing hormone (GnRH) receptor antagonist with demonstrated efficacy as first-line treatment in the management of high-risk prostate cancer, possesses some theoretical advantages over luteinizing hormone–releasing hormone (LHRH) analogues in terms of avoiding “testosterone flare” and lower follicle-stimulating hormone (FSH) levels. We set out to determine whether preoperative degarelix influenced surrogates of disease control in a randomized phase II study.Experimental Design: Thirty-nine patients were randomly assigned to one of three different neoadjuvant arms: degarelix only, degarelix/bicalutamide, or LHRH agonist/bicalutamide. Treatments were given for 3 months before prostatectomy. Patients had localized prostate cancer and had chosen radical prostatectomy as primary treatment. The primary end point was treatment effect on intratumoral dihydrotestosterone levels.Results: Intratumoral DHT levels were higher in the degarelix arm than both the degarelix/bicalutamide and LHRH agonist/bicalutamide arms (0.87 ng/g vs. 0.26 ng/g and 0.23 ng/g, P < 0.01). No significant differences existed for other intratumoral androgens, such as testosterone and dehydroepiandrosterone. Patients in the degarelix-only arm had higher AMACR levels on immunohistochemical analysis (P = 0.01). Serum FSH levels were lower after 12 weeks of therapy in both degarelix arms than the LHRH agonist/bicalutamide arm (0.55 and 0.65 vs. 3.65, P < 0.01), and inhibin B levels were lower in the degarelix/bicalutamide arm than the LHRH agonist/bicalutamide arm (82.14 vs. 126.67, P = 0.02).Conclusions: Neoadjuvant degarelix alone, compared with use of LHRH agonist and bicalutamide, is associated with higher levels of intratumoral dihydrotestosterone, despite similar testosterone levels. Further studies that evaluate the mechanisms behind these results are needed. Clin Cancer Res; 23(8); 1974–80. ©2016 AACR.

Safety Data

Supplementary Figure 1. Immunohistochemical expression of Ki-67 after degarelix, degarelix and bicalutamide, or LHRH agonist and bicalutamide. (ONLINE ONLY) Supplementary Figure 2. Immunohistochemical expression of alpha-methylacyl-CoA racemase (AMACR) after degarelix, degarelix and bicalutamide, or LHRH agonist and bicalutamide. (ONLINE ONLY)

CONSORT

BACKGROUND: Various germline genetic variants are associated with the prognosis of non-muscle invasive bladder cancer (NMIBC). Germline variants in genes frequently somatically mutated in bladder cancer have not been studied thoroughly in relation to risk of recurrence or progression in NMIBC. OBJECTIVE: To identify germline DNA variants in bladder carcinogenesis-related genes associated with recurrence or progression in NMIBC. METHODS: We analysed associations between single-nucleotide polymorphisms (SNPs) and NMIBC recurrence and progression using data from the Nijmegen Bladder Cancer Study (NBCS, 1,443 patients). We included 5,053 SNPs within 46 genes known to have mutation, overexpression or amplification in bladder cancer. We included all recurrences in the statistical analysis and performed both single variant analysis and gene-based analysis. SNPs and genes that showed significant or suggestive association (false discovery rate P value

Importance: Statins appear to lower serum prostate-specific antigen (PSA) and improve prostate cancer (PCa) outcomes through cholesterol-dependent and independent mechanisms. While dietary modifications have an established role in serum cholesterol reduction, whether diet-driven cholesterol reductions yield similar PCa benefits to that observed with statins is unclear. We aimed to study the effect of diet-driven cholesterol reduction on serum PSA and estimated-PCa risk. Methods: A total of 291 men from six published randomized controlled trials of dietary interventions were included. Men were aged ≥40 years, free of PCa, and had baseline PSA

Aim: This study examined circulating cell-free DNA (cfDNA) biomarkers associated with androgen treatment resistance in metastatic castration resistance prostate cancer (mCRPC). Materials & methods: We designed a panel of nine candidate cfDNA methylation markers using droplet digital PCR (Methyl-ddPCR) and assessed methylation levels in sequentially collected cfDNA samples from patients with mCRPC. Results: Increased cfDNA methylation in eight out of nine markers during androgen-targeted treatment correlated with a faster time to clinical progression. Cox proportional hazards modeling and logistic regression analysis further confirmed that higher cfDNA methylation during treatment was significantly associated with clinical progression. Conclusion: Overall, our findings have revealed a novel methylated cfDNA marker panel that could aid in the clinical management of metastatic prostate cancer.

Introduction: Several androgen deprivation therapy (ADT) medications are available for treating advanced prostate cancer with roughly equivalent oncological efficacy and tolerability. We investigated the proportion of physicians who predominantly prescribe one type of ADT drug (“mono-prescriber”) and assessed characteristics associated with prescription behavior. Methods: Ontario men aged ≥65 years who were diagnosed with advanced prostate cancer (1997–2017) and initiated ADT thereafter for ≥3 consecutive months were identified using population-level administrative data. Their first prescription for injectable ADT was linked to a physician, and urologists with ≥10 prescriptions over the study period were included in the analysis (n=282). Urologists were classified as high mono-prescribers if ≥80% of their prescriptions were for one drug type. Multivariable logistic regression was used to examine the association of physician characteristics with the odds of being a high mono-prescriber. Results: Overall, 67 (23.8%) of urologists were classified as high mono-prescribers but the frequency varied across health planning regions. The most commonly prescribed drugs and those used by mono-prescribers were goserelin (41.8% and 56.7%) and leuprolide (44.3% and 43.3%), respectively. In multivariable analysis, the odds of a physician being a high mono-prescriber were higher with more years in practice (odds ratio [OR] 1.06/ year, 95% confidence interval [CI] 1.03–1.09, p

Renal cell carcinomas (RCC) are usually asymptomatic until late stages, posing several challenges for early detection of malignant disease. Non-invasive liquid biopsy biomarkers are emerging as an important diagnostic tool which could aid with routine screening of RCCs. Circular RNAs (circRNAs) are novel non-coding RNAs that play diverse roles in carcinogenesis. They are promising biomarkers due to their stability and ease of detection in small quantities from non-invasive sources such as urine. In this study, we analyzed the expression of various circRNAs that were previously identified in RCC tumors (circEGLN3, circABCB10, circSOD2 and circACAD11) in urinary sediment samples from non-neoplastic controls, patients with benign renal tumors, and clear cell RCC (ccRCC) patients. We observed significantly reduced levels of circEGLN3 and circSOD2 in urine from ccRCC patients compared to healthy controls. We also assessed the linear variant of EGLN3 and found differential expression between patients with benign tumors compared to ccRCC patients. These findings highlight the potential of circRNA markers as non-invasive diagnostic tools to detect malignant RCC.

Summary Men diagnosed with low-risk prostate cancer (PC) are increasingly electing active surveillance (AS) as their initial management strategy. While this may reduce the side effects of treatment for PC, many men on AS eventually convert to active treatment. PC is one of the most heritable cancers, and genetic factors that predispose to aggressive tumors may help distinguish men who are more likely to discontinue AS. To investigate this, we undertook a multi-institutional genome-wide association study (GWAS) of 5,222 PC patients and 1,139 other patients from replication cohorts, all of whom initially elected AS and were followed over time for the potential outcome of conversion from AS to active treatment. In the GWAS we detected 18 variants associated with conversion, 15 of which were not previously associated with PC risk. With a transcriptome-wide association study (TWAS), we found two genes associated with conversion (MAST3, p = 6.9 × 10−7 and GAB2, p = 2.0 × 10−6). Moreover, increasing values of a previously validated 269-variant genetic risk score (GRS) for PC was positively associated with conversion (e.g., comparing the highest to the two middle deciles gave a hazard ratio [HR] = 1.13; 95% confidence interval [CI] = 0.94–1.36); whereas decreasing values of a 36-variant GRS for prostate-specific antigen (PSA) levels were positively associated with conversion (e.g., comparing the lowest to the two middle deciles gave a HR = 1.25; 95% CI, 1.04–1.50). These results suggest that germline genetics may help inform and individualize the decision of AS—or the intensity of monitoring on AS—versus treatment for the initial management of patients with low-risk PC., Genetic factors may distinguish who should receive active surveillance (AS) versus treatment following prostate cancer diagnosis. We undertook the first study to investigate this and report novel variants, genes, and risk scores associated with AS outcomes. These findings could help inform and individualize the decision of AS.

Urine cytology and cystoscopy are routinely employed during follow-up of patients after trimodal therapy (TMT) for muscle-invasive bladder cancer (MIBC). The significance of positive or equivocal cytology without visible disease recurrence on cystoscopy during follow-up is unknown, and studies informing outcomes in this scenario are lacking. This study aims to investigate the temporal trends of positive/equivocal cytology in the absence of visible disease recurrence and the association with bladder cancer recurrence and survival outcomes.One hundred and twenty-nine patients with available post-TMT cytology data and negative cystoscopy from a single academic institution between 2002 and 2017 with a median follow-up of 3.4 (range 0.1-14.2) years were analyzed. Cytology results, first post-TMT cytology positive/equivocal (CP) and negative (CN), were evaluated for association with disease recurrence and survival. Kaplan. Meier and competing risks methods were used to assess time-to-negative cytology in CP patients with ≥2 interval post-TMT cytology results (n = 33), time-to-recurrence, and disease-specific mortality (DSM) stratified by first post-TMT cytology result.At first follow-up (6-8 weeks post-TMT completion), CP was observed in 41 (32%) and CN in 88 (68%) of patients. With further follow-up of CP patients with ≥2 interval post-TMT cytology results, the probability of developing negative cytology was 57% (95% CI 42, 77) at 6 months post-TMT, and the median time-to-negative cytology was 3.2 months (95% CI 2.99, 5.80). The median time-to-recurrence was reduced in CP patients compared to CN (24.3 vs. 78.1 months, p = 0.1), corresponding with an apparent increase in the cumulative incidence of recurrence rate at 3 years in the CP vs. CN group (62% vs. 42%, p = 0.1). No significant difference was observed in the 3-year DSM rates. On univariable analysis, the hazards of recurrence and DSM for patients with CP were 1.5 (95% CI 0.9, 2.5, p = 0.1) and 2.1 (95% CI 0.9, 4.7, p = 0.07) respectively.This is the first study to investigate the significance of a positive/equivocal cytology without visible disease following TMT for MIBC. Positive cytology is common and does not preclude subsequent negative cytology supporting a watchful waiting approach rather than proceeding immediately to biopsy. However, cytology that remains positive at subsequent follow-up may be associated with adverse recurrence and survival outcomes.

Patients with bladder cancer who undergo intestinal urinary diversion may be at increased risk for bone fractures thought to be secondary to chronic metabolic acidosis and ensuing bone loss. Our main objective was to assess whether patients who undergo intestinal urinary diversion are at increased risk for fracture.Patients who underwent intestinal urinary diversion between 1994 and 2014 in Ontario, Canada were identified using linked administrative databases. Patients were categorized as undergoing diversion for bladder cancer or nonbladder cancer causes and matched 4:1 to a healthy cohort. We determined incidence rates of the incidence of fractures per 100 person-years. Multivariable Cox proportional hazards models were used to evaluate the impact of intestinal urinary diversion on the risk of fracture.Overall 4,301 patients with and 907 without bladder cancer underwent intestinal urinary diversion. The fracture incidence rate was significantly greater in the bladder cancer and nonbladder cancer cohorts compared to respective matched controls. In the bladder cancer cohort vs matched controls there were 4.41 vs 2.63 fractures per 100 person-years and in the nonbladder cancer cohort vs matched controls there were 5.67 vs 3.51 fractures per 100 person-years (each p0.001). On multivariable analysis patients who underwent intestinal urinary diversion for bladder cancer or nonbladder cancer reasons had significantly shorter fracture-free survival compared to the respective matched cohorts (HR 1.48, IQR 1.35-1.63, and HR 1.48, IQR 1.31-1.69, respectively).Our results demonstrated that regardless of age patients with intestinal urinary diversion are at increased risk for bone fractures compared to the general population. Our findings are in line with previous reports and support the need for bone health monitoring.

ImportanceEpidemiological evidence supports a role for statins in improving survival in advanced prostate cancer, particularly among men receiving androgen-ablative therapies.ObjectiveTo study the association between statin use and survival among men with prostate cancer receiving androgen deprivation therapy (ADT) or androgen receptor axis–targeted therapies (ARATs).Data SourcesThis systemic review and meta-analysis used sources from MEDLINE, EMBASE, Epub Ahead of Print, Cochrane Clinical Trials, Cochrane Systematic Reviews, and Web of Science from inception to September 6, 2022.Study SelectionObservational studies reporting associations of concurrent statin use and survival outcomes (in hazard ratios [HRs]).Data Extraction and SynthesisTwo authors independently abstracted all data. Summary estimates pooled multivariable HRs with 95% CIs using the generic inverse variance method with random-effects modeling. A priori specified subgroup and sensitivity analyses were undertaken, and heterogeneity, study quality, and publication bias were evaluated. Confidence in the evidence was assessed using the GRADE (Grading of Recommendations Assessment, Development, and Evaluation) approach.Main Outcomes and MeasuresOverall mortality and prostate cancer–specific mortality (PCSM).ResultsTwenty-five cohorts of 119 878 men (65 488 statin users [55%]) with more than 74 416 deaths were included. Concurrent statin use was associated with a 27% reduction in the risk of overall mortality (HR, 0.73 [95% CI, 0.66-0.82]; I2 = 83%) and a 35% reduction in the risk of PCSM (HR, 0.65 [95% CI, 0.58-0.73]; I2 = 74%), with substantial heterogeneity in both estimates. Subgroup analyses identified a PCSM advantage associated with statins for men receiving ARATs compared with ADT alone (HR, 0.40 [95% CI, 0.30-0.55] vs 0.68 [95% CI, 0.60-0.76]; P = .002 for difference). Confidence in the evidence was rated low for both outcomes.Conclusions and RelevanceThe findings of this meta-analysis show that concurrent statin use was associated with reduced overall mortality and PCSM among men receiving androgen-ablative therapies for advanced prostate cancer. These findings are limited by the observational nature of the data and residual unexplained interstudy heterogeneity. Randomized clinical trials are warranted to validate these results.

AimWe examined methylation changes in cell-free DNA (cfDNA) in metastatic castration resistant prostate cancer (mCRPC) during treatment.Materials and MethodsGenome-wide methylation analysis of sequentially collected cfDNA samples derived from mCRPC patients undergoing androgen-targeting therapy was performed.ResultsAlterations in methylation states previously implicated in prostate cancer progression were observed and patients that maintained methylation changes throughout therapy tended to have a longer time to clinical progression (TTP). Importantly, we also report that markers associated with a highly aggressive form of the disease, Neuroendocrine-CRPC, were associated with a faster TTP.ConclusionOur findings highlight the potential of monitoring cfDNA methylome during therapy in mCRPC, which may serve as predictive markers of response to androgen-targeting agents.

Development of neuroendocrine prostate cancer (NEPC) is emerging as a major problem in clinical management of advanced prostate cancer (PCa). As increasingly potent androgen receptor (AR)‐targeting antiandrogens are more widely used, PCa transdifferentiation into AR‐independent NEPC as a mechanism of treatment resistance becomes more common and precarious, since NEPC is a lethal PCa subtype urgently requiring effective therapy. Reprogrammed glucose metabolism of cancers, that is elevated aerobic glycolysis involving increased lactic acid production/secretion, plays a key role in multiple cancer‐promoting processes and has been implicated in therapeutics development. Here, we examined NEPC glucose metabolism using our unique panel of patient‐derived xenograft PCa models and patient tumors. By calculating metabolic pathway scores using gene expression data, we found that elevated glycolysis coupled to increased lactic acid production/secretion is an important metabolic feature of NEPC. Specific inhibition of expression of MCT4 (a plasma membrane lactic acid transporter) by antisense oligonucleotides led to reduced lactic acid secretion as well as reduced glucose metabolism and NEPC cell proliferation. Taken together, our results indicate that elevated glycolysis coupled to excessive MCT4‐mediated lactic acid secretion is clinically relevant and functionally important to NEPC. Inhibition of MCT4 expression appears to be a promising therapeutic strategy for NEPC.

To test the agreement between high-grade PCa at RP and TMA, and the ability of TMA to predict BCR. Validation of concordance between tissue microarray (TMA) and radical prostatectomy (RP) high-grade prostate cancer (PCa) is crucial because latter determines the treated natural history of PCa. We hypothesized that TMA Gleason score is in agreement with RP pathology and capable of accurately predicting biochemical recurrence (BCR). Data were provided from a multi-institutional Canadian sample of 1333 TMA and RP specimens with complete clinicopathological data. First, rate of agreement between TMA and high-grade Gleason at RP or biopsy and RP was tested. Second, ability of RP, TMA and biopsy to predict BCR was compared. Multivariable (MVA) Cox regression models were fitted and BCR rates were illustrated with Kaplan-Meier plots. Agreement between RP and TMA and between RP and biopsy was 72.6% (95% CI:69.7-75.5) and 60.4% (95% CI:57.2-63.6), respectively. In MVA predicting BCR, the accuracy for RP, TMA and biopsy was 0.73, 0.72 and 0.68, respectively. TMA added discriminatory ability among exclusively low-grade Gleason RP patients (p = 0.02), but did not improve BCR discrimination in exclusive high-grade PCa RP patients (p = 0.8). TMA Gleason grade accurately reflects presence of high-grade Gleason in RP specimen, accurately predicts BCR rates after RP and improves prediction of BCR in low-grade Gleason patients at RP.

83 Background: Mounting evidence support a role for statins in improving survival in advanced prostate cancer (PC), particularly among men on androgen-ablative therapies. This study aimed to systemically review and meta-analyze the relationship between statin use and survival among men with PC on androgen deprivation therapy (ADT) or androgen receptor-axis-targeted therapies (ARATs). Methods: This review was conducted in accordance with the Cochrane Handbook for Systematic Reviews and reported in compliance with the MOOSE guidelines. Medline, Embase, Epub Ahead of Print, Cochrane CT, Cochrane SR, and Web of Science were searched from inception to May 18, 2021, for observational studies reporting associations of postdiagnostic statin use and survival outcomes (hazard ratios [HRs]). Two authors independently abstracted all data. Study quality was assessed using the Newcastle-Ottawa Scale. The primary outcomes included overall mortality (OM) and Prostate cancer-specific mortality (PCSM). Summary estimates pooled multivariable HRs with 95% confidence intervals (CIs) using the generic inverse variance method with random-effects modelling. Heterogeneity was assessed and quantified. A priori subgroup and sensitivity analyses were undertaken, and publication bias was evaluated. Confidence in the evidence was assessed using GRADE. Results: Twenty-five cohorts of 119,878 men (64,717 statin users [54%]) with over 74,416 mortality events were included. Postdiagnostic statin use was associated with a 27% reduction in the risk of OM (19 cohorts, HR 0.73 [95%CI: 0.66 to 0.82], I2= 83%) and a 35% reduction in the risk of PCSM (14 cohorts, HR 0.65 [95%CI: 0.58 to 0.73], I2= 74%), with significant heterogeneity in both estimates. Subgroup analyses identified a PCSM-advantage of statins for men on ARATs compared to ADT (HR 0.40 [95%CI: 0.30 to 0.55] vs HR 0.68 [95%CI: 0.60 to 0.76], p-difference < 0.01). Confidence in the overall evidence was “low” for both outcomes. Conclusions: Postdiagnostic statin use reduced both overall and prostate cancer-specific mortality in men on androgen-ablative therapies for advanced PC. Randomized controlled trials are warranted to validate these findings.

224 Background: High-risk prostate cancer has a significant risk of recurrence when treated with unimodal therapy. The utility of neoadjuvant therapy prior to radical prostatectomy (RP) has yet to be defined. The ACDC-RP study investigated the use of abiraterone acetate (AA) + prednisone (P) + leuprolide (LHRH) with or without cabazitaxel prior to RP in high-risk patients. Methods: This phase II trial randomized patients to Arm A (AA/P + LHRH + cabazitaxel 20 mg/m2 with peg-filgrastim 6 cycles) or Arm B (AA/P + LHRH) for 6 months prior to RP. The primary objective was to compare the rate of pathological complete response (CR) or minimal residual disease (MRD) between treatment arms. MRD was defined as ≤5% of prostate volume involved by tumor. We present RP pathological outcomes, safety signals, and early biochemical response data. Results: Out of 78 randomized participants, 70 completed the full course of study treatment and underwent RP. Across both treatment arms, 31 (44%) men achieved either CR or MRD; 5 men had CR (2 in Arm A) and an additional 26 men exhibited MRD (15 in Arm A), p = 1 between Arm A and B. Kaplan-Meier analysis demonstrated no difference in biochemical-free survival (BFS) rate between the two treatment groups. Patients who achieved a CR/MRD experienced significantly longer BFS. Conclusions: Study findings indicate significant tumor response with 44% of patients exhibiting CR/MRD, with no significant difference observed between the two treatment arms. Patients who exhibit CR/MRD experienced better BFS rates. Genomic efforts are underway to determine predictors of response. Clinical trial information: NCT02543255. [Table: see text]

433 Background: Prior randomized controlled trials (RCT) comparing bladder preservation to radical cystectomy (RC) for muscle invasive bladder cancer (MIBC) closed early due to lack of accrual. Given that no future RCTs are foreseen, and in the absence of level 1 data, we aimed to provide the best evidence possible on outcomes of matched cohorts comparing trimodality therapy (TMT, maximal transurethral resection of bladder tumor followed by concurrent chemoradiation) to RC in order to guide management. Methods: This retrospective analysis included 703 patients with MIBC clinical stage T2-T3/4aN0M0 MIBC urothelial carcinoma of the bladder, 421 RC and 282 TMT who would have been eligible for both TMT or RC, treated at the Massachusetts General Hospital, Boston; Princess Margaret Cancer Centre, Toronto; and University of Southern California, Los Angeles between 2005-2017. To compare homogeneous cohorts, all patients included in this analysis had solitary tumors < 7 cm, no or unilateral hydronephrosis, and no multifocal carcinoma in situ. Treatment propensity scores were estimated using logistic regression, and patients were matched 3:1 with replacement. Covariates included age, sex, clinical T stage, hydronephrosis, (neo)adjuvant chemotherapy, body mass index, smoking history, and ECOG status. Overall survival (OS) was estimated with adjusted Cox models; cancer-specific survival (CSS), distant failure-free survival, pelvic nodal failure-free survival and metastasis-free survival (combined distant and pelvic nodal failure) were estimated with adjusted competing risk models. Our primary endpoint of interest was metastasis-free survival. The analysis was performed as intent-to-treat. Results: The 3:1 matched cohort comprised of 1,116 patients (834 RC vs 282 TMT). After matching, age (71.3 vs 71.6), cT2 clinical stage (88 vs 90%), presence of hydronephrosis (12 vs 10%), and use of (neo)adjuvant chemotherapy (60 vs 65%) were similar between RC and TMT cohorts. Salvage cystectomy was performed in 38 patients (13%) treated by TMT. At 5 years, metastasis-free (73 vs 78%, p = 0.07), distant failure-free (78 vs 82%, p = 0.14), and pelvic nodal failure-free (96 vs 94%, p = 0.33) survival were not statistically different between RC and TMT, whereas CSS and OS favored TMT (78 vs 85%, p = 0.02; 70 vs 78%, p < 0.001). Outcomes for RC and TMT were not different among centers. Final pT stage in the RC patients was: pT0 14%, pT1 7%, pT2 29%, pT3/4 42% and N+ 24%. Peri RC mortality was 2.1% and median number of nodes removed was 40. NMIBC recurrence occurred in 57/278 (20.5%) TMT patients. Conclusions: This large multi-institutional contemporary study provides the best evidence to date, in the absence of randomized trials, supporting TMT for select patients with MIBC. Oncologic outcomes seem to be equivalent between TMT and RC, affirming the position that TMT should be offered as an effective alternative.

Contains fulltext : 190683.pdf (Publisher’s version ) (Open Access) Background: Urologists are frequently confronted with questions of urinary bladder cancer (UBC) patients about what they can do to improve their prognosis. Unfortunately, it is largely unknown which lifestyle factors can influence prognosis. Objective: To systematically review the available evidence on the association between body mass index (BMI), diet, dietary supplements, and physical activity and UBC prognosis. Methods: We searched PubMed and Embase up to May 2017. We included thirty-one articles reporting on observational and randomized controlled trials investigating BMI, diet and dietary supplements in relation to recurrence, progression, cancer-specific or all-cause mortality in UBC patients. Results: In non-muscle invasive bladder cancer (NMIBC) patients, both overweight (3 studies, pooled hazard ratio (HR) 1.29, 95% CI 1.05-1.58, I(2) = 0%) as well as obesity (3 studies, pooled HR 1.82, 95% CI 1.12-2.95, I(2) = 79%) were associated with increased risk of recurrence when compared to normal weight. No association of BMI with risk of progression was found. Results for BMI and prognosis in muscle-invasive or in all stages series were inconsistent. Observational studies on diet and randomized controlled trials with dietary supplements showed inconsistent results. No studies on physical activity and UBC prognosis have been published to date. Conclusions: Evidence for an association of lifestyle factors with UBC prognosis is limited, with some evidence for an association of BMI with risk of recurrence in NMIBC. Well-designed, prospective studies are needed to develop evidence-based guidelines on this topic.

Research examining the association between physical activity (PA) and prostate cancer (PCa) has accumulated; however, few studies have examined this association in the context of active surveillance. The current study examines this among men initially diagnosed with favorable-risk PCa and managed by active surveillance at Sunnybrook Health Sciences Centre in Canada and the Royal Marsden Hospital in the United Kingdom. Participants completed a questionnaire on daily participation in non-leisure, transport, and recreational PA. A logistic regression was employed using PA as the independent variable and whether the patient reclassified to higher-risk PCa while on active surveillance as the dependent variable. Demographic and lifestyle covariates were incorporated in the analysis to assess potential confounding and effect modification. Men from both hospitals presented with similar clinical and demographic characteristics. Total PA was inversely associated with odds of reclassification while on active surveillance (p-trend = 0.027). A weaker inverse association was observed with recreational PA (p-trend = 0.30). Men who participated in weekly vigorous PA were less likely to reclassify than those who did not (odds ratio (95% confidence interval): 0.42 (0.20–0.85)). Total and vigorous PA were inversely associated with odds of reclassification in two active surveillance cohorts. Given the limitations of this study, more robust prospective observational studies involving objective PA measures are warranted to confirm findings.

MC3 Working Group: Rehan Akbani21, Pavana Anur22, Matthew H. Bailey1,2,3, Alex Buchanan9, Kami Chiotti9, Kyle Covington12,23, Allison Creason9, Li Ding1,2,3,20, Kyle Ellrott9, Yu Fan21, Steven Foltz1,2, Gad Getz8,14,15,16, Walker Hale12, David Haussler24,25, Julian M. Hess8,26, Carolyn M. Hutter27, Cyriac Kandoth28, Katayoon Kasaian29,30, Melpomeni Kasapi27, Dave Larson1 , Ignaty Leshchiner8, John Letaw31, Singer Ma32, Michael D. McLellan1,3,20, Yifei Men32, Gordon B. Mills33,34, Beifang Niu35, Myron Peto22, Amie Radenbaugh24, Sheila M. Reynolds36, Gordon Saksena8, Heidi Sofia27, Chip Stewart8, Adam J. Struck31, Joshua M. Stuart24,37, Wenyi Wang21, John N. Weinstein38, David A. Wheeler12,13, Christopher K. Wong24,39, Liu Xi12 & Kai Ye40,41 21Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. 22Molecular and Medical Genetics, OHSU Knight Cancer Institute, Oregon Health and Science University, Portland, OR 97239, USA. 23Castle Biosciences Inc, Friendswood, TX 77546, USA. 24UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95064, USA. 25Howard Hughes Medical Institute, University of California Santa Cruz, Santa Cruz, CA 95064, USA. 26Massachusetts General Hospital Center for Cancer Research, Charlestown, MA 02114, USA. 27National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20894, USA. 28Marie-Josée and Henry R. Kravis Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA. 29Ontario Institute for Cancer Research, Toronto, ON M5G 0A3, Canada. 30Canada’s Michael Smith Genome Sciences Centre, BC Cancer, Vancouver, BC V5Z 4S6, Canada. 31Computational Biology Program, School of Medicine, Oregon Health and Science University, Portland, OR 97239, USA. 32DNAnexus Inc, Mountain View, CA 94040, USA. 33Department of Systems Biology, UT MD Anderson Cancer Center, Houston, TX 77030, USA. 34Precision Oncology, OHSU Knight Cancer Institute, Oregon Health and Science University, Portland, OR 97239, USA. 35Computer Network Information Center, Chinese Academy of Sciences, Beijing, China. 36Institute for Systems Biology, Seattle, WA 98109, USA. 37Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA 95064, USA. 38Department of Bioinformatics and Computational Biology and Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. 39Biomolecular Engineering Department, University of California Santa Cruz, Santa Cruz, CA 95064, USA. 40School of Elect, PCAWG novel somatic mutation calling methods working group: Matthew H. Bailey1,2,3, Beifang Niu35, Matthias Bieg42,43, Paul C. Boutros6,44,45,46, Ivo Buchhalter43,47,48, Adam P. Butler49, Ken Chen50, Zechen Chong51, Li Ding1,2,3,20, Oliver Drechsel52,53, Lewis Jonathan Dursi6,7, Roland Eils47,48,54,55, Kyle Ellrott9, Shadrielle M. G. Espiritu6, Yu Fan21, Robert S. Fulton1,3,20, Shengjie Gao56, Josep L. l. Gelpi57,58, Mark B. Gerstein5,18,19, Gad Getz8,14,15,16, Santiago Gonzalez59,60, Ivo G. Gut52,61, Faraz Hach62,63, Michael C. Heinold47,48, Julian M. Hess8,26, Jonathan Hinton49, Taobo Hu64, Vincent Huang6, Yi Huang65,66, Barbara Hutter43,67,68, David R. Jones49, Jongsun Jung69, Natalie Jäger47, Hyung-Lae Kim70, Kortine Kleinheinz47,48, Sushant Kumar5,19, Yogesh Kumar64, Christopher M. Lalansingh6, Ignaty Leshchiner8, Ivica Letunic71, Dimitri Livitz8, Eric Z. Ma64, Yosef E. Maruvka8,26,72, R. Jay Mashl1,2, Michael D. McLellan1,3,20, Andrew Menzies49, Ana Milovanovic57, Morten Muhlig Nielsen73, Stephan Ossowski52,53,74, Nagarajan Paramasivam43,47, Jakob Skou Pedersen73,75, Marc D. Perry76,77, Montserrat Puiggròs57, Keiran M. Raine49, Esther Rheinbay8,14,72, Romina Royo57, S. Cenk Sahinalp62,78,79, Gordon Saksena8, Iman Sarrafi62,78, Matthias Schlesner47,80, Jared T. Simpson6,17, Lucy Stebbings49, Chip Stewart8, Miranda D. Stobbe52,61, Jon W. Teague49, Grace Tiao8, David Torrents57,81, Jeremiah A. Wala8,14,82, Jiayin Wang1,40,66, Wenyi Wang21, Sebastian M. Waszak60, Joachim Weischenfeldt60,83,84, Michael C. Wendl1,10,11, Johannes Werner47,85, Zhenggang Wu64, Hong Xue64, Sergei Yakneen60, Takafumi N. Yamaguchi6, Kai Ye40,41, Venkata D. Yellapantula20,86, Christina K. Yung76 & Junjun Zhang76, PCAWG Consortium: Lauri A. Aaltonen87, Federico Abascal49, Adam Abeshouse88, Hiroyuki Aburatani89, David J. Adams49, Nishant Agrawal90, Keun Soo Ahn91, Sung-Min Ahn92, Hiroshi Aikata93, Rehan Akbani21, Kadir C. Akdemir50, Hikmat Al-Ahmadie88, Sultan T. Al-Sedairy94, Fatima Al-Shahrour95, Malik Alawi96,97, Monique Albert98, Kenneth Aldape99,100, Ludmil B. Alexandrov49,101,102, Adrian Ally30, Kathryn Alsop103, Eva G. Alvarez104,105,106, Fernanda Amary107, Samirkumar B. Amin108,109,110, Brice Aminou76, Ole Ammerpohl111,112, Matthew J. Anderson113, Yeng Ang114, Davide Antonello115, Pavana Anur22, Samuel Aparicio116, Elizabeth L. Appelbaum1,117, Yasuhito Arai118, Axel Aretz119, Koji Arihiro93, Shun-ichi Ariizumi120, Joshua Armenia121, Laurent Arnould122, Sylvia Asa123,124, Yassen Assenov125, Gurnit Atwal6,126,127, Sietse Aukema112,128, J. Todd Auman129, Miriam R. Aure130, Philip Awadalla6,126, Marta Aymerich131, Gary D. Bader126, Adrian Baez-Ortega132, Matthew H. Bailey1,2,3, Peter J. Bailey133, Miruna Balasundaram30, Saianand Balu134, Pratiti Bandopadhayay8,135,136, Rosamonde E. Banks137, Stefano Barbi138, Andrew P. Barbour139,140, Jonathan Barenboim6, Jill Barnholtz-Sloan141,142, Hugh Barr143, Elisabet Barrera59, John Bartlett98,144, Javier Bartolome57, Claudio Bassi115, Oliver F. Bathe145,146, Daniel Baumhoer147, Prashant Bavi148, Stephen B. Baylin149,150, Wojciech Bazant59, Duncan Beardsmore151, Timothy A. Beck152,153, Sam Behjati49, Andreas Behren154, Beifang Niu35, Cindy Bell155, Sergi Beltran52,61, Christopher Benz156, Andrew Berchuck157, Anke K. Bergmann158, Erik N. Bergstrom101,102, Benjamin P. Berman159,160,161, Daniel M. Berney162, Stephan H. Bernhart163,164,165, Rameen Beroukhim8,14,82, Mario Berrios166, Samantha Bersani167, Johanna Bertl73,168, Miguel Betancourt169, Vinayak Bhandari6,44, Shriram G. Bhosle49, Andrew V. Biankin133,170,171,172, Matthias Bieg42,43, Darell Bigner173, Hans Binder163,164, Ewan Birney59, Michael Birrer72, Nidhan K. Biswas174, Bodil Bjerkehagen147,175, Tom Bodenheimer134, Lori Boice176, Giada Bonizzato177, Johann S. De Bono178, Arnoud Boot179,180, Moiz S. Bootwalla166, Ake Borg181, Arndt Borkhardt182, Keith A. Boroevich183,184, Ivan Borozan6, Christoph Borst185, Marcus Bosenberg186, Mattia Bosio52,53,57, Jacqueline Boultwood187, Guillaume Bourque188,189, Paul C. Boutros6,44,45,46, G. Steven Bova190, David T. Bowen49,191, Reanne Bowlby30, David D. L. Bowtell103, Sandrine Boyault192, Rich Boyce59, Jeffrey Boyd193, Alvis Brazma59, Paul Brennan194, Daniel S. Brewer195,196, Arie B. Brinkman197, Robert G. Bristow44,198,199,200,201, Russell R. Broaddus99, Jane E. Brock202, Malcolm Brock203, Annegien Broeks204, Angela N. Brooks8,24,37,82, Denise Brooks30, Benedikt Brors67,205,206, Søren Brunak207,208, Timothy J. C. Bruxner113,209, Alicia L. Bruzos104,105,106, Alex Buchanan9, Ivo Buchhalter43,47,48, Christiane Buchholz210, Susan Bullman8,82, Hazel Burke211, Birgit Burkhardt212, Kathleen H. Burns213,214, John Busanovich8,215, Carlos D. Bustamante216,217, Adam P. Butler49, Atul J. Butte218, Niall J. Byrne76, Anne-Lise Børresen-Dale130,219, Samantha J. Caesar-Johnson220, Andy Cafferkey59, Declan Cahill221, Claudia Calabrese59,60, Carlos Caldas222,223, Fabien Calvo224, Niedzica Camacho178, Peter J. Campbell49,225, Elias Campo226,227, Cinzia Cantù177, Shaolong Cao21, Thomas E. Carey228, Joana Carlevaro-Fita229,230,231, Rebecca Carlsen30, Ivana Cataldo167,177, Mario Cazzola232, Jonathan Cebon154, Robert Cerfolio233, Dianne E. Chadwick234, Dimple Chakravarty235, Don Chalmers236, Calvin Wing Yiu Chan47,237, Kin Chan238, Michelle Chan-Seng-Yue148, Vishal S. Chandan239, David K. Chang133,170, Stephen J. Chanock240, Lorraine A. Chantrill170,241, Aurélien Chateigner76,242, Nilanjan Chatterjee149,243, Kazuaki Chayama93, Hsiao-Wei Chen114,121, Jieming Chen218, Ken Chen50, Yiwen Chen21, Zhaohong Chen244, Andrew D. Cherniack8,82, Jeremy Chien245, Yoke-Eng Chiew246,247, Suet-Feung Chin222,223, Juok Cho8, Sunghoon Cho248, Jung Kyoon Choi249, Wan Choi250, Christine Chomienne251, Zechen Chong51, Su Pin Choo252, Angela Chou170,246, Angelika N. Christ113, Elizabeth L. Christie103, Eric Chuah30, Carrie Cibulskis8, Kristian Cibulskis8, Sara Cingarlini253, Peter Clapham49, Alexander Claviez254, Sean Cleary148,255, Nicole Cloonan256, Marek Cmero257,258,259, Colin C. Collins62, Ashton A. Connor255,260, Susanna L. Cooke133, Colin S. Cooper178,196,261, Leslie Cope149, Vincenzo Corbo138,177, Matthew G. Cordes1,262, Stephen M. Cordner263, Isidro Cortés-Ciriano264,265,266, Kyle Covington12,23, Prue A. Cowin267, Brian Craft24, David Craft8,268, Chad J. Creighton269, Yupeng Cun270, Erin Curley271, Ioana Cutcutache179,180, Karolina Czajka272, Bogdan Czerniak99,273, Rebecca A. Dagg274, Ludmila Danilova149, Maria Vittoria Davi275, Natalie R. Davidson276,277,278,279,280, Helen Davies49,281,282, Ian J. Davis283, Brandi N. Davis-Dusenbery284, Kevin J. Dawson49, Francisco M. De La Vega216,217,285, Ricardo De Paoli-Iseppi211, Timothy Defreitas8, Angelo P. Dei Tos286, Olivier Delaneau287,288,289, John A. Demchok220, Jonas Demeulemeester290,291, German M. Demidov52,53,74, Deniz Demircioğlu292,293, Nening M. Dennis221, Robert E. Denroche148, Stefan C. Dentro49,290,294, Nikita Desai76, Vikram Deshpande72, Amit G. Deshwar295, Christine Desmedt296,297, Jordi Deu-Pons298,299, Noreen Dhalla30, Neesha C. Dhani300, Priyanka Dhingra301,302, Rajiv Dhir303, Anthony DiBiase304, Klev Diamanti305, Li Ding1,2,3,20, Shuai Ding306, Huy Q. Dinh159, Luc Dirix307, HarshaVardhan Doddapaneni12, Nilgun Donmez62,78, Michelle T. Dow244, Ronny Drapkin308, Oliver Drechsel52,53, Ruben M. Drews223, Serge Serge49, Tim Dudderidge150,221, Ana Dueso-Barroso57, Andrew J. Dunford8, Michael Dunn309, Lewis Jonathan Dursi6,7, Fraser R. Duthie133,310, Ken Dutton-Regester311, Jenna Eagles272, Douglas F. Easton312,313, Stuart Edmonds314, Paul A. Edwards223,315, Sandra E. Edwards178, Rosalind A. Eeles178,221, Anna Ehinger316, Juergen Eils54,55, Roland Eils47,48,54,55, Adel El-Naggar99,273, Matthew Eldridge223, Kyle Ellrott9, Serap Erkek60, Georgia Escaramis53,317,318, Shadrielle M. G. Espiritu6, Xavier Estivill53,319, Dariush Etemadmoghadam103, Jorunn E. Eyfjord320, Bishoy M. Faltas280, Daiming Fan321, Yu Fan21, William C. Faquin72, Claudiu Farcas244, Matteo Fassan322, Aquila Fatima323, Francesco Favero324, Nodirjon Fayzullaev76, Ina Felau220, Sian Fereday103, Martin L. Ferguson325, Vincent Ferretti76,326, Lars Feuerbach205, Matthew A. Field327, J. Lynn Fink57,113, Gaetano Finocchiaro328, Cyril Fisher221, Matthew W. Fittall290, Anna Fitzgerald329, Rebecca C. Fitzgerald282, Adrienne M. Flanagan330, Neil E. Fleshner331, Paul Flicek59, John A. Foekens332, Kwun M. Fong333, Nuno A. Fonseca59,334, Christopher S. Foster335,336, Natalie S. Fox6, Michael Fraser6, Scott Frazer8, Milana Frenkel-Morgenstern337, William Friedman338, Joan Frigola298, Catrina C. Fronick1,262, Akihiro Fujimoto184, Masashi Fujita184, Masashi Fukayama339, Lucinda A. Fulton1 , Robert S. Fulton1,3,20, Mayuko Furuta184, P. Andrew Futreal340, Anja Füllgrabe59, Stacey B. Gabriel8, Steven Gallinger148,255,260, Carlo Gambacorti-Passerini341, Jianjiong Gao121, Shengjie Gao56, Levi Garraway82, Øystein Garred342, Erik Garrison49, Dale W. Garsed103, Nils Gehlenborg8,343, Josep L. l. Gelpi57,58, Joshy George110, Daniela S. Gerhard344, Clarissa Gerhauser345, Jeffrey E. Gershenwald346,347, Mark B. Gerstein5,18,19, Moritz Gerstung59,60, Gad Getz8,14,15,16, Mohammed Ghori49, Ronald Ghossein348, Nasra H. Giama349, Richard A. Gibbs12, Anthony J. Gill170,350, Pelvender Gill351, Dilip D. Giri348, Dominik Glodzik49, Vincent J. Gnanapragasam352,353, Maria Elisabeth Goebler354, Mary J. Goldman24, Carmen Gomez355, Santiago Gonzalez59,60, Abel Gonzalez-Perez298,299,356, Dmitry A. Gordenin357, James Gossage358, Kunihito Gotoh359, Ramaswamy Govindan3, Dorthe Grabau360, Janet S. Graham133,361, Robert C. Grant148,260, Anthony R. Green315, Eric Green27, Liliana Greger59, Nicola Grehan282, Sonia Grimaldi177, Sean M. Grimmond362, Robert L. Grossman363, Adam Grundhoff97,364, Gunes Gundem88, Qianyun Guo75, Manaswi Gupta8, Shailja Gupta365, Ivo G. Gut52,61, Marta Gut52,61, Jonathan Göke292,366, Gavin Ha8, Andrea Haake111, David Haan37, Siegfried Haas185, Kerstin Haase290, James E. Haber367, Nina Habermann60, Faraz Hach62,63, Syed Haider6, Natsuko Hama118, Freddie C. Hamdy351, Anne Hamilton267, Mark P. Hamilton368, Leng Han369, George B. Hanna370, Martin Hansmann371, Nicholas J. Haradhvala8,72, Olivier Harismendy102,372, Ivon Harliwong113, Arif O. Harmanci5,373, Eoghan Harrington374, Takanori Hasegawa375, David Haussler24,25, Steve Hawkins223, Shinya Hayami376, Shuto Hayashi375, D. Neil Hayes134,377,378, Stephen J. Hayes379,380, Nicholas K. Hayward211,311, Steven Hazell221, Yao He381, Allison P. Heath382, Simon C. Heath52,61, David Hedley300, Apurva M. Hegde38, David I. Heiman8, Michael C. Heinold47,48, Zachary Heins88, Lawrence E. Heisler152, Eva Hellstrom-Lindberg383, Mohamed Helmy384, Seong Gu Heo385, Austin J. Hepperla134, José María Heredia-Genestar386, Carl Herrmann47,48,387, Peter Hersey211, Julian M. Hess8,26, Holmfridur Hilmarsdottir320, Jonathan Hinton49, Satoshi Hirano388, Nobuyoshi Hiraoka389, Katherine A. Hoadley134,390, Asger Hobolth75,168, Ermin Hodzic78, Jessica I. Hoell182, Steve Hoffmann163,164,165,391, Oliver Hofmann392, Andrea Holbrook166, Aliaksei Z. Holik53, Michael A. Hollingsworth393, Oliver Holmes209,311, Robert A. Holt30, Chen Hong205,237, Eun Pyo Hong385, Jongwhi H. Hong394, Gerrit K. Hooijer395, Henrik Hornshøj73, Fumie Hosoda118, Yong Hou56,396, Volker Hovestadt397, William Howat352, Alan P. Hoyle134, Ralph H. Hruban149, Jianhong Hu12, Taobo Hu64, Xing Hua240, Kuan-lin Huang1,398, Mei Huang176, Mi Ni Huang179,180, Vincent Huang6, Yi Huang65,66, Wolfgang Huber60, Thomas J. Hudson272,399, Michael Hummel400, Jillian A. Hung246,247, David Huntsman401, Ted R. Hupp402, Jason Huse88, Matthew R. Huska403, Barbara Hutter43,67,68, Carolyn M. Hutter27, Daniel Hübschmann48,54,404,405,406, Christine A. Iacobuzio-Donahue348, Charles David Imbusch205, Marcin Imielinski407,408, Seiya Imoto375, William B. Isaacs409, Keren Isaev6,44, Shumpei Ishikawa410, Murat Iskar397, S. M. Ashiqul Islam244, Michael Ittmann411,412,413, Sinisa Ivkovic284, Jose M. G. Izarzugaza414, Jocelyne Jacquemier415, Valerie Jakrot211, Nigel B. Jamieson133,172,416, Gun Ho Jang148, Se Jin Jang417, Joy C. Jayaseelan12, Reyka Jayasinghe1 , Stuart R. Jefferys134, Karine Jegalian418, Jennifer L. Jennings419, Seung-Hyup Jeon250, Lara Jerman60,420, Yuan Ji421,422, Wei Jiao6, Peter A. Johansson311, Amber L. Johns170, Jeremy Johns272, Rory Johnson230,423, Todd A. Johnson183, Clemency Jolly290, Yann Joly424, Jon G. Jonasson320, Corbin D. Jones425, David R. Jones49, David T. W. Jones426,427, Nic Jones428, Steven J. M. Jones30, Jos Jonkers204, Young Seok Ju49,249, Hartmut Juhl429, Jongsun Jung69, Malene Juul73, Randi Istrup Juul73, Sissel Juul374, Natalie Jäger47, Rolf Kabbe47, Andre Kahles276,277,278,279,430, Abdullah Kahraman431,432,433, Vera B. Kaiser434, Hojabr Kakavand211, Sangeetha Kalimuthu148, Christof von Kalle405, Koo Jeong Kang91, Katalin Karaszi351, Beth Karlan435, Rosa Karlić436, Dennis Karsch437, Katayoon Kasaian29,30, Karin S. Kassahn113,438, Hitoshi Katai439, Mamoru Kato440, Hiroto Katoh410, Yoshiiku Kawakami93, Jonathan D. Kay117, Stephen H. Kazakoff209,311, Marat D. Kazanov441,442,443, Maria Keays59, Electron Kebebew444,445, Richard F. Kefford446, Manolis Kellis8,447, James G. Kench170,350,448, Catherine J. Kennedy246,247, Jules N. A. Kerssemakers47, David Khoo273, Vincent Khoo221, Narong Khuntikeo115,449, Ekta Khurana301,302,450,451, Helena Kilpinen117, Hark Kyun Kim452, Hyung-Lae Kim70, Hyung-Yong Kim415, Hyunghwan Kim250, Jaegil Kim8, Jihoon Kim453, Jong K. Kim454, Youngwook Kim455,456, Tari A. King457,458,459, Wolfram Klapper128, Kortine Kleinheinz47,48, Leszek J. Klimczak460, Stian Knappskog49,461, Michael Kneba437, Bartha M. Knoppers424, Youngil Koh462,463, Jan Komorowski305,464, Daisuke Komura410, Mitsuhiro Komura375, Gu Kong415, Marcel Kool426,465, Jan O. Korbel59,60, Viktoriya Korchina12, Andrey Korshunov465, Michael Koscher465, Roelof Koster466, Zsofia Kote-Jarai178, Antonios Koures244, Milena Kovacevic284, Barbara Kremeyer49, Helene Kretzmer164,165, Markus Kreuz467, Savitri Krishnamurthy99,468, Dieter Kube469, Kiran Kumar8, Pardeep Kumar221, Sushant Kumar5,19, Yogesh Kumar64, Ritika Kundra114,121, Kirsten Kübler8,14,72, Ralf Küppers470, Jesper Lagergren383,471, Phillip H. Lai166, Peter W. Laird472, Sunil R. Lakhani473, Christopher M. Lalansingh6, Emilie Lalonde6, Fabien C. Lamaze6, Adam Lambert351, Eric Lander8, Pablo Landgraf474,475, Luca Landoni115, Anita Langerød130, Andrés Lanzós230,231,423, Denis Larsimont476, Erik Larsson477, Mark Lathrop189, Loretta M. S. Lau478, Chris Lawerenz55, Rita T. Lawlor177, Michael S. Lawrence8,72,183, Alexander J. Lazar99,108, Xuan Le479, Darlene Lee30, Donghoon Lee5, Eunjung Alice Lee480, Hee Jin Lee417, Jake June-Koo Lee264,266, Jeong-Yeon Lee481, Juhee Lee482, Ming Ta Michael Lee340, Henry Lee-Six49, Kjong-Van Lehmann276,277,278,279,430, Hans Lehrach483, Dido Lenze400, Conrad R. Leonard209,311, Daniel A. Leongamornlert49,178, Ignaty Leshchiner8, Louis Letourneau484, Ivica Letunic71, Douglas A. Levine88,485, Lora Lewis12, Tim Ley486, Chang Li56,396, Constance H. Li6,44, Haiyan Irene Li30, Jun Li21, Lin Li56, Shantao Li5, Siliang Li56,396, Xiaobo Li56,396, Xiaotong Li5, Xinyue Li56, Yilong Li49, Han Liang21, Sheng-Ben Liang234, Peter Lichter68,397, Pei Lin8, Ziao Lin8,487, W. M. Linehan488, Ole Christian Lingjærde489, Dongbing Liu56,396, Eric Minwei Liu88,301,302, Fei-Fei Liu201,490, Fenglin Liu381,491, Jia Liu492, Xingmin Liu56,396, Julie Livingstone6, Dimitri Livitz8, Naomi Livni221, Lucas Lochovsky5,19,110, Markus Loeffler467, Georgina V. Long211, Armando Lopez-Guillermo493, Shaoke Lou5,19, David N. Louis72, Laurence B. Lovat117, Yiling Lu38, Yong-Jie Lu162,494, Youyong Lu495,496,497, Claudio Luchini167, Ilinca Lungu144,148, Xuemei Luo152, Hayley J. Luxton117, Andy G. Lynch223,315,498, Lisa Lype36, Cristina López111,112, Carlos López-Otín499, Eric Z. Ma64, Yussanne Ma30, Gaetan MacGrogan500, Shona MacRae501, Geoff Macintyre223, Tobias Madsen73, Kazuhiro Maejima184, Andrea Mafficini177, Dennis T. Maglinte166,502, Arindam Maitra174, Partha P. Majumder174, Luca Malcovati232, Salem Malikic62,78, Giuseppe Malleo115, Graham J. Mann211,246,503, Luisa Mantovani-Löffler504, Kathleen Marchal505,506, Giovanni Marchegiani115, Elaine R. Mardis1,193,507, Adam A. Margolin31, Maximillian G. Marin37, Florian Markowetz223,315, Julia Markowski403, Jeffrey Marks508, Tomas Marques-Bonet61,81,386,509, Marco A. Marra30, Luke Marsden351, John W. M. Martens332, Sancha Martin49,510, Jose I. Martin-Subero81,511, Iñigo Martincorena49, Alexander Martinez-Fundichely301,302,451 Yosef E. Maruvka8,26,72, R. Jay Mashl1,2, Charlie E. Massie223, Thomas J. Matthew37, Lucy Matthews178, Erik Mayer221,512, Simon Mayes513, Michael Mayo30, Faridah Mbabaali272, Karen McCune514, Ultan McDermott49, Patrick D. McGillivray19, Michael D. McLellan1,3,20, John D. McPherson148,272,515, John R. McPherson179,180, Treasa A. McPherson260, Samuel R. Meier8, Alice Meng516, Shaowu Meng134, Andrew Menzies49, Neil D. Merrett115,517, Sue Merson178, Matthew Meyerson8,14,82, William U. Meyerson4,5, Piotr A. Mieczkowski518, George L. Mihaiescu76, Sanja Mijalkovic284, Ana Mijalkovic Mijalkovic-Lazic284, Tom Mikkelsen519, Michele Milella253, Linda Mileshkin103, Christopher A. Miller1 , David K. Miller113,170, Jessica K. Miller272, Gordon B. Mills33,34, Ana Milovanovic57, Sarah Minner520, Marco Miotto115, Gisela Mir Arnau267, Lisa Mirabello240, Chris Mitchell103, Thomas J. Mitchell49,315,352, Satoru Miyano375, Naoki Miyoshi375, Shinichi Mizuno521, Fruzsina Molnár-Gábor522, Malcolm J. Moore300, Richard A. Moore30, Sandro Morganella49, Quaid D. Morris127,490, Carl Morrison523,524, Lisle E. Mose134, Catherine D. Moser349, Ferran Muiños298,299, Loris Mularoni298,299, Andrew J. Mungall30, Karen Mungall30, Elizabeth A. Musgrove133, Ville Mustonen525,526,527, David Mutch528, Francesc Muyas52,53,74, Donna M. Muzny12, Alfonso Muñoz59, Jerome Myers529, Ola Myklebost461, Peter Möller530, Genta Nagae89, Adnan M. Nagrial170, Hardeep K. Nahal-Bose76, Hitoshi Nakagama531, Hidewaki Nakagawa184, Hiromi Nakamura118, Toru Nakamura388, Kaoru Nakano184, Tannistha Nandi532, Jyoti Nangalia49, Mia Nastic284, Arcadi Navarro61,81,386, Fabio C. P. Navarro19, David E. Neal223,352, Gerd Nettekoven533, Felicity Newell209,311, Steven J. Newhouse59, Yulia Newton37, Alvin Wei Tian Ng534, Anthony Ng535, Jonathan Nicholson49, David Nicol221, Yongzhan Nie321,536, G. Petur Nielsen72, Morten Muhlig Nielsen73, Serena Nik-Zainal49,281,282,537, Michael S. Noble8, Katia Nones209,311, Paul A. Northcott538, Faiyaz Notta148,539, Brian D. O’Connor76,540, Peter O’Donnell541, Maria O’Donovan282, Sarah O’Meara49, Brian Patrick O’Neill542, J. Robert O’Neill543, David Ocana59, Angelica Ochoa88, Layla Oesper544, Christopher Ogden221, Hideki Ohdan93, Kazuhiro Ohi375, Lucila Ohno-Machado244, Karin A. Oien523,545, Akinyemi I. Ojesina546,547,548, Hidenori Ojima549, Takuji Okusaka550, Larsson Omberg551, Choon Kiat Ong552, Stephan Ossowski52,53,74, German Ott553, B. F. Francis Ouellette76,554, Christine P’ng6, Marta Paczkowska6, Salvatore Paiella115, Chawalit Pairojkul523, Marina Pajic170, Qiang Pan-Hammarström56,555, Elli Papaemmanuil49, Irene Papatheodorou59, Nagarajan Paramasivam43,47, Ji Wan Park385, Joong-Won Park556, Keunchil Park557,558, Kiejung Park559, Peter J. Park264,266, Joel S. Parker518, Simon L. Parsons124, Harvey Pass560, Danielle Pasternack272, Alessandro Pastore276, Ann-Marie Patch209,311, Iris Pauporté251, Antonio Pea115, John V. Pearson209,311, Chandra Sekhar Pedamallu8,14,82, Jakob Skou Pedersen73,75, Paolo Pederzoli115, Martin Peifer270, Nathan A. Pennell561, Charles M. Perou129,518, Marc D. Perry76,77, Gloria M. Petersen562, Myron Peto22, Nicholas Petrelli563, Robert Petryszak59, Stefan M. Pfister426,465,564, Mark Phillips424, Oriol Pich298,299, Hilda A. Pickett478, Todd D. Pihl565, Nischalan Pillay566, Sarah Pinder567, Mark Pinese170, Andreia V. Pinho568, Esa Pitkänen60, Xavier Pivot569, Elena Piñeiro-Yáñez95, Laura Planko533, Christoph Plass345, Paz Polak8,14,15, Tirso Pons570, Irinel Popescu571, Olga Potapova572, Aparna Prasad52, Shaun R. Preston573, Manuel Prinz47, Antonia L. Pritchard311, Stephenie D. Prokopec6, Elena Provenzano574, Xose S. Puente499, Sonia Puig176, Montserrat Puiggròs57, Sergio Pulido-Tamayo505,506, Gulietta M. Pupo246, Colin A. Purdie575, Michael C. Quinn209,311, Raquel Rabionet52,53,576, Janet S. Rader577, Bernhard Radlwimmer397, Petar Radovic284, Benjamin Raeder60, Keiran M. Raine49, Manasa Ramakrishna49, Kamna Ramakrishnan49, Suresh Ramalingam578, Benjamin J. Raphael579, W. Kimryn Rathmell580, Tobias Rausch60, Guido Reifenberger475, Jüri Reimand6,44, Jorge Reis-Filho348, Victor Reuter348, Iker Reyes-Salazar298, Matthew A. Reyna579, Sheila M. Reynolds36, Esther Rheinbay8,14,72, Yasser Riazalhosseini189, Andrea L. Richardson323, Julia Richter111,128, Matthew Ringel581, Markus Ringnér181, Yasushi Rino582, Karsten Rippe405, Jeffrey Roach583, Lewis R. Roberts349, Nicola D. Roberts49, Steven A. Roberts584, A. Gordon Robertson30, Alan J. Robertson113, Javier Bartolomé Rodriguez57, Bernardo Rodriguez-Martin104,105,106, F. Germán Rodríguez-González83,332, Michael H. A. Roehrl44,123,148,234,585,586, Marius Rohde587, Hirofumi Rokutan440, Gilles Romieu588, Ilse Rooman170, Tom Roques262, Daniel Rosebrock8, Mara Rosenberg8,72, Philip C. Rosenstiel589, Andreas Rosenwald590, Edward W. Rowe221,591, Romina Royo57, Steven G. Rozen179,180,592, Yulia Rubanova17,127, Mark A. Rubin423,593,594,595,596, Carlota Rubio-Perez298,299,597, Vasilisa A. Rudneva60, Borislav C. Rusev177, Andrea Ruzzenente598, Gunnar Rätsch276,277,278,279,280,430, Radhakrishnan Sabarinathan298,299,599, Veronica Y. Sabelnykova6, Sara Sadeghi30, S. Cenk Sahinalp62,78,79, Natalie Saini357, Mihoko Saito-Adachi440, Gordon Saksena8, Adriana Salcedo6, Roberto Salgado600, Leonidas Salichos5,19, Richard Sallari8, Charles Saller601, Roberto Salvia115, Michelle Sam272, Jaswinder S. Samra115,602, Francisco Sanchez-Vega114,121, Chris Sander276,603,604, Grant Sanders134, Rajiv Sarin605, Iman Sarrafi62,78, Aya Sasaki-Oku184, Torill Sauer489, Guido Sauter520, Robyn P. M. Saw211, Maria Scardoni167, Christopher J. Scarlett170,606, Aldo Scarpa177, Ghislaine Scelo194, Dirk Schadendorf68,607, Jacqueline E. Schein30, Markus B. Schilhabel589, Matthias Schlesner47,80, Thorsten Schlomm84,608, Heather K. Schmidt1 , Sarah-Jane Schramm246, Stefan Schreiber609, Nikolaus Schultz121, Steven E. Schumacher8,323, Roland F. Schwarz59,403,405,610, Richard A. Scolyer211,448,602, David Scott428, Ralph Scully611, Raja Seethala612, Ayellet V. Segre8,613, Iris Selander260, Colin A. Semple434, Yasin Senbabaoglu276, Subhajit Sengupta614, Elisabetta Sereni115, Stefano Serra585, Dennis C. Sgroi72, Mark Shackleton103, Nimish C. Shah352, Sagedeh Shahabi234, Catherine A. Shang329, Ping Shang211, Ofer Shapira8,323, Troy Shelton271, Ciyue Shen603,604, Hui Shen615, Rebecca Shepherd49, Ruian Shi490, Yan Shi134, Yu-Jia Shiah6, Tatsuhiro Shibata118,616, Juliann Shih8,82, Eigo Shimizu375, Kiyo Shimizu617, Seung Jun Shin618, Yuichi Shiraishi375, Tal Shmaya285, Ilya Shmulevich36, Solomon I. Shorser6, Charles Short59, Raunak Shrestha62, Suyash S. Shringarpure217, Craig Shriver619, Shimin Shuai6,126, Nikos Sidiropoulos83, Reiner Siebert112,620, Anieta M. Sieuwerts332, Lina Sieverling205,237, Sabina Signoretti202,621, Katarzyna O. Sikora177, Michele Simbolo138, Ronald Simon520, Janae V. Simons134, Jared T. Simpson6,17, Peter T. Simpson473, Samuel Singer115,458, Nasa Sinnott-Armstrong8,217, Payal Sipahimalani30, Tara J. Skelly390, Marcel Smid332, Jaclyn Smith622, Karen Smith-McCune514, Nicholas D. Socci276, Heidi J. Sofia27, Matthew G. Soloway134, Lei Song240, Anil K. Sood623,624,625, Sharmila Sothi626, Christos Sotiriou244, Cameron M. Soulette37, Paul N. Span627, Paul T. Spellman22, Nicola Sperandio177, Andrew J. Spillane211, Oliver Spiro8, Jonathan Spring628, Johan Staaf181, Peter F. Stadler163,164,165, Peter Staib629, Stefan G. Stark277,279,618,630, Lucy Stebbings49, Ólafur Andri Stefánsson631, Oliver Stegle59,60,632, Lincoln D. Stein6,126, Alasdair Stenhouse633, Chip Stewart8, Stephan Stilgenbauer634, Miranda D. Stobbe52,61, Michael R. Stratton49, Jonathan R. Stretch211, Adam J. Struck31, Joshua M. Stuart24,37, Henk G. Stunnenberg396,635, Hong Su56,396, Xiaoping Su99, Ren X. Sun6, Stephanie Sungalee60, Hana Susak52,53, Akihiro Suzuki89,636, Fred Sweep637, Monika Szczepanowski128, Holger Sültmann67,638, Takashi Yugawa617, Angela Tam30, David Tamborero298,299, Benita Kiat Tee Tan639, Donghui Tan518, Patrick Tan180,532,592,640, Hiroko Tanaka375, Hirokazu Taniguchi616, Tomas J. Tanskanen641, Maxime Tarabichi49,290, Roy Tarnuzzer220, Patrick Tarpey642, Morgan L. Taschuk152, Kenji Tatsuno89, Simon Tavaré223,643, Darrin F. Taylor113, Amaro Taylor-Weiner8, Jon W. Teague49, Bin Tean Teh180,592,640,644,645, Varsha Tembe246, Javier Temes104,105, Kevin Thai76, Sarah P. Thayer393, Nina Thiessen30, Gilles Thomas646, Sarah Thomas221, Alan Thompson221, Alastair M. Thompson633, John F. Thompson211, R. Houston Thompson647, Heather Thorne103, Leigh B. Thorne176, Adrian Thorogood424, Grace Tiao8, Nebojsa Tijanic284, Lee E. Timms272, Roberto Tirabosco648, Marta Tojo106, Stefania Tommasi649, Christopher W. Toon170, Umut H. Toprak48,650, David Torrents57,81, Giampaolo Tortora651,652, Jörg Tost653, Yasushi Totoki118, David Townend654, Nadia Traficante103, Isabelle Treilleux655,656, Jean-Rémi Trotta61, Lorenz H. P. Trümper469, Ming Tsao124,539, Tatsuhiko Tsunoda183,657,658,659, Jose M. C. Tubio104,105,106, Olga Tucker660, Richard Turkington661, Daniel J. Turner513, Andrew Tutt323, Masaki Ueno376, Naoto T. Ueno662, Christopher Umbricht151,213,663, Husen M. Umer305,664, Timothy J. Underwood665, Lara Urban59,60, Tomoko Urushidate616, Tetsuo Ushiku339, Liis Uusküla-Reimand666,667, Alfonso Valencia57,81, David J. Van Den Berg166, Steven Van Laere307, Peter Van Loo290,291, Erwin G. Van Meir668, Gert G. Van den Eynden307, Theodorus Van der Kwast123, Naveen Vasudev137, Miguel Vazquez57,669, Ravikiran Vedururu267, Umadevi Veluvolu518, Shankar Vembu490,670, Lieven P. C. Verbeke506,671, Peter Vermeulen307, Clare Verrill351,672, Alain Viari177, David Vicente57, Caterina Vicentini177, K. Vijay Raghavan365, Juris Viksna673, Ricardo E. Vilain674, Izar Villasante57, Anne Vincent-Salomon635, Tapio Visakorpi190, Douglas Voet8, Paresh Vyas311,351, Ignacio Vázquez-García49,86,675,676, Nick M. Waddell209, Nicola Waddell209,311, Claes Wadelius677, Lina Wadi6, Rabea Wagener111,112, Jeremiah A. Wala8,14,82, Jian Wang56, Jiayin Wang1,40,66, Linghua Wang12, Qi Wang465, Wenyi Wang21, Yumeng Wang21, Zhining Wang220, Paul M. Waring523, Hans-Jörg Warnatz483, Jonathan Warrell5,19, Anne Y. Warren352,678, Sebastian M. Waszak60, David C. Wedge49,294,679, Dieter Weichenhan345, Paul Weinberger680, John N. Weinstein38, Joachim Weischenfeldt60,83,84, Daniel J. Weisenberger166, Ian Welch681, Michael C. Wendl1,10,11, Johannes Werner47,85, Justin P. Whalley61,682, David A. Wheeler12,13, Hayley C. Whitaker117, Dennis Wigle683, Matthew D. Wilkerson518, Ashley Williams244, James S. Wilmott211, Gavin W. Wilson6,148, Julie M. Wilson148, Richard K. Wilson1,684, Boris Winterhoff685, Jeffrey A. Wintersinger17,127,384, Maciej Wiznerowicz686,687, Stephan Wolf688, Bernice H. Wong689, Tina Wong1,30, Winghing Wong690, Youngchoon Woo250, Scott Wood209,311, Bradly G. Wouters44, Adam J. Wright6, Derek W. Wright133,691, Mark H. Wright217, Chin-Lee Wu72, Dai-Ying Wu285, Guanming Wu692, Jianmin Wu170, Kui Wu56,396, Yang Wu179,180, Zhenggang Wu64, Liu Xi12, Tian Xia693, Qian Xiang76, Xiao Xiao66, Rui Xing497, Heng Xiong56,396, Qinying Xu209,311, Yanxun Xu694, Hong Xue64, Shinichi Yachida118,695, Sergei Yakneen60, Rui Yamaguchi375, Takafumi N. Yamaguchi6, Masakazu Yamamoto120, Shogo Yamamoto89, Hiroki Yamaue376, Fan Yang490, Huanming Yang56, Jean Y. Yang696, Liming Yang220, Lixing Yang697, Shanlin Yang306, Tsun-Po Yang270, Yang Yang369, Xiaotong Yao408,698, Marie-Laure Yaspo483, Lucy Yates49, Christina Yau156, Chen Ye56,396, Kai Ye40,41, Venkata D. Yellapantula20,86, Christopher J. Yoon249, Sung-Soo Yoon463, Fouad Yousif6, Jun Yu699, Kaixian Yu700, Willie Yu701, Yingyan Yu702, Ke Yuan223,510,703, Yuan Yuan21, Denis Yuen6, Takashi Yugawa617, Christina K. Yung76, Olga Zaikova704, Jorge Zamora49,104,105,106, Marc Zapatka397, Jean C. Zenklusen220, Thorsten Zenz67, Nikolajs Zeps705,706, Cheng-Zhong Zhang8,707, Fan Zhang381, Hailei Zhang8, Hongwei Zhang494, Hongxin Zhang121, Jiashan Zhang220, Jing Zhang5, Junjun Zhang76, Xiuqing Zhang56, Xuanping Zhang66,369, Yan Zhang5,708,709, Zemin Zhang381,710, Zhongming Zhao711, Liangtao Zheng381, Xiuqing Zheng381, Wanding Zhou615, Yong Zhou56, Bin Zhu240, Hongtu Zhu700,712, Jingchun Zhu24, Shida Zhu56,396, Lihua Zou713, Xueqing Zou49, Anna deFazio246,247,714, Nicholas van As221, Carolien H. M. van Deurzen715, Marc J. van de Vijver523, L. van’t Veer716 & Christian von Mering433,717, The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts.

To examine cancer prevalence in men with and without military service history, using national-level self-reported outcomes.A cross-sectional survey-based US study, including men aged 18 and above from the Health Information National Trends Survey database between 2011 and 2014. The primary endpoint was self-reported cancer prevalence. Multivariable logistic regression analyses assessed the association of various covariates with the prevalence of cancer.A total of 4,527 men were analyzed, with 1,352 (29.9%) reporting a history of military service. Compared to men with no military service history, men with a military service history were older (median of 65 [IQR 56, 74] vs. 53 [IQR 41, 62] years, p 0.0001), more commonly Caucasian (71.4% vs. 61.4%, p 0.0001), born in the US (95.6% vs. 79.5%, p 0.0001), attained higher education level and annual household income (p 0.0001), and consisted of more smokers(58.3% vs. 44.5%, p 0.0001). The age-adjusted comparison demonstrated a higher cancer prevalence in men with military service history (20.5% vs. 7.6%, p 0.0001). Specifically, genitourinary, dermatological, gastrointestinal, and hematological cancers were generally more prevalent. Adjusting for all available confounders, multivariable models showed that military service history was associated with 1.56 (95% CI 1.20-2.03), and 1.57 (95% CI 1.07-2.31) increased odds of having any cancer, and specifically genitourinary cancer, respectively.Further research is needed to ascertain whether the association between military service and increased cancer diagnosis results from better screening programs or increased exposure to risk factors during military service.

Background Global DNA methylation alterations are hallmarks of cancer. The tumor-suppressive TET enzymes, which are involved in DNA demethylation, are decreased in prostate cancer (PCa); in particular, TET2 is specifically targeted by androgen-dependent mechanisms of repression in PCa and may play a central role in carcinogenesis. Thus, the identification of key genes targeted by TET2 dysregulation may provide further insight into cancer biology. Results Using a CRISPR/Cas9-derived TET2-knockout prostate cell line, and through whole-transcriptome and whole-methylome sequencing, we identified seven candidate genes—ASB2, ETNK2, MEIS2, NRG1, NTN1, NUDT10, and SRPX—exhibiting reduced expression and increased promoter methylation, a pattern characteristic of tumor suppressors. Decreased expression of these genes significantly discriminates between recurrent and non-recurrent prostate tumors from the Cancer Genome Atlas (TCGA) cohort (n = 423), and ASB2, NUDT10, and SRPX were significantly correlated with lower recurrence-free survival in patients by Kaplan-Meier analysis. ASB2, MEIS2, and SRPX also showed significantly lower expression in high-risk Gleason score 8 tumors as compared to low or intermediate risk tumors, suggesting that these genes may be particularly useful as indicators of PCa progression. Furthermore, methylation array probes in the TCGA dataset, which were proximal to the highly conserved, differentially methylated sites identified in our TET2-knockout cells, were able to significantly distinguish between matched prostate tumor and normal prostate tissues (n = 50 pairs). Except ASB2, all genes exhibited significantly increased methylation at these probes, and methylation status of at least one probe for each of these genes showed association with measures of PCa progression such as recurrence, stage, or Gleason score. Since ASB2 did not have any probes within the TET2-knockout differentially methylated region, we validated ASB2 methylation in an independent series of matched tumor-normal samples (n = 19) by methylation-specific qPCR, which revealed concordant and significant increases in promoter methylation within the TET2-knockout site. Conclusions Our study identifies seven genes governed by TET2 loss in PCa which exhibit an association between their methylation and expression status and measures of PCa progression. As differential methylation profiles and TET2 expression are associated with advanced PCa, further investigation of these specialized TET2 targets may provide important insights into patterns of carcinogenic gene dysregulation. Electronic supplementary material The online version of this article (10.1186/s13148-019-0651-z) contains supplementary material, which is available to authorized users.

Patients with prostate cancer on active surveillance are monitored by repeat prostate specific antigen measurements, digital rectal examinations and prostate biopsies. A subset of patients on active surveillance will later reclassify with disease progression, prompting definitive treatment. To minimize the risk of under treating such patients on active surveillance minimally invasive tests are urgently needed incorporating biomarkers to identify patients who will reclassify.We assessed post-digital rectal examination urine samples of patients on active surveillance for select DNA methylation biomarkers that were previously investigated in radical prostatectomy specimens and shown to correlate with an increasing risk of prostate cancer. Post-digital rectal examination urine samples were prospectively collected from 153 men on active surveillance who were diagnosed with Gleason score 6 disease. Urinary sediment DNA was analyzed for 8 DNA methylation biomarkers by multiplex MethyLight assay. Correlative analyses were performed on gene methylation and clinicopathological variables to test the ability to predict patient risk reclassification.Using backward logistic regression a 4-gene methylation classifier panel (APC, CRIP3, GSTP1 and HOXD8) was identified. The classifier panel was able to predict patient reclassification (OR 2.559, 95% CI 1.257-5.212). We observed this panel to be an independent and superior predictor compared to current clinical predictors such as prostate specific antigen at diagnosis or the percent of tumor positive cores in the initial biopsy.We report that a urine based classifier panel of 4 methylation biomarkers predicts disease progression in patients on active surveillance. Once validated in independent active surveillance cohorts, these promising biomarkers may help establish a less invasive method to monitor patients on active surveillance programs.

Purpose Liquid biopsies that noninvasively detect molecular correlates of aggressive prostate cancer (PCa) could be used to triage patients, reducing the burdens of unnecessary invasive prostate biopsy and enabling early detection of high-risk disease. DNA hypermethylation is among the earliest and most frequent aberrations in PCa. We investigated the accuracy of a six-gene DNA methylation panel (Epigenetic Cancer of the Prostate Test in Urine [epiCaPture]) at detecting PCa, high-grade (Gleason score greater than or equal to 8) and high-risk (D’Amico and Cancer of the Prostate Risk Assessment] PCa from urine. Patients and Methods Prognostic utility of epiCaPture genes was first validated in two independent prostate tissue cohorts. epiCaPture was assessed in a multicenter prospective study of 463 men undergoing prostate biopsy. epiCaPture was performed by quantitative methylation-specific polymerase chain reaction in DNA isolated from prebiopsy urine sediments and evaluated by receiver operating characteristic and decision curves (clinical benefit). The epiCaPture score was developed and validated on a two thirds training set to one third test set. Results Higher methylation of epiCaPture genes was significantly associated with increasing aggressiveness in PCa tissues. In urine, area under the receiver operating characteristic curve was 0.64, 0.86, and 0.83 for detecting PCa, high-grade PCa, and high-risk PCa, respectively. Decision curves revealed a net benefit across relevant threshold probabilities. Independent analysis of two epiCaPture genes in the same clinical cohort provided analytical validation. Parallel epiCaPture analysis in urine and matched biopsy cores showed added value of a liquid biopsy. Conclusion epiCaPture is a urine DNA methylation test for high-risk PCa. Its tumor specificity out-performs that of prostate-specific antigen (greater than 3 ng/mL). Used as an adjunct to prostate-specific antigen, epiCaPture could aid patient stratification to determine need for biopsy.

ObjectivesTo systematically review and meta-analyze the current literature in a methodologically rigorous and transparent manner for quantitative evidence on survival outcomes among patients diagnosed with muscle-invasive bladder cancer that were treated by either trimodal therapy or radical cystectomy.Materials and methodsMEDLINE, EMBASE, CENTRAL were systematically searched for comparative observational studies reporting disease-specific survival and/or overall survival on adult patients diagnosed with localized muscle-invasive bladder cancer that were exposed to either trimodal therapy or radical cystectomy. Studies qualified for meta-analysis (random effects model) if they were not at critical risk of bias (RoB).ResultsThe literature search identified 12 eligible studies. Three (all rated as "moderate RoB") out of 6 studies reporting on disease-specific survival qualified for quantitative analysis and yielded a pooled hazard ratio (trimodal therapy versus radical cystectomy) of 1.39 (95% confidence interval: 1.03-1.88). Four (mainly rated as "serious RoB") out of 12 studies were included in the meta-analysis of overall survival and estimated a hazard ratio of 1.39 (1.20-1.59).ConclusionPooled results were significant in favor of radical cystectomy. The conclusion is mainly driven by large population-based studies that are at high RoB. Hence, the certainty of these treatment estimates can be considered very low and further research will likely have an important impact on these estimates. At present, the ultimate decision between trimodal therapy and radical cystectomy should be left to the patient based on individual preferences and on the recommendation of a multidisciplinary provider team experienced with both approaches.