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While being in a committed relationship is associated with a better prostate cancer prognosis, little is known about how marital status relates to its incidence. Social support provided by marriage/relationship could promote a healthy lifestyle and an increased healthcare seeking behavior. We investigated the association between marital status and prostate cancer risk using data from the PRACTICAL Consortium. Pooled analyses were conducted combining 12 case–control studies based on histologically-confirmed incident prostate cancers and controls with information on marital status prior to diagnosis/interview. Marital status was categorized as married/partner, separated/divorced, single, or widowed. Tumours with Gleason scores ≥ 8 defined high-grade cancers, and low-grade otherwise. NCI-SEER’s summary stages (local, regional, distant) indicated the extent of the cancer. Logistic regression was used to derive odds ratios (ORs) and 95% confidence intervals (CI) for the association between marital status and prostate cancer risk, adjusting for potential confounders. Overall, 14,760 cases and 12,019 controls contributed to analyses. Compared to men who were married/with a partner, widowed men had an OR of 1.19 (95% CI 1.03–1.35) of prostate cancer, with little difference between low- and high-grade tumours. Risk estimates among widowers were 1.14 (95% CI 0.97–1.34) for local, 1.53 (95% CI 1.22–1.92) for regional, and 1.56 (95% CI 1.05–2.32) for distant stage tumours. Single men had elevated risks of high-grade cancers. Our findings highlight elevated risks of incident prostate cancer among widowers, more often characterized by tumours that had spread beyond the prostate at the time of diagnosis. Social support interventions and closer medical follow-up in this sub-population are warranted.

Background Family history of prostate cancer (PCa) is a well-known risk factor, and both common and rare genetic variants are associated with the disease. Objective To detect new genetic variants associated with PCa, capitalizing on the role of family history and more aggressive PCa. Design, setting, and participants A two-stage design was used. In stage one, whole-exome sequencing was used to identify potential risk alleles among affected men with a strong family history of disease or with more aggressive disease (491 cases and 429 controls). Aggressive disease was based on a sum of scores for Gleason score, node status, metastasis, tumor stage, prostate-specific antigen at diagnosis, systemic recurrence, and time to PCa death. Genes identified in stage one were screened in stage two using a custom-capture design in an independent set of 2917 cases and 1899 controls. Outcome measurements and statistical analysis Frequencies of genetic variants (singly or jointly in a gene) were compared between cases and controls. Results and limitations Eleven genes previously reported to be associated with PCa were detected (ATM, BRCA2, HOXB13, FAM111A, EMSY, HNF1B, KLK3, MSMB, PCAT1, PRSS3, and TERT), as well as an additional 10 novel genes (PABPC1, QK1, FAM114A1, MUC6, MYCBP2, RAPGEF4, RNASEH2B, ULK4, XPO7, and THAP3). Of these 10 novel genes, all but PABPC1 and ULK4 were primarily associated with the risk of aggressive PCa. Conclusions Our approach demonstrates the advantage of gene sequencing in the search for genetic variants associated with PCa and the benefits of sampling patients with a strong family history of disease or an aggressive form of disease. Patient summary Multiple genes are associated with prostate cancer (PCa) among men with a strong family history of this disease or among men with an aggressive form of PCa.

International audience; Although men of African ancestry have a high risk of prostate cancer (PCa), no genes or mutations have been identified that contribute to familial clustering of PCa in this population. We investigated whether the African ancestry-specific PCa risk variant at 8q24, rs72725854, is enriched in men with a PCa family history in 9052 cases, 143 cases from high-risk families, and 8595 controls of African ancestry. We found the risk allele to be significantly associated with earlier age at diagnosis, more aggressive disease, and enriched in men with a PCa family history (32% of high-risk familial cases carried the variant vs 23% of cases without a family history and 12% of controls). For cases with two or more first-degree relatives with PCa who had at least one family member diagnosed at age

Background: Molecular studies have tried to address the unmet need for prognostic biomarkers in prostate cancer (PCa). Some gene expression tests improve upon clinical factors for prediction of outcomes, but additional tools for accurate prediction of tumor aggressiveness are needed. Methods: Based on a previously published panel of 23 gene transcripts that distinguished patients with metastatic progression, we constructed a prediction model using independent training and testing datasets. Using the validated messenger RNAs and Gleason score (GS), we performed model selection in the training set to define a final locked model to classify patients who developed metastatic-lethal events from those who remained recurrence-free. In an independent testing dataset, we compared our locked model to established clinical prognostic factors and utilized Kaplan-Meier curves and receiver operating characteristic analyses to evaluate the model's performance. Results: Thirteen of 23 previously identified gene transcripts that stratified patients with aggressive PCa were validated in the training dataset. These biomarkers plus GS were used to develop a four-gene (CST2, FBLN1, TNFRSF19, and ZNF704) transcript (4GT) score that was significantly higher in patients who progressed to metastatic-lethal events compared to those without recurrence in the testing dataset (P = 5.7 × 10-11). The 4GT score provided higher prediction accuracy (area under the ROC curve [AUC] = 0.76; 95% confidence interval [CI] = 0.69-0.83; partial area under the ROC curve [pAUC] = 0.008) than GS alone (AUC = 0.63; 95% CI = 0.56-0.70; pAUC = 0.002), and it improved risk stratification in subgroups defined by a combination of clinicopathological features (ie, Cancer of the Prostate Risk Assessment-Surgery). Conclusion: Our validated 4GT score has prognostic value for metastatic-lethal progression in men treated for localized PCa and warrants further evaluation for its clinical utility.

While being in a committed relationship is associated with a better prostate cancer prognosis, little is known about how marital status relates to its incidence. Social support provided by marriage/relationship could promote a healthy lifestyle and an increased healthcare seeking behavior. We investigated the association between marital status and prostate cancer risk using data from the PRACTICAL Consortium. Pooled analyses were conducted combining 12 case-control studies based on histologically-confirmed incident prostate cancers and controls with information on marital status prior to diagnosis/interview. Marital status was categorized as married/partner, separated/divorced, single, or widowed. Tumours with Gleason scores ≥ 8 defined high-grade cancers, and low-grade otherwise. NCI-SEER's summary stages (local, regional, distant) indicated the extent of the cancer. Logistic regression was used to derive odds ratios (ORs) and 95% confidence intervals (CI) for the association between marital status and prostate cancer risk, adjusting for potential confounders. Overall, 14,760 cases and 12,019 controls contributed to analyses. Compared to men who were married/with a partner, widowed men had an OR of 1.19 (95% CI 1.03-1.35) of prostate cancer, with little difference between low- and high-grade tumours. Risk estimates among widowers were 1.14 (95% CI 0.97-1.34) for local, 1.53 (95% CI 1.22-1.92) for regional, and 1.56 (95% CI 1.05-2.32) for distant stage tumours. Single men had elevated risks of high-grade cancers. Our findings highlight elevated risks of incident prostate cancer among widowers, more often characterized by tumours that had spread beyond the prostate at the time of diagnosis. Social support interventions and closer medical follow-up in this sub-population are warranted.

Background: There is preliminary evidence linking physical activity to better prostate cancer outcomes, though the molecular mechanisms underlying this association are not clear. Methods: In a Seattle-based cohort of patients diagnosed with clinically localized prostate cancer and prospective follow-up for outcomes (n = 1,354), we studied the association between self-reported vigorous physical activity and prostate cancer progression to a metastatic–lethal phenotype. A subset of patients had prostate cancer tissue samples available for investigating DNA methylation (Infinium HumanMethylation450 BeadChip array) and exercise (n = 524). Results: Patients who had vigorous physical activity at least once per week during the year before diagnosis (∼79% of the cohort) were significantly less likely to progress to metastatic–lethal prostate cancer compared with those who had vigorous physical activity less frequently (adjusted hazard ratio = 0.63; P = 0.029). Among the subset of men who had radical prostatectomy as primary treatment and tumor tissue available, a differentially methylated region (DMR) was identified (family-wise error rate = 0.03, hypomethylated in the weekly exercise group), with 9 methylation probes located in the promoter region of CRACR2A. This gene encodes a calcium binding protein involved in innate immune response. The methylation level of the nine CpGs was inversely correlated with CRACR2A gene expression (average correlation coefficient = –0.35). Conclusions: Vigorous physical activity before diagnosis is associated with epigenetic alterations of CRACR2A and prostate cancer metastatic–lethal progression. Impact: This analysis provides strong evidence for the association between vigorous physical activity and a less likelihood to develop metastatic–lethal progression, and a suggestive link between exercise and DNA methylation in the CRACRA2A gene.

Background: Whether associations between circulating metabolites and prostate cancer are causal is unknown. We report on the largest study of metabolites and prostate cancer (2,291 cases and 2,661 controls) and appraise causality for a subset of the prostate cancer–metabolite associations using two-sample Mendelian randomization (MR). Methods: The case–control portion of the study was conducted in nine UK centers with men ages 50–69 years who underwent prostate-specific antigen screening for prostate cancer within the Prostate Testing for Cancer and Treatment (ProtecT) trial. Two data sources were used to appraise causality: a genome-wide association study (GWAS) of metabolites in 24,925 participants and a GWAS of prostate cancer in 44,825 cases and 27,904 controls within the Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL) consortium. Results: Thirty-five metabolites were strongly associated with prostate cancer (P < 0.0014, multiple-testing threshold). These fell into four classes: (i) lipids and lipoprotein subclass characteristics (total cholesterol and ratios, cholesterol esters and ratios, free cholesterol and ratios, phospholipids and ratios, and triglyceride ratios); (ii) fatty acids and ratios; (iii) amino acids; (iv) and fluid balance. Fourteen top metabolites were proxied by genetic variables, but MR indicated these were not causal. Conclusions: We identified 35 circulating metabolites associated with prostate cancer presence, but found no evidence of causality for those 14 testable with MR. Thus, the 14 MR-tested metabolites are unlikely to be mechanistically important in prostate cancer risk. Impact: The metabolome provides a promising set of biomarkers that may aid prostate cancer classification.

This study examined whether differential DNA methylation is associated with clinical features of more aggressive disease at diagnosis and prostate cancer recurrence in African American men, who are more likely to die from prostate cancer than other populations. Tumor tissues from 76 African Americans diagnosed with prostate cancer who had radical prostatectomy as their primary treatment were profiled for epigenome-wide DNA methylation levels. Long-term follow-up identified 19 patients with prostate cancer recurrence. Twenty-three CpGs were differentially methylated (FDR q≤0.25, mean methylation difference ≥0.10) in patients with vs. without recurrence, including CpGs in GCK, CDKL2, PRDM13, and ZFR2. Methylation differences were also observed between men with metastatic-lethal prostate cancer vs. no recurrence (five CpGs), regional vs. local pathological stage (two CpGs), and higher vs. lower tumor aggressiveness (one CpG). These results indicate that differentially methylated CpG sites identified in tumor tissues of African American men may contribute to prostate cancer aggressiveness.

Motivation The use of single nucleotide polymorphism (SNP) interactions to predict complex diseases is getting more attention during the past decade, but related statistical methods are still immature. We previously proposed the SNP Interaction Pattern Identifier (SIPI) approach to evaluate 45 SNP interaction patterns/patterns. SIPI is statistically powerful but suffers from a large computation burden. For large-scale studies, it is necessary to use a powerful and computation-efficient method. The objective of this study is to develop an evidence-based mini-version of SIPI as the screening tool or solitary use and to evaluate the impact of inheritance mode and model structure on detecting SNP–SNP interactions. Results We tested two candidate approaches: the ‘Five-Full’ and ‘AA9int’ method. The Five-Full approach is composed of the five full interaction models considering three inheritance modes (additive, dominant and recessive). The AA9int approach is composed of nine interaction models by considering non-hierarchical model structure and the additive mode. Our simulation results show that AA9int has similar statistical power compared to SIPI and is superior to the Five-Full approach, and the impact of the non-hierarchical model structure is greater than that of the inheritance mode in detecting SNP–SNP interactions. In summary, it is recommended that AA9int is a powerful tool to be used either alone or as the screening stage of a two-stage approach (AA9int+SIPI) for detecting SNP–SNP interactions in large-scale studies. Availability and implementation The ‘AA9int’ and ‘parAA9int’ functions (standard and parallel computing version) are added in the SIPI R package, which is freely available at https://linhuiyi.github.io/LinHY_Software/. Supplementary information Supplementary data are available at Bioinformatics online.

Urologists have been criticized for overtreating men with low risk prostate cancer and for passively observing older men with higher risk disease. Proponents of active surveillance for low risk disease and critics of watchful waiting for higher risk disease have advocated for more judicious use of observation. Thus, we compared 2 population based cohorts to determine how expectant management has evolved during the last 2 decades.A total of 5,871 men with localized prostate cancer were enrolled in the PCOS (Prostate Cancer Outcomes Study) or the CEASAR (Comparative Effectiveness Analysis of Surgery and Radiation) study. We compared the use of definitive treatment vs expectant management (watchful waiting or active surveillance) across cohorts, focusing on the influence of disease risk, age and comorbidities.Use of watchful waiting or active surveillance was similar in PCOS and CEASAR (14% in each). Compared to the PCOS, more men in the CEASAR study with low risk disease selected watchful waiting or active surveillance (25% vs 15%, respectively), whereas fewer men with intermediate (7% vs 14%) and high risk (3% vs 10%) disease chose watchful waiting or active surveillance (p0.001 for each). The association of disease risk with watchful waiting or active surveillance was significantly larger in CEASAR than in PCOS (OR 7.3, 95% CI 3.4 to 15.7). Older age was associated with watchful waiting or active surveillance in both cohorts but there was no association between comorbidity and watchful waiting or active surveillance in the CEASAR study.Use of watchful waiting or active surveillance was more aligned with disease risk in CEASAR compared to PCOS, suggesting there has been a pivot from watchful waiting to active surveillance. While older men were more likely to be observed, comorbidity had little, if any, influence.

Next-generation sequencing technologies have afforded unprecedented characterization of low-frequency and rare genetic variation. Due to low power for single-variant testing, aggregative methods are commonly used to combine observed rare variation within a single gene. Causal variation may also aggregate across multiple genes within relevant biomolecular pathways. Kernel-machine regression and adaptive testing methods for aggregative rare-variant association testing have been demonstrated to be powerful approaches for pathway-level analysis, although these methods tend to be computationally intensive at high-variant dimensionality and require access to complete data. An additional analytical issue in scans of large pathway definition sets is multiple testing correction. Gene set definitions may exhibit substantial genic overlap, and the impact of the resultant correlation in test statistics on Type I error rate control for large agnostic gene set scans has not been fully explored. Herein, we first outline a statistical strategy for aggregative rare-variant analysis using component gene-level linear kernel score test summary statistics as well as derive simple estimators of the effective number of tests for family-wise error rate control. We then conduct extensive simulation studies to characterize the behavior of our approach relative to direct application of kernel and adaptive methods under a variety of conditions. We also apply our method to two case-control studies, respectively, evaluating rare variation in hereditary prostate cancer and schizophrenia. Finally, we provide open-source R code for public use to facilitate easy application of our methods to existing rare-variant analysis results.

Supplemental Data Supplemental Data include one figure and five tables and can be found with this article online at http://dx.doi.org/10.1016/j.ajhg.2016.08.016. Supplemental Data Document S1. Figure S1 and Tables S1–S5 Download Document S2. Article plus Supplemental Data Download Web Resources ClinVar, https://www.ncbi.nlm.nih.gov/clinvar/ dbNSFP, https://sites.google.com/site/jpopgen/dbNSFP Human Gene Mutation Database, http://www.hgmd.cf.ac.uk/ REVEL, https://sites.google.com/site/revelgenomics/ SwissVar, http://swissvar.expasy.org/ The vast majority of coding variants are rare, and assessment of the contribution of rare variants to complex traits is hampered by low statistical power and limited functional data. Improved methods for predicting the pathogenicity of rare coding variants are needed to facilitate the discovery of disease variants from exome sequencing studies. We developed REVEL (rare exome variant ensemble learner), an ensemble method for predicting the pathogenicity of missense variants on the basis of individual tools: MutPred, FATHMM, VEST, PolyPhen, SIFT, PROVEAN, MutationAssessor, MutationTaster, LRT, GERP, SiPhy, phyloP, and phastCons. REVEL was trained with recently discovered pathogenic and rare neutral missense variants, excluding those previously used to train its constituent tools. When applied to two independent test sets, REVEL had the best overall performance (p < 10−12) as compared to any individual tool and seven ensemble methods: MetaSVM, MetaLR, KGGSeq, Condel, CADD, DANN, and Eigen. Importantly, REVEL also had the best performance for distinguishing pathogenic from rare neutral variants with allele frequencies

Rare variants (RVs) have been shown to be significant contributors to complex disease risk. By definition, these variants have very low minor allele frequencies and traditional single-marker methods for statistical analysis are underpowered for typical sequencing study sample sizes. Multimarker burden-type approaches attempt to identify aggregation of RVs across case-control status by analyzing relatively small partitions of the genome, such as genes. However, it is generally the case that the aggregative measure would be a mixture of causal and neutral variants, and these omnibus tests do not directly provide any indication of which RVs may be driving a given association. Recently, Bayesian variable selection approaches have been proposed to identify RV associations from a large set of RVs under consideration. Although these approaches have been shown to be powerful at detecting associations at the RV level, there are often computational limitations on the total quantity of RVs under consideration and compromises are necessary for large-scale application. Here, we propose a computationally efficient alternative formulation of this method using a probit regression approach specifically capable of simultaneously analyzing hundreds to thousands of RVs. We evaluate our approach to detect causal variation on simulated data and examine sensitivity and specificity in instances of high RV dimensionality as well as apply it to pathway-level RV analysis results from a prostate cancer (PC) risk case-control sequencing study. Finally, we discuss potential extensions and future directions of this work.

Background Aberrant DNA methylation may promote prostate carcinogenesis. We investigated epigenome-wide DNA methylation profiles in prostate cancer (PCa) compared to adjacent benign tissue to identify differentially methylated CpG sites. Methods The study included paired PCa and adjacent benign tissue samples from 20 radical prostatectomy patients. Epigenetic profiling was done using the Infinium HumanMethylation450 BeadChip. Linear models that accounted for the paired study design and False Discovery Rate Q-values were used to evaluate differential CpG methylation. mRNA expression levels of the genes with the most differentially methylated CpG sites were analyzed. Results In total, 2,040 differentially methylated CpG sites were identified in PCa versus adjacent benign tissue (Q-value

BACKGROUND: Polygenic risk scores comprising established susceptibility variants have shown to be informative classifiers for several complex diseases including prostate cancer. For prostate cancer it is unknown if inclusion of genetic markers that have so far not been associated with prostate cancer risk at a genome-wide significant level will improve disease prediction. METHODS: We built polygenic risk scores in a large training set comprising over 25,000 individuals. Initially 65 established prostate cancer susceptibility variants were selected. After LD pruning additional variants were prioritized based on their association with prostate cancer. Six-fold cross validation was performed to assess genetic risk scores and optimize the number of additional variants to be included. The final model was evaluated in an independent study population including 1,370 cases and 1,239 controls. RESULTS: The polygenic risk score with 65 established susceptibility variants provided an area under the curve (AUC) of 0.67. Adding an additional 68 novel variants significantly increased the AUC to 0.68 (P = 0.0012) and the net reclassification index with 0.21 (P = 8.5E-08). All novel variants were located in genomic regions established as associated with prostate cancer risk. CONCLUSIONS: Inclusion of additional genetic variants from established prostate cancer susceptibility regions improves disease prediction.

© 2014 European Association of Urology. Published by Elsevier B.V. All rights reserved. Background Despite the paramount importance of patient-reported outcomes, little is known about the evolution of patient-reported urinary and sexual function over time. Objective To evaluate differences in pretreatment urinary and sexual function in two population-based cohorts of men with prostate cancer enrolled nearly 20 yr apart. Design, setting, and participants Patients were enrolled in the Prostate Cancer Outcomes Study (PCOS) or the Comparative Effectiveness Analysis of Surgery and Radiation (CEASAR) study, two population-based cohorts that enrolled patients with incident prostate cancer from 1994 to 1995 and from 2011 to 2012, respectively. Participants completed surveys at baseline and various time points thereafter. Outcome measurements and statistical analysis We performed multivariable logistic and linear regression analysis to investigate differences in pretreatment function between studies. Results and limitations The study comprised 5469 men of whom 2334 (43%) were enrolled in PCOS and 3135 (57%) were enrolled in CEASAR. Self-reported urinary incontinence was higher in CEASAR compared with PCOS (7.7% vs 4.7%; adjusted odds ratio [OR]: 1.83; 95% confidence interval [CI], 1.39-2.43). Similarly, self-reported erectile dysfunction was more common among CEASAR participants (44.7% vs 24.0%) with an adjusted OR of 3.12 (95% CI, 2.68-3.64). Multivariable linear regression models revealed less favorable self-reported baseline function among CEASAR participants in the urinary incontinence and sexual function domains. The study is limited by its observational design and possibility of unmeasured confounding. Conclusions Reporting of pretreatment urinary incontinence and erectile dysfunction has increased over the past two decades. These findings may reflect sociological changes including heightened media attention and direct-to-consumer marketing, among other potential explanations. Patient summary Patient reporting of urinary and sexual function has evolved and is likely contingent on continually changing societal norms. Recognizing the evolving nature of patient reporting is essential in efforts to conduct high-quality, impactful comparative effectiveness research.

BACKGROUND Prostate cancer (PCa) is clinically and biologically heterogeneous, making it difficult to predict at detection whether it will take an indolent or aggressive disease course. Cell cycle-regulated genes may be more highly expressed in actively dividing cells, with transcript levels reflecting tumor growth rate. Here, we evaluated expression of cell cycle genes in relation to PCa outcomes in a population-based cohort. METHODS Gene expression data were generated from tumor tissues obtained at radical prostatectomy for 383 population-based patients (12.3-years average follow-up). The overall mean and individual transcript levels of 30 selected cell cycle genes was compared between patients with no evidence of recurrence (73%) and those who recurred (27%) or died (7%) from PCa. RESULTS The multivariate adjusted hazard ratio (HR) for a change from the 25th to 75th percentile of mean gene expression level (range 8.02–10.05) was 1.25 (95%CI 0.96–1.63; P = 0.10) for PCa recurrence risk, and did not vary substantially by Gleason score, TMPRSS2-ERG fusion status, or family history of PCa. For lethal PCa, the HR for a change (25th to 75th percentile) in mean gene expression level was 2.04 (95%CI 1.26–3.31; P = 0.004), adjusted for clinicopathological variables. The ROC curve for mean gene expression level alone (AUC = 0.740) did not perform as well as clinicopathological variables alone (AUC = 0.803) for predicting lethal PCa, and the addition of mean gene expression to clinicopathological variables did not substantially improve prediction (AUC = 0.827; P = 0.18). Higher TK1 expression was strongly associated with both recurrent (P = 6.7 × 10−5) and lethal (P = 6.4 × 10−6) PCa. CONCLUSIONS Mean expression level for 30 selected cell cycle-regulated genes was unrelated to recurrence risk, but was associated with a twofold increase in risk of lethal PCa. However, gene expression had less discriminatory accuracy than clinical variables alone for predicting lethal events. Transcript levels for several genes in the panel were significantly overexpressed in lethal versus non-recurrent PCa. Prostate 75:1354–1362, 2015. © 2015 Wiley Periodicals, Inc.

The T2E gene fusion, formed by fusion of the transmembrane protease, serine 2, gene (TMPRSS2) with the erythroblast transformation-specific (ETS)-related gene (ERG), is found in approximately 50% of prostate cancers and may characterize distinct molecular subtypes of prostate cancer with different etiologies. We investigated the relationship between body mass index (BMI; weight (kg)/height (m)(2)) and prostate cancer risk by T2E status. Study participants were residents of King County, Washington, recruited for 2 population-based case-control studies conducted in 1993-1996 and 2002-2005. Tumor T2E status was determined for 563 prostate cancer patients who underwent radical prostatectomy. Information on weight, height, and covariables was obtained through in-person interviews. We performed polytomous logistic regression to calculate odds ratios and 95% confidence intervals for T2E-positive and -negative prostate cancer. Comparing the highest BMI quartile with the lowest, inverse associations were observed between recent (≥29.7 vs.

Genetic studies have identified single nucleotide polymorphisms (SNPs) associated with the risk of prostate cancer (PC). It remains unclear whether such genetic variants are associated with disease aggressiveness. The NCI-SPORE Genetics Working Group retrospectively collected clinicopathologic information and genotype data for 36 SNPs which at the time had been validated to be associated with PC risk from 25,674 cases with PC. Cases were grouped according to race, Gleason score (Gleason ≤6, 7, ≥8) and aggressiveness (non-aggressive, intermediate, and aggressive disease). Statistical analyses were used to compare the frequency of the SNPs between different disease cohorts. After adjusting for multiple testing, only PC-risk SNP rs2735839 (G) was significantly and inversely associated with aggressive (OR=0.77; 95% CI 0.69–0.87) and high-grade disease (OR=0.77; 95% CI 0.68–0.86) in European men. Similar associations with aggressive (OR=0.72; 95% CI 0.58–0.89) and high-grade disease (OR=0.69; 95% CI 0.54–0.87) were documented in African-American subjects. The G allele of rs2735839 was associated with disease aggressiveness even at low PSA levels (

To assess the relationship between androgen deprivation therapy (ADT) exposure and self-reported bone complications among men in a population-based cohort of prostate cancer survivors followed for 15 years after diagnosis. The Prostate Cancer Outcomes Study enrolled 3533 patients diagnosed with prostate cancer between 1994 and 1995. This analysis included participants with non-metastatic disease at the time of diagnosis who completed 15-year follow-up surveys to report development of fracture, and use of bone-related medications. The relationship between ADT duration and bone complications was assessed using multivariable logistic regression models. Among 961 surviving men, 157 (16.3%) received prolonged ADT (>1 year), 120 (12.5%) received short-term ADT (⩽1 year) and 684 (71.2%) did not receive ADT. Men receiving prolonged ADT had higher odds of fracture (OR 2.5; 95% confidence interval (CI): 1.1–5.7), bone mineral density testing (OR 5.9; 95% CI: 3.0–12) and bone medication use (OR 4.3; 95% CI: 2.3–8.0) than untreated men. Men receiving short-term ADT reported rates of fracture similar to untreated men. Half of men treated with prolonged ADT reported bone medication use. In this population-based cohort study with long-term follow-up, prolonged ADT use was associated with substantial risks of fracture, whereas short-term use was not. This information should be considered when weighing the advantages and disadvantages of ADT in men with prostate cancer.

Background: One challenge in prostate cancer is distinguishing indolent from aggressive disease at diagnosis. DNA promoter hypermethylation is a frequent epigenetic event in prostate cancer, but few studies of DNA methylation in relation to features of more aggressive tumors or prostate cancer recurrence have been completed. Methods: We used the Infinium HumanMethylation450 BeadChip to assess DNA methylation in tumor tissue from 407 patients with clinically localized prostate cancer who underwent radical prostatectomy. Recurrence status was determined by follow-up patient surveys, medical record review, and linkage with the Surveillance, Epidemiology, and End Results (SEER) registry. The methylation status of 14 genes for which promoter hypermethylation was previously correlated with advanced disease or biochemical recurrence was evaluated. Average methylation level for promoter region CpGs in patients who recurred compared with those with no evidence of recurrence was analyzed. For two genes with differential methylation, time to recurrence was examined. Results: During an average follow-up of 11.7 years, 104 (26%) patients recurred. Significant promoter hypermethylation in at least 50% of CpG sites in two genes, ABHD9 and HOXD3, was found in tumors from patients who recurred compared with those without recurrence. Evidence was strongest for HOXD3 (lowest P = 9.46 × 10−6), with higher average methylation across promoter region CpGs associated with reduced recurrence-free survival (P = 2 × 10−4). DNA methylation profiles did not differ by recurrence status for the other genes. Conclusions: These results validate the association between promoter hypermethylation of ADHB9 and HOXD3 and prostate cancer recurrence. Impact: Tumor DNA methylation profiling may help to distinguish patients with prostate cancer at higher risk for disease recurrence. Cancer Epidemiol Biomarkers Prev; 23(7); 1331–9. ©2014 AACR.

Genome-wide association studies (GWAS) have identified 76 variants associated with prostate cancer risk predominantly in populations of European ancestry. To identify additional susceptibility loci for this common cancer, we conducted a meta-analysis of > 10 million SNPs in 43,303 prostate cancer cases and 43,737 controls from studies in populations of European, African, Japanese and Latino ancestry. Twenty-three new susceptibility loci were identified at association P < 5 × 10(-8); 15 variants were identified among men of European ancestry, 7 were identified in multi-ancestry analyses and 1 was associated with early-onset prostate cancer. These 23 variants, in combination with known prostate cancer risk variants, explain 33% of the familial risk for this disease in European-ancestry populations. These findings provide new regions for investigation into the pathogenesis of prostate cancer and demonstrate the usefulness of combining ancestrally diverse populations to discover risk loci for disease.

Background: Rare, inherited mutations account for 5% to 10% of all prostate cancer cases. However, to date, few causative mutations have been identified. Methods: To identify rare mutations for prostate cancer, we conducted whole-exome sequencing (WES) in multiple kindreds (n = 91) from 19 hereditary prostate cancer (HPC) families characterized by aggressive or early-onset phenotypes. Candidate variants (n = 130) identified through family- and bioinformatics-based filtering of WES data were then genotyped in an independent set of 270 HPC families (n = 819 prostate cancer cases; n = 496 unaffected relatives) for replication. Two variants with supportive evidence were subsequently genotyped in a population-based case–control study (n = 1,155 incident prostate cancer cases; n = 1,060 age-matched controls) for further confirmation. All participants were men of European ancestry. Results: The strongest evidence was for two germline missense variants in the butyrophilin-like 2 (BTNL2) gene (rs41441651, p.Asp336Asn and rs28362675, p.Gly454Cys) that segregated with affection status in two of the WES families. In the independent set of 270 HPC families, 1.5% (rs41441651; P = 0.0032) and 1.2% (rs28362675; P = 0.0070) of affected men, but no unaffected men, carried a variant. Both variants were associated with elevated prostate cancer risk in the population-based study (rs41441651: OR, 2.7; 95% CI, 1.27–5.87; P = 0.010; rs28362675: OR, 2.5; 95% CI, 1.16–5.46; P = 0.019). Conclusions: Results indicate that rare BTNL2 variants play a role in susceptibility to both familial and sporadic prostate cancer. Impact: Results implicate BTNL2 as a novel prostate cancer susceptibility gene. Cancer Epidemiol Biomarkers Prev; 22(9); 1520–8. ©2013 AACR.

BACKGROUND Recently, a genetic variant (rs10993994) in the MSMB gene associated with prostate cancer (PCa) risk was shown to correlate with reduced prostate secretory protein of 94 amino acids (PSP94) levels. Although the biological activity of PSP94 is unclear, one of its hypothesized functions is to protect prostatic cells from pathogens. Number of sexual partners and a history of sexually transmitted infections (STIs) have been positively associated with PCa risk, and these associations may be related to pathogen-induced chronic prostatic inflammation. Based on these observations, we investigated whether MSMB genotype modifies the PCa-sexual history association. METHODS We estimated odds ratios (ORs) and 95% confidence intervals (CIs) for the association between number of sexual partners and PCa by fitting logistic regression models, stratified by MSMB genotype, and adjusted for age, family history of PCa, and PCa screening history among 1,239 incident cases and 1,232 controls. RESULTS Compared with 1–4 female sexual partners, men with ≥15 such partners who carried the variant T allele of rs10993994 were at increased risk for PCa (OR = 1.32; 95% CI, 1.03–1.71); no association was observed in men with the CC genotype (OR = 1.03; 95% CI, 0.73–1.46; P = 0.05 for interaction). Similar estimates were observed for total sexual partners (any T allele OR = 1.37; 95% CI, 1.07–1.77; CC genotype OR = 1.11; 95% CI, 0.79–1.55; P = 0.06 for interaction). CONCLUSIONS The rs10993994 genotype in the MSMB gene modifies the association between number of sexual partners and PCa risk. These findings support a hypothesized biological mechanism whereby prostatic infection/inflammation may enhance risk of PCa. Prostate 73:1803–1809, 2013. © 2013 Wiley Periodicals, Inc.

INTRODUCTION Obese men have an increased risk of prostate cancer (PCa)-specific mortality. Potential mechanisms include insulin and related proteins. We investigate whether a short-term caloric restriction diet in overweight/obese men with newly diagnosed PCa can lead to measurable changes in patient anthropometrics and insulin-related proteins. METHODS Overweight and obese PCa patients choosing active surveillance or radical prostatectomy were randomized to a 6-week, caloric-restricted diet or to continue their current diet. Changes from baseline to end of study in anthropometrics, dietary constituents and serum proteins (insulin, c-peptide, IGF-1, adiponectin, IGF-BP3) were compared between the intervention and control groups using a Generalized Estimating Equation model. RESULTS Nineteen patients were randomized to the intervention (N = 10) or control (N = 9) group. Men in the intervention group had a 1.7% (3.7 lbs) mean decline in weight versus 1.0% (2.0 lbs) in controls (P