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We determined the effect of sample size on performance of polygenic hazard score (PHS) models in prostate cancer. Age and genotypes were obtained for 40,861 men from the PRACTICAL consortium. The dataset included 201,590 SNPs per subject, and was split into training and testing sets. Established-SNP models considered 65 SNPs that had been previously associated with prostate cancer. Discovery-SNP models used stepwise selection to identify new SNPs. The performance of each PHS model was calculated for random sizes of the training set. The performance of a representative Established-SNP model was estimated for random sizes of the testing set. Mean HR98/50 (hazard ratio of top 2% to average in test set) of the Established-SNP model increased from 1.73 [95% CI: 1.69-1.77] to 2.41 [2.40-2.43] when the number of training samples was increased from 1 thousand to 30 thousand. Corresponding HR98/50 of the Discovery-SNP model increased from 1.05 [0.93-1.18] to 2.19 [2.16-2.23]. HR98/50 of a representative Established-SNP model using testing set sample sizes of 0.6 thousand and 6 thousand observations were 1.78 [1.70-1.85] and 1.73 [1.71-1.76], respectively. We estimate that a study population of 20 thousand men is required to develop Discovery-SNP PHS models while 10 thousand men should be sufficient for Established-SNP models.

BackgroundA polygenic hazard score (PHS), the weighted sum of 54 SNP genotypes, was previously validated for association with clinically significant prostate cancer and for improved prostate cancer screening accuracy. Here, we assess the potential impact of PHS-informed screening.MethodsUnited Kingdom population incidence data (Cancer Research United Kingdom) and data from the Cluster Randomized Trial of PSA Testing for Prostate Cancer were combined to estimate age-specific clinically significant prostate cancer incidence (Gleason score ≥7, stage T3-T4, PSA ≥10, or nodal/distant metastases). Using HRs estimated from the ProtecT prostate cancer trial, age-specific incidence rates were calculated for various PHS risk percentiles. Risk-equivalent age, when someone with a given PHS percentile has prostate cancer risk equivalent to an average 50-year-old man (50-year-standard risk), was derived from PHS and incidence data. Positive predictive value (PPV) of PSA testing for clinically significant prostate cancer was calculated using PHS-adjusted age groups.ResultsThe expected age at diagnosis of clinically significant prostate cancer differs by 19 years between the 1st and 99th PHS percentiles: men with PHS in the 1st and 99th percentiles reach the 50-year-standard risk level at ages 60 and 41, respectively. PPV of PSA was higher for men with higher PHS-adjusted age.ConclusionsPHS provides individualized estimates of risk-equivalent age for clinically significant prostate cancer. Screening initiation could be adjusted by a man's PHS.ImpactPersonalized genetic risk assessments could inform prostate cancer screening decisions.

Genome-wide association studies (GWAS) and fine-mapping efforts to date have identified more than 100 prostate cancer (PrCa)-susceptibility loci. We meta-analyzed genotype data from a custom high-density array of 46,939 PrCa cases and 27,910 controls of European ancestry with previously genotyped data of 32,255 PrCa cases and 33,202 controls of European ancestry. Our analysis identified 62 novel loci associated (P C, p.Pro1054Arg) in ATM and rs2066827 (OR = 1.06; P = 2.3 × 10-9; T>G, p.Val109Gly) in CDKN1B. The combination of all loci captured 28.4% of the PrCa familial relative risk, and a polygenic risk score conferred an elevated PrCa risk for men in the ninetieth to ninety-ninth percentiles (relative risk = 2.69; 95% confidence interval (CI): 2.55-2.82) and first percentile (relative risk = 5.71; 95% CI: 5.04-6.48) risk stratum compared with the population average. These findings improve risk prediction, enhance fine-mapping, and provide insight into the underlying biology of PrCa1.

ObjectivesTo develop and validate a genetic tool to predict age of onset of aggressive prostate cancer (PCa) and to guide decisions of who to screen and at what age.DesignAnalysis of genotype, PCa status, and age to select single nucleotide polymorphisms (SNPs) associated with diagnosis. These polymorphisms were incorporated into a survival analysis to estimate their effects on age at diagnosis of aggressive PCa (that is, not eligible for surveillance according to National Comprehensive Cancer Network guidelines; any of Gleason score ≥7, stage T3-T4, PSA (prostate specific antigen) concentration ≥10 ng/L, nodal metastasis, distant metastasis). The resulting polygenic hazard score is an assessment of individual genetic risk. The final model was applied to an independent dataset containing genotype and PSA screening data. The hazard score was calculated for these men to test prediction of survival free from PCa.SettingMultiple institutions that were members of international PRACTICAL consortium.ParticipantsAll consortium participants of European ancestry with known age, PCa status, and quality assured custom (iCOGS) array genotype data. The development dataset comprised 31 747 men; the validation dataset comprised 6411 men.Main outcome measuresPrediction with hazard score of age of onset of aggressive cancer in validation set.ResultsIn the independent validation set, the hazard score calculated from 54 single nucleotide polymorphisms was a highly significant predictor of age at diagnosis of aggressive cancer (z=11.2, P98th centile) were compared with those with average scores (30th-70th centile), the hazard ratio for aggressive cancer was 2.9 (95% confidence interval 2.4 to 3.4). Inclusion of family history in a combined model did not improve prediction of onset of aggressive PCa (P=0.59), and polygenic hazard score performance remained high when family history was accounted for. Additionally, the positive predictive value of PSA screening for aggressive PCa was increased with increasing polygenic hazard score.ConclusionsPolygenic hazard scores can be used for personalised genetic risk estimates that can predict for age at onset of aggressive PCa.

Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling.

Global changes in chromatin accessibility may drive cancer progression by reprogramming transcription factor (TF) binding. In addition, histone acetylation readers such as bromodomain-containing protein 4 (BRD4) have been shown to associate with these TFs and contribute to aggressive cancers including prostate cancer (PC). Here, we show that chromatin accessibility defines castration-resistant prostate cancer (CRPC). We show that the deregulation of androgen receptor (AR) expression is a driver of chromatin relaxation and that AR/androgen-regulated bromodomain-containing proteins (BRDs) mediate this effect. We also report that BRDs are overexpressed in CRPCs and that ATAD2 and BRD2 have prognostic value. Finally, we developed gene stratification signature (BROMO-10) for bromodomain response and PC prognostication, to inform current and future trials with drugs targeting these processes. Our findings provide a compelling rational for combination therapy targeting bromodomains in selected patients in which BRD-mediated TF binding is enhanced or modified as cancer progresses.

Although genome-wide association studies have identified over 100 risk loci that explain ∼33% of familial risk for prostate cancer (PrCa), their functional effects on risk remain largely unknown. Here we use genotype data from 59,089 men of European and African American ancestries combined with cell-type-specific epigenetic data to build a genomic atlas of single-nucleotide polymorphism (SNP) heritability in PrCa. We find significant differences in heritability between variants in prostate-relevant epigenetic marks defined in normal versus tumour tissue as well as between tissue and cell lines. The majority of SNP heritability lies in regions marked by H3k27 acetylation in prostate adenoc7arcinoma cell line (LNCaP) or by DNaseI hypersensitive sites in cancer cell lines. We find a high degree of similarity between European and African American ancestries suggesting a similar genetic architecture from common variation underlying PrCa risk. Our findings showcase the power of integrating functional annotation with genetic data to understand the genetic basis of PrCa.

Randomized clinical trials have shown that use of 5α-reductase inhibitors (5-ARIs) lowers overall prostate cancer (PCa) risk compared to placebo, while the proportion of Gleason 8-10 tumors is elevated. It is unknown whether this affects PCa-specific survival. We studied disease-specific survival by 5-ARI usage in a cohort of 6,537 prostate cancer cases diagnosed in the Finnish Prostate Cancer Screening Trial and linked to the national prescription database for information on medication use. Cox proportional hazards regression was used to estimate hazard ratios and 95% confidence intervals for prostate cancer-specific deaths. For comparison, survival among alpha-blocker users was also evaluated. During the median follow-up of 7.5 years after diagnosis a total of 2,478 men died; 617 due to prostate cancer and 1,861 due to other causes. The risk of prostate cancer death did not differ between 5-ARI users and nonusers (multivariable adjusted HR 0.94, 95% CI 0.72-1.24 and HR 0.98, 95% CI 0.69-1.41 for usage before and after the diagnosis, respectively). Alpha-blocker usage both before and after diagnosis was associated with increased risk of prostate cancer death (HR 1.29, 95% CI 1.08-1.54 and HR 1.56, 95% CI 1.30-1.86, respectively). The risk increase vanished in long-term alpha-blocker usage. Use of 5-ARIs does not appear to affect prostate cancer mortality when used in management of benign prostatic hyperplasia. Increased risk associated with alpha-blocker usage should prompt further exploration on the prognostic role of lower urinary tract symptoms. [ABSTRACT FROM AUTHOR]

In prostate cancer (PCa), lower education level is associated with less screening, more advanced stage at diagnosis and worse survival. The aim of this study was to estimate the association between education level and treatment modality and subsequently survival. The 9255 men diagnosed with PCa in the Finnish Randomized Study of Screening for Prostate Cancer were included. Cancer stage, comorbidity, education level and primary treatment modality were extracted from the patient records, the Finnish Cancer Registry, Statistics Finland and the National Institute of Health and Welfare, and these covariates were used in logistic regression (treatment selection) and Cox regression (survival analysis). In high-risk cancers, men with tertiary education were more likely to be treated with radical prostatectomy (odds ratio [OR] = 1.76; 95% confidence interval [CI] = 1.27–2.44) than men with primary education. Men with secondary (OR = 0.57; 95% CI = 0.38–0.84) or tertiary (OR = 0.42; 95% CI = 0.29–0.60) education were managed less frequently with mere hormonal therapy. In locally advanced cases, tertiary education was associated with more curatively aimed therapies and less hormonal therapy (OR for radical prostatectomy = 2.34; 95% CI = 1.49–3.66; OR for radiotherapy = 1.42; 95% CI = 1.09–1.85; OR for hormonal therapy = 0.45; 95% CI = 0.33–0.60). The hazard ratio for PCa death was lower in men with secondary (0.81; 95% CI = 0.69–0.95) and tertiary (0.75; 95% CI = 0.65–0.87) education than in the patients with primary education. When controlled for the cancer risk group, comorbidity and patient's age, low education level is independently associated with less curatively aimed treatment in men with high-risk or locally advanced PCa and subsequently worse prognosis. • In prostate cancer, the lower education level is associated with worse survival. • The primary treatment modality and education level were analysed in 9255 men. • Cancer stage, the patient's age and comorbidity burden were included in analysis. • Men with a higher education level are treated with more radical intention. • Less curatively aimed therapy is likely to influence worse cancer survival. [ABSTRACT FROM AUTHOR]