Risk Analysis of Prostate Cancer in PRACTICAL Consortium--Response.

D.F. Easton was recipient of the CR-UK grant C1287/A10118. R.A. Eeles was recipient of the CR-UK grant C5047/A10692.This is the author accepted manuscript. The final version is available from the American Association for Cancer Research via http://dx.doi.org/10.1158/1055-9965.EPI-15-100

HOXB13 G84E Mutation and Prostate Cancer Risk: Kin-Cohort Analysis Using Data From the UK Genetic Prostate Cancer Study

G84E missense mutations in HOXB13 are associated with prostate cancer. However, a wide range of risk estimates has been reported. Based on case-control studies, reported OR range from 2 to 20, often with wide confidence intervals because mutations are rare in the population. To obtain more precise risk estimates, we used a kin-cohort study design and modified segregation analysis, using family data on 11,988 PCa index-cases (4509 consecutive cases, 870 and 6609 cases recruited based on family history and young age at diagnosis, respectively) enrolled in the UK Genetic Prostate Cancer Study, who had been genotyped for G84E. Among index-cases, 182 carried at least one copy of G84E. PCa incidence was assumed to follow a mixed Cox regression model of the form λ(t)=λ_0 (t)"×exp" (G+P), where G is a fixed effect which depends on G84E, P∈N(0,σ_P^2 ) a residual polygenic random effect, and λ_0 (t) is the baseline incidence for non-carriers to age t. Using maximum likelihood, after adjusting for ascertainment, we estimated the frequency and RR (i.e. penetrance) for G84E under different genetic models, and σ_P. Preliminary results suggest that under the best fitting model, the data are consistent with a multiplicative model where each copy of G84E confers RR for PCa of 2.6 (95%CI 1.7-4.2), and a significant σ_P of 1.8 (95%CI 1.7-1.9), indicating that family history increases risk above that resulting from being a mutation carrier. Ongoing work will evaluate effect-modification of RR and/or σ_P by age, birth cohort, and mutation status, and estimate absolute risks for reference family structures

Polygenic risk-tailored screening for prostate cancer: A benefit-harm and cost-effectiveness modelling study.

BACKGROUND: The United States Preventive Services Task Force supports individualised decision-making for prostate-specific antigen (PSA)-based screening in men aged 55-69. Knowing how the potential benefits and harms of screening vary by an individual's risk of developing prostate cancer could inform decision-making about screening at both an individual and population level. This modelling study examined the benefit-harm tradeoffs and the cost-effectiveness of a risk-tailored screening programme compared to age-based and no screening. METHODS AND FINDINGS: A life-table model, projecting age-specific prostate cancer incidence and mortality, was developed of a hypothetical cohort of 4.48 million men in England aged 55 to 69 years with follow-up to age 90. Risk thresholds were based on age and polygenic profile. We compared no screening, age-based screening (quadrennial PSA testing from 55 to 69), and risk-tailored screening (men aged 55 to 69 years with a 10-year absolute risk greater than a threshold receive quadrennial PSA testing from the age they reach the risk threshold). The analysis was undertaken from the health service perspective, including direct costs borne by the health system for risk assessment, screening, diagnosis, and treatment. We used probabilistic sensitivity analyses to account for parameter uncertainty and discounted future costs and benefits at 3.5% per year. Our analysis should be considered cautiously in light of limitations related to our model's cohort-based structure and the uncertainty of input parameters in mathematical models. Compared to no screening over 35 years follow-up, age-based screening prevented the most deaths from prostate cancer (39,272, 95% uncertainty interval [UI]: 16,792-59,685) at the expense of 94,831 (95% UI: 84,827-105,630) overdiagnosed cancers. Age-based screening was the least cost-effective strategy studied. The greatest number of quality-adjusted life-years (QALYs) was generated by risk-based screening at a 10-year absolute risk threshold of 4%. At this threshold, risk-based screening led to one-third fewer overdiagnosed cancers (64,384, 95% UI: 57,382-72,050) but averted 6.3% fewer (9,695, 95% UI: 2,853-15,851) deaths from prostate cancer by comparison with age-based screening. Relative to no screening, risk-based screening at a 4% 10-year absolute risk threshold was cost-effective in 48.4% and 57.4% of the simulations at willingness-to-pay thresholds of GBP£20,000 (US$26,000) and £30,000 ($39,386) per QALY, respectively. The cost-effectiveness of risk-tailored screening improved as the threshold rose. CONCLUSIONS: Based on the results of this modelling study, offering screening to men at higher risk could potentially reduce overdiagnosis and improve the benefit-harm tradeoff and the cost-effectiveness of a prostate cancer screening program. The optimal threshold will depend on societal judgements of the appropriate balance of benefits-harms and cost-effectiveness

Validation of loci at 2q14.2 and 15q21.3 as risk factors for testicular cancer.

Testicular germ cell tumor (TGCT), the most common cancer in men aged 18 to 45 years, has a strong heritable basis. Genome-wide association studies (GWAS) have proposed single nucleotide polymorphisms (SNPs) at a number of loci influencing TGCT risk. To further evaluate the association of recently proposed risk SNPs with TGCT at 2q14.2, 3q26.2, 7q36.3, 10q26.13 and 15q21.3, we analyzed genotype data on 3,206 cases and 7,422 controls. Our analysis provides independent replication of the associations for risk SNPs at 2q14.2 (rs2713206 at P = 3.03 × 10-2; P-meta = 3.92 × 10-8; nearest gene, TFCP2L1) and rs12912292 at 15q21.3 (P = 7.96 × 10-11; P-meta = 1.55 × 10-19; nearest gene PRTG). Case-only analyses did not reveal specific associations with TGCT histology. TFCP2L1 joins the growing list of genes located within TGCT risk loci with biologically plausible roles in developmental transcriptional regulation, further highlighting the importance of this phenomenon in TGCT oncogenesis

Rare germline variants in DNA repair genes and the angiogenesis pathway predispose prostate cancer patients to develop metastatic disease

Background Prostate cancer (PrCa) demonstrates a heterogeneous clinical presentation ranging from largely indolent to lethal. We sought to identify a signature of rare inherited variants that distinguishes between these two extreme phenotypes. Methods We sequenced germline whole exomes from 139 aggressive (metastatic, age of diagnosis < 60) and 141 non-aggressive (low clinical grade, age of diagnosis ≥60) PrCa cases. We conducted rare variant association analyses at gene and gene set levels using SKAT and Bayesian risk index techniques. GO term enrichment analysis was performed for genes with the highest differential burden of rare disruptive variants. Results Protein truncating variants (PTVs) in specific DNA repair genes were significantly overrepresented among patients with the aggressive phenotype, with BRCA2, ATM and NBN the most frequently mutated genes. Differential burden of rare variants was identified between metastatic and non-aggressive cases for several genes implicated in angiogenesis, conferring both deleterious and protective effects. Conclusions Inherited PTVs in several DNA repair genes distinguish aggressive from non-aggressive PrCa cases. Furthermore, inherited variants in genes with roles in angiogenesis may be potential predictors for risk of metastases. If validated in a larger dataset, these findings have potential for future clinical application

Role of Engrailed-2 (EN2) as a prostate cancer detection biomarker in genetically high risk men

Controversy surrounds the use of PSA as a biomarker for prostate cancer detection, leaving an unmet need for a novel biomarker in this setting; urinary EN2 may identify individuals with clinically relevant prostate cancer. Male BRCA1 and BRCA2 mutation carriers are at increased risk of clinically significant prostate cancer and may benefit from screening. Urine samples from 413 BRCA1 and BRCA2 mutation carriers and controls were evaluated. Subjects underwent annual PSA screening with diagnostic biopsy triggered by PSA > 3.0 ng/ml; 21 men were diagnosed with prostate cancer. Urinary EN2 levels were measured by ELISA and had a sensitivity of 66.7% and specificity of 89.3% for cancer detection. There was no statistically significant difference in EN2 levels according to genetic status or Gleason score. Urinary EN2 may be useful as a non-invasive early biomarker for prostate cancer detection in genetically high-risk individuals

Prediction of individual genetic risk to prostate cancer using a polygenic score

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

Investigating the possible causal role of coffee consumption with prostate cancer risk and progression using Mendelian randomization analysis.

Coffee consumption has been shown in some studies to be associated with lower risk of prostate cancer. However, it is unclear if this association is causal or due to confounding or reverse causality. We conducted a Mendelian randomisation analysis to investigate the causal effects of coffee consumption on prostate cancer risk and progression. We used two genetic variants robustly associated with caffeine intake (rs4410790 and rs2472297) as proxies for coffee consumption in a sample of 46,687 men of European ancestry from 25 studies in the PRACTICAL consortium. Associations between genetic variants and prostate cancer case status, stage and grade were assessed by logistic regression and with all-cause and prostate cancer-specific mortality using Cox proportional hazards regression. There was no clear evidence that a genetic risk score combining rs4410790 and rs2472297 was associated with prostate cancer risk (OR per additional coffee increasing allele: 1.01, 95% CI: 0.98,1.03) or having high-grade compared to low-grade disease (OR: 1.01, 95% CI: 0.97,1.04). There was some evidence that the genetic risk score was associated with higher odds of having nonlocalised compared to localised stage disease (OR: 1.03, 95% CI: 1.01, 1.06). Amongst men with prostate cancer, there was no clear association between the genetic risk score and all-cause mortality (HR: 1.00, 95% CI: 0.97,1.04) or prostate cancer-specific mortality (HR: 1.03, 95% CI: 0.98,1.08). These results, which should have less bias from confounding than observational estimates, are not consistent with a substantial effect of coffee consumption on reducing prostate cancer incidence or progression.British Heart Foundation, Cancer Research UK, Economic and Social Research Council, Medical Research Council, and the National Institute for Health Research, under the auspices of the UK Clinical Research Collaboration Cancer Research UK. Grant Number: C18281/A19169 RMM and Caroline Relton (Integrative Cancer Epidemiology Programme) Canadian Institutes of Health Research the European Commission's Seventh Framework Programme. Grant Numbers: 223175, HEALTH-F2-2009-223175 Cancer Research UK. Grant Numbers: C5047/A7357, C1287/A10118, C5047/A3354, C5047/A10692, C16913/A6135 National Institute of Health (NIH) Cancer Post-Cancer GWAS. Grant Number: 1 U19 CA 148537-01 the GAME-ON initiative the European Community's Seventh Framework Programme. Grant Numbers: 223175, HEALTH-F2-2009-223175 Cancer Research UK. Grant Numbers: C1287/A10118, C1287/A 10710, C12292/A11174, C1281/A12014, C5047/A8384, C5047/A15007, C5047/A10692 the National Institutes of Health. Grant Number: CA128978 Post-Cancer GWAS initiative. Grant Numbers: 1U19 CA148537, 1U19 CA148065, 1U19 CA148112 the GAME-ON initiative the Department of Defence. Grant Number: W81XWH-10-1-0341 the Canadian Institutes of Health Research (CIHR) CIHR Team in Familial Risks of Breast Cancer Komen Foundation for the Cure Breast Cancer Research Foundation. Grant Number: Ovarian Cancer Research Fund VicHealth and Cancer Council Victoria Australian NHMRC. Grant Numbers: 209057, 251553, 504711 Cancer Council Victoria Australian Institute of Health and Welfare (AIHW) National Death Index and the Australian Cancer Database U.K. Health Technology Assessment (HTA) Programme of the NIH Research. Grant Numbers: HTA 96/20/99, ISRCTN20141297 Prodigal study and the ProMPT (Prostate Mechanisms of Progression and Treatment) National Cancer Research Institute (NCRI) Department of Health, the Medical Research Council and Cancer Research UK. Grant Number: G0500966/75466 Cancer Research UK. Grant Number: C5047/A7357 NIHR Biomedical Research Centre at The Institute of Cancer Research and Royal Marsden NHS Foundation Trust National Institute for Health Research Bristol Nutrition Biomedical Research Unit based at University Hospitals Bristol NHS Foundation Trust and the University of Bristol FCH, DEN and JLD are NIHR Senior Investigators MRC and the University of Bristol. Grant Numbers: G0600705, MC_UU_12013/6This is the final version of the article. It first appeared from Wiley via https://doi.org/10.1002/ijc.3046

Gene and pathway level analyses of germline DNA-repair gene variants and prostate cancer susceptibility using the iCOGS-genotyping array.

BACKGROUND: Germline mutations within DNA-repair genes are implicated in susceptibility to multiple forms of cancer. For prostate cancer (PrCa), rare mutations in BRCA2 and BRCA1 give rise to moderately elevated risk, whereas two of B100 common, low-penetrance PrCa susceptibility variants identified so far by genome-wide association studies implicate RAD51B and RAD23B. METHODS: Genotype data from the iCOGS array were imputed to the 1000 genomes phase 3 reference panel for 21 780 PrCa cases and 21 727 controls from the Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL) consortium. We subsequently performed single variant, gene and pathway-level analyses using 81 303 SNPs within 20 Kb of a panel of 179 DNA-repair genes. RESULTS: Single SNP analyses identified only the previously reported association with RAD51B. Gene-level analyses using the SKAT-C test from the SNP-set (Sequence) Kernel Association Test (SKAT) identified a significant association with PrCa for MSH5. Pathway-level analyses suggested a possible role for the translesion synthesis pathway in PrCa risk and Homologous recombination/Fanconi Anaemia pathway for PrCa aggressiveness, even though after adjustment for multiple testing these did not remain significant. CONCLUSIONS: MSH5 is a novel candidate gene warranting additional follow-up as a prospective PrCa-risk locus. MSH5 has previously been reported as a pleiotropic susceptibility locus for lung, colorectal and serous ovarian cancers.This is the final version of the article. It first appeared from Nature Publishing Group via http://dx.doi.org/10.1038/bjc.2016.5