Prostate cancer is the most frequently diagnosed cancer in males in developed countries. To identify common prostate cancer susceptibility alleles, we genotyped 211,155 SNPs on a custom Illumina array (iCOGS) in blood DNA from 25,074 prostate cancer cases and 24,272 controls from the international PRACTICAL Consortium. Twenty-three new prostate cancer susceptibility loci were identified at genome-wide significance (P < 5 × 10−8). More than 70 prostate cancer susceptibility loci, explaining ~30% of the familial risk for this disease, have now been identified. On the basis of combined risks conferred by the new and previously known risk loci, the top 1% of the risk distribution has a 4.7-fold higher risk than the average of the population being profiled. These results will facilitate population risk stratification for clinical studies.
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 43,303prostate cancer cases and 43,737 controls from studies in populations of European, African, Japanese and Latino ancestry. Twenty-three novel susceptibility loci were revealed at P<5×10-8; 15 variants were identified among men of European ancestry, 7 from multiethnic analyses and one was associated with early-onset prostate cancer. These 23 variants, in combination with the known prostate cancer risk variants, explain 33% of the familial risk of the disease in European ancestry populations. These findings provide new regions for investigation into the pathogenesis of prostate cancer and demonstrate the utility of combining ancestrally diverse populations to discover risk loci for disease.
Objectives To 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. Design Analysis 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. Setting Multiple institutions that were members of international PRACTICAL consortium. Participants All 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 Measures Prediction with hazard score of age of onset of aggressive cancer in validation set. Results In 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, P<10−16). When men in the validation set with high scores (>98th 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. Conclusions Polygenic hazard scores can be used for personalised genetic risk estimates that can predict for age at onset of aggressive PCa.
BackgroundMen with germline breast cancer 1, early onset (BRCA1) or breast cancer 2, early onset (BRCA2) gene mutations have a higher risk of developing prostate cancer (PCa) than noncarriers. IMPACT (Identification of Men with a genetic predisposition to ProstAte Cancer: Targeted screening in BRCA1/2 mutation carriers and controls) is an international consortium of 62 centres in 20 countries evaluating the use of targeted PCa screening in men with BRCA1/2 mutations.ObjectiveTo report the first year's screening results for all men at enrolment in the study.Design, setting and participantsWe recruited men aged 40–69 yr with germline BRCA1/2 mutations and a control group of men who have tested negative for a pathogenic BRCA1 or BRCA2 mutation known to be present in their families. All men underwent prostate-specific antigen (PSA) testing at enrolment, and those men with PSA >3 ng/ml were offered prostate biopsy.Outcome measurements and statistical analysisPSA levels, PCa incidence, and tumour characteristics were evaluated. The Fisher exact test was used to compare the number of PCa cases among groups and the differences among disease types.Results and limitationsWe recruited 2481 men (791 BRCA1 carriers, 531 BRCA1 controls; 731 BRCA2 carriers, 428 BRCA2 controls). A total of 199 men (8%) presented with PSA >3.0 ng/ml, 162 biopsies were performed, and 59 PCas were diagnosed (18 BRCA1 carriers, 10 BRCA1 controls; 24 BRCA2 carriers, 7 BRCA2 controls); 66% of the tumours were classified as intermediate- or high-risk disease. The positive predictive value (PPV) for biopsy using a PSA threshold of 3.0 ng/ml in BRCA2 mutation carriers was 48%—double the PPV reported in population screening studies. A significant difference in detecting intermediate- or high-risk disease was observed in BRCA2 carriers. Ninety-five percent of the men were white, thus the results cannot be generalised to all ethnic groups.ConclusionsThe IMPACT screening network will be useful for targeted PCa screening studies in men with germline genetic risk variants as they are discovered. These preliminary results support the use of targeted PSA screening based on BRCA genotype and show that this screening yields a high proportion of aggressive disease.Patient summaryIn this report, we demonstrate that germline genetic markers can be used to identify men at higher risk of prostate cancer. Targeting screening at these men resulted in the identification of tumours that were more likely to require treatment.
Breast, ovarian, and prostate cancers are hormone-related and may have a shared genetic basis, but this has not been investigated systematically by genome-wide association (GWA) studies. Meta-analyses combining the largest GWA meta-analysis data sets for these cancers totaling 112,349 cases and 116,421 controls of European ancestry, all together and in pairs, identifi ed at P < 10 −8 seven new cross-cancer loci: three associated with susceptibility to all three cancers (rs17041869/2q13/ BCL2L11 ; rs7937840/11q12/ INCENP ; rs1469713/19p13/ GATAD2A ), two breast and ovarian cancer risk loci (rs200182588/9q31/ SMC2 ; rs8037137/15q26/ RCCD1 ), and two breast and prostate cancer risk loci (rs5013329/1p34/ NSUN4 ; rs9375701/6q23/ L3MBTL3 ). Index variants in fi ve additional regions previously associated with only one cancer also showed clear association with a second cancer type. Cell-type-specifi c expression quantitative trait locus and enhancer-gene interaction annotations suggested target genes with potential cross-cancer roles at the new loci. Pathway analysis revealed signifi cant enrichment of death receptor signaling genes near loci with P < 10 −5 in the three-cancer meta-analysis. SIGNIFICANCE:We demonstrate that combining large-scale GWA meta-analysis fi ndings across cancer types can identify completely new risk loci common to breast, ovarian, and prostate cancers. We show that the identifi cation of such cross-cancer risk loci has the potential to shed new light on the shared biology underlying these hormone-related cancers. Cancer Discov; 6(9); 1052-67.
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.
Considering that mutations in known prostate cancer (PrCa) predisposition genes, including those responsible for hereditary breast/ovarian cancer and Lynch syndromes, explain less than 5% of early-onset/familial PrCa, we have sequenced 94 genes associated with cancer predisposition using next generation sequencing (NGS) in a series of 121 PrCa patients. We found monoallelic truncating/functionally deleterious mutations in seven genes, including ATM and CHEK2, which have previously been associated with PrCa predisposition, and five new candidate PrCa associated genes involved in cancer predisposing recessive disorders, namely RAD51C, FANCD2, FANCI, CEP57 and RECQL4. Furthermore, using in silico pathogenicity prediction of missense variants among 18 genes associated with breast/ovarian cancer and/or Lynch syndrome, followed by KASP genotyping in 710 healthy controls, we identified “likely pathogenic” missense variants in ATM, BRIP1, CHEK2 and TP53. In conclusion, this study has identified putative PrCa predisposing germline mutations in 14.9% of early-onset/familial PrCa patients. Further data will be necessary to confirm the genetic heterogeneity of inherited PrCa predisposition hinted in this study.
Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in 25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16 regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP, while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium (LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region. Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the refined data for existing association signals, we estimate that these loci now explain ∼38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent signals within the same region.
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