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

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

Fine-mapping identifies multiple prostate cancer risk loci at 5p15, one of which associates with TERT expression

Associations between single nucleotide polymorphisms (SNPs) at 5p15 and multiple cancer types have been reported. We have previously shown evidence for a strong association between prostate cancer (PrCa) risk and rs2242652 at 5p15, intronic in the telomerase reverse transcriptase (TERT) gene that encodes TERT. To comprehensively evaluate the association between genetic variation across this region and PrCa, we performed a fine-mapping analysis by genotyping 134 SNPs using a custom Illumina iSelect array or Sequenom MassArray iPlex, followed by imputation of 1094 SNPs in 22 301 PrCa cases and 22 320 controls in The PRACTICAL consortium. Multiple stepwise logistic regression analysis identified four signals in the promoter or intronic regions of TERT that independently associated with PrCa risk. Gene expression analysis of normal prostate tissue showed evidence that SNPs within one of these regions also associated with TERT expression, providing a potential mechanism for predisposition to disease

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

Risk Analysis of Prostate Cancer in PRACTICAL, a Multinational Consortium, Using 25 Known Prostate Cancer Susceptibility Loci.

BACKGROUND: Genome-wide association studies have identified multiple genetic variants associated with prostate cancer risk which explain a substantial proportion of familial relative risk. These variants can be used to stratify individuals by their risk of prostate cancer. METHODS: We genotyped 25 prostate cancer susceptibility loci in 40,414 individuals and derived a polygenic risk score (PRS). We estimated empirical odds ratios (OR) for prostate cancer associated with different risk strata defined by PRS and derived age-specific absolute risks of developing prostate cancer by PRS stratum and family history. RESULTS: The prostate cancer risk for men in the top 1% of the PRS distribution was 30.6 (95% CI, 16.4-57.3) fold compared with men in the bottom 1%, and 4.2 (95% CI, 3.2-5.5) fold compared with the median risk. The absolute risk of prostate cancer by age of 85 years was 65.8% for a man with family history in the top 1% of the PRS distribution, compared with 3.7% for a man in the bottom 1%. The PRS was only weakly correlated with serum PSA level (correlation = 0.09). CONCLUSIONS: Risk profiling can identify men at substantially increased or reduced risk of prostate cancer. The effect size, measured by OR per unit PRS, was higher in men at younger ages and in men with family history of prostate cancer. Incorporating additional newly identified loci into a PRS should improve the predictive value of risk profiles. IMPACT: We demonstrate that the risk profiling based on SNPs can identify men at substantially increased or reduced risk that could have useful implications for targeted prevention and screening programs.D F. Easton was recipient of the CR-UK grant C1287/A10118. R A. Eeles was recipient of the CR-UK grant C5047/A10692 and B E. Henderson was recipient of the NIH grant 1U19CA148537-01This is the author accepted manuscript. The final version is available via AACR at http://cebp.aacrjournals.org/content/early/2015/04/02/1055-9965.EPI-14-0317.long

Fine-mapping the HOXB region detects common variants tagging a rare coding allele: evidence for synthetic association in prostate cancer.

The HOXB13 gene has been implicated in prostate cancer (PrCa) susceptibility. We performed a high resolution fine-mapping analysis to comprehensively evaluate the association between common genetic variation across the HOXB genetic locus at 17q21 and PrCa risk. This involved genotyping 700 SNPs using a custom Illumina iSelect array (iCOGS) followed by imputation of 3195 SNPs in 20,440 PrCa cases and 21,469 controls in The PRACTICAL consortium. We identified a cluster of highly correlated common variants situated within or closely upstream of HOXB13 that were significantly associated with PrCa risk, described by rs117576373 (OR 1.30, P = 2.62×10(-14)). Additional genotyping, conditional regression and haplotype analyses indicated that the newly identified common variants tag a rare, partially correlated coding variant in the HOXB13 gene (G84E, rs138213197), which has been identified recently as a moderate penetrance PrCa susceptibility allele. The potential for GWAS associations detected through common SNPs to be driven by rare causal variants with higher relative risks has long been proposed; however, to our knowledge this is the first experimental evidence for this phenomenon of synthetic association contributing to cancer susceptibility

Height, selected genetic markers and prostate cancer risk:Results from the PRACTICAL consortium

Background: Evidence on height and prostate cancer risk is mixed, however, recent studies with large data sets support a possible role for its association with the risk of aggressive prostate cancer. Methods: We analysed data from the PRACTICAL consortium consisting of 6207 prostate cancer cases and 6016 controls and a subset of high grade cases (2480 cases). We explored height, polymorphisms in genes related to growth processes as main effects and their possible interactions. Results: The results suggest that height is associated with high-grade prostate cancer risk. Men with height 4180cm are at a 22% increased risk as compared to men with height o173cm (OR 1.22, 95% CI 1.01–1.48). Genetic variants in the growth pathway gene showed an association with prostate cancer risk. The aggregate scores of the selected variants identified a significantly increased risk of overall prostate cancer and high-grade prostate cancer by 13% and 15%, respectively, in the highest score group as compared to lowest score group. Conclusions: There was no evidence of gene-environment interaction between height and the selected candidate SNPs. Our findings suggest a role of height in high-grade prostate cancer. The effect of genetic variants in the genes related to growth is seen in all cases and high-grade prostate cancer. There is no interaction between these two exposures.</p

Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans

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 regio