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.

Chromosome 8q24 is a susceptibility locus for multiple cancers, including prostate cancer. Here we combine genetic data across the 8q24 susceptibility region from 71,535 prostate cancer cases and 52,935 controls of European ancestry to define the overall contribution of germline variation at 8q24 to prostate cancer risk. We identify 12 independent risk signals for prostate cancer (p < 4.28 × 10−15), including three risk variants that have yet to be reported. From a polygenic risk score (PRS) model, derived to assess the cumulative effect of risk variants at 8q24, men in the top 1% of the PRS have a 4-fold (95%CI = 3.62–4.40) greater risk compared to the population average. These 12 variants account for ~25% of what can be currently explained of the familial risk of prostate cancer by known genetic risk factors. These findings highlight the overwhelming contribution of germline variation at 8q24 on prostate cancer risk which has implications for population risk stratification.

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Background ERG fusion‐related prostate cancer (PrCa) is the most prevalent oncogenic driver subclass. SPOP, FOXA1, and IDH1 mutations are other three main oncogenic driver subclasses in non–ETS‐fusion PrCa. ERG protein levels seem to be increased in SPOP‐mutated cases, and different studies reported that SPOP mutations and ERG fusions are mutually exclusive. The aim of this study has been to analyze the alterations in non–ETS‐oncogenic drivers in PrCa. Methods SPOP, FOXA1, and IDH mutations were investigated by polymerase chain reaction (PCR) and Sanger direct sequencing. ERG, SPOP, and TMPRSS2‐ERG messenger RNA expression was assessed by quantitative real‐time PCR from complementary DNA, and the presence of the fusion was also analyzed by nonquantitative PCR. The clinical pathological features were retrieved from the charts of the 111 patients included in the study (MARBiobanc, Barcelona, Spain). Results Loss of SPOP expression (25.2%) was associated with ERG overexpression (P = 0.0036). SPOP mutations were found in 5.4% cases, all with wild‐type (wt) ERG (P = 0.007). FOXA1 mutations were found in 8.2% cases, most of them ERG wt (P = 0.06). No IDH1 mutations were found. SPOP or FOXA1 mutations were found in 1.7% of ERG‐rearranged, and 34.2% of non–ERG‐rearranged cases (P < 0.0001). SPOP or FOXA1 alterations (mutations or expression loss) were significantly more common in GG5, while isolated ERG overexpression was more common in GG1 tumors (P = 0.042). SPOP‐or FOXA1‐mutated cases were associated with a shorter time to prostate‐specific antigen (PSA) recurrence in the univariate (P = 0.0009), and with the PSA recurrence risk in the multivariate (P = 0.023) analysis. Conclusions In conclusion, SPOP and FOXA1 mutations may have prognostic value in ERG wt tumors. Interestingly, in absence of SPOP mutations, downregulation of this gene is a feature of many ERG‐rearranged prostate tumors.

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