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.

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.

Chaperone and protease systems play essential roles in cellular homeostasis and have vital functions in controlling the abundance of specific cellular proteins involved in processes such as transcription, replication, metabolism and virulence. Bacteria have evolved accurate regulatory systems to control the expression and function of chaperones and potentially destructive proteases. Here, we have used a combination of transcriptomics, proteomics and targeted mutagenesis to reveal that the clp gene regulator (ClgR) of Mycobacterium tuberculosis activates the transcription of at least ten genes, including four that encode protease systems (ClpP1/C, ClpP2/C, PtrB and HtrA-like protease Rv1043c) and three that encode chaperones (Acr2, ClpB and the chaperonin Rv3269). Thus, M. tuberculosis ClgR controls a larger network of protein homeostatic and regulatory systems than ClgR in any other bacterium studied to date. We demonstrate that ClgR-regulated transcriptional activation of these systems is essential for M. tuberculosis to replicate in macrophages. Furthermore, we observe that this defect is manifest early in infection, as M. tuberculosis lacking ClgR is deficient in the ability to control phagosome pH 1 h post-phagocytosis

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.

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.