SummaryAll cancers carry somatic mutations. The patterns of mutation in cancer genomes reflect the DNA damage and repair processes to which cancer cells and their precursors have been exposed. To explore these mechanisms further, we generated catalogs of somatic mutation from 21 breast cancers and applied mathematical methods to extract mutational signatures of the underlying processes. Multiple distinct single- and double-nucleotide substitution signatures were discernible. Cancers with BRCA1 or BRCA2 mutations exhibited a characteristic combination of substitution mutation signatures and a distinctive profile of deletions. Complex relationships between somatic mutation prevalence and transcription were detected. A remarkable phenomenon of localized hypermutation, termed “kataegis,” was observed. Regions of kataegis differed between cancers but usually colocalized with somatic rearrangements. Base substitutions in these regions were almost exclusively of cytosine at TpC dinucleotides. The mechanisms underlying most of these mutational signatures are unknown. However, a role for the APOBEC family of cytidine deaminases is proposed.PaperClip

Adenoid cystic carcinoma (ACC) is a rare malignancy that can occur in multiple organ sites and is primarily found in the salivary gland. While the identification of recurrent fusions of the MYB-NFIB genes have begun to shed light on the molecular underpinnings, little else is known about the molecular genetics of this frequently fatal cancer. We have undertaken exome sequencing in a series of 24 ACC to further delineate the genetics of the disease. We identified multiple mutated genes that, combined, implicate chromatin deregulation in half of cases. Further, mutations were identified in known cancer genes, including PIK3CA, ATM, CDKN2A, SF3B1, SUFU, TSC1, and CYLD. Mutations in NOTCH1/2 were identified in 3 cases, and we identify the negative NOTCH signaling regulator, SPEN, as a new cancer gene in ACC with mutations in 5 cases. Finally, the identification of 3 likely activating mutations in the tyrosine kinase receptor FGFR2, analogous to those reported in ovarian and endometrial carcinoma, point to potential therapeutic avenues for a subset of cases.

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.

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.

Background Rare germline mutations in DNA repair genes are associated with prostate cancer (PCa) predisposition and prognosis. Objective To quantify the frequency of germline DNA repair gene mutations in UK PCa cases and controls, in order to more comprehensively evaluate the contribution of individual genes to overall PCa risk and likelihood of aggressive disease. Design, setting, and participants We sequenced 167 DNA repair and eight PCa candidate genes in a UK-based cohort of 1281 young-onset PCa cases (diagnosed at ≤60 yr) and 1160 selected controls. Outcome measurements and statistical analysis Gene-level SKAT-O and gene-set adaptive combination of p values (ADA) analyses were performed separately for cases versus controls, and aggressive (Gleason score ≥8, n = 201) versus nonaggressive (Gleason score ≤7, n = 1048) cases. Results and limitations We identified 233 unique protein truncating variants (PTVs) with minor allele frequency <0.5% in controls in 97 genes. The total proportion of PTV carriers was higher in cases than in controls (15% vs 12%, odds ratio [OR] = 1.29, 95% confidence interval [CI] 1.01–1.64, p = 0.036). Gene-level analyses selected NBN ( p SKAT-O = 2.4 × 10 −4 ) for overall risk and XPC ( p SKAT-O = 1.6 × 10 −4 ) for aggressive disease, both at candidate-level significance ( p < 3.1 × 10 −4 and p < 3.4 × 10 −4 , respectively). Gene-set analysis identified a subset of 20 genes associated with increased PCa risk (OR = 3.2, 95% CI 2.1–4.8, p ADA = 4.1 × 10 −3 ) and four genes that increased risk of aggressive disease (OR = 11.2, 95% CI 4.6–27.7, p ADA = 5.6 × 10 −3 ), three of which overlap the predisposition gene set. Conclusions The union of the gene-level and gene-set-level analyses identified 23 unique DNA repair genes associated with PCa predisposition or risk of aggressive disease. These findings will help facilitate the development of a PCa-specific sequencing panel with both predictive and prognostic potential. Patient summary This large sequencing study assessed the rate of inherited DNA repair gene mutations between prostate cancer patients and disease-free men. A panel of 23 genes was identified, which may improve risk prediction or treatment pathways in future clinical practice.