We performed a meta-analysis of five genome-wide association studies to identify common variants influencing colorectal cancer (CRC) risk comprising 8,682 cases and 9,649 controls. Replication analysis was performed in case-control sets totalling 21,096 cases and 19,555 controls. We identified three novel CRC risk loci at 6p21 (rs1321311, near CDKN1A; P=1.14×10−10), 11q13.4 (rs3824999, intronic to POLD3; P=3.65×10−10) and Xp22.2 (rs5934683, near SHROOM2; P=7.30×10−10) This brings to 20 the number of independent loci associated with CRC risk, and provides further insight into the genetic architecture of inherited susceptibility to CRC.

Colorectal cancer (CRC) displays a complex pattern of inheritance. It is postulated that much of the missing heritability of CRC is enshrined in high-impact rare alleles, which are mechanistically and clinically important. In this study, we assay the impact of rare germline mutations on CRC, analysing high-coverage exome sequencing data on 1,006 early-onset familial CRC cases and 1,609 healthy controls, with additional sequencing and array data on up to 5,552 cases and 6,792 controls. We identify highly penetrant rare mutations in 16% of familial CRC. Although the majority of these reside in known genes, we identify POT1, POLE2 and MRE11 as candidate CRC genes. We did not identify any coding low-frequency alleles (1–5%) with moderate effect. Our study clarifies the genetic architecture of CRC and probably discounts the existence of further major high-penetrance susceptibility genes, which individually account for >1% of the familial risk. Our results inform future study design and provide a resource for contextualizing the impact of new CRC genes.

Personalised screening using PRS has the potential to optimise population screening for CRC and to define those likely to maximally benefit from chemoprevention. There are however significant technical and operational details to be addressed before any such programme is introduced.

In addition to HLA, recent genome-wide association studies (GWASs) of Hodgkin's lymphoma (HL) have identified susceptibility loci for HL at 2p16.1, 8q24.21 and 10p14. In this study, we perform a GWAS meta-analysis with published GWAS (totalling 1,465 cases and 6,417 controls of European background), and follow-up the most significant association signals in 2,024 cases and 1,853 controls. A combined analysis identifies new HL susceptibility loci mapping to 3p24.1 (rs3806624; P ¼ 1.14 Â 10 À 12 , odds ratio (OR) ¼ 1.26) and 6q23.3 (rs7745098; P ¼ 3.42 Â 10 À 9 , OR ¼ 1.21). rs3806624 localizes 5 0 to the EOMES (eomesodermin) gene within a p53 response element affecting p53 binding. rs7745098 maps intergenic to HBS1L and MYB, a region previously associated with haematopoiesis. These findings provide further insight into the genetic and biological basis of inherited susceptibility to HL.

A genetic diagnosis is feasible in a high proportion of familial CRC. Mainstreaming such analysis in clinical practice should enable the medical management of patients and their families to be optimized. Findings suggest CRC screening of POLE and POLD1 mutation carriers should be comparable to that afforded to those at risk of HNPCC. Although the risk of CRC associated with unexplained familial CRC is in general moderate, in some families the risk is substantive and likely to be the consequence of unidentified genes, as exemplified by POLE and POLD1. Our findings have utility in the design of genetic analyses to identify such novel CRC risk genes.

We describe a process for automatically detecting decision-making sub-dialogues in transcripts of multi-party, human-human meetings. Extending our previous work on action item identification, we propose a structured approach that takes into account the different roles utterances play in the decisionmaking process. We show that this structured approach outperforms the accuracy achieved by existing decision detection systems based on flat annotations, while enabling the extraction of more fine-grained information that can be used for summarization and reporting.

No abstract

Genome-wide association studies (GWASs) of renal cell cancer (RCC) have identified four susceptibility loci thus far. To identify an additional RCC common susceptibility locus, we conducted a GWAS and performed a meta-analysis with published GWASs (totalling 2215 cases and 8566 controls of European background) and followed up the most significant association signals [nine single nucleotide polymorphisms (SNPs) in eight genomic regions] in 3739 cases and 8786 controls. A combined analysis identified a novel susceptibility locus mapping to 2q22.3 marked by rs12105918 (P = 1.80 × 10(-8); odds ratio 1.29, 95% CI: 1.18-1.41). The signal localizes to intron 2 of the ZEB2 gene (zinc finger E box-binding homeobox 2). Our findings suggest that genetic variation in ZEB2 influences the risk of RCC. This finding provides further insights into the genetic and biological basis of inherited genetic susceptibility to RCC.