Validation of Recently Proposed Colorectal Cancer Susceptibility Gene Variants in an Analysis of Families and Patients-a Systematic Review.

High-throughput sequencing analysis has accelerated searches for genes associated with risk for colorectal cancer (CRC); germline mutations in NTHL1, RPS20, FANCM, FAN1, TP53, BUB1, BUB3, LRP6, and PTPN12 have been recently proposed to increase CRC risk. We attempted to validate the association between variants in these genes and development of CRC in a systematic review of 11 publications, using sequence data from 863 familial CRC cases and 1604 individuals without CRC (controls). All cases were diagnosed at an age of 55 years or younger and did not carry mutations in an established CRC predisposition gene. We found sufficient evidence for NTHL1 to be considered a CRC predisposition gene-members of 3 unrelated Dutch families were homozygous for inactivating p.Gln90Ter mutations; a Canadian woman with polyposis, CRC, and multiple tumors was reported to be heterozygous for the inactivating NTHL1 p.Gln90Ter/c.709+1G>A mutations; and a man with polyposis was reported to carry p.Gln90Ter/p.Gln287Ter; whereas no inactivating homozygous or compound heterozygous mutations were detected in controls. Variants that disrupted RPS20 were detected in a Finnish family with early-onset CRC (p.Val50SerfsTer23), a 39-year old individual with metachronous CRC (p.Leu61GlufsTer11 mutation), and a 41-year-old individual with CRC (missense p.Val54Leu), but not in controls. We therefore found published evidence to support the association between variants in NTHL1 and RPS20 with CRC, but not of other recently reported CRC susceptibility variants. We urge the research community to adopt rigorous statistical and biological approaches coupled with independent replication before making claims of pathogenicity.

Identification of susceptibility loci for colorectal cancer in a genome-wide meta-analysis.

To identify common variants influencing colorectal cancer (CRC) risk, we performed a meta-analysis of five genome-wide association studies, comprising 5626 cases and 7817 controls of European descent. We conducted replication of top ranked single nucleotide polymorphisms (SNPs) in additional series totalling 14 037 cases and 15 937 controls, identifying a new CRC risk locus at 10q24.2 [rs1035209; odds ratio (OR) = 1.13, P = 4.54 × 10(-11)]. We also performed meta-analysis of our studies, with previously published data, of several recently purported CRC risk loci. We failed to find convincing evidence for a previously reported genome-wide association at rs11903757 (2q32.3). Of the three additional loci for which evidence of an association in Europeans has been previously described we failed to show an association between rs59336 (12q24.21) and CRC risk. However, for the other two SNPs, our analyses demonstrated new, formally significant associations with CRC. These are rs3217810 intronic in CCND2 (12p13.32; OR = 1.19, P = 2.16 × 10(-10)) and rs10911251 near LAMC1 (1q25.3; OR = 1.09, P = 1.75 × 10(-8)). Additionally, we found some evidence to support a relationship between, rs647161, rs2423297 and rs10774214 and CRC risk originally identified in East Asians in our European datasets. Our findings provide further insights into the genetic and biological basis of inherited genetic susceptibility to CRC.

Developmental timing of mutations revealed by whole-genome sequencing of twins with acute lymphoblastic leukemia.

Acute lymphoblastic leukemia (ALL) is the major pediatric cancer. At diagnosis, the developmental timing of mutations contributing critically to clonal diversification and selection can be buried in the leukemia's covert natural history. Concordance of ALL in monozygotic, monochorionic twins is a consequence of intraplacental spread of an initiated preleukemic clone. Studying monozygotic twins with ALL provides a unique means of uncovering the timeline of mutations contributing to clonal evolution, pre- and postnatally. We sequenced the whole genomes of leukemic cells from two twin pairs with ALL to comprehensively characterize acquired somatic mutations in ALL, elucidating the developmental timing of all genetic lesions. Shared, prenatal, coding-region single-nucleotide variants were limited to the putative initiating lesions. All other nonsynonymous single-nucleotide variants were distinct between tumors and, therefore, secondary and postnatal. These changes occurred in a background of noncoding mutational changes that were almost entirely discordant in twin pairs and likely passenger mutations acquired during leukemic cell proliferation.

Deciphering the genetic architecture of low-penetrance susceptibility to colorectal cancer.

Recent genome-wide association studies (GWASs) have identified common variants at 16 autosomal regions influencing the risk of developing colorectal cancer (CRC). To decipher the genetic basis of the association signals at these loci, we performed a meta-analysis of data from five GWASs, totalling 5626 cases and 7817 controls, using imputation to recover un-typed genotypes. To enhance our ability to discover low-frequency risk variants, in addition to using 1000 Genomes Project data as a reference panel, we made use of high-coverage sequencing data on 253 individuals, 199 with early-onset familial CRC. For 13 of the regions, it was possible to refine the association signal identifying a smaller region of interest likely to harbour the functional variant. Our analysis did not provide evidence that any of the associations at the 16 loci being a consequence of synthetic associations rather than linkage disequilibrium with a common risk variant.

Multiple common susceptibility variants near BMP pathway loci GREM1, BMP4, and BMP2 explain part of the missing heritability of colorectal cancer.

Genome-wide association studies (GWAS) have identified 14 tagging single nucleotide polymorphisms (tagSNPs) that are associated with the risk of colorectal cancer (CRC), and several of these tagSNPs are near bone morphogenetic protein (BMP) pathway loci. The penalty of multiple testing implicit in GWAS increases the attraction of complementary approaches for disease gene discovery, including candidate gene- or pathway-based analyses. The strongest candidate loci for additional predisposition SNPs are arguably those already known both to have functional relevance and to be involved in disease risk. To investigate this proposition, we searched for novel CRC susceptibility variants close to the BMP pathway genes GREM1 (15q13.3), BMP4 (14q22.2), and BMP2 (20p12.3) using sample sets totalling 24,910 CRC cases and 26,275 controls. We identified new, independent CRC predisposition SNPs close to BMP4 (rs1957636, P = 3.93×10(-10)) and BMP2 (rs4813802, P = 4.65×10(-11)). Near GREM1, we found using fine-mapping that the previously-identified association between tagSNP rs4779584 and CRC actually resulted from two independent signals represented by rs16969681 (P = 5.33×10(-8)) and rs11632715 (P = 2.30×10(-10)). As low-penetrance predisposition variants become harder to identify-owing to small effect sizes and/or low risk allele frequencies-approaches based on informed candidate gene selection may become increasingly attractive. Our data emphasise that genetic fine-mapping studies can deconvolute associations that have arisen owing to independent correlation of a tagSNP with more than one functional SNP, thus explaining some of the apparently missing heritability of common diseases.

The silent mutational landscape of infant MLL-AF4 pro-B acute lymphoblastic leukemia.

Over 90% of infants (< 1-year-old) diagnosed with leukemia have pro-B acute lymphoblastic leukemia (ALL) containing the MLL-AF4 fusion. When compared with other forms of paediatric ALL affecting later B-cell differentiation, MLL-AF4 pro-B is associated with a dismal prognosis with a typical 5-year disease-free survival of <20%. MLL-AF4 may be sufficient on its own for leukemogenesis or the gene-fusion product may alternatively predispose transformed cells to global genetic instability, enhancing the acquisition of additional key mutations. To gain insight into the genomic landscape of infant MLL-AF4 pro-B ALL we performed whole genome sequencing of diagnostic leukemic blasts and matched germline samples from three MLL-AF4 pro-B ALL infants. Our analysis revealed few somatic changes (copy number abnormalities, loss of heterozygosity, or single nucleotide variants), demonstrating that only a very small number of mutations are necessary to generate infant MLL-leukemia.

Chromosome 7p11.2 (EGFR) variation influences glioma risk.

While gliomas are the most common primary brain tumors, their etiology is largely unknown. To identify novel risk loci for glioma, we conducted genome-wide association (GWA) analysis of two case-control series from France and Germany (2269 cases and 2500 controls). Pooling these data with previously reported UK and US GWA studies provided data on 4147 glioma cases and 7435 controls genotyped for 424 460 common tagging single-nucleotide polymorphisms. Using these data, we demonstrate two statistically independent associations between glioma and rs11979158 and rs2252586, at 7p11.2 which encompasses the EGFR gene (population-corrected statistics, P(c) = 7.72 × 10(-8) and 2.09 × 10(-8), respectively). Both associations were independent of tumor subtype, and were independent of EGFR amplification, p16INK4a deletion and IDH1 mutation status in tumors; compatible with driver effects of the variants on glioma development. These findings show that variation in 7p11.2 is a determinant of inherited glioma risk.

MHC variation and risk of childhood B-cell precursor acute lymphoblastic leukemia.

A role for specific human leukocyte antigen (HLA) variants in the etiology of childhood acute lymphoblastic leukemia (ALL) has been extensively studied over the last 30 years, but no unambiguous association has been identified. To comprehensively study the relationship between genetic variation within the 4.5 Mb major histocompatibility complex genomic region and precursor B-cell (BCP) ALL risk, we analyzed 1075 observed and 8176 imputed single nucleotide polymorphisms and their related haplotypes in 824 BCP-ALL cases and 4737 controls. Using these genotypes we also imputed both common and rare alleles at class I (HLA-A, HLA-B, and HLA-C) and class II (HLA-DRB1, HLA-DQA1, and HLA-DQB1) HLA loci. Overall, we found no statistically significant association between variants and BCP-ALL risk. We conclude that major histocompatibility complex-defined variation in immune-mediated response is unlikely to be a major risk factor for BCP-ALL.

Investigation of clinical characteristics and genome associations in the 'UK Lipoedema' cohort.

Lipoedema is a chronic adipose tissue disorder mainly affecting women, causing excess subcutaneous fat deposition on the lower limbs with pain and tenderness. There is often a family history of lipoedema, suggesting a genetic origin, but the contribution of genetics is currently unclear. A tightly phenotyped cohort of 200 lipoedema patients was recruited from two UK specialist clinics. Objective clinical characteristics and measures of quality of life data were obtained. In an attempt to understand the genetic architecture of the disease better, genome-wide single nucleotide polymorphism (SNP) genotype data were obtained, and a genome wide association study (GWAS) was performed on 130 of the recruits. The analysis revealed genetic loci suggestively associated with the lipoedema phenotype, with further support provided by an independent cohort taken from the 100,000 Genomes Project. The top SNP rs1409440 (ORmeta ≈ 2.01, Pmeta ≈ 4 x 10-6) is located upstream of LHFPL6, which is thought to be involved with lipoma formation. Exactly how this relates to lipoedema is not yet understood. This first GWAS of a UK lipoedema cohort has identified genetic regions of suggestive association with the disease. Further replication of these findings in different populations is warranted.

Allergy and glioma risk: test of association by genotype.

Although epidemiological studies have suggested an association between atopy and glioma risk, these observations have been based on self-reporting of allergic conditions raising the possibility that associations may be noncausal and arise as a consequence of bias, reverse causation or other artifacts. Genetic information provides an alternative approach to investigate the relationship avoiding such biases. We analyzed 1,878 glioma cases and 3,670 controls for variants at 2q12, 5q12.1, 11q13 and 17q21 that are associated with asthma or eczema risk at p < 5.0 × 10(-7) . The SNP rs7216389, which tags the 3' flanking region of ORMDL3 at 17q21 and has been associated with childhood asthma, was correlated with increased glioma risk (OR = 1.10; 95% CI: 1.01-1.19). These data provide evidence for a correlation between asthma susceptibility and glioma risk and illustrate the value of using genetics as an investigative tool for developing etiological hypotheses.

Genome-wide association studies for detecting cancer susceptibility.

Genome-wide association (GWA) studies search for genetic variants, across the entire genome, which display differences in frequencies between cases and controls. Studies in PubMed using the keywords 'genomewide association' and 'cancer' are reported together with selected literature. Since 2007, GWA studies have successfully yielded risk loci for most common cancers. Findings have provided insights into the biological basis of cancer susceptibility implicating previously unsuspected genes in tumourogenesis. The variants identified typically account for only a small proportion of the familial risk of cancer and thus their application for individual risk prediction is poor. Furthermore, the genotyped variants are unlikely to be directly causal and identifying the causal basis is a major challenge. Methodological developments are desirable to fully utilize existing data sets and to enable more complex models of inherited predisposition to be investigated. Annotation of low frequency variation coupled with next-generation sequencing is making the search for rare disease-causing variants a realistic prospect.

Insights into protein flexibility: The relationship between normal modes and conformational change upon protein-protein docking.

Understanding protein interactions has broad implications for the mechanism of recognition, protein design, and assigning putative functions to uncharacterized proteins. Studying protein flexibility is a key component in the challenge of describing protein interactions. In this work, we characterize the observed conformational change for a set of 20 proteins that undergo large conformational change upon association (>2 A Calpha RMSD) and ask what features of the motion are successfully reproduced by the normal modes of the system. We demonstrate that normal modes can be used to identify mobile regions and, in some proteins, to reproduce the direction of conformational change. In 35% of the proteins studied, a single low-frequency normal mode was found that describes well the direction of the observed conformational change. Finally, we find that for a set of 134 proteins from a docking benchmark that the characteristic frequencies of normal modes can be used to predict reliably the extent of observed conformational change. We discuss the implications of the results for the mechanics of protein recognition.

Mutational processes contributing to the development of multiple myeloma.

To gain insight into multiple myeloma (MM) tumorigenesis, we analyzed the mutational signatures in 874 whole-exome and 850 whole-genome data from the CoMMpass Study. We identified that coding and non-coding regions are differentially dominated by distinct single-nucleotide variant (SNV) mutational signatures, as well as five de novo structural rearrangement signatures. Mutational signatures reflective of different principle mutational processes-aging, defective DNA repair, and apolipoprotein B editing complex (APOBEC)/activation-induced deaminase activity-characterize MM. These mutational signatures show evidence of subgroup specificity-APOBEC-attributed signatures associated with MAF translocation t(14;16) and t(14;20) MM; potentially DNA repair deficiency with t(11;14) and t(4;14); and aging with hyperdiploidy. Mutational signatures beyond that associated with APOBEC are independent of established prognostic markers and appear to have relevance to predicting high-risk MM.

Identification of recurrent noncoding mutations in B-cell lymphoma using capture Hi-C.

The identification of driver mutations is fundamental to understanding oncogenesis. Although genes frequently mutated in B-cell lymphoma have been identified, the search for driver mutations has largely focused on the coding genome. Here we report an analysis of the noncoding genome using whole-genome sequencing data from 117 patients with B-cell lymphoma. Using promoter capture Hi-C data in naive B cells, we define cis-regulatory elements, which represent an enriched subset of the noncoding genome in which to search for driver mutations. Regulatory regions were identified whose mutation significantly alters gene expression, including copy number variation at cis-regulatory elements targeting CD69, IGLL5, and MMP14, and single nucleotide variants in a cis-regulatory element for TPRG1 We also show the commonality of pathways targeted by coding and noncoding mutations, exemplified by MMP14, which regulates Notch signaling, a pathway important in lymphomagenesis and whose expression is associated with patient survival. This study provides an enhanced understanding of lymphomagenesis and describes the advantages of using chromosome conformation capture to decipher noncoding mutations relevant to cancer biology.

Whole-genome sequencing of multiple myeloma reveals oncogenic pathways are targeted somatically through multiple mechanisms.

Multiple myeloma (MM) is a biologically heterogeneous malignancy, however, the mechanisms underlying this complexity are incompletely understood. We report an analysis of the whole-genome sequencing of 765 MM patients from CoMMpass. By employing promoter capture Hi-C in naïve B-cells, we identify cis-regulatory elements (CREs) that represent a highly enriched subset of the non-coding genome in which to search for driver mutations. We identify regulatory regions whose mutation significantly alters the expression of genes as candidate non-coding drivers, including copy number variation (CNV) at CREs of MYC and single-nucleotide variants (SNVs) in a PAX5 enhancer. To better inform the interplay between non-coding driver mutations with other driver mechanisms, and their respective roles in oncogenic pathways, we extended our analysis identifying coding drivers in 40 genes, including 11 novel candidates. We demonstrate the same pathways can be targeted by coding and non-coding mutations; exemplified by IRF4 and PRDM1, along with BCL6 and PAX5, genes that are central to plasma cell differentiation. This study reveals new insights into the complex genetic alterations driving MM development and an enhanced understanding of oncogenic pathways.

Promoter capture Hi-C-based identification of recurrent noncoding mutations in colorectal cancer.

Efforts are being directed to systematically analyze the non-coding regions of the genome for cancer-driving mutations1-6. cis-regulatory elements (CREs) represent a highly enriched subset of the non-coding regions of the genome in which to search for such mutations. Here we use high-throughput chromosome conformation capture techniques (Hi-C) for 19,023 promoter fragments to catalog the regulatory landscape of colorectal cancer in cell lines, mapping CREs and integrating these with whole-genome sequence and expression data from The Cancer Genome Atlas7,8. We identify a recurrently mutated CRE interacting with the ETV1 promoter affecting gene expression. ETV1 expression influences cell viability and is associated with patient survival. We further refine our understanding of the regulatory effects of copy-number variations, showing that RASL11A is targeted by a previously identified enhancer amplification1. This study reveals new insights into the complex genetic alterations driving tumor development, providing a paradigm for employing chromosome conformation capture to decipher non-coding CREs relevant to cancer biology.

Genome-wide association analysis identifies a meningioma risk locus at 11p15.5.

Background: Meningiomas are adult brain tumors originating in the meningeal coverings of the brain and spinal cord, with significant heritable basis. Genome-wide association studies (GWAS) have previously identified only a single risk locus for meningioma, at 10p12.31. Methods: To identify a susceptibility locus for meningioma, we conducted a meta-analysis of 2 GWAS, imputed using a merged reference panel from the 1000 Genomes Project and UK10K data, with validation in 2 independent sample series totaling 2138 cases and 12081 controls. Results: We identified a new susceptibility locus for meningioma at 11p15.5 (rs2686876, odds ratio = 1.44, P = 9.86 × 10-9). A number of genes localize to the region of linkage disequilibrium encompassing rs2686876, including RIC8A, which plays a central role in the development of neural crest-derived structures, such as the meninges. Conclusions: This finding advances our understanding of the genetic basis of meningioma development and provides additional support for a polygenic model of meningioma.

Search for rare protein altering variants influencing susceptibility to multiple myeloma.

The genetic basis underlying the inherited risk of developing multiple myeloma (MM) is largely unknown. To examine the impact of rare protein altering variants on the risk of developing MM we analyzed high-coverage exome sequencing data on 513 MM cases and 1,569 healthy controls, performing both single variant and gene burden tests. We did not identify any recurrent coding low-frequency alleles (1-5%) with moderate effect that were statistically associated with MM. In a gene burden analysis we did however identify a promising relationship between variation in the marrow kinetochore microtubule stromal gene KIF18A, which plays a role in control mitotic chromosome positioning dynamics, and risk of MM (P =3.6x10-6). Further analysis showed KIF18A displays a distinct pattern of expression across molecular subgroups of MM as well as being associated with patient survival. Our results inform future study design and provide a resource for contextualizing the impact of candidate MM susceptibility genes.

Genetic Predisposition to Multiple Myeloma at 5q15 Is Mediated by an ELL2 Enhancer Polymorphism.

Multiple myeloma (MM) is a malignancy of plasma cells. Genome-wide association studies have shown that variation at 5q15 influences MM risk. Here, we have sought to decipher the causal variant at 5q15 and the mechanism by which it influences tumorigenesis. We show that rs6877329 G > C resides in a predicted enhancer element that physically interacts with the transcription start site of ELL2. The rs6877329-C risk allele is associated with reduced enhancer activity and lowered ELL2 expression. Since ELL2 is critical to the B cell differentiation process, reduced ELL2 expression is consistent with inherited genetic variation contributing to arrest of plasma cell development, facilitating MM clonal expansion. These data provide evidence for a biological mechanism underlying a hereditary risk of MM at 5q15.

CanVar: A resource for sharing germline variation in cancer patients.

The advent of high-throughput sequencing has accelerated our ability to discover genes predisposing to disease and is transforming clinical genomic sequencing. In both contexts knowledge of the spectrum and frequency of genetic variation in the general population and in disease cohorts is vital to the interpretation of sequencing data. While population level data is becoming increasingly available from publicly accessible sources, as exemplified by The Exome Aggregation Consortium (ExAC), the availability of large-scale disease-specific frequency information is limited. These data are of particular importance to contextualise findings from clinical mutation screens and small gene discovery projects. This is especially true for cancer, which is typified by a number of hereditary predisposition syndromes.  Although mutation frequencies in tumours are available from resources such as Cosmic and The Cancer Genome Atlas, a similar facility for germline variation is lacking. Here we present the Cancer Variation Resource (CanVar) an online database which has been developed using the ExAC framework to provide open access to germline variant frequency data from the sequenced exomes of cancer patients. In its first release, CanVar catalogues the exomes of 1,006 familial early-onset colorectal cancer (CRC) patients sequenced at The Institute of Cancer Research. It is anticipated that CanVar will host data for additional cancers, providing a resource for others studying cancer predisposition and an example of how the research community can utilise the ExAC framework to share sequencing data.