Angela Risch

A common coding variant in CASP8 is associated with breast cancer risk

The Breast Cancer Association Consortium (BCAC) has been established to conduct combined case-control analyses with augmented statistical power to try to confirm putative genetic associations with breast cancer. We genotyped nine SNPs for which there was some prior evidence of an association with breast cancer: CASP8 D302H (rs1045485), IGFBP3 −202 C → A (rs2854744), SOD2 V16A (rs1799725), TGFB1 L10P (rs1982073), ATM S49C (rs1800054), ADH1B 3′ UTR A → G (rs1042026), CDKN1A S31R (rs1801270), ICAM5 V301I (rs1056538) and NUMA1 A794G (rs3750913). We included data from 9–15 studies, comprising 11,391–18,290 cases and 14,753–22,670 controls. We found evidence of an association with breast cancer for CASP8 D302H (with odds ratios (OR) of 0.89 (95% confidence interval (c.i.): 0.85–0.94) and 0.74 (95% c.i.: 0.62–0.87) for heterozygotes and rare homozygotes, respectively, compared with common homozygotes; Ptrend = 1.1 × 10−7) and weaker evidence for TGFB1 L10P (OR = 1.07 (95% c.i.: 1.02–1.13) and 1.16 (95% c.i.: 1.08–1.25), respectively; Ptrend = 2.8 × 10−5). These results demonstrate that common breast cancer susceptibility alleles with small effects on risk can be identified, given sufficiently powerful studies.NOTE: In the version of this article initially published, there was an error that affected the calculations of the odds ratios, confidence intervals, between-study heterogeneity, trend test and test for association for SNP ICAM5 V301I in Table 1 (ICAM5 V301I); genotype counts in Supplementary Table 2 (ICAM5; ICR_FBCS and Kuopio studies) and minor allele frequencies, trend test and odds ratios for heterozygotes and rare homozygotes in Supplementary Table 3 (ICAM5; ICR_FBCS and Kuopio studies). The errors in Table 1 have been corrected in the PDF version of the article. The errors in supplementary information have been corrected online.

A Genome-wide Association Study of Lung Cancer Identifies a Region of Chromosome 5p15 Associated with Risk for Adenocarcinoma

Three genetic loci for lung cancer risk have been identified by genome-wide association studies (GWAS), but inherited susceptibility to specific histologic types of lung cancer is not well established. We conducted a GWAS of lung cancer and its major histologic types, genotyping 515,922 single-nucleotide polymorphisms (SNPs) in 5739 lung cancer cases and 5848 controls from one population-based case-control study and three cohort studies. Results were combined with summary data from ten additional studies, for a total of 13,300 cases and 19,666 controls of European descent. Four studies also provided histology data for replication, resulting in 3333 adenocarcinomas (AD), 2589 squamous cell carcinomas (SQ), and 1418 small cell carcinomas (SC). In analyses by histology, rs2736100 (TERT), on chromosome 5p15.33, was associated with risk of adenocarcinoma (odds ratio [OR]=1.23, 95% confidence interval [CI]=1.13-1.33, p=3.02x10(-7)), but not with other histologic types (OR=1.01, p=0.84 and OR=1.00, p=0.93 for SQ and SC, respectively). This finding was confirmed in each replication study and overall meta-analysis (OR=1.24, 95% CI=1.17-1.31, p=3.74x10(-14) for AD; OR=0.99, p=0.69 and OR=0.97, p=0.48 for SQ and SC, respectively). Other previously reported association signals on 15q25 and 6p21 were also refined, but no additional loci reached genome-wide significance. In conclusion, a lung cancer GWAS identified a distinct hereditary contribution to adenocarcinoma.

Principles for the post-GWAS functional characterization of cancer risk loci

Genome wide association studies (GWAS) have identified more than 200 mostly new common low-penetrance susceptibility loci for cancers. The predicted risk associated with each locus is generally modest (with a per-allele odds ratio typically less than 2) and so, presumably, are the functional effects of individual genetic variants conferring disease susceptibility. Perhaps the greatest challenge in the ‘post-GWAS’ era is to understand the functional consequences of these loci. Biological insights can then be translated to clinical benefits, including reliable biomarkers and effective strategies for screening and disease prevention. The purpose of this article is to propose principles for the initial functional characterization of cancer risk loci, with a focus on non-coding variants, and to define ‘post-GWAS’ functional characterization. n nBy December 2010, there were 1,212 published GWAS studies1 reporting significant (P < 5 × 10−8) associations for 210 traits (Table 1), and the Catalog of Published GWAS states that by March 2011, 812 publications reported 3,977 SNP associations1. This is likely a small fraction of the common susceptibility loci of low penetrance that will eventually be identified. Despite these successes in identifying risk loci, the causal variant and/or the molecular basis of risk etiology has been determined for only a small fraction of these associations2–4. Plausible candidate genes can be based on proximity to risk loci, but few have so far been defined in a more systematic manner (Supplementary Table 1). n n n nTable 1 n nThe genomic context in which a variant is found can be used as preliminary functional analysis n n n nIncreased investment in post-GWAS functional characterization of risk loci5 has now been advocated across diseases and for cardiovascular disease and diabetes6. For cancer biology, the complex interplay between genetics and the environment in many cancers poses a particularly exciting challenge for post-GWAS research. Here we suggest a systematic strategy for understanding how cancer-associated variants exert their effects. We mostly refer to SNPs throughout the paper, but we recognize that other types of common genetic (for example, copy number variants) or epigenetic variation may influence risk. n nOur understanding of the way in which a risk variant initiates disease pathogenesis progresses from statistical association between genetic variation and trait or disease variation to functionality and causality. The functional consequences of variants in protein-coding regions causing most monogenic disorders are more readily interpreted because we know the genetic code. For non-Mendelian or multifactorial traits, most of the common DNA variants have so far mapped to non-protein–coding regions2, where our understanding of functional consequences and causality is more rudimentary. n nOur hypothesis is that the trait-associated alleles exert their effects by influencing transcriptional output (such as transcript levels and splicing) through multiple mechanisms. We emphasize appropriate assays and models to test the functional effects of both SNPs and genes mapping to cancer predisposition loci. Although much of what is written is applicable to alleles discovered for any trait, the section on modeling gene effects will emphasize measuring cancer-related phenotypes. n nAt some loci, multiple, independently associated risk alleles rather than single risk alleles may be functionally responsible for the occurrence of disease. Genotyping susceptibility loci (and their correlated variants) in multiple populations with different linkage disequilibrium (LD) structures may prove effective in substantially reducing the number of potentially causative variants (that is, the same causal variant may segregate in multiple populations), as shown for the FGFR2 locus in breast cancer7, but for most loci there will remain a set of potentially causative variants that cannot be separated at the statistical level from case-control genotype data. n nA susceptibility locus should be re-sequenced to ascertain all genetic variation, identifying candidate functional or causal variants and identifying candidate causal genes. Ideally, the identification of a causal SNP would be the next step to reveal the molecular mechanisms of risk modification. Practically, however, it is unclear what the criteria for causality should be, particularly in non-protein–coding regions. Thus, although we propose a framework set of analyses (Box 1), we acknowledge that the techniques and methods will continue to evolve with the field. n nBox 1 nStrategies to progress from tag SNP to mechanism n n nTarget resequencing efforts using linkage disequilibrium (LD) structure. n n nUse other populations to refine LD regions (for example African ancestry with shorter LD and more heterogeneity). n n nDetermine expression levels of nearby genes as a function of genotype at each locus (eQTL). n n nCharacterize gene regulatory regions by multiple empirical techniques bearing in mind that these are tissue and context specific. n n nCombine regulatory regions with risk loci using coordinates from multiple reference genomes to capture all variation within the shorter regulatory regions that correlates with the tag SNP at each locus. n n nMultiple experimental manipulations in model systems are needed to progressively implicate transcription units (genes) in mechanisms relevant to the associated loci: n n nKnockouts of regulatory regions in animal (difficult and may be limited by functional redundancy, but new targeting methods in rat are promising) models followed by genome-wide expression analysis. n n nUse chromatin association methods (3C, CHIA-PET) of regulatory regions to determine the identity of target genes (compare with eQTL data). n n nTargeted gene perturbations in somatic cell models. n n nExplore fully genome-wide eQTL and miRNA quantitative variation correlation in relevant tissues and cells. n n n n nExplore epigenetic mechanisms in the context of genome-wide genetic polymorphism. n n nEmploy cell models and tissue reconstructions to evaluate mechanisms using gene perturbations and polymorphic variants. The human cancer cell xenograft has re-emerged as a minimal in vivo validation of these models. n n nAbove all, resist the temptation to equate any partial functional evidence as sufficient. Published claims of functional relevance should be fully evaluated using the steps detailed above.

Lung cancer epigenetics and genetics

Lung cancer is the leading cause of cancer‐related death and thus a major health problem. The efficiency of current treatment modalities for lung cancer depends strongly on the time of diagnosis, with better chances of survival if a tumor has been detected at an early stage. Thus, there is an urgent need for rapid and efficient early detection methods. Biomarkers represent a possible alternative to current, rather expensive, screening tools such as spiral computer tomography (CT), or may allow the identification of high risk groups for whom screening would be cost efficient. Although most lung cancers are the consequence of smoking, a substantial fraction of molecular‐epidemiological studies point to high‐prevalence, low‐penetrance genetic polymorphisms as modifiers of environmental lung cancer risk. In the past the genomics field has also made significant advances in identifying genetic lesions that can now be harvested with the goal of identifying novel biomarkers for lung cancer. Furthermore, the importance of epigenetic changes that occur during lung cancer development has been reported, but has been underestimated in the past. Novel high‐throughput, quantitative assays for the detection of DNA methylation or histone tail modifications are now applied, to search for alterations in the lung cancer genome and will identify novel cancer‐related genes that may become attractive targets for treatment, provide new insight into the biology of lung cancers, and could also become useful biomarkers for the early detection of lung cancer in sputum, or may be used as prognostic markers. Thus, an integrative approach in lung cancer research combining epidemiological, genetic and epigenetic information becomes an important concept for the future.

hOGG1 polymorphism and loss of heterozygosity (LOH): significance for lung cancer susceptibility in a caucasian population.

Oxidative damage is implicated in several chronic diseases including cancer. 8‐Hydroxyguanine (8‐oxoG) is one of the major promutagenic DNA lesions, which is produced by reactive oxygen species, causes G:C to T:A transversions and is excised by OGG1, an 8‐oxoG specific DNA glycosylase/AP−Lyase. In a nested case‐control study, gDNA from 105 Caucasian primary non‐small cell lung cancer cases and 105 matched controls was screened for 6 possible new polymorphic sites in the human OGG1 gene, detected previously mainly in tumour tissue. The previously described Ser326Cys polymorphism was found to be common (allele frequency 0.22) in Caucasians. However, no major difference in Ser326Cys genotype distribution could be detected between cases and controls. Two 5`‐end polymorphisms previously found in Japanese as well as Arg131Gln could not be detected in this population. An Ala85Ser polymorphism was found in 2 controls, whereas Arg46Gln was detected in only 1 case. As the hOGG1 gene is mapped (3p26.2) to a region frequently lost in primary lung tumours, the frequency of loss of heterozygosity (LOH) was investigated. Forty‐three percent of the studied lung tumours exhibited loss of one of the hOGG1 alleles. The wt Ser326 allele was not predominantly lost in our sample set, which suggests a minor role of this polymorphism in tumourgenesis. Our results show that LOH at the hOGG1 gene locus is a very common occurrence in lung tumourgenesis, possibly leading to increased mutational damage due to ROS in smokers. However, the hOGG1 polymorphisms studied are probably not major contributors to individual lung cancer susceptibility in Caucasians. Int. J. Cancer 88:932–937, 2000.

Replication of Lung Cancer Susceptibility Loci at Chromosomes 15q25, 5p15, and 6p21: A Pooled Analysis From the International Lung Cancer Consortium

BACKGROUNDnGenome-wide association studies have identified three chromosomal regions at 15q25, 5p15, and 6p21 as being associated with the risk of lung cancer. To confirm these associations in independent studies and investigate heterogeneity of these associations within specific subgroups, we conducted a coordinated genotyping study within the International Lung Cancer Consortium based on independent studies that were not included in previous genome-wide association studies.nnnMETHODSnGenotype data for single-nucleotide polymorphisms at chromosomes 15q25 (rs16969968, rs8034191), 5p15 (rs2736100, rs402710), and 6p21 (rs2256543, rs4324798) from 21 case-control studies for 11 645 lung cancer case patients and 14 954 control subjects, of whom 85% were white and 15% were Asian, were pooled. Associations between the variants and the risk of lung cancer were estimated by logistic regression models. All statistical tests were two-sided.nnnRESULTSnAssociations between 15q25 and the risk of lung cancer were replicated in white ever-smokers (rs16969968: odds ratio [OR] = 1.26, 95% confidence interval [CI] = 1.21 to 1.32, P(trend) = 2 x 10(-26)), and this association was stronger for those diagnosed at younger ages. There was no association in never-smokers or in Asians between either of the 15q25 variants and the risk of lung cancer. For the chromosome 5p15 region, we confirmed statistically significant associations in whites for both rs2736100 (OR = 1.15, 95% CI = 1.10 to 1.20, P(trend) = 1 x 10(-10)) and rs402710 (OR = 1.14, 95% CI = 1.09 to 1.19, P(trend) = 5 x 10(-8)) and identified similar associations in Asians (rs2736100: OR = 1.23, 95% CI = 1.12 to 1.35, P(trend) = 2 x 10(-5); rs402710: OR = 1.15, 95% CI = 1.04 to 1.27, P(trend) = .007). The associations between the 5p15 variants and lung cancer differed by histology; odds ratios for rs2736100 were highest in adenocarcinoma and for rs402710 were highest in adenocarcinoma and squamous cell carcinomas. This pattern was observed in both ethnic groups. Neither of the two variants on chromosome 6p21 was associated with the risk of lung cancer.nnnCONCLUSIONSnIn this international genetic association study of lung cancer, previous associations found in white populations were replicated and new associations were identified in Asian populations. Future genetic studies of lung cancer should include detailed stratification by histology.

Effect of NAT1 and NAT2 Genetic Polymorphisms on Colorectal Cancer Risk Associated with Exposure to Tobacco Smoke and Meat Consumption

N-Acetyltransferases 1 and 2 (NAT1 and NAT2), both being highly polymorphic, are involved in the metabolism of aromatic and heterocyclic aromatic amines present in cigarette smoke and red meat cooked by high-temperature cooking techniques. We investigated the effect of differences in acetylation capacity, determined by NAT1 and NAT2 genotypes, on colorectal cancer risk associated with exposure to tobacco smoke or red meat consumption. In this population-based case-control study in Germany, 505 patients with incident colorectal cancer and 604 age- and sex-matched control individuals with genotyping data and detailed risk factor information were included. Genotyping of NAT1 and NAT2 genetic polymorphisms was done using a fluorescence-based melting curve analysis method. The association between genotypes, environmental exposures, and colorectal cancer risk was estimated using multivariate logistic regression. Colorectal cancer risk associated with active smoking was elevated after accumulation of 30+ pack-years of smoking [odds ratio (OR), 1.4; 95% confidence interval (95% CI), 0.9-2.2] but not significantly modified by either NAT1 or NAT2 genotype. Exposure to environmental tobacco smoke was associated with an increased risk for colorectal cancer only among NAT2 fast acetylators (OR, 2.6; 95% CI, 1.1-5.9 for exposure in childhood and adulthood). Frequent consumption of red meat significantly increased colorectal cancer risk for the group comprising all NAT2 fast acetylators or carriers of the NAT1*10 allele (OR, 2.6; 95% CI, 1.1-6.1) but not among those with “slow” NAT1 and NAT2 genotypes. Our findings indicate that NAT1 and NAT2 genotypes may contribute jointly to individual susceptibility and that heterocyclic aromatic amines may play an important role in colorectal cancer associated with red meat and possibly also exposure to environmental tobacco smoke. (Cancer Epidemiol Biomarkers Prev 2006;15(1):99–107)

Influence of common genetic variation on lung cancer risk: meta-analysis of 14 900 cases and 29 485 controls

Recent genome-wide association studies (GWASs) have identified common genetic variants at 5p15.33, 6p21–6p22 and 15q25.1 associated with lung cancer risk. Several other genetic regions including variants of CHEK2 (22q12), TP53BP1 (15q15) and RAD52 (12p13) have been demonstrated to influence lung cancer risk in candidate- or pathway-based analyses. To identify novel risk variants for lung cancer, we performed a meta-analysis of 16 GWASs, totaling 14 900 cases and 29 485 controls of European descent. Our data provided increased support for previously identified risk loci at 5p15 (P = 7.2 × 10−16), 6p21 (P = 2.3 × 10−14) and 15q25 (P = 2.2 × 10−63). Furthermore, we demonstrated histology-specific effects for 5p15, 6p21 and 12p13 loci but not for the 15q25 region. Subgroup analysis also identified a novel disease locus for squamous cell carcinoma at 9p21 (CDKN2A/p16INK4A/p14ARF/CDKN2B/p15INK4B/ANRIL; rs1333040, P = 3.0 × 10−7) which was replicated in a series of 5415 Han Chinese (P = 0.03; combined analysis, P = 2.3 × 10−8). This large analysis provides additional evidence for the role of inherited genetic susceptibility to lung cancer and insight into biological differences in the development of the different histological types of lung cancer.

Long Noncoding RNA TARID Directs Demethylation and Activation of the Tumor Suppressor TCF21 via GADD45A

DNA methylation is a dynamic and reversible process that governs gene expression during development and disease. Several examples of active DNA demethylation have been documented, involving genome-wide and gene-specific DNA demethylation. How demethylating enzymes are targeted to specific genomic loci remains largely unknown. We show that an antisense lncRNA, termed TARID (for TCF21 antisense RNA inducing demethylation), activates TCF21 expression by inducing promoter demethylation. TARID interacts with both the TCF21 promoter and GADD45A (growth arrest and DNA-damage-inducible, alpha), a regulator of DNA demethylation. GADD45A in turn recruits thymine-DNA glycosylase for base excision repair-mediated demethylation involving oxidation of 5-methylcytosine to 5-hydroxymethylcytosine in the TCF21 promoter by ten-eleven translocation methylcytosine dioxygenase proteins. The results reveal a function of lncRNAs, serving as a genomic address label for GADD45A-mediated demethylation of specific target genes.

International Lung Cancer Consortium: Pooled Analysis of Sequence Variants in DNA Repair and Cell Cycle Pathways

Background: The International Lung Cancer Consortium was established in 2004. To clarify the role of DNA repair genes in lung cancer susceptibility, we conducted a pooled analysis of genetic variants in DNA repair pathways, whose associations have been investigated by at least 3 individual studies. Methods: Data from 14 studies were pooled for 18 sequence variants in 12 DNA repair genes, including APEX1, OGG1, XRCC1, XRCC2, XRCC3, ERCC1, XPD, XPF, XPG, XPA, MGMT, and TP53. The total number of subjects included in the analysis for each variant ranged from 2,073 to 13,955 subjects. Results: Four of the variants were found to be weakly associated with lung cancer risk with borderline significance: these were XRCC3 T241M [heterozygote odds ratio (OR), 0.89; 95% confidence interval (95% CI), 0.79-0.99 and homozygote OR, 0.84; 95% CI, 0.71-1.00] based on 3,467 cases and 5,021 controls from 8 studies, XPD K751Q (heterozygote OR, 0.99; 95% CI, 0.89-1.10 and homozygote OR, 1.19; 95% CI, 1.02-1.39) based on 6,463 cases and 6,603 controls from 9 studies, and TP53 R72P (heterozygote OR, 1.14; 95% CI, 1.00-1.29 and homozygote OR, 1.20; 95% CI, 1.02-1.42) based on 3,610 cases and 5,293 controls from 6 studies. OGG1 S326C homozygote was suggested to be associated with lung cancer risk in Caucasians (homozygote OR, 1.34; 95% CI, 1.01-1.79) based on 2,569 cases and 4,178 controls from 4 studies but not in Asians. The other 14 variants did not exhibit main effects on lung cancer risk. Discussion: In addition to data pooling, future priorities of International Lung Cancer Consortium include coordinated genotyping and multistage validation for ongoing genome-wide association studies. (Cancer Epidemiol Biomarkers Prev 2008;17(11):3081–9)