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Genome Res. 16:693-701, 2006 ©2006 by Cold Spring Harbor Laboratory Press; ISSN 1088-9051/06 $5.00 Letter Variants in the GH-IGF axis confer susceptibilityto lung cancer1 Section of Cancer Genetics, 2 Section of Paediatrics 3 Section of Medicine, Institute of Cancer Research, Sutton, Surrey SM2 5NG, United Kingdom
We conducted a large-scale genome-wide association study in UK Caucasians to identify susceptibility alleles for lung cancer, analyzing 1529 cases and 2707 controls. To increase the likelihood of identifying disease-causing alleles, we genotyped 1476 nonsynonymous single nucleotide polymorphisms (nsSNPs) in 871 candidate cancer genes, biasing SNP selection toward those predicted to be deleterious. Statistically significant associations were identified for 64 nsSNPs, generating a genome-wide significance level of P = 0.002. Eleven of the 64 SNPs mapped to genes encoding pivotal components of the growth hormone/insulin-like growth factor (GH-IGF) pathway, including CAMKK1 E375G (OR = 1.37, P = 5.4 x 105), AKAP9 M463I (OR = 1.32, P = 1.0 x 104) and GHR P495T (OR = 12.98, P = 0.0019). Significant associations were also detected for SNPs within genes in the DNA damage-response pathway, including BRCA2 K3326X (OR = 1.72, P = 0.0075) and XRCC4 I137T (OR = 1.31, P = 0.0205). Our study provides evidence that inherited predisposition to lung cancer is in part mediated through low-penetrance alleles and specifically identifies variants in GH-IGF and DNA damage-response pathways with risk of lung cancer.
Lung cancer is the most common cancer in the world and represents a major public health problem, accounting for 1.2 million cancer-related deaths worldwide each year (Parkin et al. 2005
Lung cancer is frequently cited as a malignancy solely attributable to environmental exposure. However, it has long been postulated that individuals may differ in their susceptibility and there is increasing evidence from epidemiological studies for a familial risk (Matakidou et al. 2005 The genetic basis of inherited susceptibility to lung cancer outside the context of the rare Mendelian cancer predisposition syndromes is at present undefined, but a model in which dominantly acting, high-risk alleles account for all of the excess familial risk seems unlikely. An alternative hypothesis about the allelic architecture of lung cancer susceptibility proposes that most of the genetic risk is caused by low-penetrance alleles. This hypothesis implies that testing for allelic association should be a powerful strategy for identifying lung cancer predisposition alleles. We sought to identify novel low-penetrance susceptibility alleles to lung cancer by genotyping SNPs across 871 genes with relevance to cancer biology. To increase the likelihood of identifying disease-causing alleles, we biased selection of nsSNPs to those likely to have functionally deleterious consequences. Genotyping 1529 lung cancer cases and 2707 controls from the UK population across 1476 nsSNPs provided strong evidence that low-penetrance alleles in genes involved in the hormone/insulin-like growth factor (GH-IGF) and DNA damage-response pathways are associated with lung cancer susceptibility
Genotypes were obtained for 1526 cases (99.8%) and 2695 controls (99.6%). Of the 1476 SNPs submitted for analysis, 1221 SNPs had sample call rates >95%. Of these, 180 were fixed, leaving 1041 SNPs for which genotype data were informative (Supplemental Table 1). Implementing the genomic control method indicated no evidence of population stratification in our data as a cause of false-positive results, as the 95% confidence interval for the stratification parameter Significant associations with risk of lung cancer were identified for 64 of 1041 nsSNPs at the 5% level. The over-representation of associations between SNPs and lung cancer risk was confirmed by a joint analysis of their combined effect using the set-association approach (smallest global significance level of P = 4.2 x 104). After further adjustment for the number of terms in the set being a priori, unknown, the genome-wide significance was P = 0.002. Two of the 64 SNPs identified through the set association procedure, rs2602141 (K1136Q) and rs560191 (D353E), map to the tumor protein p53 binding protein 1 (TP53BP1) and are in strong linkage disequilibrium (LD). A further group of three SNPs in the MHC region spaced within 100 kb; rs1052486 (S625P) in HLA-B-associated transcript 3 (BAT3), rs3130618 (R41L) in HLA-B-associated transcript 4 (BAT4), and rs16900023 (P786S) in mutS homolog 5 (MSH5) also formed a cluster of high LD. Although the permutation procedure implemented in the set-association strategy allows for such substructure in the data when estimating significance levels, it may not be desirable to include highly correlated SNPs in the analysis. A total of 262 SNPs displayed high LD with an adjacent SNP. High LD was found to occur primarily within the same gene, but there were 80 instances where strong LD was observed between SNPs in different genes. We repeated our analysis by omitting markers in LD, retaining one SNP per LD set on the basis of maximum GenCall score or call rate, yielding almost identical sum statistics (P = 0.005) with inclusion of 70 SNPs.
Sixty-seven SNPs displayed significant association at the 5% level with familial lung cancer, but only 52 when the analysis was restricted to sporadic cases. After permutation, the overall significance level attained from the set-association analysis for the familial cases was P = 0.015 compared with P = 0.076 for sporadic cases. Familial cases contributed significantly to overall study findings with 13 SNPs contributing to the 20 associated at the 1% level in the overall data set (Table 1). Stratification of cases by cancer histology (small cell and non-small cell, global P-values 0.11 and 0.06, respectively), age at diagnosis (<60 and
The SNP showing the most significant allelic association with lung cancer was rs1052486 (S625P) in BAT3, a nuclear protein implicated in the control of apoptosis, with strongest association under a recessive model (ORR = 0.69, 95% CI: 0.590.82, PR = 8.3 x 106) (Table 1). Two additional SNPs, rs7214723 (E375G) in calcium/calmodulin-dependent protein kinase kinase 1 (CAMKK1), belonging to the Serine/Threonine protein kinase family (ORR = 1.37, 95% CI: 1.171.59, PR = 5.4 x 105) and rs6964587 (M463I) in A kinase anchor protein 9 (AKAP9), a key component of signal transduction (ORD = 1.32, 95% CI: 1.151.52, PD = 7.6 x 105), also showed highly significant nominal association under recessive and dominant models, respectively. Empirical limits for genome-wide significance for individual TA, TD, and TR statistics were established at 16.12, 16.23, and 15.66, respectively. Hence, BAT3 S625P and CAMKK1 E375G were both significantly associated with lung cancer with adjusted P-values of 0.006 and 0.036, respectively, with AKAP9 M463I showing borderline significance with adjusted P = 0.066. Of the 64 SNPs identified, two SNPs have been documented to be functional, i.e., K3326X in breast cancer 2 early onset (BRCA2) and N700S in thrombospondin 1 (THBS1), and a further 37 SNPs are predicted in silico to deleteriously impact on the expressed proteins (Table 2).
Through interrogation of the Pathway Assist program (Stratagene), 11 of the 64 SNPs associated with risk of lung cancer were located within individual genes encoding pivotal components of the extended GH-IGF pathway, including CAMKK1 E375G and AKAP9 M463I (both of which were globally significant), growth hormone receptor (GHR) P495T (ORD = 12.98, PD = 0.0019), A kinase anchor protein 10 (AKAP10) R249H (ORR = 1.25, PR = 0.0085), and insulin-like growth-factor binding protein 5 (IGFBP5) R138W (ORD = 1.29, PD = 0.027) (Table 1). A further five SNPs were located in genes directly involved in the DNA damage-response pathway, including the functional BRCA2 SNP K3326X (ORD = 1.72, PD = 0.0075), X-ray repair complementing defective repair in Chinese hamster cells 4 (XRCC4) I134T (ORD = 1.31, PD = 0.0205), mutS homolog 5 (MSH5) P786S (ORD = 0.64, PD = 0.0228), mutS homolog 4 (MSH4) S914N (ORD = 1.27, PD = 0.0461), and BRCA1-associated RING domain 1 (BARD1) R658C (ORD = 1.59, PD = 0.0329) (Table 1). Haplotype frequencies defined by the two sets of SNPs displaying high LD, TP53BP1 K1136Q and D353E, and BAT3 S625P, BAT4 R41L, and MSH5 P786S were significantly different in cases and controls (adjusted P-values, 0.01 and 0.01, respectively, after permutation testing). We examined for potential interactive effects between the 64 SNPs significantly associated with lung cancer risk (PA < 0.05) by fitting full logistic regression models for each pair, generating 2016 models, and comparing these with the main effects model. Ninety-six pairs of SNPs showed nominally significant interaction at the 5% level. The largest interactive effect identified was between 1-aminocyclopropane-1-carboxylate synthase (PHACS) P421L and toll-like receptor 1 (TLR1) R80T (P = 3.3 x 104), albeit nonsignificant after correction for multiple testing.
To date, the only evidence for a major locus for lung cancer susceptibility is provided by the linkage scan conducted by Bailey-Wilson et al. (2004) Previous association studies aimed at identifying low-penetrance alleles for lung cancer susceptibility have evaluated a restricted number of polymorphisms, primarily in genes implicated in the metabolism of tobacco-associated carcinogens and protection of DNA from carcinogen-induced damage. To identify novel lung cancer susceptibility alleles, we extended our search to include genes with relevance to cancer biology, evaluating only nsSNPs that have a higher probability of being directly causal. We acknowledge that the loci considered as candidates will be based on current preconceptions of cancer biology, and it is likely that other genes may influence tumor development. The number of candidate loci will inevitably increase with advances in cancer biology. The number of nsSNPs that displayed significant association with lung cancer risk was greater than that expected, supporting the tenet that polymorphic variation contributes to lung cancer susceptibility. This assertion is supported by the fact that associations were stronger when the analysis was restricted to those cases with a family history of lung cancer. We cannot exclude the possibility that some of the associations detected are a consequence of LD with causal mutations. It is noteworthy that the SNPs in BAT3, BAT4, and MSH5, which were all associated with lung cancer risk, were in strong LD. Of the 64 SNPs found to be associated with lung cancer risk, several reside in genes involved in either apoptosis (BARD1 and death associated transcription factor 1 [DATF1]), or the DNA damage-response pathway (BRCA2, MSH4, MSH5, XRCC4), thereby having relevance to the pathobiology of lung cancer a priori.
There is evidence that several of the associated SNPs directly impact on the structure and function of the expressed protein, and are therefore likely to be directly responsible for the observed association. SNPs BRCA2 K3326X and THBS1 N700S are pre-eminent in this respect. The K3326X polymorphism in BRCA2 results in loss of the terminal 91 amino acids of the expressed protein. The C-terminal region of BRCA2 is involved in the nuclear colocalization of Fanconi anemia complementation group D2 (FANCD2) (Wang et al. 2004
For 37 SNPs correlated with lung cancer risk, evidence that they are deleterious is supported by predictions of functionality based on the PolyPhen and/or SIFT programs. Although in silico predictions about the functional consequences of amino acid changes are in part speculative, such algorithms have been demonstrated in benchmarking studies to successfully categorize 80% of amino acid substitutions (Xi et al. 2004
Eleven of the 64 associated SNPs map to genes encoding pivotal components of the GH-IGF1 pathways (Fig. 1). The absence of suitable nsSNPs in AKT1, ARG2, FGF2, IGF1, PZDK1, and PRKCE did not permit us to examine whether variants in these genes also contribute to lung cancer susceptibility. The prior probability of identifying a significant association with lung cancer risk for a series of 11 SNPs mapping to a single defined pathway of genes is intuitively small. The assertion that polymorphic variation and subsequent dysregulation in the GH-IGF axis could be associated with risk of lung cancer is not without precedent. IGF1, which is up-regulated by GH, regulates cellular proliferation and apoptosis and has been shown to increase tumor growth (Khandwala et al. 2000
While it is desirable to validate our findings through analysis of additional large data sets, our study provides evidence that inherited predisposition to lung cancer is in part mediated through low-penetrance alleles and specifically identifies variants in genes comprising the GH-IGF pathway as susceptibility alleles.
Patients and control subjects Patients with lung cancer were ascertained from the Genetic Lung Cancer Predisposition Study (GELCAPS) based in the United Kingdom (UK). Information on clinico-pathological characteristics and family history was collected using standardized questionnaires (Matakidou et al. 2005 A total of 2707 healthy individuals were recruited through either the Royal Marsden Hospital Trust/Institute of Cancer Research Family History and DNA Registry (19992004; http://intra-test.icr.ac.uk/tissueres/patient_blood.html), the National Study of Colorectal Cancer Genetics Trial (2004; http://www.ncrn.org.uk/portfolio/data.asp?ID=1269) or GELCAPS, all established within the UK. The control group contained 836 (31%) males and 1871 (69%) females, median age 59 yr (range 2192 yr). None of the controls reported a personal history of cancer. All cases and controls were British Caucasians and there were no obvious demographic differences between groups in terms of place of residence within the UK. All study participants provided written informed consent. Ethical approval for the study was obtained from the London Multi-Center Research Ethics Committee (MREC/98/2/67) in accordance with the tenets of the Declaration of Helsinki. DNA was extracted from blood samples using conventional methodologies and quantified using PicoGreen (Invitrogen).
Selection of candidate genes and SNPs
SNP genotyping and data manipulation
Population stratification
Risk of lung cancer associated with nsSNPs
To increase the power to detect associations, we further analyzed case and control genotypes adopting a set-association approach, combining the largest TA statistics from individual tests into a single genome-wide statistic to model the joint effects of individual loci on lung cancer risk. Set-association analysis was conducted using the Sumstat program (Hoh et al. 2001
Multiple testing
Assessment of linkage disequilibrium between SNPs
Covariates and interactions
Under certain conditions, a two-stage process incorporating estimates of pairwise interaction between significant SNPs can yield greater power to detect association (Marchini et al. 2005
Funding for this work was undertaken with support from Cancer Research UK, the Arbib Foundation, HEAL, the National Cancer Research Network, the European Union Network of Excellence, and the Institute of Cancer Research. A.M. was the recipient of a clinical research fellowship from the Allan J. Lerner Fund. We gratefully acknowledge the participation of patient and control individuals. The authors are indebted to Richard Coleman, Christina Fleischmann, Olivia Fletcher, Nick Hearle, Nichola Johnson, Rosalind Mutch, Claire Palle, Julian Peto, Mobshra Qureshi, Elaine Ryder-Mills, Hayley Spendlove, and Remben Talaban for sample ascertainment. We thank Jurg Ott for access to a recompiled version of his Sumstat program.
4 These two authors contributed equally to this work.
E-mail Richard.Houlston{at}icr.ac.uk; fax 4-20-8722-4359.
6 List of GELCAPS Consortium collaborators available on request. [Supplemental material is available online at www.genome.org.] Article is online at http://www.genome.org/cgi/doi/10.1101/gr.5120106
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Received January 6, 2006; accepted in revised format March 20, 2006. This article has been cited by other articles:
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