DNA Repair Polymorphisms Modify Bladder Cancer Risk: A Multi-factor Analytic StrategyAndrew A.S.a · Karagas M.R.a · Nelson H.H.e · Guarrera S.c · Polidoro S.c · Gamberini S.c · Sacerdote C.c · Moore J.H.b · Kelsey K.T.f · Demidenko E.a · Vineis P.c, g · Matullo G.c, d
aDepartment of Community and Family Medicine, Section of Biostatistics and Epidemiology, and bDepartment of Genetics, Computational Genetics Laboratory, Dartmouth Medical School, Lebanon, N.H., USA; cI.S.I Foundation and dDepartment of Genetics, Biology and Biochemistry, Torino, Italy; Departments of eEnvironmental Health and fGenetics and Complex Diseases, Harvard School of Public Health, Boston, Mass., gImperial College London, St Mary’s Campus, London, UK
Dr. Angeline S. Andrew
Dartmouth Medical School
Section of Biostatistics and Epidemiology , 7927 Rubin 860
One Medical Center Drive, Lebanon, NH 03756
Tel. +1 603 653 9019, Fax +1 603 653 9093, E-Mail Angeline.Andrew@dartmouth.edu
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Objectives: A number of common non-synonymous single nucleotide polymorphisms (SNPs) in DNA repair genes have been reported to modify bladder cancer risk. These include: APE1-Asn148Gln, XRCC1-Arg399Gln and XRCC1-Arg194Trp in the BER pathway, XPD-Gln751Lys in the NER pathway and XRCC3-Thr241Met in the DSB repair pathway. Methods: To examine the independent and interacting effects of these SNPs in a large study group, we analyzed these genotypes in 1,029 cases and 1,281 controls enrolled in two case-control studies of incident bladder cancer, one conducted in New Hampshire, USA and the other in Turin, Italy. Results: The odds ratio among current smokers with the variant XRCC3-241 (TT) genotype was 1.7 (95% CI 1.0–2.7) compared to wild-type. We evaluated gene-environment and gene-gene interactions using four analytic approaches: logistic regression, Multifactor Dimensionality Reduction (MDR), hierarchical interaction graphs, classification and regression trees (CART), and logic regression analyses. All five methods supported a gene-gene interaction between XRCC1-399/XRCC3-241 (p = 0.001) (adjusted OR for XRCC1-399 GG, XRCC3-241 TT vs. wild-type 2.0 (95% CI 1.4–3.0)). Three methods predicted an interaction between XRCC1-399/XPD-751 (p = 0.008) (adjusted OR for XRCC1-399 GA or AA, XRCC3-241 AA vs. wild-type 1.4 (95% CI 1.1–2.0)). Conclusions: These results support the hypothesis that common polymorphisms in DNA repair genes modify bladder cancer risk and highlight the value of using multiple complementary analytic approaches to identify multi-factor interactions.
© 2007 S. Karger AG, Basel
- Kirkali Z, Chan T, Manoharan M, et al: Bladder cancer: Epidemiology, staging and grading, and diagnosis. Urology 2005;66:4–34.
- Cartwright RA: Genetic association with bladder cancer. Br Med J 1979;2:798.
- Sullivan JW: Epidemiologic survey of bladder cancer in greater New Orleans. J Urol 1982;128:281–283.
- Kantor AF, Hartge P, Hoover RN, Fraumeni JF Jr: Familial and environmental interactions in bladder cancer risk. Int J Cancer 1985;35:703–706.
- Goode EL, Ulrich CM, Potter JD: Polymorphisms in DNA repair genes and associations with cancer risk. Cancer Epidemiol Biomarkers Prev 2002;11:1513–1530.
- Stern MC, Johnson LR, Bell DA, Taylor JA: XPD codon 751 polymorphism, metabolism genes, smoking, and bladder cancer risk. Cancer Epidemiol Biomarkers Prev 2002;11:1004–1011.
- Schabath MB, Delclos GL, Grossman HB, et al: Polymorphisms in XPD exons 10 and 23 and bladder cancer risk. Cancer Epidemiol Biomarkers Prev 2005;14:878–884.
- Matullo G, Guarrera S, Carturan S, et al: DNA repair gene polymorphisms, bulky DNA adducts in white blood cells and bladder cancer in a case-control study. Int J Cancer 2001;92:562–567.
- Sanyal S, Festa F, Sakano S, et al: Polymorphisms in DNA repair and metabolic genes in bladder cancer. Carcinogenesis 2004;25:729–734.
- Shen M, Hung RJ, Brennan P, et al: Polymorphisms of the DNA repair genes XRCC1, XRCC3, XPD, interaction with environmental exposures, and bladder cancer risk in a case-control study in northern Italy. Cancer Epidemiol Biomarkers Prev 2003;12:1234–1240.
- Matullo G, Palli D, Peluso M, et al: XRCC1, XRCC3, XPD gene polymorphisms, smoking and (32)P-DNA adducts in a sample of healthy subjects. Carcinogenesis 2001;22:1437–1445.
- Stern MC, Umbach DM, van Gils CH, Lunn RM, Taylor JA: DNA repair gene XRCC1 polymorphisms, smoking, and bladder cancer risk. Cancer Epidemiol Biomarkers Prev 2001;10:125–131.
- Stern MC, Umbach DM, Lunn RM, Taylor JA: DNA Repair Gene XRCC3 Codon 241 Polymorphism, Its Interaction with Smoking and XRCC1 Polymorphisms, and Bladder Cancer Risk. Cancer Epidemiol Biomarkers Prev 2002;11:939–943.
- Garcia-Closas M, Malats N, Real FX, et al : Genetic variation in the nucleotide excision repair pathway and bladder cancer risk. Cancer Epidemiol Biomarkers Prev 2006;15:536–542.
- Matullo G, Guarrera S, Sacerdote C, et al: Polymorphisms/Haplotypes in DNA repair genes and smoking: A bladder cancer case-control study. Cancer Epidemiol Biomarkers Prev 2005;14:2569–2578.
- Andrew AS, Nelson HH, Kelsey KT, et al: Concordance of multiple analytical approaches demonstrates a complex relationship between DNA repair gene SNPs, smoking, and bladder cancer susceptibility. Carcinogenesis 2006;27:1030–1037.
- Zhou W, Liu G, Miller DP, et al : Polymorphisms in the DNA repair genes XRCC1 and ERCC2, smoking, and lung cancer risk. Cancer Epidemiol Biomarkers Prev 2003;12:359–365.
- Chen S, Tang D, Xue K, et al : DNA repair gene XRCC1 and XPD polymorphisms and risk of lung cancer in a Chinese population. Carcinogenesis 2002;23:1321–1325.
- Pharoah PD, Dunning AM, Ponder BA, Easton DF: Association studies for finding cancer-susceptibility genetic variants. Nat Rev Cancer 2004;4:850–860.
- Moore JH: The ubiquitous nature of epistasis in determining susceptibility to common human diseases. Hum Hered 2003;56:73–82.
- Caporaso NE: Why have we failed to find the low penetrance genetic constituents of common cancers? Cancer Epidemiol Biomarkers Prev 2002;11:1544–1549.
- Karagas MR, Tosteson TD, Blum J, et al: Design of an epidemiologic study of drinking water arsenic exposure and skin and bladder cancer risk in a U.S. population. Environ Health Perspect 1998;106(suppl 4):1047–1050.
- Kelsey KT, Park S, Nelson HH, Karagas MR: A population-based case-control study of the XRCC1 Arg399Gln polymorphism and susceptibility to bladder cancer. Cancer Epidemiol Biomarkers Prev 2004;13:1337–1341.
- Ritchie MD, Hahn LW, Roodi N, et al: Multifactor-dimensionality reduction reveals high-order interactions among estrogen-metabolism genes in sporadic breast cancer. Am J Hum Genet 2001;69:138–147.
- Ritchie MD, Hahn LW, Moore JH: Power of multifactor dimensionality reduction for detecting gene-gene interactions in the presence of genotyping error, missing data, phenocopy, and genetic heterogeneity. Genet Epidemiol 2003;24:150–157.
- Hahn LW, Ritchie MD, Moore JH: Multifactor dimensionality reduction software for detecting gene-gene and gene-environment interactions. Bioinformatics 2003;19:376–382.
- Hahn LW, Moore JH: Ideal discrimination of discrete clinical endpoints using multilocus genotypes. In Silico Biol 2004;4:183–194.
- Moore JH: Computational analysis of gene-gene interactions using multifactor dimensionality reduction. Expert Rev Mol Diagn 2004;4:795–803.
- Moore JH: Cross-validation consistency for the assessment of genetic programming results in microarray studies. Lecture Notes in Computer Science 2003;2611:99–106.
- Coffey CS, Hebert PR, Ritchie MD, et al : An application of conditional logistic regression and multifactor dimensionality reduction for detecting gene-gene interactions on risk of myocardial infarction: The importance of model validation. BMC Bioinformatics 2004;5:49–59.
- Coffey CS, Hebert PR, Krumholz HM, et al: Reporting of model validation procedures in human studies of genetic interactions. Nutrition 2004;20:69–73.
Jakulin A, Bratko I: Analyzing attribute dependencies; in Lavrac N, Gamberger D, Blockeel H, Todorovski L (eds): PKDD 2003, LNAI 2838. Cavtat, Croatia: Springer-Verlag, 2003, pp 229–240.
Jakulin A, Bratko I, Smrke D, Demsar J, Zupan B: Attribute interactions in medical data analysis. Artificial intelligence in medicine Europe. Protaras, Cyprus, 2003, pp 229–238.
Pierce JR: An introduction to information theory – Symbols, signals and noise. New York, Dover Publications, 1980.
Demsar J, Zupan B. Orange: From Experimental Machine Learning to Interactive Data Mining, White Paper. Ljublijana, Slovenia, Faculty of Computer and Information Science, University of Ljublijana, 2004.
Breiman L, Friendman JH, Olshen RA, Stone CJ: Classification and regression trees. Belmont, Wadsworth, 1984.
- Cook NR, Zee RY, Ridker PM: Tree and spline based association analysis of gene-gene interaction models for ischemic stroke. Stat Med 2004;23:1439–1453.
- Ruczinski I, Kooperberg C, LeBlanc M: Logic regression. J Comput Graph Stat 2003;12:475–511.
- Ruczinski I, Kooperberg C, LeBlanc M: Exploring interactions in high dimensional genomic data: An overview of logic regression, with applications. J Mult Anal 2004;90:178–195.
- Wacholder S, Chanock S, Garcia-Closas M, El Ghormli L, Rothman N: Assessing the probability that a positive report is false: An approach for molecular epidemiology studies. J Natl Cancer Inst 2004;96:434–442.
- Hung RJ, Brennan P, Canzian F, et al : Large-scale investigation of base excision repair genetic polymorphisms and lung cancer risk in a multicenter study. J Natl Cancer Inst 2005;97:567–576.
- Matullo G, Dunning AM, Guarrera S, et al: DNA repair polymorphisms and cancer risk in non-smokers in a cohort study. Carcinogenesis 2006;27:997–1007.
- Duell EJ, Holly EA, Bracci PM, Wiencke JK, Kelsey KT: A population-based study of the Arg399Gln polymorphism in X-ray repair cross-complementing group 1 (XRCC1) and risk of pancreatic adenocarcinoma. Cancer Res 2002;62:4630–4636.
- Ye W, Kumar R, Bacova G, et al: The XPD 751Gln allele is associated with an increased risk for esophageal adenocarcinoma: a population-based case-control study in Sweden. Carcinogenesis 2006;27:1835–1841.
- Kubota Y, Nash RA, Klungland A, et al: Reconstitution of DNA base excision-repair with purified human proteins: Interaction between DNA polymerase beta and the XRCC1 protein. EMBO J 1996;15:6662–6670.
- Marsin S, Vidal AE, Sossou M, et al : Role of XRCC1 in the coordination and stimulation of oxidative DNA damage repair initiated by the DNA glycosylase hOGG1. J Biol Chem 2003;278:44068–44074.
- Bishop DK, Ear U, Bhattacharyya A, et al: Xrcc3 is required for assembly of Rad51 complexes in vivo. J Biol Chem 1998;273:21482–21488.
- Ronen A, Glickman BW: Human DNA repair genes. Environ Mol Mutagen 2001;37:241–283.
- Araujo FD, Pierce AJ, Stark JM, Jasin M: Variant XRCC3 implicated in cancer is functional in homology-directed repair of double-strand breaks. Oncogene 2002;21:4176–4180.
- Henry-Mowatt J, Jackson D, Masson JY, et al: XRCC3 and Rad51 modulate replication fork progression on damaged vertebrate chromosomes. Mol Cell 2003;11:1109–1117.
- Taylor RM, Moore DJ, Whitehouse J, Johnson P, Caldecott KW: A cell cycle-specific requirement for the XRCC1 BRCT II domain during mammalian DNA strand break repair. Mol Cell Biol 2000;20:735–740.
- Araujo SJ, Wood RD: Protein complexes in nucleotide excision repair. Mutat Res 1999;435:23–33.
Silverman DT, Morrison AS, Devesa SS: Bladder Cancer; in Schottenfeld D FJ (ed): Cancer Epidemiology and Prevention. New York, Oxford University Press, 1996, pp 1156–1179.
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