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- Vineis, P., et al.
(författare)
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Genetic susceptibility according to three metabolic pathways in cancers of the lung and bladder and in myeloid leukemias in nonsmokers
- 2007
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Ingår i: Annals of Oncology. - : Elsevier BV. - 1569-8041 .- 0923-7534. ; 18:7, s. 1230-1242
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Tidskriftsartikel (refereegranskat)abstract
- Background: We chose a set of candidate single nucleotide polymorphisms (SNPs) to investigate gene-environment interactions in three types of cancer that have been related to air pollution (lung, bladder and myeloid leukemia). Patients and methods: The study has been conducted as a nested case-control study within the European Prospective Investigation into Cancer and Nutrition cohort (409 cancer cases and 757 matched controls). We included never and ex-smokers. SNPs were in genes involved in oxidative stress, phase I metabolizing genes, phase 11 metabolizing genes and methylenetetrahydrofolate reductase (MTHFR). Results: The most notable findings are: GSTM1 deletion and bladder cancer risk [odds ratio (OR) = 1.60; 95% confidence interval 1.00-2.56]; CYP1A1 and leukemia (2.22, 1.33-3.70; heterozygotes); CYP1B1 and leukemia (0.47, 0.27-0.84; homozygotes); MnSOD and leukemia (1.91, 1.08-3.38; homozygotes) and NQO1 and lung cancer (8.03, 1.73-37.3; homozygotes). Other statistically significant associations were found in subgroups defined by smoking habits (never or ex-smokers), environmental tobacco smoke or gender, with no obvious pattern. When gene variants were organized according to the three main pathways, the emerging picture was of a strong involvement of combined phase I enzymes in leukemia, with an OR of 5 (1.63-15.4) for those having three or more variant alleles. The association was considerably stronger for leukemias arising before the age of 55.
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- Lumbreras, B., et al.
(författare)
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Meat intake and bladder cancer in a prospective study: a role for heterocyclic aromatic amines?
- 2008
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Ingår i: Cancer Causes and Control. - : Springer Science and Business Media LLC. - 1573-7225 .- 0957-5243. ; 19:6, s. 649-656
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Tidskriftsartikel (refereegranskat)abstract
- Objective The suspect carcinogens, heterocyclic amines (HAAs), found in well-done meat require host-mediated metabolic activation before inducing DNA mutations. The role of SULT1A1 and of NAT2 on the activation of HAAs suggests that NAT2 rapid acetylator genotype and SULT1A1 allele variants can have an effect on HAA carcinogenicity. Methods Data were collected as part of a case-control study nested within the EPIC cohort, the Gen Air investigation. EPIC is a prospective study designed to investigate the relationship between nutrition and cancer. Information was collected through a non-dietary questionnaire on lifestyle variables and through a dietary questionnaire. The subjects were restricted to non-smokers. We calculated the matched odds ratio for bladder cancer risk using logistic regression, controlling for potential confounders. Results There were 227 bladder cases and 612 controls matched 1:3. Meat intake and NAT2 genotype were not independently associated with bladder cancer risk. A significant relationship was observed between bladder cancer risk and consumption of meat only among subjects with the rapid NAT2 genotype (odds ratios [OR] 2.9, 95% CI 1.0-7.9 for the 2nd quartile of meat intake; 3.6, 95% CI 1.3-9.7 for the 3rd quartile; and 3.5, 95% CI 1.2-9.7 for the 4th quartile), and was not present among subjects with the slow genotype. An interaction between NAT2 and meat intake was found in logistic regression (P = 0.034). No association was observed for SULT1A *1/2 genotype (1.0; 95% CI 0.7-1.5) and for SULT1A1 *2/2 genotype (0.9; 95% CI 0.5-1.7). Conclusions These results are suggestive of a role of meat intake and NAT2 on bladder cancer risk. They support the hypothesis that among subjects with the rapid NAT2 acetylation genotype higher levels of HAAs exposure are a bladder cancer risk factor. We did not observe an effect of SULT1A1 allele variants on this cancer. The present study adds new information on the possible long-term adverse effects of diets with high meat intake.
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- Manuguerra, M., et al.
(författare)
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Multi-factor dimensionality reduction applied to a large prospective investigation on gene-gene and gene-environment interactions
- 2007
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Ingår i: Carcinogenesis. - : Oxford University Press (OUP). - 0143-3334 .- 1460-2180. ; 28:2, s. 414-422
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Tidskriftsartikel (refereegranskat)abstract
- It is becoming increasingly evident that single-locus effects cannot explain complex multifactorial human diseases like cancer. We applied the multi-factor dimensionality reduction (MDR) method to a large cohort study on gene-environment and gene-gene interactions. The study (case-control nested in the EPIC cohort) was established to investigate molecular changes and genetic susceptibility in relation to air pollution and environmental tobacco smoke (ETS) in non-smokers. We have analyzed 757 controls and 409 cases with bladder cancer (n = 124), lung cancer (n = 116) and myeloid leukemia (n = 169). Thirty-six gene variants (DNA repair and metabolic genes) and three environmental exposure variables (measures of air pollution and ETS at home and at work) were analyzed. Interactions were assessed by prediction error percentage and cross-validation consistency (CVC) frequency. For lung cancer, the best model was given by a significant gene-environment association between the base excision repair (BER) XRCC1-Arg399Gln polymorphism, the double-strand break repair (DSBR) BRCA2-Asn372His polymorphism and the exposure variable 'distance from heavy traffic road', an indirect and robust indicator of air pollution (mean prediction error of 26%, P < 0.001, mean CVC of 6.60, P = 0.02). For bladder cancer, we found a significant 4-loci association between the BER APE1-Asp148Glu polymorphism, the DSBR RAD52-3'-untranslated region (3'-UTR) polymorphism and the metabolic gene polymorphisms COMT-Val158Met and MTHFR-677C > T (mean prediction error of 22%, P < 0.001, mean CVC consistency of 7.40, P < 0.037). For leukemia, a 3-loci model including RAD52-2259C > T, MnSOD-Ala9Val and CYP1A1-Ile462Val had a minimum prediction error of 31% (P < 0.001) and a maximum CVC of 4.40 (P = 0.086). The MDR method seems promising, because it provides a limited number of statistically stable interactions; however, the biological interpretation remains to be understood.
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