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Udgivelsesdato: 2009-May-24 Cell-free circulating DNA isolated from the plasma of individuals with cancer has been shown to harbor cancer-associated changes in DNA methylation, and thus it represents an attractive target for biomarker discovery. However, the reliable detection of DNA methylation changes in body fluids has proven to be technically challenging. Here we describe a novel combination of methods that allows quantitative and sensitive detection of DNA methylation in minute amounts of DNA present in body fluids (quantitative Methylation Analysis of Minute DNA amounts after whole Bisulfitome Amplification, qMAMBA). This method involves genome-wide amplification of bisulphite-modified DNA template followed by quantitative methylation detection using pyrosequencing and allows analysis of multiple genes from a small amount of starting DNA. To validate our method we used qMAMBA assays for four genes and LINE1 repetitive sequences combined with plasma DNA samples as a model system. qMAMBA offered high efficacy in the analysis of methylation levels and patterns in plasma samples with extremely small amounts of DNA and low concentrations of methylated alleles. Therefore, qMAMBA will facilitate methylation studies aiming to discover epigenetic biomarkers, and should prove particularly valuable in profiling a large sample series of body fluids from molecular epidemiology studies as well as in tracking disease in early diagnostics.

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Background: Genetic association studies are generating much information, usually in the form of single nucleotide polymorphisms in candidate genes. Analyzing such data is challenging, and raises issues of multiple comparisons and potential false-positive associations. Using data from a case-control study of bladder cancer, we showed how to use hierarchical modeling in genetic epidemiologic studies with multiple markers to control overestimation of effects and potential false-positive associations. Methods: The data were first analyzed with the conventional approach of estimating each main effect individually. We subsequently employed hierarchical modeling by adding a second stage (prior) model that incorporated information on the potential function of the genes. We used an empirical-Bayes approach, estimating the residual effects of the genes from the data. When the residual effect was set to zero, we instead used a semi-Bayes approach, in which they were pre-specified. We also explored the impact of using different second-stage design matrices. Finally, we used two approaches for assessing gene-environment interactions. The first approach added product terms into the first-stage model. The second approach used three indicators for subjects exposed to gene-only, environment-only, and both genetic and environmental factors. Results: By pre-specifying the prior second-stage covariates, the estimates were shrunk to the mean of each pathway. The conventional model detected a number of positive associations, which were reduced with the hierarchical model. For example, the odds ratio for myeloperoxidase (G/G, G/A) genotype changed from 3.17 [95% confidence interval (CI), 1.32-7.59] to 1.64 (95% CI, 0.81-3.34). A similar phenomenon was observed for the gene-environment interactions. The odds ratio for the gene-environment interaction between tobacco smoking and N-acetyltransferase 1 fast genotype was 2.74 (95% CI, 0.68-11.0) from the conventional analysis and 1.24 (95% CI, 0.80-1.93) from the hierarchical model. Conclusion: Adding a second-stage hierarchical modeling can reduce the likelihood of false positive via shrinkage toward the prior mean, improve the risk estimation by increasing the precision, and, therefore, represents an alternative to conventional methods for genetic association studies.

Cell-free circulating DNA isolated from the plasma of individuals with cancer has been shown to harbor cancer-associated changes in DNA methylation, and thus it represents an attractive target for biomarker discovery. However, the reliable detection of DNA methylation changes in body fluids has proven to be technically challenging. Here we describe a novel combination of methods that allows quantitative and sensitive detection of DNA methylation in minute amounts of DNA present in body fluids (quantitative Methylation Analysis of Minute DNA amounts after whole Bisulfitome Amplification, qMAMBA). This method involves genome-wide amplification of bisulphite-modified DNA template followed by quantitative methylation detection using pyrosequencing and allows analysis of multiple genes from a small amount of starting DNA. To validate our method we used qMAMBA assays for four genes and LINE1 repetitive sequences combined with plasma DNA samples as a model system. qMAMBA offered high efficacy in the analysis of methylation levels and patterns in plasma samples with extremely small amounts of DNA and low concentrations of methylated alleles. Therefore, qMAMBA will facilitate methylation studies aiming to discover epigenetic biomarkers, and should prove particularly valuable in profiling a large sample series of body fluids from molecular epidemiology studies as well as in tracking disease in early diagnostics.

We followed-up for mortality and cancer incidence 1088 healthy non-smokers from a population-based study, who were characterized for 22 variants in 16 genes involved in DNA repair pathways. Follow-up was 100% complete. The association between polymorphism and mortality or cancer incidence was analyzed using Cox Proportional Hazard regression models. Ninety-five subjects had died in a median follow-up time of 78 months (inter-quartile range 59-93 months). None of the genotypes was clearly associated with total mortality, except variants for two Double-Strand Break DNA repair genes, XRCC3 18067 C > T (rs#861539) and XRCC2 31479 G > A (rs#3218536). Adjusted hazard ratios were 2.25 (1.32-3.83) for the XRCC3 C/T genotype and 2.04 (1.00-4.13) for the T/T genotype (reference C/C), and 2.12 (1.14-3.97) for the XRCC2 G/A genotype (reference G/G). For total cancer mortality, the adjusted hazard ratios were 3.29 (1.23-7.82) for XRCC3 C/T, 2.84 (0.81-9.90) for XRCC3 T/T and 3.17 (1.21-8.30) for XRCC2 G/A. With combinations of three or more adverse alleles, the adjusted hazard ratio for all cause mortality was 17.29 (95% C.I. 8.13-36.74), and for all incident cancers the HR was 5.28 (95% C.I. 2.17-12.85). Observations from this prospective study suggest that polymorphisms of genes involved in the repair of DNA double-strand breaks significantly influence the risk of cancer and non-cancer disease, and can influence mortality. © 2008 Elsevier B.V. All rights reserved.

Background: 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. © 2008 Springer Science+Business Media B.V.

In contrast to some extensively examined food mutagens, for example, aflatoxins, N-nitrosamines and heterocyclic amines, some other food contaminants, in particular polycyclic aromatic hydrocarbons (PAH) and other aromatic compounds, have received less attention. Therefore, exploring the relationships between dietary habits and the levels of biomarkers related to exposure to aromatic compounds is highly relevant. We have investigated in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort the association between dietary items (food groups and nutrients) and aromatic DNA adducts and 4-aminobiphenyl-Hb adducts. Both types of adducts are biomarkers of carcinogen exposure and possibly of cancer risk, and were measured, respectively, in leucocytes and erythrocytes of 1086 (DNA adducts) and 190 (Hb adducts) non-smokers. An inverse, statistically significant, association has been found between DNA adduct levels and dietary fibre intake (P=0.02), vitamin E (P=0.04) and alcohol (P=0.03) but not with other nutrients or food groups. Also, an inverse association between fibre and fruit intake, and BMI and 4-aminobiphenyl-Hb adducts (P=0.03, 0.04, and 0.03 respectively) was observed. After multivariate regression analysis these inverse correlations remained statistically significant, except for the correlation adducts v. fruit intake. The present study suggests that fibre intake in the usual range can modify the level of DNA or Hb aromatic adducts, but such role seems to be quantitatively modest. Fibres could reduce the formation of DNA adducts in different manners, by diluting potential food mutagens and carcinogens in the gastrointestinal tract, by speeding their transit through the colon and by binding carcinogenic substances.

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.

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 II 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. © 2007 European Society for Medical Oncology.

Environmental carcinogens contained in air pollution, such as polycyclic aromatic hydrocarbons, aromatic amines or N-nitroso compounds, predominantly form DNA adducts but can also generate interstrand cross-links and reactive oxygen species. If unrepaired, such lesions increase the risk of somatic mutations and cancer. Our study investigated the relationships between 22 polymorphisms (and their haplotypes) in 16 DNA repair genes belonging to different repair pathways in 1094 controls and 567 cancer cases (bladder cancer, 131; lung cancer, 134; oral-pharyngeal cancer, 41; laryngeal cancer, 47; leukaemia, 179; death from emphysema and chronic obstructive pulmonary disease, 84). The design was a case-control study nested within a prospective investigation. Among the many comparisons, few polymorphisms were associated with the diseases at the univariate analysis: XRCC1-399 Gln/Gln variant homozygotes [odds ratios (OR) = 2.20, 95% confidence intervals (CI) = 1.16-4.17] and XRCC3-241 Met/Met homozygotes (OR = 0.51, 95% CI = 0.27-0.96) and leukaemia. The recessive model in the stepwise multivariate analysis revealed a possible protective effect of XRCC1-399Gln/Gln in lung cancer (OR = 0.22, 95% CI = 0.05-0.98), and confirmed an opposite effect (OR = 2.47, 95% CI = 1.02-6.02) in the leukaemia group. Our results also suggest that the XPD/ERCC1-GAT haplotype may modulate leukaemia (OR = 1.28, 95% CI = 1.02-1.61), bladder cancer (OR = 1.38, 95% CI = 1.06-1.79) and possibly other cancer risks. Further investigations of the combined effects of polymorphisms within these DNA repair genes, smoking and other risk factors may help to clarify the influence of genetic variation in the carcinogenic process. © 2006 Oxford University Press.

To estimate the relationship between air pollution and lung cancer, a nested case-control study was set up within EPIC (European Prospective Investigation on Cancer and Nutrition). Cases had newly diagnosed lung cancer, accrued after a median follow-up of 7 years among the EPIC exsmokers (since at least 10 years) and never smokers. Three controls per case were matched. Matching criteria were gender, age (±5 years), smoking status, country of recruitment and time elapsed between recruitment and diagnosis. We studied residence in proximity of heavy traffic roads as an indicator of exposure to air pollution. In addition, exposure to air pollutants (NO2, PM10, SO2) was assessed using concentration data from monitoring stations in routine air quality monitoring networks. Cotinine was measured in plasma. We found a nonsignificant association between lung cancer and residence nearby heavy traffic roads (odds ratio = 1.46, 95% confidence interval, CI, 0.89-2.40). Exposure data for single pollutants were available for 197 cases and 556 matched controls. For NO2 we found an odds ratio of 1.14 (95% CI, 0.78-1.67) for each increment of 10 μg/m3, and an odds ratio of 1.30 (1.02-1.66) for concentrations greater than 30 μg/m3. The association with NO2 did not change after adjustment by cotinine and additional potential confounders, including occupational exposures. No clear association was found with other pollutants. © 2006 Wiley-Liss, Inc.

Objectives were to investigate prospectively the ability of DNA adducts to predict cancer and to study the determinants of adducts, especially air pollutants. DNA adducts were measured in a case-control study nested in the European Prospective Investigation into Cancer and Nutrition (EPIC) investigation. Cases included newly diagnosed lung cancer (n = 115), upper respiratory cancers (pharynx and larynx; n = 82), bladder cancer (n = 124), leukemia (n = 166), and chronic obstructive pulmonary disease or emphysema deaths (n = 77) accrued after a median follow-up of 7 years among the EPIC former smokers and never-smokers. Three controls per case were matched for questionnaire analyses and two controls per case for laboratory analyses. Matching criteria were gender, age, smoking status, country of recruitment, and follow-up time. Individual exposure to air pollution was assessed using concentration data from monitoring stations in routine air quality monitoring networks. Leukocyte DNA adducts were analyzed blindly using 32P postlabeling technique. Adducts were associated with the subsequent risk of lung cancer, with an odds ratio (OR) of 1.86 [95% confidence interval (95% CI), 0.88-3.93] when comparing detectable versus nondetectable adducts. The association with lung cancer was stronger in never-smokers (OR, 4.04; 95% CI, 1.06-15.42) and among the younger age groups. After exclusion of the cancers occurring in the first 36 months of follow-up, the OR was 4.16 (95% CI, 1.24-13.88). A positive association was found between DNA adducts and ozone (O 3) concentration. Our prospective study suggests that leukocyte DNA adducts may predict lung cancer risk of never-smokers. Besides, the association of DNA adduct levels with O 3 indicates a possible role for photochemical smog in determining DNA damage. ©2005 American Association for Cancer Research.

Levels of plasma DNA concentrations in cancer patients have been shown to be higher than the plasma DNA concentrations found in healthy subjects. The value of plasma DNA levels for development of neoplastic or pulmonary disease was evaluated in a large prospective study. Plasma samples (n = 1, 184) were analyzed from 776 controls, 359 cases of cancer (lung, bladder, oral cavity, pharynx, larynx, leukemia) and 49 deaths from chronic obstructive pulmonary disease (COPD), including never smokers and ex-smokers, from 9 countries across Europe. The amount of plasma DNA was variable across the European Prospective Investigation into Cancer and Nutrition (EPIC) centers. High DNA concentrations in some centers might be due to the type of population recruited and/or the treatment of the samples. An elevated and statistically significant odds ratio (OR) was found for COPID deaths (OR = 2.53; 95% CI = 1.06-6.02), while nonsignificant increased ORs were present for oral cancers, cancers of the pharynx and larynx and leukemia. When the analyses were stratified by time since recruitment (below or above 36 months), the increased ORs were limited to the more recent period of recruitment, i.e., a time elapsed between blood drawing and disease onset lower than 36 months. This was particularly true for COPID deaths (OR = 12.7; 95% CI = 1.57-103) and leukemia (OR = 2.37; 95% Cl = 1.20-4.67). (C) 2004 Wiley-Liss, Inc.

Carcinogens present in cigarette smoke and diet have been associated with pancreatic cancer. We hypothesized that heterocyclic and aromatic amines implicated in these exposures could be involved as causative agents and that therefore genetic variation in enzymes metabolizing these carcinogens could modify the risk of developing malignant and benign pancreatic disease. The effect of the genetic polymorphism of acetyltransferases (NAT1) and NAT2), glutathione S-transferase M1 (GSTM1) and NAD(P)H: quinone oxidoreductase 1 (NQO1) on the risk of pancreatic diseases (cancer, pancreatitis) was examined in a case-control study. PCR-based assays were used for genotype analysis of genomic DNA from whole blood cells. Samples collected from Caucasian patients with diagnosed pancreatic cancer (n = 81), with non-alcoholic (n = 41) and alcoholic pancreatitis (n = 73) and from asymptomatic control subjects (n = 78) were analysed. The prevalence of GSTM1 null genotype and of NAT2 fast and slow acetylator genotypes and the distribution of frequencies for NQO1 genotypes did not differ in subjects with pancreatic diseases vs controls. For NAT1 slow acetylators a non-significant excess (P = 0.18) was found among pancreatic cancer cases vs controls. There was a significant over-representation of the GSTM1 AB or B genotype in all pancreatic disease cases combined (OR = 2.6; P0.05). When concurrent controls were pooled with literature controls (n = 1427), OR was 1.4 (P = 0.08). The results of this study, requiring confirmation, suggest that the polymorphism of GSTM1 and NAT1 enzymes may be associated with a modest increase in susceptibility to pancreatic diseases.

We conducted a case-control study on 114 bladder cancer patients and 46 hospital controls. DNA adducts were measured in WBCs by 32P postlabeling and showed no association with smoking habits and the glutathione-S-transferase M1 genotype. A strong association between adduct levels and the N-acetyltransferase (NAT2) genotype was found (P = 0.0002). The NAT2 genotype was associated in a nonstatistically significant way to the case-control status (odds ratio, 1.6; 95% confidence interval, 0.8-3.2). In a logistic regression model, the log of DNA adduct levels was associated in a highly significant way to the risk of bladder cancer (regression coefficient, 0.75; P = 0.0006), independently of smoking habits. Using the median of DNA adducts (RAL, 0.3) as a cutoff point, the odds ratio for the risk of bladder cancer was 4.1 (age-adjusted; 95% confidence interval, 1.9-9.0). Our study suggests that sources other than tobacco smoke contribute to the formation of aromatic DNA adducts in WBCs. The role of WBC-DNA adducts in predicting bladder cancer is still to be clarified.

International audience; In the assessment of genotoxic risk factors in the environment, the measurement of DNA adducts in aquatic organisms and in plants may have considerable implications. Using 32P-postlabelling, we have detected DNA adducts in the liver of carp (Chondrostoma nasus) from the River Rhône (France), both downstream and upstream from a polychlorinated biphenyl incineration plant. Some of the DNA adducts were specific to downstream fish, suggesting a differential pattern of exposure. We have also detected DNA damage in needles in a declining spruce forest. We found that, in the declining forest, the amounts of DNA adducts increase in relation to the degree of damage to the needles whereas, in a healthy forest, the levels of DNA adducts were low. We have also found DNA adducts in the leaves of hops grown in fields where heptachlor residues persisted.

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