Nitrate Intake Does Not Influence Bladder Cancer Risk: The Netherlands Cohort Study

OBJECTIVES: N-nitroso compounds, endogenously formed from nitrate-derived nitrite, are suspected to be important bladder carcinogens. However, the association between nitrate exposure from food or drinking water and bladder cancer has not been substantially investigated in epidemiologic studies. METHODS: We evaluated the associations between nitrate exposure and bladder cancer in the Netherlands Cohort Study, conducted among 120,852 men and women, 55–69 years of age at entry. Information on nitrate from diet was collected via a food frequency questionnaire in 1986 and a database on nitrate content of foods. Individual nitrate exposures from beverages prepared with tap water were calculated by linking the postal code of individual residence at baseline to water company data. After 9.3 years of follow-up and after excluding subjects with incomplete or inconsistent dietary data, 889 cases and 4,441 subcohort members were available for multivariate analyses. We calculated incidence rate ratios (RR) and corresponding 95% confidence intervals (CIs) using Cox regression analyses. We also evaluated possible effect modification of dietary intake of vitamins C and E (low/high) and cigarette smoking (never/ever). RESULTS: The multivariate RRs for nitrate exposure from food, drinking water, and estimated total nitrate exposure were 1.06 (95% CI, 0.81–1.31), 1.06 (95% CI, 0.82–1.37), and 1.09 (95% CI, 0.84–1.42), respectively, comparing the highest to the lowest quintiles of intake. Dietary intake of vitamins C and E (low/high) and cigarette smoking (never/ever) had no significant impact on these results. CONCLUSION: Although the association between nitrate exposure and bladder cancer risk is biologically plausible, our results in this study do not support an association between nitrate exposure and bladder cancer risk

Transcriptome Analysis in Peripheral Blood of Humans Exposed to Environmental Carcinogens: A Promising New Biomarker in Environmental Health Studies

BACKGROUND: Human carcinogenesis is known to be initiated and/or promoted by exposure to chemicals that occur in the environment. Molecular cancer epidemiology is used to identify human environmental cancer risks by applying a range of effect biomarkers, which tend to be nonspecific and do not generate insights into underlying modes of action. Toxicogenomic technologies may improve on this by providing the opportunity to identify, molecular biomarkers consisting of altered gene expression profiles. OBJECTIVES: The aim of the present study, was to monitor the expression of selected genes in a random sample of adults in Flanders selected from specific regions with (presumably,) different environmental burdens. Furthermore, associations of gene expression with blood and urinary, measures of biomarkers of exposure, early, phenotypic effects, and tumor markers were investigated. RESULTS: Individual gene expression of cytochrome p450 1B1, activating transcription factor 4, mitogen-activated protein kinase K superoxide dismutase 2 (Mn), chemokine (C-X-C motif) ligand 1 (melanoma growth stimulating activity, alpha), diacylglycerol 0 acyltransferase homolog 2 (mouse), tigger transposable element derived 3, and PTEN-induced putative kinasel were measured by means of quantitative polymerase chain reaction in peripheral blood cells of 398 individuals. After correction for the confounding effect of tobacco smoking, inhabitants of the Olen region showed the highest differences in gene expression levels compared with inhabitants from the Gent and fruit cultivation regions. Importantly, we observed multiple significant correlations of particular gene expressions with blood and urinary, measures of various environmental carcinogens. CONCLUSIONS: Considering the observed significant differences between gene expression levels in inhabitants of various regions in Flanders and the associations of gene expression with blood or urinary measures of environmental carcinogens, we conclude that gene expression profiling appears promising as a tool for biological monitoring in relation to environmental exposures in humans

diXa: a data infrastructure for chemical safety assessment

Motivation: The field of toxicogenomics (the application of ‘-omics' technologies to risk assessment of compound toxicities) has expanded in the last decade, partly driven by new legislation, aimed at reducing animal testing in chemical risk assessment but mainly as a result of a paradigm change in toxicology towards the use and integration of genome wide data. Many research groups worldwide have generated large amounts of such toxicogenomics data. However, there is no centralized repository for archiving and making these data and associated tools for their analysis easily available. Results: The Data Infrastructure for Chemical Safety Assessment (diXa) is a robust and sustainable infrastructure storing toxicogenomics data. A central data warehouse is connected to a portal with links to chemical information and molecular and phenotype data. diXa is publicly available through a user-friendly web interface. New data can be readily deposited into diXa using guidelines and templates available online. Analysis descriptions and tools for interrogating the data are available via the diXa portal. Availability and implementation: http://www.dixa-fp7.eu Contact: [email protected]; [email protected] Supplementary information: Supplementary data are available at Bioinformatics onlin

Toxicogenomics and Toxicoinformatics: Supporting Systems Biology in the Big Data Era

Within Toxicology, Toxicogenomics stands out as a unique research field aiming at the investigation of molecular alterations induced by chemical exposure. Toxicogenomics comprises a wide range of technologies developed to measure and quantify the '-omes (transcriptome, (epi)genome, proteome and metalobome), offering a human-based approach in contrast to traditional animal-based toxicity testing. With the growing acceptance and continuous improvements in high-throughput technologies, we observed a fast increase in the generation of 'omics outputs. As a result, Toxicogenomics entered a new, challenging era facing the characteristic 4 Vs of Big Data: volume, velocity, variety and veracity. This chapter addresses these challenges by focusing on computational methods and Toxicoinformatics in the scope of Big 'omics Data. First, we provide an overview of current technologies and the steps involved in storage, pre-processing and integration of high-throughput datasets, describing databases, standard pipelines and routinely used tools. We show how data mining, pattern recognition and mechanistic/pathway analyses contribute to elucidate mechanisms of adverse effects to build knowledge in Systems Toxicology. Finally, we present the recent progress in tackling current computational and biological limitations. Throughout the chapter, we also provide relevant examples of successful applications of Toxicoinformatics in predicting toxicity in the Big Data era

Multiplex genotyping as a biomarker for susceptibility to carcinogenic exposure in the FLEHS biomonitoring study

Cancer has been suggested to result from interactions between genetic and environmental factors, and certain subgroups in the general population may be at increased risk because of their relatively higher susceptibility to environmental carcinogens. The current study, part of a large biomonitoring study conducted in Flanders from 2002 to 2006 (The Flanders Environment and Health Survey), aims to determine these susceptible subpopulations based on multiple genotypic differences between individuals. A random selection of 429 adolescents and 361 adults was genotyped for 36 polymorphisms in 23 genes selected because of their known role in carcinogen metabolism, DNA repair, and oxidative stress. In both age groups, relationships between endogenous exposure to organochloride substances (polychlorinated biphenyl, hexachlorobenzene, dichlorodiphenyl dichloroethane), metals (cadmium, lead), and urinary metabolites (1-hydroxypyrene, trans-trans muconic acid) versus genotoxic effects (Comet assay and micronuclei in lymphocytes, and urinary 8-hydroxydeoxyguanosine) were investigated. In addition, in the study among adults, the relationship of these exposures with several tumor markers (prostate-specific antigen, carcinoembryonic antigen, and p53) was tested. The impact of the genotype on established exposure-effect relationships was evaluated. Eight exposure-effect relationships were found, including three novel associations, with an impact of various genotypes, predominantly affecting biotransformation and oxidative stress response. This study shows that at least part of the interindividual differences in relationships between carcinogen exposure and genotoxic effect can be explained by genotypic differences, enabling the identification of more susceptible subgroups for environmental cancer risks. This may be of relevance for environmental health policy setting