Persistent transcriptional responses show the involvement of feed-forward control in a repeated dose toxicity study

Chemical carcinogenesis, albeit complex, often relies on modulation of transcription through activation or repression of key transcription factors. While analyzing extensive networks may hinder the biological interpretation, one may focus on dynamic network motifs, among which persistent feed-forward loops (FFLs) are known to chronically influence transcriptional programming. Here, to investigate the relevance a FFL-oriented approach in depth, we have focused on aflatoxin B1-induced transcriptomic alterations during distinct states of exposure (daily administration during 5 days followed by a non-exposed period) of human hepatocytes, by exploring known interactions in human transcription. Several TF-coding genes were persistently deregulated after washout of AFB1. Oncogene MYC was identified as the prominent regulator and driver of many FFLs, among which a FFL comprising MYC/HIF1A was the most recurrent. The MYC/HIF1A FFL was also identified and validated in an independent set as the master regulator of metabolic alterations linked to initiation and progression of carcinogenesis, i.e. the Warburg effect, possibly as result of persistent intracellular alterations arising from AFB1 exposure (nuclear and mitochondrial DNA damage, oxidative stress, transcriptional activation by secondary messengers). In summary, our analysis shows the involvement of FFLs as modulators of gene expression suggestive of a carcinogenic potential even after termination of exposure

Integrating transcriptomics and metabonomics to unravel modes-of-action of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) in HepG2 cells

<p>Abstract</p> <p>Background</p> <p>The integration of different 'omics' technologies has already been shown in several <it>in vivo </it>studies to offer a complementary insight into cellular responses to toxic challenges. Being interested in developing <it>in vitro </it>cellular models as alternative to animal-based toxicity assays, we hypothesize that combining transcriptomics and metabonomics data improves the understanding of molecular mechanisms underlying the effects caused by a toxic compound also <it>in vitro </it>in human cells. To test this hypothesis, and with the focus on non-genotoxic carcinogenesis as an endpoint of toxicity, in the present study, the human hepatocarcinoma cell line HepG2 was exposed to the well-known environmental carcinogen 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD).</p> <p>Results</p> <p>Transcriptomics as well as metabonomics analyses demonstrated changes in TCDD-exposed HepG2 in common metabolic processes, e.g. amino acid metabolism, of which some of the changes only being confirmed if both 'omics' were integrated. In particular, this integrated analysis identified unique pathway maps involved in receptor-mediated mechanisms, such as the G-protein coupled receptor protein (GPCR) signaling pathway maps, in which the significantly up-regulated gene son of sevenless 1 (SOS1) seems to play an important role. SOS1 is an activator of several members of the RAS superfamily, a group of small GTPases known for their role in carcinogenesis.</p> <p>Conclusions</p> <p>The results presented here were not only comparable with other <it>in vitro </it>studies but also with <it>in vivo </it>studies. Moreover, new insights on the molecular responses caused by TCDD exposure were gained by the cross-omics analysis.</p

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

Automatic vs. manual curation of a multi-source chemical dictionary: the impact on text mining

Background. Previously, we developed a combined dictionary dubbed Chemlist for the identification of small molecules and drugs in text based on a number of publicly available databases and tested it on an annotated corpus. To achieve an acceptable recall and precision we used a number of automatic and semi-automatic processing steps together with disambiguation rules. However, it remained to be investigated which impact an extensive manual curation of a multi-source chemical dictionary would have on chemical term identification in text. ChemSpider is a chemical database that has undergone extensive manual curation aimed at establishing valid chemical name-to-structure relationships. Results. We acquired the component of ChemSpider containing only manually curated names and synonyms. Rule-based term filtering, semi-automatic manual curation, and disambiguation rules were applied. We tested the dictionary from ChemSpider on an annotated corpus and compared the results with those for the Chemlist dictionary. The ChemSpider dictionary of ca. 80 k names was only a 1/3 to a 1/4 the size of Chemlist at around 300 k. The ChemSpider dictionary had a precision of 0.43 and a recall of 0.19 before the application of filtering and disambiguation and a precision of 0.87 and a recall of 0.19 after filtering and disambiguation. The Chemlist dictionary had a precision of 0.20 and a recall of 0.47 before the application of filtering and disambiguation and a precision of 0.67 and a recall of 0.40 after filtering and disambiguation. Conclusions. We conclude the following: (1) The ChemSpider dictionary achieved the best precision but the Chemlist dictionary had a higher recall and the best F-score; (2) Rule-based filtering and disambiguation is necessary to achieve a high precision for both the automatically generated and the manually curated dictionary. ChemSpider is available as a web service at http://www.chemspider. com/ and the Chemlist dictionary is freely available as an XML file in Simple Knowledge Organization System format on the web at http://www.biosemantics.org/ chemlist

Moving Forward in Human Cancer Risk Assessment

The goal of human risk assessment is to decide whether a given exposure level to a particular chemical or substance is acceptable to human health, and to provide risk management measures based on an evaluation and prediction of the effects of that exposure on human health. Within this framework, the current safety paradigm for assessing possible carcinogenic properties of drugs, cosmetics, industrial chemicals and environmental exposures relies mainly on in vitro genotoxicity testing followed by 2-year bioassays in mice and rats. This testing paradigm was developed 40 to 50 years ago with the initial premise that ¿mutagens are also carcinogens¿ and that the carcinogenic risk to humans can be extrapolated from the tumor incidence after lifetime exposure to maximally tolerated doses of chemicals in rodents. Genotoxicity testing is used as a surrogate for carcinogenicity testing and is required for initiation of clinical trials (Jacobs and Jacobson-Kram 2004) and for most industrial chemicals safety assessment. Although the carcinogenicity-testing paradigm has effectively protected patients and consumers from introduction of harmful carcinogens as drugs and other products, the testing paradigm is clearly not sustainable in the future. The causal link between genetic damage and carcinogenicity is well documented; however, the limitations of genotoxicity/carcinogenicity testing assays, the presence of additional non-genotoxic mechanisms, issues of species-specific effects, and the lack of mechanistic insights provide an enormous scientific challenge. The 2-year rodent carcinogenicity bioassays are associated with technical complexity, high costs, high animal burden as well as the uncertainty associated with extrapolating from rodents to humans. Additional frustrations exist because of the limited predictability of the 2-year bioassay and, in particular, with regard to the problem of the prediction of false positives. For instance, in the Carcinogenic Potency Project DataBase (CPDB) which includes results from chronic, long-term animal cancer tests with mice, rats, hamsters amounting to a total of 6540 individual experiments with 1547 chemicals, 751 of those chemicals or 51% have positive findings in rodent studies. Similarly, when one considers all chronically used human pharmaceuticals, some 50% induce tumors in rodents. Yet only 20 human pharmaceutical compounds have been identified as carcinogens in epidemiological studies, despite the fact that quite a large number of epidemiological studies have been carried out on these compounds, e.g. NSAID¿s, benzodiazepines, phenobarbital. This high incidence of tumors in bioassays has lead to questions concerning the human relevance of tumors induced in rodents (Knight et al. 2006; Ward 2008). In summary, dependency on the rodent model as a golden standard of cancer risk assessment is neglecting the high number of false positives and clearly has serious limitations. Consequently, there is a growing appeal for a paradigm change after "50 years of rats and mice". For instance, the current demands for volume of carcinogenic testing together with limitations of animal usage as initially stipulated by REACH (Combes et al. 2006) will require revolutionary change in the testing paradigm. For the purpose of developing a road map for this needed paradigm change in carcinogenicity testing, a workshop was held in August 2009 in Venice, Italy entitled ¿Genomics in Cancer Risk Assessment.¿ This workshop brought together toxicologists from academia and industry with governmental regulators and risk assessors from the US and the EU, for discussing the state-of-the-art in developing alternative testing strategies for genotoxicity and carcinogenicity, thereby focusing on the contribution from the ¿omics technologies. What follows is a highlight of the major conclusions and suggestions from this workshop as a path forward.JRC.DG.I.3-In-vitro method

Next-generation text-mining mediated generation of chemical response-specific gene sets for interpretation of gene expression data

Background: Availability of chemical response-specific lists of genes (gene sets) for pharmacological and/or toxic effect prediction for compounds is limited. We hypothesize that more gene sets can be created by next-generation text mining (next-gen TM), and that these can be used with gene set analysis (GSA) methods for chemical treatment identification, for pharmacological mechanism elucidation, and for comparing compound toxicity profiles. Methods. We created 30,211 chemical response-specific gene sets for human and mouse by next-gen TM, and derived 1,189 (human) and 588 (mouse) gene sets from the Comparative Toxicogenomics Database (CTD). We tested for significant differential expression (SDE) (false discovery rate -corrected p-values < 0.05) of the next-gen TM-derived gene sets and the CTD-derived gene sets in gene expression (GE) data sets of five chemicals (from experimental models). We tested for SDE of gene sets for six fibrates in a peroxisome proliferator-activated receptor alpha (PPARA) knock-out GE dataset and compared to results from the Connectivity Map. We tested for SDE of 319 next-gen TM-derived gene sets for environmental toxicants in three GE data sets of triazoles, and tested for SDE of 442 gene sets associated with embryonic structures. We compared the gene sets to triazole effects seen in the Whole Embryo Culture (WEC), and used principal component analysis (PCA) to discriminate triazoles from other chemicals. Results: Next-gen TM-derived gene sets matching the chemical treatment were significantly altered in three GE data sets, and the corresponding CTD-derived gene sets were significantly altered in five GE data sets. Six next-gen TM-derived and four CTD-derived fibrate gene sets were significantly altered in the PPARA knock-out GE dataset. None of the fibrate signatures in cMap scored significant against the PPARA GE signature. 33 environmental toxicant gene sets were significantly altered in the triazole GE data sets. 21 of these toxicants had a similar toxicity pattern as the triazoles. We confirmed embryotoxic effects, and discriminated triazoles from other chemicals. Conclusions: Gene set analysis with next-gen TM-derived chemical response-specific gene sets is a scalable method for identifying similarities in gene responses to other chemicals, from which one may infer potential mode of action and/or toxic effect

Human Embryonic Stem Cell Derived Hepatocyte-Like Cells as a Tool for In Vitro Hazard Assessment of Chemical Carcinogenicity

Hepatocyte-like cells derived from the differentiation of human embryonic stem cells (hES-Hep) have potential to provide a human relevant in vitro test system in which to evaluate the carcinogenic hazard of chemicals. In this study, we have investigated this potential using a panel of 15 chemicals classified as noncarcinogens, genotoxic carcinogens, and nongenotoxic carcinogens and measured whole-genome transcriptome responses with gene expression microarrays. We applied an ANOVA model that identified 592 genes highly discriminative for the panel of chemicals. Supervised classification with these genes achieved a cross-validation accuracy of > 95%. Moreover, the expression of the response genes in hES-Hep was strongly correlated with that in human primary hepatocytes cultured in vitro. In order to infer mechanistic information on the consequences of chemical exposure in hES-Hep, we developed a computational method that measures the responses of biochemical pathways to the panel of treatments and showed that these responses were discriminative for the three toxicity classes and linked to carcinogenesis through p53, mitogen-activated protein kinases, and apoptosis pathway modules. It could further be shown that the discrimination of toxicity classes was improved when analyzing the microarray data at the pathway level. In summary, our results demonstrate, for the first time, the potential of human embryonic stem cell--derived hepatic cells as an in vitro model for hazard assessment of chemical carcinogenesis, although it should be noted that more compounds are needed to test the robustness of the assay

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

Altered sphingolipid function in Alzheimer's disease;:a gene regulatory network approach

Sphingolipids (SLs) are bioactive lipids involved in various important physiological functions. The SL pathway has been shown to be affected in several brain-related disorders, including Alzheimer's disease (AD). Recent evidence suggests that epigenetic dysregulation plays an important role in the pathogenesis of AD as well. Here, we use an integrative approach to better understand the relationship between epigenetic and transcriptomic processes in regulating SL function in the middle temporal gyrus of AD patients. Transcriptomic analysis of 252 SL-related genes, selected based on GO term annotations, from 46 AD patients and 32 healthy age-matched controls, revealed 103 differentially expressed SL-related genes in AD patients. Additionally, methylomic analysis of the same subjects revealed parallel hydroxymethylation changes in PTGIS, GBA, and ITGB2 in AD. Subsequent gene regulatory network-based analysis identified 3 candidate genes, that is, SELPLG, SPHK1 and CAV1 whose alteration holds the potential to revert the gene expression program from a diseased towards a healthy state. Together, this epigenomic and transcriptomic approach highlights the importance of SL-related genes in AD, and may provide novel biomarkers and therapeutic alternatives to traditionally investigated biological pathways in AD.</p