Identification of a gene expression profile that discriminates indirect-acting genotoxins from direct-acting genotoxins

Application of transfer learning to predict drug-induced human in vivo gene expression changes using rat in vitro and in vivo data

The liver is the primary site for the metabolism and detoxification of many compounds, including pharmaceuticals. Consequently, it is also the primary location for many adverse reactions. As the liver is not readily accessible for sampling in humans; rodent or cell line models are often used to evaluate potential toxic effects of a novel compound or candidate drug. However, relating the results of animal and in vitro studies to relevant clinical outcomes for the human in vivo situation still proves challenging. In this study, we incorporate principles of transfer learning within a deep artificial neural network allowing us to leverage the relative abundance of rat in vitro and in vivo exposure data from the Open TG-GATEs data set to train a model to predict the expected pattern of human in vivo gene expression following an exposure given measured human in vitro gene expression. We show that domain adaptation has been successfully achieved, with the rat and human in vitro data no longer being separable in the common latent space generated by the network. The network produces physiologically plausible predictions of human in vivo gene expression pattern following an exposure to a previously unseen compound. Moreover, we show the integration of the human in vitro data in the training of the domain adaptation network significantly improves the temporal accuracy of the predicted rat in vivo gene expression pattern following an exposure to a previously unseen compound. In this way, we demonstrate the improvements in prediction accuracy that can be achieved by combining data from distinct domains.

Effects of antioxidant capacity on micronucleus induction by cigarette smoke in mammalian cells

We have compared micronucleus (MN) induction by cigarette smoke in the L5178Y, TK6, and CHL/IU cell lines. The test sample was total particulate matter of 3R4F reference cigarette smoke, suspended in DMSO. After 3-h treatment, with or without a rat liver S9 metabolic activation system, followed by 24-h recovery, dose-dependent MN increases were seen in all cell lines. However, CHL/IU and TK6 cells were more resistant than L5178Y cells (comparison by Benchmark Doses with PROAST software). 3R4F smoke generates reactive oxygen species (ROS). Therefore, we explored the relationship between the sensitivities to 3R4F smoke and the antioxidant capacities of the cell lines. While the total antioxidant capacities were not significantly different among the cell lines, cellular glutathione (GSH) was higher in CHL/IU cells than in L5178Y cells. Pretreatment of CHL/IU cells with a GSH precursor, N-acetylcysteine (NAC), reduced the genotoxicity/cytotoxicity of 3R4F, whereas an inhibitor of GSH biosynthesis, buthionine sulfoximine (BSO), enhanced it. The effects of NAC and BSO were also seen after treatment with allyl isothiocyanate, a ROS-generating chemical, but not with mitomycin C, a ROS-independent genotoxicant. Pretreatment with NAC increased cellular thiol levels. From the present results, the genotoxicity and cytotoxicity of cigarette smoke differs among these cell lines in a manner that may be related to their antioxidant thiol levels.

Use of deep learning methods to translate drug-induced gene expression changes from rat to human primary hepatocytes

In clinical trials, animal and cell line models are often used to evaluate the potential toxic effects of a novel compound or candidate drug before progressing to human trials. However, relating the results of animal and in vitro model exposures to relevant clinical outcomes in the human in vivo system still proves challenging, relying on often putative orthologs. In recent years, multiple studies have demonstrated that the repeated dose rodent bioassay, the current gold standard in the field, lacks sufficient sensitivity and specificity in predicting toxic effects of pharmaceuticals in humans. In this study, we evaluate the potential of deep learning techniques to translate the pattern of gene expression measured following an exposure in rodents to humans, circumventing the current reliance on orthologs, and also from in vitro to in vivo experimental designs. Of the applied deep learning architectures applied in this study the convolutional neural network (CNN) and a deep artificial neural network with bottleneck architecture significantly outperform classical machine learning techniques in predicting the time series of gene expression in primary human hepatocytes given a measured time series of gene expression from primary rat hepatocytes following exposure in vitro to a previously unseen compound across multiple toxicologically relevant gene sets. With a reduction in average mean absolute error across 76 genes that have been shown to be predictive for identifying carcinogenicity from 0.0172 for a random regression forest to 0.0166 for the CNN model (p < 0.05). These deep learning architecture also perform well when applied to predict time series of in vivo gene expression given measured time series of in vitro gene expression for rats.

Preclinical safety evaluation of the aqueous extract from Mangifera indica Linn. (Anacardiaceae): genotoxic, clastogenic and cytotoxic assessment in experimental models of genotoxicity in rats to predict potential human risks

ETHNOPHARMACOLOGICAL RELEVANCE

Medicinal plants widely used by the population contain significant concentrations of biologically active compounds and, although they have proven pharmacological properties, can cause DNA damage and develop fatal diseases.

AIM OF THE STUDY

The present study aimed to evaluate the genotoxic, cytotoxic potential and clastogenic effects of the aqueous extract from Mangifera indica leaves (EAMI) on rats submitted to experimental genotoxicity models and through the SMART test performed in Drosophila melanogaster.

MATERIAL AND METHODS

The comet assay and the micronucleus test were performed on peripheral and bone marrow blood, respectively, of Wistar rats, orally treated with EAMI at doses of 125, 250, 500 and 1000 mg/kg/bw for 28 days. In the SMART test, the standard cross between three mutant D. melanogaster strains was used. Larvae were treated with EAMI at different concentrations, and the wings of adult flies were evaluated for the presence/frequency of mutant spots and compared to the negative control group.

RESULTS

Phytochemical analysis of EAMI indicated high levels of flavonoids. The tests performed in rats showed that EAMI did not present significant genotoxic or clastogenic effects. The results showed a critical dose-dependent cytoprotective effect exerted by EAMI. This result was attributed to the high content of polyphenols and flavonoids. The biotransformation metabolites of EAMI did not present genotoxic activity, as demonstrated by the SMART test.

CONCLUSIONS

These results are relevant since they provide safety information about a plant species of great therapeutic, economical, nutritious and ethnopharmacological value for the population.

TGx-DDI, a Transcriptomic Biomarker for Genotoxicity Hazard Assessment of Pharmaceuticals and Environmental Chemicals

Genotoxicity testing is an essential component of the safety assessment paradigm required by regulatory agencies world-wide for analysis of drug candidates, and environmental and industrial chemicals. Current genotoxicity testing batteries feature a high incidence of irrelevant positive findings—particularly for in vitro chromosomal damage (CD) assays. The risk management of compounds with positive in vitro findings is a major challenge and requires complex, time consuming, and costly follow-up strategies including animal testing. Thus, regulators are urgently in need of new testing approaches to meet legislated mandates. Using machine learning, we identified a set of transcripts that responds predictably to DNA-damage in human cells that we refer to as the TGx-DDI biomarker, which was originally referred to as TGx-28.65. We proposed to use this biomarker in conjunction with current genotoxicity testing batteries to differentiate compounds with irrelevant “false” positive findings in the in vitro CD assays from true DNA damaging agents (i.e., for de-risking agents that are clastogenic in vitro but not in vivo). We validated the performance of the TGx-DDI biomarker to identify true DNA damaging agents, assessed intra- and inter- laboratory reproducibility, and cross-platform performance. Recently, to augment the application of this biomarker, we developed a high-throughput cell-based genotoxicity testing system using the NanoString nCounter® technology. Here, we review the status of TGx-DDI development, its integration in the genotoxicity testing paradigm, and progress to date in its qualification at the US Food and Drug Administration (FDA) as a drug development tool. If successfully validated and implemented, the TGx-DDI biomarker assay is expected to significantly augment the current strategy for the assessment of genotoxic hazards for drugs and chemicals.

Preclinical safety evaluation of the ethanolic extract fromCampomanesia pubescens(Mart. ex DC.) O.BERG (guavira) fruits: analysis of genotoxicity and clastogenic effects

Genotoxicity studies of medicinal plants are recommended by international regulatory agencies as part of the risk assessment.

Identification of essential transcription factors for adequate DNA damage response after benzo(a)pyrene and aflatoxin B1 exposure by combining transcriptomics with functional genomics

DNA damage mediates widespread changes in transcription through activation or repression of transcription factors (TFs). However, the consequences of regulating specific TFs for the outcome of the DNA repair process remain incompletely understood. Here, we combined transcriptomics and TF binding prediction with functional genomics to identify TFs essential for adequate DNA repair in HepG2 liver cells after a non-cytotoxic dose of carcinogens benzo(a)pyrene (BaP) (2μM) and aflatoxin B1 (AFB1) (5μM). BaP and AFB1 induced a largely common transcriptional response, mediated by similar TFs. A lentiviral shRNA screen knocking down the top31 identified TFs, was performed to determine their effect on DNA repair by assessing phosphorylation of H2AX (γ-H2AX). In addition to the top candidate p53, we identified several other interesting TFs that modulated γ-H2AX after BaP and AFB1 treatment. Validation studies confirmed the role of p53 in reducing γ-H2AX formation and DNA breaks measured by COMET assay after BaP and AFB1 exposure. Expression of the cell cycle inhibitor p21 was profoundly impaired upon p53 knock-down. In addition, the expression of 2 genes involved in nucleotide exchange repair, DDB2 and XPC was significantly reduced in p53 knock-down cells. Although p63 knock-down affected DNA damage upon BaP treatment this was not associated with altered expression of DDB2 or XPC. Finally, knock-down of ARNT reduced γ-H2AX in response to BaP, which was associated with reduced CYP1A1 expression. Importantly, our results suggest a new role for ARNT and its dimerization partner AHR in the occurrence of H2AX phosphorylation after AFB1 treatment. These data show that modulation of TF activity impacts on the repair of BaP- and AFB1-induced DNA damage. Our study also demonstrates the potential of combining functional genomics with genome-wide expression analysis to identify yet unknown causal relationships, thereby aiding in the interpretation of complex biological systems.

The TGx-28.65 biomarker online application for analysis of transcriptomics data to identify DNA damage-inducing chemicals in human cell cultures

The TGx-28.65 biomarker is a 65-gene expression profile generated from testing 28 model chemicals (13 that cause DNA damage and 15 that do not) in human TK6 cells. It is used to predict whether a chemical induces DNA damage or not. We expanded availability to the biomarker by developing the online TGx-28.65 biomarker application for predicting the DNA damage inducing (DDI) potential of suspect toxicants tested in p53-proficient human cells and assessing putative mode(s) of action (MOA). Applications like this that analyse gene expression data to predict the hazard potential of test chemicals hold great promise for risk assessment paradigms. The TGx-28.65 biomarker interfaces with an analytical tool to predict the probability that a test chemical can directly or indirectly induce DNA damage. User submitted in vitro microarray data are compared to the 28-chemical x 65-gene signature profile and the probability that the data fit the profile for a DDI or a non-DDI (NDDI) chemical is calculated. The results are displayed in the Results Table, which includes the classification probability and hyperlinks to view heatmaps, hierarchical clustering, and principal component analyses of user-input data in the context of the reference profile. The heatmaps and cluster plots, along with the corresponding text data files of fold changes in gene expression and Euclidean distances can be downloaded. Review of the test chemical data in relationship to the biomarker allows rapid identification of key gene alterations associated with DNA damage as well as chemicals in the reference set that produced a similar response. Environ. Mol. Mutagen. 58:529-535, 2017. © 2017 Wiley Periodicals, Inc.

Quantitative analysis of gene expression changes in response to genotoxic compounds

Techniques that quantify molecular endpoints sufficiently sensitive to identify and classify potentially toxic compounds have wide potential for high-throughput in vitro screening. Expression of three genes, RAD51C, TP53 and cystatin A (CSTA), in HEPG2 cells was measured by Q-PCR amplification. In parallel, we developed alternative assays for the same 3 gene signature based on an acridinium-ester chemiluminescent reporter molecule. HEPG2 cells were challenged with eighteen different compounds (n=18) chosen to represent compounds that are genotoxic (n=8), non-genotoxic non-carcinogenic (n=2) or have a less well defined mechanism of action with respect to genotoxicity (n=8). At least one of the three genes displayed dysregulated expression in the majority of compounds tested by Q-PCR and ten compounds changed the CSTA expression significantly. Acridinium-ester labelled probes for the three genes were synthesised and tested. Analytical sensitivity was characterised and suggested a limit of detection generally better than 0.1fmol but often 10-50 attomol. A linear amplification step was optimised and this quantitative method detected statistically significant increases in RAD51C and CSTA expression in agreement with the Q-PCR results, demonstrating the potential of this technology. The broad agreement of the amplified chemiluminescent method and Q-PCR in measuring gene expression suggests wider potential application for this chemiluminescent technology.

Toxicogenomics: regulatory perspective on current position

Published studies on the utility of toxicogenomic approaches (transcriptomics, proteomics and metabonomics) in screening for toxicological mechanisms and evaluation of dose response effects have been reviewed. The information supports the use of transcriptomics to screen for specific toxicological mechanisms for which there is an a priori hypothesis, although in some areas such as mutagenicity testing, toxicogenomics appear to have limited value for identifying mutagens. Data from such screening approaches cannot be used to exclude the possibility of toxicity. Targeted transcriptomics might be valuable for screening for specific mechanisms of toxicity considered to be irrelevant for assessing risk to humans, which would help to reduce the need for detailed testing of some chemicals. An integrated approach is suggested where data from more than one toxicogenomic approach could be used as an adjunct to conventional toxicology to assess dose-response in toxicological tests. An outline preliminary proposal for use by regulators is suggested although it is noted that more data are required before this could be formally used in a decision-making process.

Application of the TGx-28.65 transcriptomic biomarker to classify genotoxic and non-genotoxic chemicals in human TK6 cells in the presence of rat liver S9

In vitro transcriptional signatures that predict toxicities can facilitate chemical screening. We previously developed a transcriptomic biomarker (known as TGx-28.65) for classifying agents as genotoxic (DNA damaging) and non-genotoxic in human lymphoblastoid TK6 cells. Because TK6 cells do not express cytochrome P450s, we confirmed accurate classification by the biomarker in cells co-exposed to 1% 5,6 benzoflavone/phenobarbital-induced rat liver S9 for metabolic activation. However, chemicals may require different types of S9 for activation. Here we investigated the response of TK6 cells to higher percentages of Aroclor-, benzoflavone/phenobarbital-, or ethanol-induced rat liver S9 to expand TGx-28.65 biomarker applicability. Transcriptional profiles were derived 3 to 4 hr following a 4 hr co-exposure of TK6 cells to test chemicals and S9. Preliminary studies established that 10% Aroclor- and 5% ethanol-induced S9 alone did not induce the TGx-28.65 biomarker genes. Seven genotoxic and two non-genotoxic chemicals (and concurrent solvent and positive controls) were then tested with one of the S9s (selected based on cell survival and micronucleus induction). Relative survival and micronucleus frequency was assessed by flow cytometry in cells 20 hr post-exposure. Genotoxic/non-genotoxic chemicals were accurately classified using the different S9s. One technical replicate of cells co-treated with dexamethasone and 10% Aroclor-induced S9 was falsely classified as genotoxic, suggesting caution in using high S9 concentrations. Even low concentrations of genotoxic chemicals (those not causing cytotoxicity) were correctly classified, demonstrating that TGx-28.65 is a sensitive biomarker of genotoxicity. A meta-analysis of datasets from 13 chemicals supports that different S9s can be used in TK6 cells, without impairing classification using the TGx-28.65 biomarker.

Inhibitory effect of Camellia sinensis, Ilex paraguariensis and Ardisia compressa tea extracts on the proliferation of human head and neck squamous carcinoma cells

In vitro cell proliferation, cell cycle arrest and induction of apoptosis were investigated, using three human head and neck squamous cell carcinoma (HNSCC) cell lines (OSCC-3, SCC-61, and SQ-20B). Aqueous extracts of Camellia sinensis, Ilex paraguariensis, and Ardisia compressa were tested and (-) epigallocatechin-3-gallate (EGCG) was used for comparison. For EGCG the IC₅₀ values were between 80 and 166 μM and for the extracts among 75 and 505 μM eq. (+) catechin, with C. sinensis demonstrating dominant cytotoxicity. There was not a correlation between antioxidant capacity and cytotoxicity. Flow cytometry analysis revealed similarities in response for EGCG and C. sinensis. The A. compressa extract altered DNA distribution (P < 0.05) and was the most effective in induction of apoptosis via caspases (P < 0.05). Not all HNSCC cells tested responded to the same preventive agents. The fact that A. compressa inhibits HNSCC cell proliferation makes this aqueous extract a potential source of chemopreventive agents.

Integration of metabolic activation with a predictive toxicogenomics signature to classify genotoxic versus nongenotoxic chemicals in human TK6 cells

The use of integrated approaches in genetic toxicology, including the incorporation of gene expression data to determine the molecular pathways involved in the response, is becoming more common. In a companion article, a genomic biomarker was developed in human TK6 cells to classify chemicals as genotoxic or nongenotoxic. Because TK6 cells are not metabolically competent, we set out to broaden the utility of the biomarker for use with chemicals requiring metabolic activation. Specifically, chemical exposures were conducted in the presence of rat liver S9. The ability of the biomarker to classify genotoxic (benzo[a]pyrene, BaP; aflatoxin B1, AFB1) and nongenotoxic (dexamethasone, DEX; phenobarbital, PB) agents correctly was evaluated. Cells were exposed to increasing chemical concentrations for 4 hr and collected 0 hr, 4 hr, and 20 hr postexposure. Relative survival, apoptosis, and micronucleus frequency were measured at 24 hr. Transcriptome profiles were measured with Agilent microarrays. Statistical modeling and bioinformatics tools were applied to classify each chemical using the genomic biomarker. BaP and AFB1 were correctly classified as genotoxic at the mid- and high concentrations at all three time points, whereas DEX was correctly classified as nongenotoxic at all concentrations and time points. The high concentration of PB was misclassified at 24 hr, suggesting that cytotoxicity at later time points may cause misclassification. The data suggest that the use of S9 does not impair the ability of the biomarker to classify genotoxicity in TK6 cells. Finally, we demonstrate that the biomarker is also able to accurately classify genotoxicity using a publicly available dataset derived from human HepaRG cells.

High-throughput in vivo genotoxicity testing: an automated readout system for the somatic mutation and recombination test (SMART)

Genotoxicity testing is an important component of toxicity assessment. As illustrated by the European registration, evaluation, authorization, and restriction of chemicals (REACH) directive, it concerns all the chemicals used in industry. The commonly used in vivo mammalian tests appear to be ill adapted to tackle the large compound sets involved, due to throughput, cost, and ethical issues. The somatic mutation and recombination test (SMART) represents a more scalable alternative, since it uses Drosophila, which develops faster and requires less infrastructure. Despite these advantages, the manual scoring of the hairs on Drosophila wings required for the SMART limits its usage. To overcome this limitation, we have developed an automated SMART readout. It consists of automated imaging, followed by an image analysis pipeline that measures individual wing genotoxicity scores. Finally, we have developed a wing score-based dose-dependency approach that can provide genotoxicity profiles. We have validated our method using 6 compounds, obtaining profiles almost identical to those obtained from manual measures, even for low-genotoxicity compounds such as urethane. The automated SMART, with its faster and more reliable readout, fulfills the need for a high-throughput in vivo test. The flexible imaging strategy we describe and the analysis tools we provide should facilitate the optimization and dissemination of our methods.

Cross-species toxicogenomic analyses and phenotypic anchoring in response to groundwater low-level pollution

Background

Comparison of toxicogenomic data facilitates the identification of deregulated gene patterns and maximizes health risk prediction in human.

Results

Here, we performed phenotypic anchoring on the effects of acute exposure to low-grade polluted groundwater using mouse and zebrafish. Also, we evaluated two windows of chronic exposure in mouse, starting in utero and at the end of lactation. Bioinformatic analysis of livers microarray data showed that the number of deregulated biofunctions and pathways is higher after acute exposure, compared to the chronic one. It also revealed specific profiles of altered gene expression in all treatments, pointing to stress response/mitochondrial pathways as major players of environmental toxicity. Of note, dysfunction of steroid hormones was also predicted by bioinformatic analysis and verified in both models by traditional approaches, serum estrogens measurement and vitellogenin mRNA determination in mice and zebrafish, respectively.

Conclusions

In our report, phenotypic anchoring in two vertebrate model organisms highlights the toxicity of low-grade pollution, with varying susceptibility based on exposure window. The overlay of zebrafish and mice deregulated pathways, more than single genes, is useful in risk identification from chemicals implicated in the observed effects.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-1067) contains supplementary material, which is available to authorized users.

A review on ochratoxin A transcriptomic studies

The mycotoxin Ochratoxin A (OTA) is a potent renal carcinogen in male rats. Transcriptomic studies on OTA (4 in vitro, 6 in vivo, 2 in vitro/in vivo) have been reviewed. The aim of 6 of them was mainly mechanistic whereas the rest had mostly predictive (1) or evaluation (5) purposes. An overall tendency towards gene expression downregulation was observed, probably as a result of protein synthesis inhibition. DNA damage response genes were not deregulated in most of the studies. Genes involved in acute renal injury, cell survival and cell proliferation were upregulated in several in vivo studies. Apoptosis genes were deregulated in vitro but less affected in vivo; activation of several MAPKs has been observed. Many genes related to oxidative stress or involved in cell-to-cell interaction pathways (Wnt) or cytoskeleton structure appeared to be deregulated either in vitro or in vivo. Regucalcin was highly downregulated in vivo and other calcium homeostasis genes were significantly deregulated in vitro. Genes related to OTA transport (OATs) and metabolism (CYPs) appeared downregulated in vivo. Overall, the mechanism of action of OTA remains unclear, however transcriptomic data have contributed to new mechanistic hypothesis generation and to in vitro-in vivo comparison.

Characterization of formaldehyde's genotoxic mode of action by gene expression analysis in TK6 cells

Gene expression analysis has been established as a tool for the characterization of genotoxic mechanisms of chemical mutagens. It has been suggested that expression analysis is capable of distinguishing compounds that cause DNA damage from those that interfere with mitotic spindle function. Formaldehyde (FA) is known to be a DNA-reactive substance which mainly induces chromosomal damage in cultured mammalian cells. However, there has been concern that FA might also induce leukemia-specific aneuploidies, although recent cytogenetic studies excluded a relevant aneugenic potential of FA. We now investigated whether gene expression profiling can be used as a molecular tool to further characterize FA's genotoxic mode of action and to differentiate between clastogenic and aneugenic activity. TK6 cells were exposed to FA for 4 and 24 h, and changes in gene expression were analyzed using a whole-genome human microarray. Results were compared to the expression profiles of two DNA-damaging clastogens (methyl methanesulfonate and ethyl methanesulfonate) and two aneugens (colcemid and vincristine). The genotoxic activity of FA, MMS and EMS under these conditions was confirmed by comet assay experiments. The gene expression profiles indicated that clastogens and aneugens induce discriminable gene expression patterns. Exposure of TK6 cells to FA led to a discrete gene expression pattern, and all toxicogenomics analyses revealed a closer relationship of FA with clastogens than with aneugens.

Effect of chemical mutagens and carcinogens on gene expression profiles in human TK6 cells

Characterization of toxicogenomic signatures of carcinogen exposure holds significant promise for mechanistic and predictive toxicology. In vitro transcriptomic studies allow the comparison of the response to chemicals with diverse mode of actions under controlled experimental conditions. We conducted an in vitro study in TK6 cells to characterize gene expression signatures of exposure to 15 genotoxic carcinogens frequently used in European industries. We also examined the dose-responsive changes in gene expression, and perturbation of biochemical pathways in response to these carcinogens. TK6 cells were exposed at 3 dose levels for 24 h with and without S9 human metabolic mix. Since S9 had an impact on gene expression (885 genes), we analyzed the gene expression data from cells cultures incubated with S9 and without S9 independently. The ribosome pathway was affected by all chemical-dose combinations. However in general, no similar gene expression was observed among carcinogens. Further, pathways, i.e. cell cycle, DNA repair mechanisms, RNA degradation, that were common within sets of chemical-dose combination were suggested by clustergram. Linear trends in dose–response of gene expression were observed for Trichloroethylene, Benz[a]anthracene, Epichlorohydrin, Benzene, and Hydroquinone. The significantly altered genes were involved in the regulation of (anti-) apoptosis, maintenance of cell survival, tumor necrosis factor-related pathways and immune response, in agreement with several other studies. Similarly in S9+ cultures, Benz[a]pyrene, Styrene and Trichloroethylene each modified over 1000 genes at high concentrations. Our findings expand our understanding of the transcriptomic response to genotoxic carcinogens, revealing the alteration of diverse sets of genes and pathways involved in cellular homeostasis and cell cycle control.

A combined DNA-microarray and mechanism-specific toxicity approach with zebrafish embryos to investigate the pollution of river sediments

The zebrafish embryo has repeatedly proved to be a useful model for the analysis of effects by environmental toxicants. This proof-of-concept study was performed to investigate if an approach combining mechanism-specific bioassays with microarray techniques can obtain more in-depth insights into the ecotoxicity of complex pollutant mixtures as present, e.g., in sediment extracts. For this end, altered gene expression was compared to data from established bioassays as well as to results from chemical analysis. Mechanism-specific biotests indicated a defined hazard potential of the sediment extracts, and microarray analysis revealed several classes of significantly regulated genes which could be related to the hazard potential. Results indicate that potential classes of contaminants can be assigned to sediment extracts by both classical biomarker genes and corresponding expression profile analyses of known substances. However, it is difficult to distinguish between specific responses and more universal detoxification of the organism.

Induction of DNA damage signaling genes in benzidine-treated HepG2 cells

We examined genotoxicity and DNA damage response in HepG2 cells following exposure to benzidine. Using the Comet assay, we showed that benzidine (50-200 μM) induces DNA damage in HepG2 cells. DNA damage signaling pathway-based PCR arrays were used to investigate expression changes in genes involved in cell-cycle arrest, apoptosis, and DNA repair and showed upregulation of 23 genes and downregulation of one gene in benzidine-treated cells. Induction of G2/M arrest and apoptosis was confirmed at the protein level. Real-time PCR and Western blots were used to demonstrate the expression of select DNA repair-associated genes from the PCR array. Upregulation of the p53 protein in benzidine-treated cells suggests the induction of the p53 DNA damage signaling pathway. Collectively, DNA damage response genes induced by benzidine indicate recruitment complex molecular machinery involved in DNA repair, cell-cycle arrest, and potentially, activation of the apoptosis.

Large-scale analysis of expression signatures reveals hidden links among diverse cellular processes

Background

Cells must respond to various perturbations using their limited available gene repertoires. In order to study how cells coordinate various responses, we conducted a comprehensive comparison of 1,186 gene expression signatures (gene lists) associated with various genetic and chemical perturbations.

Results

We identified 7,419 statistically significant overlaps between various published gene lists. Most (80%) of the overlaps can be represented by a highly connected network, a "molecular signature map," that highlights the correlation of various expression signatures. By dissecting this network, we identified sub-networks that define clusters of gene sets related to common biological processes (cell cycle, immune response, etc). Examination of these sub-networks has confirmed relationships among various pathways and also generated new hypotheses. For example, our result suggests that glutamine deficiency might suppress cellular growth by inhibiting the MYC pathway. Interestingly, we also observed 1,369 significant overlaps between a set of genes upregulated by factor X and a set of genes downregulated by factor Y, suggesting a repressive interaction between X and Y factors.

Conclusions

Our results suggest that molecular-level responses to diverse chemical and genetic perturbations are heavily interconnected in a modular fashion. Also, shared molecular pathways can be identified by comparing newly defined gene expression signatures with databases of previously published gene expression signatures.

Alternative (non-animal) methods for cosmetics testing: current status and future prospects-2010

The 7th amendment to the EU Cosmetics Directive prohibits to put animal-tested cosmetics on the market in Europe after 2013. In that context, the European Commission invited stakeholder bodies (industry, non-governmental organisations, EU Member States, and the Commission's Scientific Committee on Consumer Safety) to identify scientific experts in five toxicological areas, i.e. toxicokinetics, repeated dose toxicity, carcinogenicity, skin sensitisation, and reproductive toxicity for which the Directive foresees that the 2013 deadline could be further extended in case alternative and validated methods would not be available in time. The selected experts were asked to analyse the status and prospects of alternative methods and to provide a scientifically sound estimate of the time necessary to achieve full replacement of animal testing. In summary, the experts confirmed that it will take at least another 7-9 years for the replacement of the current in vivo animal tests used for the safety assessment of cosmetic ingredients for skin sensitisation. However, the experts were also of the opinion that alternative methods may be able to give hazard information, i.e. to differentiate between sensitisers and non-sensitisers, ahead of 2017. This would, however, not provide the complete picture of what is a safe exposure because the relative potency of a sensitiser would not be known. For toxicokinetics, the timeframe was 5-7 years to develop the models still lacking to predict lung absorption and renal/biliary excretion, and even longer to integrate the methods to fully replace the animal toxicokinetic models. For the systemic toxicological endpoints of repeated dose toxicity, carcinogenicity and reproductive toxicity, the time horizon for full replacement could not be estimated.

New and emerging technologies for genetic toxicity testing

The International Life Sciences Institute (ILSI) Health and Environmental Sciences Institute (HESI) Project Committee on the Relevance and Follow-up of Positive Results in In Vitro Genetic Toxicity (IVGT) Testing established an Emerging Technologies and New Strategies Workgroup to review the current State of the Art in genetic toxicology testing. The aim of the workgroup was to identify promising technologies that will improve genotoxicity testing and assessment of in vivo hazard and risk, and that have the potential to help meet the objectives of the IVGT. As part of this initiative, HESI convened a workshop in Washington, DC in May 2008 to discuss mature, maturing, and emerging technologies in genetic toxicology. This article collates the abstracts of the New and Emerging Technologies Workshop together with some additional technologies subsequently considered by the workgroup. Each abstract (available in the online version of the article) includes a section addressed specifically to the strengths, weaknesses, opportunities, and threats associated with the respective technology. Importantly, an overview of the technologies and an indication of how their use might be aligned with the objectives of IVGT are presented. In particular, consideration was given with regard to follow-up testing of positive results in the standard IVGT tests (i.e., Salmonella Ames test, chromosome aberration assay, and mouse lymphoma assay) to add weight of evidence and/or provide mechanism of action for improved genetic toxicity risk assessments in humans.

Altered gene expression and DNA damage in peripheral blood cells from Friedreich's ataxia patients: cellular model of pathology

The neurodegenerative disease Friedreich's ataxia (FRDA) is the most common autosomal-recessively inherited ataxia and is caused by a GAA triplet repeat expansion in the first intron of the frataxin gene. In this disease, transcription of frataxin, a mitochondrial protein involved in iron homeostasis, is impaired, resulting in a significant reduction in mRNA and protein levels. Global gene expression analysis was performed in peripheral blood samples from FRDA patients as compared to controls, which suggested altered expression patterns pertaining to genotoxic stress. We then confirmed the presence of genotoxic DNA damage by using a gene-specific quantitative PCR assay and discovered an increase in both mitochondrial and nuclear DNA damage in the blood of these patients (p<0.0001, respectively). Additionally, frataxin mRNA levels correlated with age of onset of disease and displayed unique sets of gene alterations involved in immune response, oxidative phosphorylation, and protein synthesis. Many of the key pathways observed by transcription profiling were downregulated, and we believe these data suggest that patients with prolonged frataxin deficiency undergo a systemic survival response to chronic genotoxic stress and consequent DNA damage detectable in blood. In conclusion, our results yield insight into the nature and progression of FRDA, as well as possible therapeutic approaches. Furthermore, the identification of potential biomarkers, including the DNA damage found in peripheral blood, may have predictive value in future clinical trials.

Estimation of gene induction enables a relevance-based ranking of gene sets

In order to handle and interpret the vast amounts of data produced by microarray experiments, the analysis of sets of genes with a common biological functionality has been shown to be advantageous compared to single gene analyses. Some statistical methods have been proposed to analyse the differential gene expression of gene sets in microarray experiments. However, most of these methods either require threshhold values to be chosen for the analysis, or they need some reference set for the determination of significance. We present a method that estimates the number of differentially expressed genes in a gene set without requiring a threshold value for significance of genes. The method is self-contained (i.e., it does not require a reference set for comparison). In contrast to other methods which are focused on significance, our approach emphasizes the relevance of the regulation of gene sets. The presented method measures the degree of regulation of a gene set and is a useful tool to compare the induction of different gene sets and place the results of microarray experiments into the biological context. An R-package is available.

Characterization and interlaboratory comparison of a gene expression signature for differentiating genotoxic mechanisms

The genotoxicity testing battery is highly sensitive for detection of chemical carcinogens. However, it features a low specificity and provides only limited mechanistic information required for risk assessment of positive findings. This is especially important in case of positive findings in the in vitro chromosome damage assays, because chromosome damage may be also induced secondarily to cell death. An increasing body of evidence indicates that toxicogenomic analysis of cellular stress responses provides an insight into mechanisms of action of genotoxicants. To evaluate the utility of such a toxicogenomic analysis we evaluated gene expression profiles of TK6 cells treated with four model genotoxic agents using a targeted high density real-time PCR approach in a multilaboratory project coordinated by the Health and Environmental Sciences Institute Committee on the Application of Genomics in Mechanism-based Risk Assessment. We show that this gene profiling technology produced reproducible data across laboratories allowing us to conclude that expression analysis of a relevant gene set is capable of distinguishing compounds that cause DNA adducts or double strand breaks from those that interfere with mitotic spindle function or that cause chromosome damage as a consequence of cytotoxicity. Furthermore, our data suggest that the gene expression profiles at early time points are most likely to provide information relevant to mechanisms of genotoxic damage and that larger gene expression arrays will likely provide richer information for differentiating molecular mechanisms of action of genotoxicants. Although more compounds need to be tested to identify a robust molecular signature, this study confirms the potential of toxicogenomic analysis for investigation of genotoxic mechanisms.

Simultaneous application of t-test and fold change criteria to identify acetaminophen and carbon tetrachloride affected genes in mice liver

t-Test and fold change criteria were employed simultaneously following acute exposure to acetaminophen and carbon tetrachloride to provide high statistical confidence in the identification of affected genes in mice livers. Furthermore, gene expression data was also investigated with either t-test or fold change criteria alone. Gene expression studies were also accompanied by liver histological and serum biochemical studies for toxicity evaluation. We identified a large number of affected genes using both filtering criteria (p<0.01 and twofold) simultaneously following both the hepatotoxicants. In some cases gene expression studies provided the earliest evidence of tissue response in the absence of traditional markers at histological and biochemical level. We conclude that simultaneous application of t-test and fold change criteria helps to identify important genes with greater statistical confidence than the use of either of them alone, however, this approach results in the reduction of identified probes. Thus, data analysis at different statistical stringencies is needed to know exact outcome of any toxicological event.

A genomic "roadmap" to "better" drugs

Utilization of pharmacogenomic information has the potential to significantly improve treatment outcome and markedly reduce the rate of attrition of drugs in clinical development. A major gap that limits our ability to utilize pharmacogenomic information in drug discovery, drug development or clinical practice is that we often do not know the genetic variants responsible for inter-individual differences in drug metabolism or drug response. We examine emerging genomic methods that can fill this gap; these methods can be used to generate new information about drug metabolism or mechanism of action, or to identify predictors of drug response. Although they have not yet had their full impact, a wider application of these emerging genomic technologies has the potential to significantly improve the safety of drugs, the quality of patient care and the efficiency of clinical drug development.

The application of discovery toxicology and pathology towards the design of safer pharmaceutical lead candidates

Toxicity is a leading cause of attrition at all stages of the drug development process. The majority of safety-related attrition occurs preclinically, suggesting that approaches to identify 'predictable' preclinical safety liabilities earlier in the drug development process could lead to the design and/or selection of better drug candidates that have increased probabilities of becoming marketed drugs. In this Review, we discuss how the early application of preclinical safety assessment--both new molecular technologies as well as more established approaches such as standard repeat-dose rodent toxicology studies--can identify predictable safety issues earlier in the testing paradigm. The earlier identification of dose-limiting toxicities will provide chemists and toxicologists the opportunity to characterize the dose-limiting toxicities, determine structure-toxicity relationships and minimize or circumvent adverse safety liabilities.

Characterization of DNA reactive and non-DNA reactive anticancer drugs by gene expression profiling

Gene expression profiling technology is expected to advance our understanding of genotoxic mechanisms involving direct or indirect interaction with DNA. We exposed human lymphoblastoid TK6 cells to 14 anticancer drugs (vincristine, paclitaxel, etoposide, daunorubicin, camptothecin, amsacrine, cytosine arabinoside, hydroxyurea, methotrexate, 5-fluorouracil, cisplatin, 1-(2-chloroethyl)-3-cyclohexyl-1-nitrosourea (CCNU), 1,3-bis (2-chloroethyl)-1-nitrosourea (BCNU), and bleomycin) for 4-h and examined them immediately or after a 20-h recovery period. Cytotoxicity and genotoxicity, respectively, were evaluated by cell counting and by in vitro micronucleus assay at 24h. Effects on the cell cycle were determined by flow cytometry at 4 and 24h. Gene expression was profiled at both sampling times by using human Affymetrix U133A GeneChips (22K). Bioanalysis was done with Resolver/Rosetta software and an in-house annotation program. Cell cycle analysis and gene expression profiling allowed us to classify the drugs according to their mechanisms of action. The molecular signature is composed of 28 marker genes mainly involved in signal transduction and cell cycle pathways. Our results suggest that these marker genes could be used as a predictive model to classify genotoxins according to their direct or indirect interaction with DNA.

Application of toxicogenomics to genetic toxicology risk assessment

Based on the assumption that compounds having similar toxic modes of action induce specific gene expression changes, the toxicity of unknown compounds can be predicted after comparison of their molecular fingerprints with those obtained with compounds of known toxicity. These predictive models will therefore rely on the characterization of marker genes. Toxicogenomics (TGX) also provides mechanistic insight into the mode of toxicity, and can therefore be used as an adjunct to the standard battery of genotoxicity tests. Promising results, highlighting the ability of TGX to differentiate genotoxic from non-genotoxic carcinogens, as well as DNA-reactive from non-DNA reactive genotoxins, have been reported. Additional data suggested the possibility of ranking genotoxins according to the nature of their interactions with DNA. This new approach could contribute to the improvement of risk assessment. TGX could be applied as a follow-up testing strategy in case of positive in vitro genotoxicity findings, and could contribute to improve our ability to identify the molecular mechanism of action and to possibly better assess dose-response curves. TGX has been found to be less sensitive than the standard genotoxicity end-points, probably because it measures the whole cell population response, when compared with standard tests designed to detect rare events in a small number of cells. Further validation will be needed (1) to better link the profiles obtained with TGX to the established genotoxicity end-points, (2) to improve the gene annotation tools, and (3) to standardise study design and data analysis and to better evaluate the impact of variability between platforms and bioinformatics approaches.

Toxicogenomics: overview and potential applications for the study of non-covalent DNA interacting chemicals

Non-covalent DNA interacting agents, DNA-groove binding chemicals and DNA intercalators, are generally considered less cytotoxic than agents producing covalent DNA adducts and other DNA damage. Although the impact of non-covalent compound-DNA interactions on convoluted molecular and biochemical pathways is not well characterized, the most prominent effects include DNA conformational and related structural perturbations, interference with normal DNA protein interactions, such as topoisomerases, as well as effects on mitochondrial DNA and function. The cellular responses to such perturbations would be expected to include changes in transcription of a variety of genes. The emerging field of toxicogenomics seeks to exploit gene responses to define expression profiling signatures for various types of drugs and toxicants, and to provide mechanistic insight into their cellular effects. There are a variety of examples whereby different classes of genotoxicants and non-genotoxic agents can be distinguished by gene expression profiling using functional genomics approaches, which survey global transcriptional responses. In this review, we will discuss the promises and precautions in the use of functional genomics approaches to characterize stress agents including non-covalent DNA interacting agents.

In vitro gene expression data supporting a DNA non-reactive genotoxic mechanism for ochratoxin A

Ochratoxin A (OTA) is a mycotoxin often found in cereals and agricultural products. There is unequivocal evidence of renal carcinogenicity of OTA in male rats, although the mechanism of action is unknown. At present, available data support an epigenetic mechanism (DNA non-reactive) resulting from oxidative stress and cytotoxicity, because a direct OTA interaction with DNA has not been demonstrated. Genotoxic mechanism (DNA-reactive vs. DNA non-reactive) may have implications on human risk assessment. Therefore, the aim of the present work was to identify biological pathways modulated by OTA in vitro in a human renal cell line (HK-2) to contribute to the elucidation of the mechanism of OTA toxicity. For that purpose, cells were exposed to 50 microM OTA during 6 and 24 h, and gene expression profiles were analyzed using Affymetrix Human Genome U133 A 2.0 Gene Chips. Under the same experimental conditions, genotoxicity was evaluated by the modified comet assay using FPG and Endo III to detect oxidative DNA damage, and intracellular ROS level by the H(2)DCF assay. After 6 h, with slight cytotoxicity (83% survival), genes involved in mitochondrial electron transport chain were up-regulated; and after 24 h, with a more pronounced cytotoxicity (51% survival), genes implicated in oxidative stress response were also up-regulated. Increase in intracellular ROS level and oxidative DNA damage was evident at both exposure times being more pronounced with high cytotoxicity. On the contrary, up-regulation of genes implicated in DNA damage response, as cell cycle control or apoptosis, was not detected at any exposure time. In conclusion, these results support a DNA non-reactive mechanism of OTA genotoxicity.

Toxicogenomics: a pivotal piece in the puzzle of toxicological research

Toxicogenomics, resulting from the merge of conventional toxicology with functional genomics, being the scientific field studying the complex interactions between the cellular genome, toxic agents in the environment, organ dysfunction and disease state. When an organism is exposed to a toxic agent the cells respond by altering the pattern of gene expression. Genes are transcribed into mRNA, which in turn is translated into proteins that serve in a variety of cellular functions. Toxicogenomics through microarray technology, offers large-scale detection and quantification of mRNA transcripts, related to alterations in mRNA stability or gene regulation. This may prove advantageous in toxicological research. In the present review, the applications of toxicogenomics, especially to mechanistic and predictive toxicology are reported. The limitations arising from the use of this technology are also discussed. Additionally, a brief report of other approaches, using other -omic technologies (proteomics and metabonomics) that overcome limitations and give global information related to toxicity, is included.

Modulation of gene expression and DNA-adduct formation in precision-cut liver slices exposed to polycyclic aromatic hydrocarbons of different carcinogenic potency

Polycyclic aromatic hydrocarbons (PAHs) differ markedly in their carcinogenic potencies. Differences in transcriptomic responses upon PAH exposures might improve our current understanding of the differences in carcinogenicity, and therefore gene expression modulation by six PAHs in precision-cut rat liver slices was investigated. Gene expression modulation by benzo[a]pyrene (B[a]P), dibenzo[a,l]pyrene (DB[a,l]P), benzo[b]fluoranthene (B[b]F), fluoranthene (FA), dibenzo[a,h]anthracene (DB[a,h]A) and 1-methylphenanthrene (1-MPA) was assessed after 6- (B[a]P, DB[a,l]P) and 24-h (all compounds) exposure, using oligonucleotide arrays. DNA-adduct formation was determined using (32)P-post-labelling. The effects of PAHs on gene expression and on DNA-adduct formation were much more pronounced after 24-h exposure than after a 6-h exposure. Each compound induced gene expression changes dose-dependently and gene expression profiles were generally compound-specific. B[a]P, B[b]F and DB[a,h]A displayed comparable gene expression profiles, and so did DB[a,l]P, FA and 1-MPA. Only the carcinogenic PAHs (B[a]P, B[b]F, DB[a,l]P and DB[a,h]A) induced the oxidative stress pathway. DNA-adduct levels were: DB[a,l]P >> B[a]P > B[b]F > or = DB[a,h]A > FA > or = 1-MPA. The expression of only a few genes was found to correlate significantly with DNA-adduct formation, carcinogenic potency or Ah-receptor binding capacity (the last two taken from literature). These genes differed between the parameters. Our results indicate that PAHs generally induce a compound-specific response on gene expression and that discrimination of carcinogenic from non-carcinogenic compounds is partly feasible using this approach. Only at a specific pathway level, namely oxidative stress response, PAHs with high and low carcinogenic potency could be discriminated.

Genotoxicants target distinct molecular networks in neonatal neurons

BACKGROUND

Exposure of the brain to environmental agents during critical periods of neuronal development is considered a key factor underlying many neurologic disorders.

OBJECTIVES

In this study we examined the influence of genotoxicants on cerebellar function during early development by measuring global gene expression changes.

METHODS

We measured global gene expression in immature cerebellar neurons (i.e., granule cells) after treatment with two distinct alkylating agents, methylazoxymethanol (MAM) and nitrogen mustard (HN2). Granule cell cultures were treated for 24 hr with MAM (10-1,000 microM) or HN2 (0.1-20 microM) and examined for cell viability, DNA damage, and markers of apoptosis.

RESULTS

Neuronal viability was significantly reduced (p < 0.01) at concentrations > 500 microM for MAM and > 1.0 microM for HN2; this correlated with an increase in both DNA damage and markers of apoptosis. Neuronal cultures treated with sublethal concentrations of MAM (100 microM) or HN2 (1.0 microM) were then examined for gene expression using large-scale mouse cDNA microarrays (27,648). Gene expression results revealed that a) global gene expression was predominantly up-regulated by both genotoxicants; b) the number of down-regulated genes was approximately 3-fold greater for HN2 than for MAM; and c) distinct classes of molecules were influenced by MAM (i.e, neuronal differentiation, the stress and immune response, and signal transduction) and HN2 (i.e, protein synthesis and apoptosis).

CONCLUSIONS

These studies demonstrate that individual genotoxicants induce distinct gene expression signatures. Further study of these molecular networks may explain the variable response of the developing brain to different types of environmental genotoxicants.

High-specificity and high-sensitivity genotoxicity assessment in a human cell line: Validation of the GreenScreen HC GADD45a-GFP genotoxicity assay

The battery of genetic toxicity tests required by most regulatory authorities includes both bacterial and mammalian cell assays and identifies practically all genotoxic carcinogens. However, the relatively high specificity of the Salmonella mutagenicity assay (Ames test) is offset by the low specificity of the established mammalian cell assays, which leads to difficulties in the interpretation of the biological relevance of results. This paper describes a new high-throughput assay that links the regulation of the human GADD45a gene to the production of Green Fluorescent Protein (GFP). A study of 75 well-characterised genotoxic and non-genotoxic compounds with diverse mechanisms of DNA-damage induction (including aneugens) reveals that the assay responds positively to all classes of genotoxic damage with both high specificity and high sensitivity. The current micro-well assay format does not include metabolic activation, but a separate low-throughput protocol demonstrates a successful proof-of-principle for an S9 metabolic activation assay with the model pro-mutagen cyclophosphamide. The test should be of value both as a tool in the selection of candidate compounds for further development, where additional data may be required because of conflicting information from the in vitro test battery, or in product development areas where the use of animals is to be discontinued. As a microplate assay however, it has the qualities of high throughput and low compound use that will facilitate its application in early screening for genotoxic liability.

Predictive value of in vitro safety studies

The predictive value of in vitro safety studies is discussed for three important areas of pharmaceutical safety evaluations. In genetic toxicology, currently assays are sensitive for the prediction of cancer, but their overall predictive value is strongly diminished because of their low specificity. In the area of safety pharmacology blockage of hERG channel in vitro has recently been introduced to predict cardiac repolarization delay (QT interval prolongation) in patients. There is a plethora of in vitro methods to predict and characterize liver toxicity. However, little data is available that demonstrate a reliable prediction for hepatotoxicity in vivo over a wide range of chemical structures. In all three areas, further improvements are needed. 'Omics' technologies and new cell lines derived from stem cells are expected to strongly contribute to establish new and more predictive in vitro assays.