A novel toxicogenomics-based approach to categorize (non-)genotoxic carcinogens

Progress in toxicogenomics to protect human health

Toxicogenomics measures molecular features, such as transcripts, proteins, metabolites and epigenomic modifications, to understand and predict the toxicological effects of environmental and pharmaceutical exposures. Transcriptomics has become an integral tool in contemporary toxicology research owing to innovations in gene expression profiling that can provide mechanistic and quantitative information at scale. These data can be used to predict toxicological hazards through the use of transcriptomic biomarkers, network inference analyses, pattern-matching approaches and artificial intelligence. Furthermore, emerging approaches, such as high-throughput dose-response modelling, can leverage toxicogenomic data for human health protection even in the absence of predicting specific hazards. Finally, single-cell transcriptomics and multi-omics provide detailed insights into toxicological mechanisms. Here, we review the progress since the inception of toxicogenomics in applying transcriptomics towards toxicology testing and highlight advances that are transforming risk assessment.

Systematic transcriptome-wide meta-analysis across endocrine disrupting chemicals reveals shared and unique liver pathways, gene networks, and disease associations

Cardiometabolic disorders (CMD) are a growing public health problem across the world. Among the known cardiometabolic risk factors are compounds that induce endocrine and metabolic dysfunctions, such as endocrine disrupting chemicals (EDCs). To date, how EDCs influence molecular programs and cardiometabolic risks has yet to be fully elucidated, especially considering the complexity contributed by species-, chemical-, and dose-specific effects. Moreover, different experimental and analytical methodologies employed by different studies pose challenges when comparing findings across studies. To explore the molecular mechanisms of EDCs in a systematic manner, we established a data-driven computational approach to meta-analyze 30 human, mouse, and rat liver transcriptomic datasets for 4 EDCs, namely bisphenol A (BPA), bis(2-ethylhexyl) phthalate (DEHP), tributyltin (TBT), and perfluorooctanoic acid (PFOA). Our computational pipeline uniformly re-analyzed pre-processed quality-controlled microarray data and raw RNAseq data, derived differentially expressed genes (DEGs) and biological pathways, modeled gene regulatory networks and regulators, and determined CMD associations based on gene overlap analysis. Our approach revealed that DEHP and PFOA shared stable transcriptomic signatures that are enriched for genes associated with CMDs, suggesting similar mechanisms of action such as perturbations of peroxisome proliferator-activated receptor gamma (PPARγ) signaling and liver gene network regulators VNN1 and ACOT2. In contrast, TBT exhibited highly divergent gene signatures, pathways, network regulators, and disease associations from the other EDCs. In addition, we found that the rat, mouse, and human BPA studies showed highly variable transcriptomic patterns, providing molecular support for the variability in BPA responses. Our work offers insights into the commonality and differences in the molecular mechanisms of various EDCs and establishes a streamlined data-driven workflow to compare molecular mechanisms of environmental substances to elucidate the underlying connections between chemical exposure and disease risks.

Comparative Analysis of Transcriptional Responses to Genotoxic and Non-Genotoxic Agents in the Blood Cell Model TK6 and the Liver Model HepaRG

Transcript signatures are a promising approach to identify and classify genotoxic and non-genotoxic compounds and are of interest as biomarkers or for future regulatory application. Not much data, however, is yet available about the concordance of transcriptional responses in different cell types or tissues. Here, we analyzed transcriptomic responses to selected genotoxic food contaminants in the human p53-competent lymphoblastoid cell line TK6 using RNA sequencing. Responses to treatment with five genotoxins, as well as with four non-genotoxic liver toxicants, were compared with previously published gene expression data from the human liver cell model HepaRG. A significant overlap of the transcriptomic changes upon genotoxic stress was detectable in TK6 cells, whereas the comparison with the HepaRG model revealed considerable differences, which was confirmed by bioinformatic data mining for cellular upstream regulators or pathways. Taken together, the study presents a transcriptomic signature for genotoxin exposure in the human TK6 blood cell model. The data demonstrate that responses in different cell models have considerable variations. Detection of a transcriptomic genotoxin signature in blood cells indicates that gene expression analyses of blood samples might be a valuable approach to also estimate responses to toxic exposure in target organs such as the liver.

Identification of key genes and pathways between mild-moderate and severe asthmatics via bioinformatics analysis

Severe asthma is the main reason for death and disability caused by asthma. However, effective biomarkers for severe asthma have not been identified. Here, we aimed to identify potential biomarkers in severe asthma. We identified 202 differentially expressed genes (DEGs) between severe asthma and mild-moderate asthma after integrating the results from GSE69683 and GSE27011 datasets. The enrichment analysis indicated that 202 DEGs were associated with metabolism- and immune-related processes. 10 hub genes were identified by Cytoscape and five of these genes’ AUC (area under the curve) values were greater than 0.6 in GSE69683. The AUC value reached to 0.701 when combined SEC61A1 and ALDH18A1 expression. The expression of the five hub genes was verified in an external dataset. The network analysis revealed that transcription factor (TF) WT1, ZEB1, RERE, FOSL1, and miR-20a may be involved in the development of asthma. In addition, we found cyclosporine and acetaminophen could interact with these hub genes and may be negatively associated with most of the five hub genes according to previous reports. Overall, key genes were identified between mild-moderate and severe asthmatics, which contributed to the understanding of the development of asthma.

Integration of Epigenetic Mechanisms into Non-Genotoxic Carcinogenicity Hazard Assessment: Focus on DNA Methylation and Histone Modifications

Epigenetics involves a series of mechanisms that entail histone and DNA covalent modifications and non-coding RNAs, and that collectively contribute to programing cell functions and differentiation. Epigenetic anomalies and DNA mutations are co-drivers of cellular dysfunctions, including carcinogenesis. Alterations of the epigenetic system occur in cancers whether the initial carcinogenic events are from genotoxic (GTxC) or non-genotoxic (NGTxC) carcinogens. NGTxC are not inherently DNA reactive, they do not have a unifying mode of action and as yet there are no regulatory test guidelines addressing mechanisms of NGTxC. To fil this gap, the Test Guideline Programme of the Organisation for Economic Cooperation and Development is developing a framework for an integrated approach for the testing and assessment (IATA) of NGTxC and is considering assays that address key events of cancer hallmarks. Here, with the intent of better understanding the applicability of epigenetic assays in chemical carcinogenicity assessment, we focus on DNA methylation and histone modifications and review: (1) epigenetic mechanisms contributing to carcinogenesis, (2) epigenetic mechanisms altered following exposure to arsenic, nickel, or phenobarbital in order to identify common carcinogen-specific mechanisms, (3) characteristics of a series of epigenetic assay types, and (4) epigenetic assay validation needs in the context of chemical hazard assessment. As a key component of numerous NGTxC mechanisms of action, epigenetic assays included in IATA assay combinations can contribute to improved chemical carcinogen identification for the better protection of public health.

Biomarkers of effect as determined in human biomonitoring studies on hexavalent chromium and cadmium in the period 2008-2020

A number of human biomonitoring (HBM) studies have presented data on exposure to hexavalent chromium [Cr(VI)] and cadmium (Cd), but comparatively few include results on effect biomarkers. The latter are needed to identify associations between exposure and adverse outcomes (AOs) in order to assess public health implications. To support improved derivation of EU regulation and policy making, it is of great importance to identify the most reliable effect biomarkers for these heavy metals that can be used in HBM studies. In the framework of the Human Biomonitoring for Europe (HBM4EU) initiative, our study aim was to identify effect biomarkers linking Cr(VI) and Cd exposure to selected AOs including cancer, immunotoxicity, oxidative stress, and omics/epigenetics. A comprehensive PubMed search identified recent HBM studies, in which effect biomarkers were examined. Validity and applicability of the markers in HBM studies are discussed. The most frequently analysed effect biomarkers regarding Cr(VI) exposure and its association with cancer were those indicating oxidative stress (e.g., 8-hydroxy-2'-deoxyguanosine (8-OHdG), malondialdehyde (MDA), glutathione (GSH)) and DNA or chromosomal damage (comet and micronucleus assays). With respect to Cd and to some extent Cr, β-2-microglobulin (B2-MG) and N-acetyl-β-D-glucosaminidase (NAG) are well-established, sensitive, and the most common effect biomarkers to relate Cd or Cr exposure to renal tubular dysfunction. Neutrophil gelatinase-associated lipocalin (NGAL) and kidney injury molecule (KIM)-1 could serve as sensitive biomarkers of acute kidney injury in response to both metals, but need further investigation in HBM studies. Omics-based biomarkers, i.e., changes in the (epi-)genome, transcriptome, proteome, and metabolome associated with Cr and/or Cd exposure, are promising effect biomarkers, but more HBM data are needed to confirm their significance. The combination of established effect markers and omics biomarkers may represent the strongest approach, especially if based on knowledge of mechanistic principles. To this aim, also mechanistic data were collected to provide guidance on the use of more sensitive and specific effect biomarkers. This also led to the identification of knowledge gaps relevant to the direction of future research.

Mode of action assessment of the genotoxic properties of antimony and its compounds evaluated in the ToxTracker assay

Antimony (Sb) and its compounds are negative in gene mutation assays in bacteria and cultured mammalian cells but positive in some assays for clastogenicity and/or DNA damage. In order to better understand the modes of action for antimony genotoxicity, we assessed reporter gene activation by antimony and antimony compounds in the new expanded ToxTracker assay. ToxTracker evaluates the activation of biomarkers for different cellular defense mechanisms using a series of green fluorescent protein reporters inserted into mouse embryonic stem cell lines. The assay responds to: 1) DNA damage and inhibition of DNA replication; 2) oxidative stress; 3) unfolded protein response (protein damage); and 4) p53-dependent cellular stress. Sb metal powder, six trivalent (Sb(III)) compounds, and five pentavalent antimony (Sb(V)) compounds were assessed. Sb powder and all six Sb(III) compounds activated oxidative stress ToxTracker reporters at non-toxic doses. Of the five Sb(V) compounds, antimony pentachloride and potassium hexahydroantimonate induced a robust oxidative stress response while sodium antimonate induced only a weak oxidative stress response. At higher concentrations (up to either 75 % toxicity or the highest dissolved concentration tested), Sb powder and all Sb(III) compounds except for antimony trichloride induced the unfolded protein response. Of the five Sb(V) compounds tested, only potassium hexahydroantimonate induced weak activation of the unfolded protein response and was also the only pentavalent compound to yield modest (30 %) cytotoxicity. None of the compounds tested activated the DNA damage/inhibition of DNA replication reporters, nor did they activate the p53-dependent response. All Sb(III) compounds, Sb powder, and three of the five Sb(V) compounds activated the oxidative stress reporters, but there was no activation of reporters associated with DNA damage and repair or p53-dependent cellular stress. The consistent activation of reporters for oxidative stress suggests this mode of action may underlie genotoxicity responses for antimony and its compounds.

Relevance of In Vitro Transcriptomics for In Vivo Mode of Action Assessment

Recently, we reported an in vitro toxicogenomics comparison approach to categorize chemical substances according to similarities in their proposed toxicological modes of action. Use of such an approach for regulatory purposes requires, among others, insight into the extent of biological concordance between in vitro and in vivo findings. To that end, we applied the comparison approach to transcriptomics data from the Open TG-GATEs database for 137 substances with diverging modes of action and evaluated the outcomes obtained for rat primary hepatocytes and for rat liver. The results showed that a relatively small number of matches observed in vitro were also observed in vivo, whereas quite a large number of matches between substances were found to be relevant solely in vivo or in vitro. The latter could not be explained by physicochemical properties, leading to insufficient bioavailability or poor water solubility. Nevertheless, pathway analyses indicated that for relevant matches the mechanisms perturbed in vitro are consistent with those perturbed in vivo. These findings support the utility of the comparison approach as tool in mechanism-based risk assessment.

Chemical carcinogen safety testing: OECD expert group international consensus on the development of an integrated approach for the testing and assessment of chemical non-genotoxic carcinogens

While regulatory requirements for carcinogenicity testing of chemicals vary according to product sector and regulatory jurisdiction, the standard approach starts with a battery of genotoxicity tests (which include mutagenicity assays). If any of the in vivo genotoxicity tests are positive, a lifetime rodent cancer bioassay may be requested, but under most chemical regulations (except plant protection, biocides, pharmaceuticals), this is rare. The decision to conduct further testing based on genotoxicity test outcomes creates a regulatory gap for the identification of non-genotoxic carcinogens (NGTxC). With the objective of addressing this gap, in 2016, the Organization of Economic Cooperation and Development (OECD) established an expert group to develop an integrated approach to the testing and assessment (IATA) of NGTxC. Through that work, a definition of NGTxC in a regulatory context was agreed. Using the adverse outcome pathway (AOP) concept, various cancer models were developed, and overarching mechanisms and modes of action were identified. After further refining and structuring with respect to the common hallmarks of cancer and knowing that NGTxC act through a large variety of specific mechanisms, with cell proliferation commonly being a unifying element, it became evident that a panel of tests covering multiple biological traits will be needed to populate the IATA. Consequently, in addition to literature and database investigation, the OECD opened a call for relevant assays in 2018 to receive suggestions. Here, we report on the definition of NGTxC, on the development of the overarching NGTxC IATA, and on the development of ranking parameters to evaluate the assays. Ultimately the intent is to select the best scoring assays for integration in an NGTxC IATA to better identify carcinogens and reduce public health hazards.

Identification of Time-Invariant Biomarkers for Non-Genotoxic Hepatocarcinogen Assessment

Non-genotoxic hepatocarcinogens (NGHCs) can only be confirmed by 2-year rodent studies. Toxicogenomics (TGx) approaches using gene expression profiles from short-term animal studies could enable early assessment of NGHCs. However, high variance in the modulation of the genes had been noted among exposure styles and datasets. Expanding from our previous strategy in identifying consensus biomarkers in multiple experiments, we aimed to identify time-invariant biomarkers for NGHCs in short-term exposure styles and validate their applicability to long-term exposure styles. In this study, nine time-invariant biomarkers, namely A2m, Akr7a3, Aqp7, Ca3, Cdc2a, Cdkn3, Cyp2c11, Ntf3, and Sds, were identified from four large-scale microarray datasets. Machine learning techniques were subsequently employed to assess the prediction performance of the biomarkers. The biomarker set along with the Random Forest models gave the highest median area under the receiver operating characteristic curve (AUC) of 0.824 and a low interquartile range (IQR) variance of 0.036 based on a leave-one-out cross-validation. The application of the models to the external validation datasets achieved high AUC values of greater than or equal to 0.857. Enrichment analysis of the biomarkers inferred the involvement of chronic inflammatory diseases such as liver cirrhosis, fibrosis, and hepatocellular carcinoma in NGHCs. The time-invariant biomarkers provided a robust alternative for NGHC prediction.

Mode of action-based risk assessment of genotoxic carcinogens

The risk assessment of chemical carcinogens is one major task in toxicology. Even though exposure has been mitigated effectively during the last decades, low levels of carcinogenic substances in food and at the workplace are still present and often not completely avoidable. The distinction between genotoxic and non-genotoxic carcinogens has traditionally been regarded as particularly relevant for risk assessment, with the assumption of the existence of no-effect concentrations (threshold levels) in case of the latter group. In contrast, genotoxic carcinogens, their metabolic precursors and DNA reactive metabolites are considered to represent risk factors at all concentrations since even one or a few DNA lesions may in principle result in mutations and, thus, increase tumour risk. Within the current document, an updated risk evaluation for genotoxic carcinogens is proposed, based on mechanistic knowledge regarding the substance (group) under investigation, and taking into account recent improvements in analytical techniques used to quantify DNA lesions and mutations as well as "omics" approaches. Furthermore, wherever possible and appropriate, special attention is given to the integration of background levels of the same or comparable DNA lesions. Within part A, fundamental considerations highlight the terms hazard and risk with respect to DNA reactivity of genotoxic agents, as compared to non-genotoxic agents. Also, current methodologies used in genetic toxicology as well as in dosimetry of exposure are described. Special focus is given on the elucidation of modes of action (MOA) and on the relation between DNA damage and cancer risk. Part B addresses specific examples of genotoxic carcinogens, including those humans are exposed to exogenously and endogenously, such as formaldehyde, acetaldehyde and the corresponding alcohols as well as some alkylating agents, ethylene oxide, and acrylamide, but also examples resulting from exogenous sources like aflatoxin B1, allylalkoxybenzenes, 2-amino-3,8-dimethylimidazo[4,5-f] quinoxaline (MeIQx), benzo[a]pyrene and pyrrolizidine alkaloids. Additionally, special attention is given to some carcinogenic metal compounds, which are considered indirect genotoxins, by accelerating mutagenicity via interactions with the cellular response to DNA damage even at low exposure conditions. Part C finally encompasses conclusions and perspectives, suggesting a refined strategy for the assessment of the carcinogenic risk associated with an exposure to genotoxic compounds and addressing research needs.

Pathway-based assessment of single chemicals and mixtures by a high-throughput transcriptomics approach

The ever-increasing number of chemicals and complex mixtures demands a high-throughput and cost-effective approach for chemical safety assessment. High-throughput transcriptomics (HTT) is promising in investigating genome-scale perturbation of chemical exposure in concentration-dependent manner. However, the application of HTT has been limited due to lack of methodology for single chemicals and mixture assessment. This study aimed to evaluate the ability of a newly-developed human reduced transcriptomics (RHT) approach to assess pathway-based profiles of single chemicals, and to develop a biological pathway-based approach for benchmarking mixture potency using single chemical-based prediction model. First, concentration-dependent RHT were used to qualitatively and quantitatively differentiate pathway-based patterns of different chemicals, using three model toxicants, 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), triclosan (TCS) and 5-Chloro-6-hydroxy-2,2',4,4'-tetrabromodiphenyl ether (5-Cl-6-OH-BDE-47). AHR-regulated genes and pathways were most sensitively induced by TCDD, while TCS and 5-Cl-6-OH-BDE-47 were much less potent in AHR-associated activation, which was concordant with known MoA of each single chemical. Second, two artificial mixtures and their components of twelve individual chemicals were performed with concentration-dependent RHT. Concentration addition (CA) and independent action (IA) models were used to predict transcriptional potency of mixtures from transcriptomics of individual chemicals. For overall bioactivity, CA and IA models can both predict potency of observed responses within 95% confidence interval. For specific biological processes, multiple biological processes such as hormone signaling and DNA damage can be predicted using CA models for mixtures. The concentration-dependent RHT can provide a powerful approach for qualitative and quantitative assessment of biological pathway perturbated by environment chemical and mixtures.

A Case Study with Triazole Fungicides to Explore Practical Application of Next-Generation Hazard Assessment Methods for Human Health

The ongoing developments in chemical risk assessment have led to new concepts building on integration of sophisticated nonanimal models for hazard characterization. Here we explore a pragmatic approach for implementing such concepts, using a case study of three triazole fungicides, namely, flusilazole, propiconazole, and cyproconazole. The strategy applied starts with evaluating the overall level of concern by comparing exposure estimates to toxicological potential, followed by a combination of in silico tools and literature-derived high-throughput screening assays and computational elaborations to obtain insight into potential toxicological mechanisms and targets in the organism. Additionally, some targeted in vitro tests were evaluated for their utility to confirm suspected mechanisms of toxicity and to generate points of departure. Toxicological mechanisms instead of the current "end point-by-end point" approach should guide the selection of methods and assays that constitute a toolbox for next-generation risk assessment. Comparison of the obtained in silico and in vitro results with data from traditional in vivo testing revealed that, overall, nonanimal methods for hazard identification can produce adequate qualitative hazard information for risk assessment. Follow-up studies are needed to further refine the proposed approach, including the composition of the toolbox, toxicokinetics models, and models for exposure assessment.

Gene expression and cytosine DNA methylation alterations in induced pluripotent stem-cell-derived human hepatocytes treated with low doses of chemical carcinogens

The increasing number of man-made chemicals in the environment that may pose a carcinogenic risk emphasizes the need to develop reliable time- and cost-effective approaches for carcinogen detection. To address this issue, we have investigated the utility of human hepatocytes for the in vitro identification of genotoxic and non-genotoxic carcinogens. Induced pluripotent stem-cell (iPSC)-derived human hepatocytes were treated with the genotoxic carcinogens aflatoxin B₁ (AFB1) and benzo[a]pyrene (B[a]P), the non-genotoxic liver carcinogen methapyrilene, and the non-carcinogens aflatoxin B₂ (AFB2) and benzo[e]pyrene (B[e]P) at non-cytotoxic concentrations for 7 days, and transcriptomic and DNA methylation profiles were examined. 1569, 1693, and 2061 differentially expressed genes (DEGs) were detected in cells treated with AFB1, B[a]P, and methapyrilene, respectively, whereas no DEGs were found in cells treated with AFB2 or B[e]P. In contrast to the profound cellular transcriptomic responses, exposure of iPSC-derived hepatocytes to the test chemicals resulted in minor random alterations in global DNA methylome, most of which were not associated with changes in gene expression. Overall, our results demonstrate that the major non-genotoxic effect of exposure to carcinogens, regardless of their mode of action, is a profound global transcriptomic response rather than global DNA methylome alterations, indicating the significance of transcriptomic alterations as an informative endpoint in short-term in vitro carcinogen testing.

Toxicogenomics - What added Value Do These Approaches Provide for Carcinogen Risk Assessment?

It is still a major challenge to protect humans at workplaces and in the environment. To cope with this task, it is a prerequisite to obtain detailed information on the extent of chemical perturbations of biological pathways, in particular, adaptive vs. adverse effects and the dose-response relationships. This knowledge serves as the basis for the classification of non-carcinogens and carcinogens and for further distinguishing carcinogens in genotoxic (DNA damaging) or non-genotoxic compounds. Basing on quantitative dose-response relationships, points of departures can be derived for chemical risk assessment. In recent years, new methods have shown their capability to support the established rodent models of carcinogenicity testing. In vitro high throughput screening assays assess more comprehensively cell response. In addition, omics technologies were applied to study the mode of action of chemicals whereby the term "toxicogenomics" comprises various technologies such as transcriptomics, epigenomics, or metabolomics. This review aims to summarize the current state of toxicogenomic approaches in risk science and to compare them with established ones. For example, measurement of global transcriptional changes generates meaningful information for toxicological risk assessment such as accurate classification of genotoxic/non-genotoxic carcinogens. Alteration in mRNA expression offers previously unknown insights in the mode of action and enables the definition of key events. Based on these, benchmark doses can be calculated for the transition from an adaptive to an adverse state. In short, this review assesses the potential and challenges of transcriptomics and addresses the impact of other omics technologies on risk assessment in terms of hazard identification and dose-response assessment.

FunMappOne: a tool to hierarchically organize and visually navigate functional gene annotations in multiple experiments

BACKGROUND

Functional annotation of genes is an essential step in omics data analysis. Multiple databases and methods are currently available to summarize the functions of sets of genes into higher level representations, such as ontologies and molecular pathways. Annotating results from omics experiments into functional categories is essential not only to understand the underlying regulatory dynamics but also to compare multiple experimental conditions at a higher level of abstraction. Several tools are already available to the community to represent and compare functional profiles of omics experiments. However, when the number of experiments and/or enriched functional terms is high, it becomes difficult to interpret the results even when graphically represented. Therefore, there is currently a need for interactive and user-friendly tools to graphically navigate and further summarize annotations in order to facilitate results interpretation also when the dimensionality is high.

RESULTS

We developed an approach that exploits the intrinsic hierarchical structure of several functional annotations to summarize the results obtained through enrichment analyses to higher levels of interpretation and to map gene related information at each summarized level. We built a user-friendly graphical interface that allows to visualize the functional annotations of one or multiple experiments at once. The tool is implemented as a R-Shiny application called FunMappOne and is available at https://github.com/grecolab/FunMappOne .

CONCLUSION

FunMappOne is a R-shiny graphical tool that takes in input multiple lists of human or mouse genes, optionally along with their related modification magnitudes, computes the enriched annotations from Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, or Reactome databases, and reports interactive maps of functional terms and pathways organized in rational groups. FunMappOne allows a fast and convenient comparison of multiple experiments and an easy way to interpret results.

Is current risk assessment of non-genotoxic carcinogens protective?

Non-genotoxic carcinogens (NGTXCs) do not cause direct DNA damage but induce cancer via other mechanisms. In risk assessment of chemicals and pharmaceuticals, carcinogenic risks are determined using carcinogenicity studies in rodents. With the aim to reduce animal testing, REACH legislation states that carcinogenicity studies are only allowed when specific concerns are present; risk assessment of compounds that are potentially carcinogenic by a non-genotoxic mode of action is usually based on subchronic toxicity studies. Health-based guidance values (HBGVs) of NGTXCs may therefore be based on data from carcinogenicity or subchronic toxicity studies depending on the legal framework that applies. HBGVs are usually derived from No-Observed-Adverse-Effect-Levels (NOAELs). Here, we investigate whether current risk assessment of NGTXCs based on NOAELs is protective against cancer. To answer this question, we estimated Benchmark doses (BMDs) for carcinogenicity data of 44 known NGTXCs. These BMDs were compared to the NOAELs derived from the same carcinogenicity studies, as well as to the NOAELs derived from the associated subchronic studies. The results lead to two main conclusions. First, a NOAEL derived from a subchronic study is similar to a NOAEL based on cancer effects from a carcinogenicity study, supporting the current practice in REACH. Second, both the subchronic and cancer NOAELs are, on average, associated with a cancer risk of around 1% in rodents. This implies that for those chemicals that are potentially carcinogenic in humans, current risk assessment of NGTXCs may not be completely protective against cancer. Our results call for a broader discussion within the scientific community, followed by discussions among risk assessors, policy makers, and other stakeholders as to whether or not the potential cancer risk levels that appear to be associated with currently derived HBGVs of NGXTCs are acceptable.

Omics Advances in Ecotoxicology

Toxic substances in the environment generate adverse effects at all levels of biological organization from the molecular level to community and ecosystem. Given this complexity, it is not surprising that ecotoxicologists have struggled to address the full consequences of toxic substance release at ecosystem level, due to the limits of observational and experimental tools to reveal the changes in deep structure at different levels of organization. -Omics technologies, consisting of genomics and ecogenomics, have the power to reveal, in unprecedented detail, the cellular processes of an individual or biodiversity of a community in response to environmental change with high sample/observation throughput. This represents a historic opportunity to transform the way we study toxic substances in ecosystems, through direct linkage of ecological effects with the systems biology of organisms. Three recent examples of -omics advance in the assessment of toxic substances are explored here: (1) the use of functional genomics in the discovery of novel molecular mechanisms of toxicity of chemicals in the environment; (2) the development of laboratory pipelines of dose-dependent, reduced transcriptomics to support high-throughput chemical testing at the biological pathway level; and (3) the use of eDNA metabarcoding approaches for assessing chemical effects on biological communities in mesocosm experiments and through direct observation in field monitoring. -Omics advances in ecotoxicological studies not only generate new knowledge regarding mechanisms of toxicity and environmental effect, improving the relevance and immediacy of laboratory toxicological assessment, but can provide a wholly new paradigm for ecotoxicology by linking ecological models to mechanism-based, systems biology approaches.

3S - Systematic, systemic, and systems biology and toxicology

A biological system is more than the sum of its parts - it accomplishes many functions via synergy. Deconstructing the system down to the molecular mechanism level necessitates the complement of reconstructing functions on all levels, i.e., in our conceptualization of biology and its perturbations, our experimental models and computer modelling. Toxicology contains the somewhat arbitrary subclass "systemic toxicities"; however, there is no relevant toxic insult or general disease that is not systemic. At least inflammation and repair are involved that require coordinated signaling mechanisms across the organism. However, the more body components involved, the greater the challenge to reca-pitulate such toxicities using non-animal models. Here, the shortcomings of current systemic testing and the development of alternative approaches are summarized. We argue that we need a systematic approach to integrating existing knowledge as exemplified by systematic reviews and other evidence-based approaches. Such knowledge can guide us in modelling these systems using bioengineering and virtual computer models, i.e., via systems biology or systems toxicology approaches. Experimental multi-organ-on-chip and microphysiological systems (MPS) provide a more physiological view of the organism, facilitating more comprehensive coverage of systemic toxicities, i.e., the perturbation on organism level, without using substitute organisms (animals). The next challenge is to establish disease models, i.e., micropathophysiological systems (MPPS), to expand their utility to encompass biomedicine. Combining computational and experimental systems approaches and the chal-lenges of validating them are discussed. The suggested 3S approach promises to leverage 21st century technology and systematic thinking to achieve a paradigm change in studying systemic effects.

Stem Cell Transcriptome Responses and Corresponding Biomarkers That Indicate the Transition from Adaptive Responses to Cytotoxicity

Analysis of transcriptome changes has become an established method to characterize the reaction of cells to toxicants. Such experiments are mostly performed at compound concentrations close to the cytotoxicity threshold. At present, little information is available on concentration-dependent features of transcriptome changes, in particular, at the transition from noncytotoxic concentrations to conditions that are associated with cell death. Thus, it is unclear in how far cell death confounds the results of transcriptome studies. To explore this gap of knowledge, we treated pluripotent stem cells differentiating to human neuroepithelial cells (UKN1 assay) for short periods (48 h) with increasing concentrations of valproic acid (VPA) and methyl mercury (MeHg), two compounds with vastly different modes of action. We developed various visualization tools to describe cellular responses, and the overall response was classified as "tolerance" (minor transcriptome changes), "functional adaptation" (moderate/strong transcriptome responses, but no cytotoxicity), and "degeneration". The latter two conditions were compared, using various statistical approaches. We identified (i) genes regulated at cytotoxic, but not at noncytotoxic, concentrations and (ii) KEGG pathways, gene ontology term groups, and superordinate biological processes that were only regulated at cytotoxic concentrations. The consensus markers and processes found after 48 h treatment were then overlaid with those found after prolonged (6 days) treatment. The study highlights the importance of careful concentration selection and of controlling viability for transcriptome studies. Moreover, it allowed identification of 39 candidate "biomarkers of cytotoxicity". These could serve to provide alerts that data sets of interest may have been affected by cell death in the model system studied.

Detection of non-genotoxic hepatocarcinogens and prediction of their mechanism of action in rats using gene marker sets

Several studies have successfully detected hepatocarcinogenicity in rats based on gene expression data. However, prediction of hepatocarcinogens with certain mechanisms of action (MOAs), such as enzyme inducers and peroxisome proliferator-activated receptor α (PPARα) agonists, can prove difficult using a single model and requires a highly toxic dose. Here, we constructed a model for detecting non-genotoxic (NGTX) hepatocarcinogens and predicted their MOAs in rats. Gene expression data deposited in the Open Toxicogenomics Project-Genomics Assisted Toxicity Evaluation System (TG-GATEs) was used to investigate gene marker sets. Principal component analysis (PCA) was applied to discriminate different MOAs, and a support vector machine algorithm was applied to construct the prediction model. This approach identified 106 probe sets as gene marker sets for PCA and enabled the prediction model to be constructed. In PCA, NGTX hepatocarcinogens were classified as follows based on their MOAs: cytotoxicants, PPARα agonists, or enzyme inducers. The prediction model detected hepatocarcinogenicity with an accuracy of more than 90% in 14- and 28-day repeated-dose studies. In addition, the doses capable of predicting NGTX hepatocarcinogenicity were close to those required in rat carcinogenicity assays. In conclusion, our PCA and prediction model using gene marker sets will help assess the risk of hepatocarcinogenicity in humans based on MOAs and reduce the number of two-year rodent bioassays.

Highlight report: Launch of a large integrated European in vitro toxicology project: EU-ToxRisk

The integrated European project, EU-ToxRisk, proudly sees itself as “flagship” exploring new alternative-to-animal approaches to chemical safety evaluation. It promotes mechanism-based toxicity testing and risk assessment according to the principles laid down for toxicology for the twenty-first century. The project was officially launched in January 2016 with a kickoff meeting in Egmond aan Zee, the Netherlands. Over 100 scientists representing academia and industry as well as regulatory authorities attended the inaugural meeting. The project will integrate advances in in vitro and in silico toxicology, read-across methods, and adverse outcome pathways. EU-ToxRisk will continue to make use of the case study strategy deployed in SEURAT-1, a FP7 initiative ended in December 2015. Even though the development of new non-animal methods is one target of EU-ToxRisk, the project puts special emphasis on their acceptance and implementation in regulatory contexts. This €30 million Horizon 2020 project involves 38 European partners and one from the USA. EU-ToxRisk aims at the “development of a new way of risk assessment.”

The Extended ToxTracker Assay Discriminates Between Induction of DNA Damage, Oxidative Stress, and Protein Misfolding

Chemical exposure of cells may damage biomolecules, cellular structures, and organelles thereby jeopardizing cellular homeostasis. A multitude of defense mechanisms have evolved that can recognize specific types of damaged molecules and will initiate distinct cellular programs aiming to remove the damage inflicted and prevent cellular havoc. As a consequence, quantitative assessment of the activity of the cellular stress responses may serve as a sensitive reporter for the induction of specific types of damage. We have previously developed the ToxTracker assay, a mammalian stem cell-based genotoxicity assay employing two green fluorescent protein reporters specific for DNA damage and oxidative stress. We have now expanded the ToxTracker assay with an additional four reporter cell lines to include monitoring of additional stress signaling pathways. This panel of six green fluorescent protein reporters is able to discriminate between different primary reactivity of chemicals being their ability to react with DNA and block DNA replication, induce oxidative stress, activate the unfolded protein response, or cause a general P53-dependent cellular stress response. Extensive validation using the compound library suggested by the European Centre for the Validation of Alternative Methods (ECVAM) and a large panel of reference chemicals shows that the ToxTracker assay has an outstanding sensitivity and specificity. In addition, we developed Toxplot, a dedicated software tool for automated data analysis and graphical representation of the test results. Rapid and reliable identification by the ToxTracker assay of specific biological reactivity can significantly improve in vitro human hazard assessment of chemicals.