Predicting developmental toxicity through toxicogenomics

An ontology for developmental processes and toxicities of neural tube closure

In recent years, the development and implementation of animal-free approaches to chemical and pharmaceutical hazard and risk assessment has taken off. Alternative approaches are being developed starting from the perspective of human biology and physiology. Neural tube closure is a vital step that occurs early in human development. Correct closure of the neural tube depends on a complex interplay between proteins along a number of protein concentration gradients. The sensitivity of neural tube closure to chemical disturbance of signalling pathways such as the retinoid pathway, is well known. To map the pathways underlying neural tube closure, literature data on the molecular regulation of neural tube closure were collected. As the process of neural tube closure is highly conserved in vertebrates, the extensive literature available for the mouse was used whilst considering its relevance for humans. Thus, important cell compartments, regulatory pathways, and protein interactions essential for neural tube closure under physiological circumstances were identified and mapped. An understanding of aberrant processes leading to neural tube defects (NTDs) requires detailed maps of neural tube embryology, including the complex genetic signals and responses underlying critical cellular dynamical and biomechanical processes. The retinoid signaling pathway serves as a case study for this ontology because of well-defined crosstalk with the genetic control of neural tube patterning and morphogenesis. It is a known target for mechanistically-diverse chemical structures that disrupt neural tube closure The data presented in this manuscript will set the stage for constructing mathematical models and computer simulation of neural tube closure for human-relevant AOPs and predictive toxicology.

Rethinking developmental toxicity testing: Evolution or revolution?

BACKGROUND

Current developmental toxicity testing adheres largely to protocols suggested in 1966 involving the administration of test compound to pregnant laboratory animals. After more than 50 years of embryo-fetal development testing, are we ready to consider a different approach to human developmental toxicity testing?

METHODS

A workshop was held under the auspices of the Developmental and Reproductive Toxicology Technical Committee of the ILSI Health and Environmental Sciences Institute to consider how we might design developmental toxicity testing if we started over with 21st century knowledge and techniques (revolution). We first consider what changes to the current protocols might be recommended to make them more predictive for human risk (evolution).

RESULTS

The evolutionary approach includes modifications of existing protocols and can include humanized models, disease models, more accurate assessment and testing of metabolites, and informed approaches to dose selection. The revolution could start with hypothesis-driven testing where we take what we know about a compound or close analog and answer specific questions using targeted experimental techniques rather than a one-protocol-fits-all approach. Central to the idea of hypothesis-driven testing is the concept that testing can be done at the level of mode of action. It might be feasible to identify a small number of key events at a molecular or cellular level that predict an adverse outcome and for which testing could be performed in vitro or in silico or, rarely, using limited in vivo models. Techniques for evaluating these key events exist today or are in development.

DISCUSSION

Opportunities exist for refining and then replacing current developmental toxicity testing protocols using techniques that have already been developed or are within reach.

Integrating toxicogenomics into human health risk assessment: lessons learned from the benzo[a]pyrene case study

The use of short-term toxicogenomic tests to predict cancer (or other health effects) offers considerable advantages relative to traditional toxicity testing methods. The advantages include increased throughput, increased mechanistic data, and significantly reduced costs. However, precisely how toxicogenomics data can be used to support human health risk assessment (RA) is unclear. In a companion paper ( Moffat et al. 2014 ), we present a case study evaluating the utility of toxicogenomics in the RA of benzo[a]pyrene (BaP), a known human carcinogen. The case study is meant as a proof-of-principle exercise using a well-established mode of action (MOA) that impacts multiple tissues, which should provide a best case example. We found that toxicogenomics provided rich mechanistic data applicable to hazard identification, dose-response analysis, and quantitative RA of BaP. Based on this work, here we share some useful lessons for both research and RA, and outline our perspective on how toxicogenomics can benefit RA in the short- and long-term. Specifically, we focus on (1) obtaining biologically relevant data that are readily suitable for establishing an MOA for toxicants, (2) examining the human relevance of an MOA from animal testing, and (3) proposing appropriate quantitative values for RA. We describe our envisioned strategy on how toxicogenomics can become a tool in RA, especially when anchored to other short-term toxicity tests (apical endpoints) to increase confidence in the proposed MOA, and emphasize the need for additional studies on other MOAs to define the best practices in the application of toxicogenomics in RA.

Critical appraisal of the assessment of benefits and risks for foods, 'BRAFO Consensus Working Group'

BRAFO, Benefit-Risk Analysis for Foods, was a European Commission project funded within Framework Six as a Specific Support Action and coordinated by ILSI Europe. BRAFO developed a tiered methodology for assessing the benefits and risks of foods and food components, utilising a quantitative, common scale for health assessment in higher tiers. This manuscript reports on the implications of the experience gained during the development of the project for the further improvement of benefit-risk assessment methodology. It was concluded that the methodology proposed is applicable to a range of situations and that it does help in optimising resource utilisation through early identification of those benefit-risk questions where benefit clearly outweighs risk or vice versa. However, higher tier assessments are complex and demanding of time and resources, emphasising the need for prioritisation. Areas identified as requiring further development to improve the utility of benefit-risk assessment include health weights for different populations and endpoints where they do not currently exist, extrapolation of effects from studies in animals to humans, use of in vitro data in benefit-risk assessments, and biomarkers of early effect and how these would be used in a quantitative assessment.

Dose response analysis of monophthalates in the murine embryonic stem cell test assessed by cardiomyocyte differentiation and gene expression

The embryonic stem cell test (EST) is based on compound-induced inhibition of cardiomyocyte differentiation of pluripotent stem cells. We examined the use of transcriptomics to assess concentration-effect relationships and performed potency ranking within a chemical class. Three embryotoxic phthalate monoesters, monobutyl phthalate (MBuP), monobenzyl phthalate (MBzP) and mono-(2-ethylhexyl) phthalate (MEHP) and the non-embryotoxic monomethyl phthalate (MMP) were studied for their effects on gene expression. Effects on gene expression were observed at concentrations that did not inhibit cardiomyocyte differentiation or induce cytotoxicity. The embryotoxic phthalate monoesters altered the expression of 668 commonly expressed genes in a concentration-dependent fashion. The same potency ranking was observed for morphology and gene expression (MEHP>MBzP>MBuP>MMP). These results indicate that integrating transcriptomics provides a sensitive method to measure the dose-dependent effects of phthalate monoester exposure and enables potency ranking based on a common mode of action within a class of compounds. Transcriptomic approaches may improve the applicability of the EST, in terms of sensitivity and specificity.

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 review of toxicogenomic approaches in developmental toxicology

Over the past decade, the use of gene expression profiling (i.e., toxicogenomics or transcriptomics) has been established as the vanguard "omics" technology to investigate exposure-induced molecular changes that underlie the development of disease. As this technology quickly advances, researchers are striving to keep pace in grasping the complexity of toxicogenomic response while at the same time determine its applicability for the field of developmental toxicology. Initial studies suggest toxicogenomics to be a promising tool for multiple types of study designs, including exposure-response investigations (dose and duration), chemical classification, and model comparisons. In this review, we examine the use of toxicogenomics in developmental toxicology, discussing biological and technical factors that influence response and interpretation. Additionally, we provide a framework to guide toxicogenomic investigations in the field of developmental toxicology.

Accelerating the development of 21st-century toxicology: outcome of a Human Toxicology Project Consortium workshop

The U.S. National Research Council (NRC) report on "Toxicity Testing in the 21st century" calls for a fundamental shift in the way that chemicals are tested for human health effects and evaluated in risk assessments. The new approach would move toward in vitro methods, typically using human cells in a high-throughput context. The in vitro methods would be designed to detect significant perturbations to "toxicity pathways," i.e., key biological pathways that, when sufficiently perturbed, lead to adverse health outcomes. To explore progress on the report's implementation, the Human Toxicology Project Consortium hosted a workshop on 9-10 November 2010 in Washington, DC. The Consortium is a coalition of several corporations, a research institute, and a non-governmental organization dedicated to accelerating the implementation of 21st-century Toxicology as aligned with the NRC vision. The goal of the workshop was to identify practical and scientific ways to accelerate implementation of the NRC vision. The workshop format consisted of plenary presentations, breakout group discussions, and concluding commentaries. The program faculty was drawn from industry, academia, government, and public interest organizations. Most presentations summarized ongoing efforts to modernize toxicology testing and approaches, each with some overlap with the NRC vision. In light of these efforts, the workshop identified recommendations for accelerating implementation of the NRC vision, including greater strategic coordination and planning across projects (facilitated by a steering group), the development of projects that test the proof of concept for implementation of the NRC vision, and greater outreach and communication across stakeholder communities.

Laboratory models and their role in assessing teratogenesis

Laboratory models have an important role in identifying exposures with teratogenic potential, determining mechanisms of abnormal development, and supporting or refuting the biological plausibility of associations identified in human studies. Laboratory animals are the most widely used models, but are rapidly being supplemented by in vitro tools. Testing paradigms that have been in place since the mid-1960s for pharmaceuticals, and soon thereafter for industrial chemicals and pesticides, have been used to evaluate the potential developmental toxicity of thousands of agents. These models have served as the principal basis for regulatory decisions about acceptable exposure levels and restrictions on use of certain drugs during pregnancy.

Gene set assembly for quantitative prediction of developmental toxicity in the embryonic stem cell test

The embryonic stem cell test (EST) is an in vitro method for predicting developmental toxicity based on compound-induced inhibition of embryonic stem cell (ESC) differentiation. We previously described how gene expression analysis in the EST can be used to describe normal ESC differentiation as well as identify compound developmental toxicity, by means of our differentiation track algorithm. In this study, we combined raw data from our three previous studies in a new integrated analysis, to identify a gene set that allows for improved prediction. By evaluating predictions of 100,000 randomly selected gene sets, we identified which genes contribute significantly to the prediction reliability. By additional cross-validation, we identified a set of 52 genes that allows for improved prediction of toxicity. The correlation between the predictions using this gene set and the magnitude of the EST endpoint was 0.85, and the gene set predicted developmental toxicity with 83% accuracy (area under the curve 89%). If compounds with ineffective data because of a too low tested concentration or too much variation between samples were excluded, even 100% accuracy could be reached based on 15 compounds. This novel gene set consists mainly of genes involved in the stem cell differentiation or other developmental processes. We expect that this set can be of use in future studies aimed at improving the EST for risk assessment, thus making a next step towards regulatory implementation of this method.

Integrating mechanistic and polymorphism data to characterize human genetic susceptibility for environmental chemical risk assessment in the 21st century

Response to environmental chemicals can vary widely among individuals and between population groups. In human health risk assessment, data on susceptibility can be utilized by deriving risk levels based on a study of a susceptible population and/or an uncertainty factor may be applied to account for the lack of information about susceptibility. Defining genetic susceptibility in response to environmental chemicals across human populations is an area of interest in the NAS' new paradigm of toxicity pathway-based risk assessment. Data from high-throughput/high content (HT/HC), including -omics (e.g., genomics, transcriptomics, proteomics, metabolomics) technologies, have been integral to the identification and characterization of drug target and disease loci, and have been successfully utilized to inform the mechanism of action for numerous environmental chemicals. Large-scale population genotyping studies may help to characterize levels of variability across human populations at identified target loci implicated in response to environmental chemicals. By combining mechanistic data for a given environmental chemical with next generation sequencing data that provides human population variation information, one can begin to characterize differential susceptibility due to genetic variability to environmental chemicals within and across genetically heterogeneous human populations. The integration of such data sources will be informative to human health risk assessment.

Discriminating classes of developmental toxicants using gene expression profiling in the embryonic stem cell test

The embryonic stem cell test (EST) has been shown to be a promising in vitro method for the prediction of developmental toxicity. In our previous studies, we demonstrated that the implementation of gene expression analysis in the EST may further improve the identification of developmental toxicants. In the present study, we investigated if gene expression profiling could be used to discriminate compound classes with distinct modes of action (MoA) using the EST protocol. Gene expression data of our previous study were used and were analyzed of embryonic stem cell (ESC) differentiation cultures exposed to six compounds belonging to two classes with distinct MoA, namely phthalates and triazoles. We used three approaches to study class-characteristic gene regulation that may be useful for discrimination of compound classes. First, at the individual gene level, gene signatures characteristic for each class were identified that successfully discriminated both classes using principal component analysis. Second, at the functional level, enriched gene ontology (GO) biological processes showed their usefulness for class discrimination via hierarchical clustering. Third, two previously identified gene sets, which we designed to predict developmental toxicity, appeared successful in separating phthalate from triazole compounds. In summary, we established the possibility to discriminate between compound classes in the EST system using three different specific transcriptomics-based approaches. Differential gene expression information specific for the class of compound under study may be employed to optimize prioritization of compounds within that class for further testing.