Integrating gene expression and splicing dynamics across dose-response oxidative modulators.

Toxicological risk assessment increasingly utilizes transcriptomics to derive point of departure (POD) and modes of action (MOA) for chemicals. One essential biological process that allows a single gene to generate several different RNA isoforms is called alternative splicing. To comprehensively assess the role of splicing dysregulation in toxicological evaluation and elucidate its potential as a complementary endpoint, we performed RNA-seq on A549 cells treated with five oxidative stress modulators across a wide dose range. Differential gene expression (DGE) showed limited pathway enrichment except at high concentrations. However, alternative splicing analysis revealed variable intron retention events affecting diverse pathways for all chemicals in the absence of significant expression changes. For instance, diazinon elicited negligible gene expression changes but progressive increase in the number of intron retention events, suggesting splicing alterations precede expression responses. Benchmark dose modeling of intron retention data highlighted relevant pathways overlooked by expression analysis. Systematic integration of splicing datasets should be a useful addition to the toxicogenomic toolkit. Combining both modalities paint a more complete picture of transcriptomic dose-responses. Overall, evaluating intron retention dynamics afforded by toxicogenomics may provide biomarkers that can enhance chemical risk assessment and regulatory decision making. This work highlights splicing-aware toxicogenomics as a possible additional tool for examining cellular responses.

Beyond pharmaceuticals: Fit-for-purpose new approach methodologies for environmental cardiotoxicity testing.

Environmental factors play a substantial role in determining cardiovascular health, but data informing the risks presented by environmental toxicants is insufficient. In vitro new approach methodologies (NAMs) offer a promising approach with which to address the limitations of traditional in vivo and in vitro assays for assessing cardiotoxicity. Driven largely by the needs of pharmaceutical toxicity testing, considerable progress in developing NAMs for cardiotoxicity analysis has already been made. As the scientific and regulatory interest in NAMs for environmental chemicals continues to grow, a thorough understanding of the unique features of environmental cardiotoxicants and their associated cardiotoxicities is needed. Here, we review the key characteristics of as well as important regulatory and biological considerations for fit-for-purpose NAMs for environmental cardiotoxicity. By emphasizing the challenges and opportunities presented by NAMs for environmental cardiotoxicity we hope to accelerate their development, acceptance, and application.

Comparison of Rat Hepatocyte 2D-Monocultures and Hepatocytes Non-Parenchymal Cell Co-Cultures for Assessing Chemical Toxicity.

Liver responses are the most common endpoints used as the basis for setting exposure standards. Liver hepatocytes play a vital role in biotransformation of xenobiotics, but non-parenchymal cells (NPCs) in the liver are also involved in certain liver responses. Development of in vitro systems that more faithfully capture liver responses to reduce reliance on animals is a major focus of New Approach Methodology (NAMs). Since rodent regulatory studies are frequently the sole source safety assessment data, mode-of-action data, and used for risk assessments, in vitro rodent models that reflect in vivo responses need to be developed to reduce reliance on animal models. In the work presented in this paper, we developed a 2-D hepatocyte monoculture and 2-D liver cell co-culture system using rat liver cells. These models were assessed for conditions for short-term stability of the cultures and phenotypic and transcriptomic responses of 2 prototypic hepatotoxicants compounds - acetaminophen and phenobarbital. The optimized multi-cellular 2-D culture required use of freshly prepared hepatocytes and NPCs from a single rat, a 3:1 ratio of hepatocytes to NPCs and growth medium using 50% Complete Williams E medium (WEM) and 50% Endothelial Cell Medium (ECM). The transcriptomic responses of the 2 model systems to PB were compared to previous studies from TG-Gates on the gene expression changes in intact rats and the co-culture model responses were more representative of the in vivo responses. Transcriptomic read-outs promise to move beyond conventional phenotypic evaluations with these in vitro NAMs and provide insights about modes of action.

NAM-based prediction of point-of-contact toxicity in the lung: A case example with 1,3-dichloropropene.

Time, cost, ethical, and regulatory considerations surrounding in vivo testing methods render them insufficient to meet existing and future chemical safety testing demands. There is a need for the development of in vitro and in silico alternatives to replace traditional in vivo methods for inhalation toxicity assessment. Exposures of differentiated airway epithelial cultures to gases or aerosols at the air-liquid interface (ALI) can assess tissue responses and in vitro to in vivo extrapolation can align in vitro exposure levels with in-life exposures expected to give similar tissue exposures. Because the airway epithelium varies along its length, with various regions composed of different cell types, we have introduced a known toxic vapor to five human-derived, differentiated, in vitro airway epithelial cell culture models-MucilAir of nasal, tracheal, or bronchial origin, SmallAir, and EpiAlveolar-representing five regions of the airway epithelium-nasal, tracheal, bronchial, bronchiolar, and alveolar. We have monitored toxicity in these cultures 24 h after acute exposure using an assay for transepithelial conductance (for epithelial barrier integrity) and the lactate dehydrogenase (LDH) release assay (for cytotoxicity). Our vapor of choice in these experiments was 1,3-dichloropropene (1,3-DCP). Finally, we have developed an airway dosimetry model for 1,3-DCP vapor to predict in vivo external exposure scenarios that would produce toxic local tissue concentrations as determined by in vitro experiments. Measured in vitro points of departure (PoDs) for all tested cell culture models were similar. Calculated rat equivalent inhaled concentrations varied by model according to position of the modeled tissue within the airway, with nasal respiratory tissue being the most proximal and most sensitive tissue, and alveolar epithelium being the most distal and least sensitive tissue. These predictions are qualitatively in accordance with empirically determined in vivo PoDs. The predicted PoD concentrations were close to, but slightly higher than, PoDs determined by in vivo subchronic studies.

Estimating provisional margins of exposure for data-poor chemicals using high-throughput computational methods.

Current computational technologies hold promise for prioritizing the testing of the thousands of chemicals in commerce. Here, a case study is presented demonstrating comparative risk-prioritization approaches based on the ratio of surrogate hazard and exposure data, called margins of exposure (MoEs). Exposures were estimated using a U.S. EPA's ExpoCast predictive model (SEEM3) results and estimates of bioactivity were predicted using: 1) Oral equivalent doses (OEDs) derived from U.S. EPA's ToxCast high-throughput screening program, together with in vitro to in vivo extrapolation and 2) thresholds of toxicological concern (TTCs) determined using a structure-based decision-tree using the Toxtree open source software. To ground-truth these computational approaches, we compared the MoEs based on predicted noncancer TTC and OED values to those derived using the traditional method of deriving points of departure from no-observed adverse effect levels (NOAELs) from in vivo oral exposures in rodents. TTC-based MoEs were lower than NOAEL-based MoEs for 520 out of 522 (99.6%) compounds in this smaller overlapping dataset, but were relatively well correlated with the same (r 2 = 0.59). TTC-based MoEs were also lower than OED-based MoEs for 590 (83.2%) of the 709 evaluated chemicals, indicating that TTCs may serve as a conservative surrogate in the absence of chemical-specific experimental data. The TTC-based MoE prioritization process was then applied to over 45,000 curated environmental chemical structures as a proof-of-concept for high-throughput prioritization using TTC-based MoEs. This study demonstrates the utility of exploiting existing computational methods at the pre-assessment phase of a tiered risk-based approach to quickly, and conservatively, prioritize thousands of untested chemicals for further study.

Considerations for Improving Metabolism Predictions for In Vitro to In Vivo Extrapolation.

High-throughput (HT) in vitro to in vivo extrapolation (IVIVE) is an integral component in new approach method (NAM)-based risk assessment paradigms, for rapidly translating in vitro toxicity assay results into the context of in vivo exposure. When coupled with rapid exposure predictions, HT-IVIVE supports the use of HT in vitro assays for risk-based chemical prioritization. However, the reliability of prioritization based on HT bioactivity data and HT-IVIVE can be limited as the domain of applicability of current HT-IVIVE is generally restricted to intrinsic clearance measured primarily in pharmaceutical compounds. Further, current approaches only consider parent chemical toxicity. These limitations occur because current state-of-the-art HT prediction tools for clearance and metabolite kinetics do not provide reliable data to support HT-IVIVE. This paper discusses current challenges in implementation of IVIVE for prioritization and risk assessment and recommends a path forward for addressing the most pressing needs and expanding the utility of IVIVE.

Biological system considerations for application of toxicogenomics in next-generation risk assessment and predictive toxicology.

There is increasing interest in using modern 'omics technologies, such as whole transcriptome sequencing, to inform decisions about human health safety and chemical toxicity hazard. High throughput methodologies using in vitro assays offer a path forward in reducing or eliminating animal testing. However, many aspects of these technologies need assessment before they will gain the trust of regulators and the public as viable alternative test methods for human health and safety. We used a high throughput whole transcriptome sequence assay (TempO-Seq) to assess the use of three widely used cancer cell lines (HepG2, MCF7, and Ishikawa cells) as in vitro systems for determination of cellular modes of action for two well studied compounds with canonical liver responses: ketoconazole and phenobarbital. We evaluated transcriptomic data to infer points of departure for use in risk analyses of compounds. Both compounds displayed shortcomings in evidence for canonical liver-related responses in any cell line, despite a strong dose response in all three. This raises questions about the competence of simple, mono-cultured cancer cell lines as appropriate surrogates for some adverse effects or toxic endpoints. Points of departure derived from benchmark doses were highly consistent across all three cell lines however, indicating the use of transcriptomic BMD analyses for such purposes would be a reliable and consistent approach.

RNA-sequencing (transcriptomic) data collected in liver and lung of male and female B6C3F1 mice exposed to various dose levels of 4-methylimidazole for 2, 5, or 28 days.

The National Toxicology Program (NTP) reported that chronic exposure to varying dietary concentrations of 4-methylimidazole (4-MeI) increased lung tumors in female and male mice [1]. In this study, mice (male and female B6C3F1 mice) were either administered 4-MeI by oral gavage (0, 50, 100, 200, or 300 mg/kg/day) for 2 days or exposed for 5 and 28 days to 4-MeI in the diet (0, 150, 300, 1250, or 2500 ppm) and whole transcriptome (RNA-Sequencing) data from 4-MeI-exposed B6C3F1 mice to determine whether changes occurred in the target (lung) and nontarget (liver) tissues. This analysis was conducted to provide information with which to evaluate biological processes affected by exposure to 4-MeI, with a focus on identifying key events that could be used to propose a plausible mode of action (MoA) for mouse lung tumors [2].

A systematic approach to evaluate plausible modes of actions for mouse lung tumors in mice exposed to 4-methylimidozole.

The National Toxicology Program (NTP) reported that chronic dietary exposure to 4-methylimidazole (4-MeI) increased the incidence of lung adenomas/carcinomas beyond the normally high spontaneous rate in B6C3F1 mice. To examine plausible modes of action (MoAs) for mouse lung tumors (MLTs) upon exposure to high levels of 4-MeI, and their relevance in assessing human risk, a systematic approach was used to identify and evaluate mechanistic data (in vitro and in vivo) in the primary and secondary literature, along with high-throughput screening assay data. Study quality, relevance, and activity of mechanistic data identified across the evidence-base were organized according to key characteristics of carcinogens (KCCs) to identify potential key events in known or novel MLT MoAs. Integration of these evidence streams provided confirmation that 4-MeI lacks genotoxic and cytotoxic activity with some evidence to support a lack of mitogenic activity. Further evaluation of contextual and chemical-specific characteristics of 4-MeI was consequently undertaken. Due to lack of genotoxicity, along with transcriptomic and histopathological lung changes up to 28 and 90 days of exposure, the collective evidence suggests MLTs observed following exposure to high levels of 4-MeI develop at a late stage in the mouse chronic bioassay, albeit the exact MoA remains unclear.

Application of a combined aggregate exposure pathway and adverse outcome pathway (AEP-AOP) approach to inform a cumulative risk assessment: A case study with phthalates.

Advancements in measurement and modeling capabilities are providing unprecedented access to estimates of chemical exposure and bioactivity. With this influx of new data, there is a need for frameworks that help organize and disseminate information on chemical hazard and exposure in a manner that is accessible and transparent. A case study approach was used to demonstrate integration of the Adverse Outcome Pathway (AOP) and Aggregate Exposure Pathway (AEP) frameworks to support cumulative risk assessment of co-exposure to two phthalate esters that are ubiquitous in the environment and that are associated with disruption of male sexual development in the rat: di(2-ethylhexyl) phthalate (DEHP) and di-n-butyl phthalate (DnBP). A putative AOP was developed to guide selection of an in vitro assay for derivation of bioactivity values for DEHP and DnBP and their metabolites. AEPs for DEHP and DnBP were used to extract key exposure data as inputs for a physiologically based pharmacokinetic (PBPK) model to predict internal metabolite concentrations. These metabolite concentrations were then combined using in vitro-based relative potency factors for comparison with an internal dose metric, resulting in an estimated margin of safety of ~13,000. This case study provides an adaptable workflow for integrating exposure and toxicity data by coupling AEP and AOP frameworks and using in vitro and in silico methodologies for cumulative risk assessment.

A toxicogenomic approach for the risk assessment of the food contaminant acetamide.

Acetamide (CAS 60-35-5) is detected in common foods. Chronic rodent bioassays led to its classification as a group 2B possible human carcinogen due to the induction of liver tumors in rats. We used a toxicogenomics approach in Wistar rats gavaged daily for 7 or 28 days at doses of 300 to 1500 mg/kg/day (mkd) to determine a point of departure (POD) and investigate its mode of action (MoA). Ki67 labeling was increased at doses ≥750 mkd up to 3.3-fold representing the most sensitive apical endpoint. Differential gene expression analysis by RNA-Seq identified 1110 and 1814 differentially expressed genes in male and female rats, respectively, following 28 days of treatment. Down-regulated genes were associated with lipid metabolism while up-regulated genes included cell signaling, immune response, and cell cycle functions. Benchmark dose (BMD) modeling of the Ki67 labeling index determined the BMD10 lower confidence limit (BMDL10) as 190 mkd. Transcriptional BMD modeling revealed excellent concordance between transcriptional POD and apical endpoints. Collectively, these results indicate that acetamide is most likely acting through a mitogenic MoA, though specific key initiating molecular events could not be elucidated. A POD value of 190 mkd determined for cell proliferation is suggested for risk assessment purposes.

Identifying qualitative differences in PPARα signaling networks in human and rat hepatocytes and their significance for next generation chemical risk assessment methods.

In this paper, we evaluate the PPARα signaling network in rats, examining transcriptional responses in primary hepatocytes exposed to a PPARα specific ligand, GW7647. These transcriptomic studies were complemented with ChIP-seq studies of PPARα binding and transcription binding motif identification for PPARα responsive genes. We also conducted a limited study of GW7647 dosing the in intact rat to examine differences in transcriptional responses for primary hepatocytes in vitro and in the intact liver. The rat network has a much larger number of down-regulated genes and pathways than we had found in the human and the PPARα binding motifs in rat differed for upregulated and down regulated genes. Based on these results and comparison with our previous work with the human PPARα signaling network, we identified qualitative differences in the transcriptional networks controlled by PPARα activation in the two species that provide an explanation of the interspecies differences in the responses of humans and rodents to GW7647 and likely to other PPARα agonists. These studies also allow some observations on the manner in which in vitro, fit-for-purpose assays in human hepatocytes could form the basis for risk assessment without recourse to in-life studies in rodents or other test species.

The role of fit-for-purpose assays within tiered testing approaches: A case study evaluating prioritized estrogen-active compounds in an in vitro human uterotrophic assay.

Chemical risk assessment relies on toxicity tests that require significant numbers of animals, time and costs. For the >30,000 chemicals in commerce, the current scale of animal testing is insufficient to address chemical safety concerns as regulatory and product stewardship considerations evolve to require more comprehensive understanding of potential biological effects, conditions of use, and associated exposures. We demonstrate the use of a multi-level new approach methodology (NAMs) strategy for hazard- and risk-based prioritization to reduce animal testing. A Level 1/2 chemical prioritization based on estrogen receptor (ER) activity and metabolic activation using ToxCast data was used to select 112 chemicals for testing in a Level 3 human uterine cell estrogen response assay (IKA assay). The Level 3 data were coupled with quantitative in vitro to in vivo extrapolation (Q-IVIVE) to support bioactivity determination (as a surrogate for hazard) in a tissue-specific context. Assay AC50s and Q-IVIVE were used to estimate human equivalent doses (HEDs), and HEDs were compared to rodent uterotrophic assay in vivo-derived points of departure (PODs). For substances active both in vitro and in vivo, IKA assay-derived HEDs were lower or equivalent to in vivo PODs for 19/23 compounds (83%). Activity exposure relationships were calculated, and the IKA assay was as or more protective of human health than the rodent uterotrophic assay for all IKA-positive compounds. This study demonstrates the utility of biologically relevant fit-for-purpose assays and supports the use of a multi-level strategy for chemical risk assessment.

Developing context appropriate toxicity testing approaches using new alternative methods (NAMs).

In the past 10 years, the public, private, and non-profit sectors have found agreement that hazard identification and risk assessment should capitalize on the explosion of knowledge in the biological sciences, moving away from in life animal testing toward more human-relevant in vitro and in silico methods, collectively referred to as new approach methodologies (NAMs). The goals for implementation of NAMs are to efficiently identify possible chemical hazards and to gather dose-response data to inform more human-relevant safety assessment. While work proceeds to develop NAMs, there has been less emphasis on creating decision criteria or showing how risk context should guide selection and use of NAMs. Here, we outline application scenarios for NAMs in different risk contexts and place different NAMs and conventional testing approaches into four broad levels. Level 1 relies solely on computational screening; Level 2 consists of high throughput in vitro screening with human cells intended to provide broad coverage of possible responses; Level 3 focuses on fit-for-purpose assays selected based on presumptive modes of action (MOA) and designed to provide more quantitative estimates of relevant dose responses; Level 4 has a variety of more complex multi-dimensional or multi-cellular assays and might include targeted in vivo studies to further define MOA. Each level also includes decision-appropriate exposure assessment tools. Our aims here are to (1) foster discussion about context-dependent applications of NAMs in relation to risk assessment needs and (2) describe a functional roadmap to identify where NAMs are expected to be adequate for chemical safety decision-making.

Addressing systematic inconsistencies between in vitro and in vivo transcriptomic mode of action signatures.

Because of their broad biological coverage and increasing affordability transcriptomic technologies have increased our ability to evaluate cellular response to chemical stressors, providing a potential means of evaluating chemical response while decreasing dependence on apical endpoints derived from traditional long-term animal studies. It has recently been suggested that dose-response modeling of transcriptomic data may be incorporated into risk assessment frameworks as a means of approximating chemical hazard. However, identification of mode of action from transcriptomics lacks a similar systematic framework. To this end, we developed a web-based interactive browser-MoAviz-that allows visualization of perturbed pathways. We populated this browser with expression data from a large public toxicogenomic database (TG-GATEs). We evaluated the extent to which gene expression changes from in-life exposures could be associated with mode of action by developing a novel similarity index-the Modified Jaccard Index (MJI)-that provides a quantitative description of genomic pathway similarity (rather than gene level comparison). While typical compound-compound similarity is low (median MJI = 0.026), clustering of the TG-GATES compounds identifies groups of similar chemistries. Some clusters aggregated compounds with known similar modes of action, including PPARa agonists (median MJI = 0.315) and NSAIDs (median MJI = 0.322). Analysis of paired in vitro (hepatocyte)-in vivo (liver) experiments revealed systematic patterns in the responses of model systems to chemical stress. Accounting for these model-specific, but chemical-independent, differences improved pathway concordance by 36% between in vivo and in vitro models.

Assessing bioactivity-exposure profiles of fruit and vegetable extracts in the BioMAP profiling system.

The ToxCast program has generated in vitro screening data on over a thousand chemicals to assess potential disruption of important biological processes and assist in hazard identification and chemical testing prioritization. Few results have been reported for complex mixtures. To extend these ToxCast efforts to mixtures, we tested extracts from 30 organically grown fruits and vegetables in concentration-response in the BioMAP® assays. BioMAP systems use human primary cells primed with endogenous pathway activators to identify phenotypic perturbations related to proliferation, inflammation, immunomodulation, and tissue remodeling. Clustering of bioactivity profiles revealed separation of these produce extracts and ToxCast chemicals. Produce extracts elicited 87 assay endpoint responses per item compared to 20 per item for ToxCast chemicals. On a molar basis, the produce extracts were 10 to 50-fold less potent and when constrained to the maximum testing concentration of the ToxCast chemicals, the produce extracts did not show activity in as many assay endpoints. Using intake adjusted measures of dose, the bioactivity potential was higher for produce extracts than for agrichemicals, as expected based on the comparatively small amounts of agrichemical residues present on conventionally grown produce. The evaluation of BioMAP readouts and the dose responses for produce extracts showed qualitative and quantitative differences from results with single chemicals, highlighting challenges in the interpretation of bioactivity data and dose-response from complex mixtures.

A Qualitative Modeling Approach for Whole Genome Prediction Using High-Throughput Toxicogenomics Data and Pathway-Based Validation.

Efficient high-throughput transcriptomics (HTT) tools promise inexpensive, rapid assessment of possible biological consequences of human and environmental exposures to tens of thousands of chemicals in commerce. HTT systems have used relatively small sets of gene expression measurements coupled with mathematical prediction methods to estimate genome-wide gene expression and are often trained and validated using pharmaceutical compounds. It is unclear whether these training sets are suitable for general toxicity testing applications and the more diverse chemical space represented by commercial chemicals and environmental contaminants. In this work, we built predictive computational models that inferred whole genome transcriptional profiles from a smaller sample of surrogate genes. The model was trained and validated using a large scale toxicogenomics database with gene expression data from exposure to heterogeneous chemicals from a wide range of classes (the Open TG-GATEs data base). The method of predictor selection was designed to allow high fidelity gene prediction from any pre-existing gene expression data set, regardless of animal species or data measurement platform. Predictive qualitative models were developed with this TG-GATES data that contained gene expression data of human primary hepatocytes with over 941 samples covering 158 compounds. A sequential forward search-based greedy algorithm, combining different fitting approaches and machine learning techniques, was used to find an optimal set of surrogate genes that predicted differential expression changes of the remaining genome. We then used pathway enrichment of up-regulated and down-regulated genes to assess the ability of a limited gene set to determine relevant patterns of tissue response. In addition, we compared prediction performance using the surrogate genes found from our greedy algorithm (referred to as the SV2000) with the landmark genes provided by existing technologies such as L1000 (Genometry) and S1500 (Tox21), finding better predictive performance for the SV2000. The ability of these predictive algorithms to predict pathway level responses is a positive step toward incorporating mode of action (MOA) analysis into the high throughput prioritization and testing of the large number of chemicals in need of safety evaluation.

Strain-related differences in mouse lung gene expression over a two-year period of inhalation exposure to styrene: Relevance to human risk assessment.

Both CD-1 and C57BL/6 wildtype (C57BL/6-WT) mice show equivalent short-term lung toxicity from exposures to styrene, while long-term tumor responses are greater in CD-1 mice. We analyzed lung gene expression from styrene exposures lasting from 1-day to 2-years in male mice from these two strains, including a Cyp2f2(-/-) knockout (C57BL/6-KO) and a Cyp2F1/2A13/2B6 transgenic mouse (C57BL/6-TG). With short term exposures (1-day to 1-week), CD-1 and C57BL/6-WT mice had thousands of differentially expressed genes (DEGs), consistent with changes in pathways for cell proliferation, cellular lipid metabolism, DNA-replication and inflammation. C57BL/6-WT mice responded within a single day; CD-1 mice required several days of exposure. The numbers of exposure related DEGs were greatly reduced at longer times (4-weeks to 2-years) with enrichment only for biological oxidations in C57BL/6-WT and metabolism of lipids and lipoproteins in CD-1. Gene expression results indicate a non-genotoxic, mouse specific mode of action for short-term styrene responses related to activation of nuclear receptor signaling and cell proliferation. Greater tumor susceptibility in CD-1 mice correlated with the presence of the Pas1 loci, differential Cytochrome P450 gene expression, down-regulation of Nr4a, and greater inflammatory pathway activation. Very few exposure-related responses occurred at any time in C57BL/6-KO or -TG mice indicating that neither the short term nor long term responses of styrene in mice are relevant endpoints for assessing human risks.

An in vitro approach for prioritization and evaluation of chemical effects on glucocorticoid receptor mediated adipogenesis.

Rising obesity rates worldwide have socio-economic ramifications. While genetics, diet, and lack of exercise are major contributors to obesity, environmental factors may enhance susceptibility through disruption of hormone homeostasis and metabolic processes. The obesogen hypothesis contends that chemical exposure early in development may enhance adipocyte differentiation, thereby increasing the number of adipocytes and predisposing for obesity and metabolic disease. We previously developed a primary human adipose stem cell (hASC) assay to evaluate the effect of environmental chemicals on PPARG-dependent adipogenesis. Here, the assay was modified to determine the effects of chemicals on the glucocorticoid receptor (GR) pathway. In differentiation cocktail lacking the glucocorticoid agonist dexamethasone (DEX), hASCs do not differentiate into adipocytes. In the presence of GR agonists, adipocyte maturation was observed using phenotypic makers for lipid accumulation, adipokine secretion, and expression of key genes. To evaluate the role of environmental compounds on adipocyte differentiation, progenitor cells were treated with 19 prioritized compounds previously identified by ToxPi as having GR-dependent bioactivity, and multiplexed assays were used to confirm a GR-dependent mode of action. Five chemicals were found to be strong agonists. The assay was also modified to evaluate GR-antagonists, and 8/10 of the hypothesized antagonists inhibited adipogenesis. The in vitro bioactivity data was put into context with extrapolated human steady state concentrations (Css) and clinical exposure data (Cmax). These data support using a human adipose-derived stem cell differentiation assay to test the potential of chemicals to alter human GR-dependent adipogenesis.

Evaluating opportunities for advancing the use of alternative methods in risk assessment through the development of fit-for-purpose in vitro assays.

An evolving regulatory, scientific, and legislative landscape is driving a fundamental change in how chemical safety decisions are made. As we move to implement changes, regulatory agencies and industry are beginning to adopt tiered approaches, which leverage high-throughput screening technologies for prioritization and read across, followed by interrogation of "hit chemicals" with more rigorous dose-response assessment either in fit-for-purpose human cell-based assays or with traditional in vivo tests. However, to date, suitable in vitro alternatives do not exist for the vast majority of the organ toxicities that form the basis of current regulatory decisions. To successfully support safety decisions, biologically relevant, quantitative, cell-based assays that evaluate dose-response and identify regions of safety for chemical exposure are required. This review evaluates the current state of the science in the development of such assays, identifies key gaps in the current tests, and recommends areas where research efforts may be focused to help move the risk assessment community towards more wide-spread use of in vitro methods. Our analysis suggests that a key shortcoming in the current efforts is the ability to test volatile compounds and to predict pulmonary toxicity. We present a mechanistically-based path forward for the development of a fit-for-purpose lung toxicity assay.