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.

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.

An in vitro approach to determine the human relevance of anti-spermatogenic effects of 4-methylmorpholine 4-oxide, monohydrate (NMMO) in rat reproductive toxicity studies.

Reduced sperm counts have been observed in male rats in an extended one generation reproductive toxicity study (EOGRTS, OECD 443) following repeated administration of 300 mg/kg/day N-Methylmorpholine N-oxide (NMMO). However, no adverse effects on reproductive organs have been reported in studies conducted with NMMO, and the mode of action (MOA) for the effects of NMMO on spermatogenesis is unknown, which complicates the interpretation of these data for human risk assessment. Here, a New Approach Method (NAM) strategy was used to evaluate NMMO MOA and compare interspecies susceptibility for anti-spermatogenic effects using organotypic in vitro assays combined with in vitro metabolism and in vitro to in vivo extrapolation (IVIVE) biokinetic modeling to compare predicted oral equivalent doses (OEDs) in human and rat. Dose-response data were collected in isolated germ cells and in an ex vivo seminiferous tubule model that recapitulates the interaction between the somatic environment and differentiating germ cells to account for potential direct and indirect effects on germ cells. With regard to direct spermatogenic effects, the human isolated germ cell model showed no toxicity at doses ≤300 µM (OED ≤ 86 mg/kg/day). With regard to indirect effects, the rat ex vivo model demonstrated dose-dependent decreases in secondary spermatocyte populations at OEDs ≥89 mg/kg/day, and reduced expression of RNAs specific to several stages of spermatogenesis (spermatogonia, pachytene spermatocytes, round spermatids) at OED = 267 mg/kg/day, consistent with in vivo observations. In contrast, the monkey ex vivo model did not show dose-dependent decreases in these same RNAs, and often demonstrated increased trends instead. These studies demonstrate clear quantitative and qualitative differences in the rat and primate response to NMMO. Furthermore, effects observed in the rat in vitro culture were not observed in the monkey at concentrations equivalent to in vivo doses of up to 1376 mg/kg/day, which is higher than the in vivo dose limit in the EOGRT study, indicating that the isolated findings on spermatogenesis in the rat studies are not likely to be relevant to humans.

Time-dependent genomic response in primary human uroepithelial cells exposed to arsenite for up to 60 days.

Evidence from both in vivo and in vitro studies suggests that gene expression changes from long-term exposure to arsenite evolve markedly over time, including reversals in the direction of expression change in key regulatory genes. In this study, human uroepithelial cells from the ureter segments of 4 kidney-donors were continuously treated in culture with arsenite at concentrations of 0.1 or 1 µM for 60 days. Gene expression at 10, 20, 30, 40, and 60 days was determined using Affymetrix human genome microarrays and signal pathway analysis was performed using GeneGo Metacore. Arsenic treated cells continued to proliferate for the full 60-day period, whereas untreated cells ceased proliferating after approximately 30 days. A peak in the number of gene changes in the treated cells compared to untreated controls was observed between 30 and 40 days of exposure, with substantially fewer changes at 10 and 60 days, suggesting remodeling of the cells over time. Consistent with this possibility, the direction of expression change for a number of key genes was reversed between 20 and 30 days, including CFOS and MDM2. While the progression of gene changes was different for each subject, a common pattern was observed in arsenic treated cells over time, with early upregulation of oxidative stress responses (HMOX1, NQ01, TXN, TXNRD1) and down-regulation of immune/inflammatory responses (IKKα). At around 30 days, there was a transition to increased inflammatory and proliferative signaling (AKT, CFOS), evidence of epithelial-to-mesenchymal transition (EMT), and alterations in DNA damage responses (MDM2, ATM). A common element in the changing response of cells to arsenite over time appears to involve up-regulation of MDM2 by inflammatory signaling (through AP-1 and NF-κB), leading to inhibition of P53 function.

Development of a physiologically based pharmacokinetic model of diisononyl phthalate (DiNP) in pregnant rat and human.

A physiologically based pharmacokinetic (PBPK) model for di-isononyl phthalate (DiNP) was developed by adapting the existing models for di(2-ethylhexyl) phthalate (DEHP) and di-butylphthalate (DBP). Both pregnant rat and human time-course plasma and urine data were used to address the hydrolysis of DiNP in intestinal tract, plasma, and liver as well as hepatic oxidative metabolism and conjugation of the monoester and primary oxidative metabolites. Data in both rats and humans were available to inform the uptake and disposition of mono-isononyl phthalate (MiNP) as well as the three primary oxidative metabolites including hydroxy (7-OH)-, oxo (7-OXO)-, and carboxy (7-COX)-monoisononyl phthalate in plasma and urine. The DiNP model was reliable over a wide range of exposure levels in the pregnant rat as well as the two low exposure levels in humans including capturing the nonlinear behavior in the pregnant rat after repeated 750 mg/kg/day dosing. The presented DiNP PBPK model in pregnant rat and human, based upon an extensive kinetic dataset in both species, may provide a basis for assessing human equivalent exposures based upon either rodent or in vitro points of departure.

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.

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.

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.

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.

An evaluation of the USEPA Proposed Approaches for applying a biologically based dose-response model in a risk assessment for perchlorate in drinking water.

The United States Environmental Protection Agency's (USEPA) 2017 report, "Draft Report: Proposed Approaches to Inform the Derivation of a Maximum Contaminant Level Goal for Perchlorate in Drinking Water", proposes novel approaches for deriving a Maximum Contaminant Level Goal (MCLG) for perchlorate using a biologically-based dose-response (BBDR) model. The USEPA (2017) BBDR model extends previously peer-reviewed perchlorate models to describe the relationship between perchlorate exposure and thyroid hormone levels during early pregnancy. Our evaluation focuses on two key elements of the USEPA (2017) report: the plausibility of BBDR model revisions to describe control of thyroid hormone production in early pregnancy and the basis for linking BBDR model results to neurodevelopmental outcomes. While the USEPA (2017) BBDR model represents a valuable research tool, the lack of supporting data for many of the model assumptions and parameters calls into question the fitness of the extended BBDR model to support quantitative analyses for regulatory decisions on perchlorate in drinking water. Until more data can be developed to address uncertainties in the current BBDR model, USEPA should continue to rely on the RfD recommended by the NAS (USEPA, 2005) when considering further regulatory action.

Dose-dependence of chemical carcinogenicity: Biological mechanisms for thresholds and implications for risk assessment.

Current regulatory practices for chemical carcinogens were established when scientific understanding of the molecular mechanisms of chemical carcinogenesis was in its infancy. Initial discovery that DNA mutation was the root of cancer led quickly to regulatory processes that assumed such a simple relationship could be described with a linear approach. This linear, no threshold approach has since become the default approach to risk assessment of chemicals with carcinogenic potential. Since then, a multitude of intrinsic processes have been identified at the molecular, cellular and organism level that work to prevent transient DNA damage from causing permanent mutations, and mutated cells from becoming cancer. Mounting evidence indicates that these protective mechanisms can prevent carcinogenesis at low doses of genotoxic chemicals, leading to non-linear dose-response. Further, a number of non-genotoxic mechanisms have demonstrated threshold-shaped dose-response for cancer outcomes. The existence of non-linear dose-response curves for both non-genotoxic and genotoxic chemical carcinogens stands in stark contrast to the default risk assessment approach that assumes low dose linearity. In this review, we highlight some of the key discoveries and technological advances that have influenced scientific understanding of chemical carcinogenesis over the last fifty years and provide case studies to demonstrate the utility of these modern technologies in providing a biologically robust evaluation of chemical dose-response for cancer risk assessment.

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.

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.

Multiple receptors shape the estrogen response pathway and are critical considerations for the future of in vitro-based risk assessment efforts.

Current in life toxicity testing paradigms are being challenged as the future of risk assessment moves towards more comprehensive mode of action/adverse outcome pathway based approaches. In particular, endocrine disruption screening is now a global activity and key initiatives in the United States focus on the use of high throughput in vitro assays to prioritize compounds for further testing of estrogen, androgen or thyroid disruption. Of these pathways, much of the emphasis to date has been on high-throughput methods for estrogenic activity primarily using ligand binding and trans-activation assays. However, as the knowledge regarding estrogen receptor signaling pathways continues to evolve, it is clear that the assumption of a simple one-receptor pathway underlying current in vitro screening assays is out of date. To develop more accurate models for estrogen-initiated pathways useful for quantitative safety assessments, we must design assays that account for the key signaling processes driving cellular dose response based on up-to-date understanding of the biological network. In this review, we summarize the state of the science for the estrogen receptor signaling network, particularly with regard to proliferative effects, and highlight gaps in current high throughput approaches. From the sum of this literature, we propose a model for the estrogen-signaling pathway that should serve as a starting point for development of new in vitro methods fit for the purpose of predicting dose response for estrogenic chemicals in the human.

Contribution of ATM and ATR kinase pathways to p53-mediated response in etoposide and methyl methanesulfonate induced DNA damage.

p53 is a key integrator of cellular response to DNA damage, supporting post-translational repair and driving transcription-mediated responses including cell cycle arrest, apoptosis, and repair. DNA damage sensing kinases recognize different types of DNA damage and initiate specific responses through various post-translational modifications of p53. This study evaluated chemical specificity of the p53 pathway response by manipulating p53 or its upstream kinases and assessing the effect on DNA damage and cellular responses to prototype chemicals: etoposide (ETP, topoisomerase II inhibitor) and methyl methane sulfonate (MMS, alkylating agent). p53-deficient cells demonstrated reduced accumulation of the p53 target proteins MDM2, p21, and Wip1; reduced apoptotic response; and increased DNA damage (p-H2AX and micronuclei) with both chemicals. However, p53 was not essential for cell cycle arrest in HT1080 or HCT116 cells. The two chemicals induced different patterns of kinase activation, particularly in terms of Chk 1, Chk 2, p38, and ERK 1/2. However, inhibition of the ATM pathway showed a greater effect on p53 activtation, apoptosis, and accumulation of DNA damage than ATR-Chk 1 or the MAP kinases regardless of the chemical used. These results indicate that ATM is the predominant upstream kinase responsible for activation of the p53-mediated DNA damage response for both MMS and ETP, though the downstream kinase response is markedly different. Environ. Mol. Mutagen. 58:72-83, 2017. © 2017 Wiley Periodicals, Inc.

Editor's Highlight: Screening ToxCast Prioritized Chemicals for PPARG Function in a Human Adipose-Derived Stem Cell Model of Adipogenesis.

The developmental origins of obesity hypothesis posits a multifaceted contribution of factors to the fetal origins of obesity and metabolic disease. Adipocyte hyperplasia in gestation and early childhood may result in predisposition for obesity later in life. Rodent in vitro and in vivo studies indicate that some chemicals may directly affect adipose progenitor cell differentiation, but the human relevance of these findings is unclear. The nuclear receptor peroxisome proliferator-activated receptor gamma (PPARG) is the master regulator of adipogenesis. Human adipose-derived stem cells (hASC) isolated from adipose tissue express endogenous isoforms of PPARG and represent a biologically relevant cell-type for evaluating activity of PPARG ligands. Here, a multi-endpoint approach based on a phenotypic adipogenesis assay was applied to screen a set of 60 chemical compounds identified in ToxCast Phase I as PPARG active (49) or inactive (11). Chemicals showing activity in the adipogenesis screen were further evaluated in a series of 4 orthogonal assays representing 7 different key events in PPARG-dependent adipogenesis, including gene transcription, protein expression, and adipokine secretion. An siRNA screen was also used to evaluate PPARG-dependence of the adipogenesis phenotype. A universal concentration-response design enabled inter-assay comparability and implementation of a weight-of-evidence approach for bioactivity classification. Collectively, a total of 14/49 (29%) prioritized chemicals were identified with moderate-to-strong activity for human adipogenesis. These results provide the first integrated screening approach of prioritized ToxCast chemicals in a human stem cell model of adipogenesis and provide insight into the capacity of PPARG-activating chemicals to modulate early life programming of adipose tissue.