A New Approach Methodology (NAM) Based Assessment of Butylated hydroxytoluene (BHT) for Endocrine Disruption Potential.

Butylated hydroxytoluene (BHT) is a synthetic antioxidant widely used in many industrial sectors. BHT is a well-studied compound for which there are many favorable regulatory decisions. However, a recent opinion by the French Agency for Food, Environmental and Occupational Health and Safety (ANSES) hypothesizes a role for BHT in endocrine disruption (ANSES (2021). This opinion is based on observations in mostly rat studies where changes to thyroid physiology are observed. Enzymatic induction of Cytochrome P450-mediated thyroid hormone catabolism has been proposed as a mechanism for these observations, however, a causal relationship has not been proven. Other evidence proposed in the document includes a read across argument to butylated hydroxyanisole (BHA), another Community Rolling Action Plan (CoRAP)-listed substance with endocrine disruption concerns. We tested the hypothesis that BHT is an endocrine disruptor by using a Next Generation Risk Assessment (NGRA) method. Four different cell lines: A549, HCC1428, HepG2, and MCF7 were treated with BHT and a series of BHT analogs at 5 different concentrations, RNA was isolated from cell extracts and run on the L1000 gene array platform. A toxicogenomics-based assessment was performed by comparing BHT's unique genomic signature to a large external database containing signatures of other compounds (including many known endocrine disruptors) to identify if any endocrine disruption-related modes of action (MoAs) are prevalent among BHT and other compounds with similar genomic signatures. In addition, we performed a toxicogenomics-based structure activity relationship (SAR) assessment of BHT and a series of structurally similar analogs to understand if endocrine disruption is a relevant MoA for chemicals that are considered suitable analogs to BHT using the P&G read across framework (Wu et al., 2010). Neither BHT nor any of its analogs connected to compounds that had endocrine activity for estrogens, androgens, thyroid, or steroidogenesis.

FutureTox IV Workshop Summary: Predictive Toxicology for Healthy Children.

FutureTox IV, a Society of Toxicology Contemporary Concepts in Toxicology workshop, was held in November 2018. Building upon FutureTox I, II, and III, this conference focused on the latest science and technology for in vitro profiling and in silico modeling as it relates to predictive developmental and reproductive toxicity (DART). Publicly available high-throughput screening data sets are now available for broad in vitro profiling of bioactivities across large inventories of chemicals. Coupling this vast amount of mechanistic data with a deeper understanding of molecular embryology and post-natal development lays the groundwork for using new approach methodologies (NAMs) to evaluate chemical toxicity, drug efficacy, and safety assessment for embryo-fetal development. NAM is a term recently adopted in reference to any technology, methodology, approach, or combination thereof that can be used to provide information on chemical hazard and risk assessment to avoid the use of intact animals (U.S. Environmental Protection Agency [EPA], Strategic plan to promote the development and implementation of alternative test methods within the tsca program, 2018, https://www.epa.gov/sites/production/files/2018-06/documents/epa_alt_strat_plan_6-20-18_clean_final.pdf). There are challenges to implementing NAMs to evaluate chemicals for developmental toxicity compared with adult toxicity. This forum article reviews the 2018 workshop activities, highlighting challenges and opportunities for applying NAMs for adverse pregnancy outcomes (eg, preterm labor, malformations, low birth weight) as well as disorders manifesting postnatally (eg, neurodevelopmental impairment, breast cancer, cardiovascular disease, fertility). DART is an important concern for different regulatory statutes and test guidelines. Leveraging advancements in such approaches and the accompanying efficiencies to detecting potential hazards to human development are the unifying concepts toward implementing NAMs in DART testing. Although use of NAMs for higher level regulatory decision making is still on the horizon, the conference highlighted novel testing platforms and computational models that cover multiple levels of biological organization, with the unique temporal dynamics of embryonic development, and novel approaches for estimating toxicokinetic parameters essential in supporting in vitro to in vivo extrapolation.

A comparison of classical and 21st century genotoxicity tools: A proof of concept study of 18 chemicals comparing in vitro micronucleus, ToxTracker and genomics-based methods (TGx-DDI, whole genome clustering and connectivity mapping).

A key step in the risk assessment process of a substance is the assessment of its genotoxic potential. Irrespective of the industry involved, current approaches rely on combinations of two or three in vitro tests and while highly sensitive, their specificity is thought to be limited. A refined in vitro genotoxicity testing strategy with improved predictive capacity would be beneficial and "3R" friendly as it helps to avoid unnecessary in vivo follow-up testing. Here, we describe a proof of concept study evaluating a balanced set of compounds that have in vivo negative or positive outcomes, but variable in vitro data, to determine if we could differentiate between direct and indirect acting genotoxicants. Compounds were examined in TK6 cells using an approach in which the same sample was used to evaluate both early genomic markers (Affymetrix analysis 4 hr post treatment), and the genotoxic outcome (micronuclei [MN] after 24 hr). The resulting genomic data was then analyzed using the TGx-DDI biomarker, Connectivity mapping and whole genome clustering. Chemicals were also tested in the ToxTracker assay, which uses six different biomarker genes. None of the methods correctly differentiated all direct from indirect acting genotoxicants when used alone, however, the ToxTracker assay, TGx-DDI biomarker and whole genome approaches provided high predictive capacity when used in combination with the MN assay (1/18, 2/18, 1/18 missed calls). Ultimately, a "fit for purpose" combination will depend on the specific tools available to the end user, as well as considerations of the unique benefits of the individual assays.

Use of connectivity mapping to support read across: A deeper dive using data from 186 chemicals, 19 cell lines and 2 case studies.

We previously demonstrated that the Connectivity Map (CMap) (Lamb et al., 2006) concept can be successfully applied to a predictive toxicology paradigm to generate meaningful MoA-based connections between chemicals (De Abrew et al., 2016). Here we expand both the chemical and biological (cell lines) domain for the method and demonstrate two applications, both in the area of read across. In the first application we demonstrate CMap's utility as a tool for testing biological relevance of source chemicals (analogs) during a chemistry led read across exercise. In the second application we demonstrate how CMap can be used to identify functionally relevant source chemicals (analogs) for a structure of interest (SOI)/target chemical with minimal knowledge of chemical structure. Finally, we highlight four factors: promiscuity of chemical, dose, cell line and timepoint as having significant impact on the output. We discuss the biological relevance of these four factors and incorporate them into a work flow.

Grouping 34 Chemicals Based on Mode of Action Using Connectivity Mapping.

Connectivity mapping is a method used in the pharmaceutical industry to find connections between small molecules, disease states, and genes. The concept can be applied to a predictive toxicology paradigm to find connections between chemicals, adverse events, and genes. In order to assess the applicability of the technique for predictive toxicology purposes, we performed gene array experiments on 34 different chemicals: bisphenol A, genistein, ethinyl-estradiol, tamoxifen, clofibrate, dehydorepiandrosterone, troglitazone, diethylhexyl phthalate, flutamide, trenbolone, phenobarbital, retinoic acid, thyroxine, 1α,25-dihydroxyvitamin D3, clobetasol, farnesol, chenodeoxycholic acid, progesterone, RU486, ketoconazole, valproic acid, desferrioxamine, amoxicillin, 6-aminonicotinamide, metformin, phenformin, methotrexate, vinblastine, ANIT (1-naphthyl isothiocyanate), griseofulvin, nicotine, imidacloprid, vorinostat, 2,3,7,8-tetrachloro-dibenzo-p-dioxin (TCDD) at the 6-, 24-, and 48-hour time points for 3 different concentrations in the 4 cell lines: MCF7, Ishikawa, HepaRG, and HepG2 GEO (super series accession no.: GSE69851). The 34 chemicals were grouped in to predefined mode of action (MOA)-based chemical classes based on current literature. Connectivity mapping was used to find linkages between each chemical and between chemical classes. Cell line-specific linkages were compared with each other and to test whether the method was platform and user independent, a similar analysis was performed against publicly available data. The study showed that the method can group chemicals based on MOAs and the inter-chemical class comparison alluded to connections between MOAs that were not predefined. Comparison to the publicly available data showed that the method is user and platform independent. The results provide an example of an alternate data analysis process for high-content data, beneficial for predictive toxicology, especially when grouping chemicals for read across purposes.

A novel transcriptomics based in vitro method to compare and predict hepatotoxicity based on mode of action.

High-content data have the potential to inform mechanism of action for toxicants. However, most data to support this notion have been generated in vivo. Because many cell lines and primary cells maintain a differentiated cell phenotype, it is possible that cells grown in culture may also be useful in predictive toxicology via high-content approaches such as whole-genome microarray. We evaluated global changes in gene expression in primary rat hepatocytes exposed to two concentrations of ten hepatotoxicants: acetaminophen (APAP), ß-naphthoflavone (BNF), chlorpromazine (CPZ), clofibrate (CLO), bis(2-ethylhexyl)phthalate (DEHP), diisononyl phthalate (DINP), methapyrilene (MP), valproic acid (VPA), phenobarbital (PB) and WY14643 at two separate time points. These compounds were selected to cover a range of mechanisms of toxicity, with some overlap in expected mechanism to address the question of how predictive gene expression analysis is, for a given mode of action. Gene expression microarray analysis was performed on cells after 24h and 48h of exposure to each chemical using Affymetrix microarrays. Cluster analysis suggests that the primary hepatocyte model was capable of responding to these hepatotoxicants, with changes in gene expression that appear to be mode of action-specific. Among the different methods used for analysis of the data, a combination method that used pathways (MOAs) to filter total probesets provided the most robust analysis. The analysis resulted in the phthalates clustering closely together, with the two other peroxisome proliferators, CLO and WY14643, eliciting similar responses at the whole-genome and pathway levels. The Cyp inducers PB, MP, CPZ and BNF also clustered together. VPA and APAP had profiles that were unique. A similar analysis was performed on externally available (TG-GATES) in vivo data for 6 of the chemicals (APAP, CLO, CPZ, MP, MP and WY14643) and compared to the in vitro result. These results indicate that transcription profiling using an in vitro assay may offer pertinent biological data to support predictions of in vivo hepatotoxicity potential.

TCDD induces dermal accumulation of keratinocyte-derived matrix metalloproteinase-10 in an organotypic model of human skin.

The epidermis of skin is the first line of defense against the environment. A three dimensional model of human skin was used to investigate tissue-specific phenotypes induced by the environmental contaminant, 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD). Continuous treatment of organotypic cultures of human keratinocytes with TCDD resulted in intracellular spaces between keratinocytes of the basal and immediately suprabasal layers as well as thinning of the basement membrane, in addition to the previously reported hyperkeratinization. These tissue remodeling events were preceded temporally by changes in expression of the extracellular matrix degrading enzyme, matrix metalloproteinase-10 (MMP-10). In organotypic cultures MMP-10 mRNA and protein were highly induced following TCDD treatment. Q-PCR and immunoblot results from TCDD-treated monolayer cultures, as well as indirect immunofluorescence and immunoblot analysis of TCDD-treated organotypic cultures, showed that MMP-10 was specifically contributed by the epidermal keratinocytes but not the dermal fibroblasts. Keratinocyte-derived MMP-10 protein accumulated over time in the dermal compartment of organotypic cultures. TCDD-induced epidermal phenotypes in organotypic cultures were attenuated by the keratinocyte-specific expression of tissue inhibitor of metalloproteinase-1, a known inhibitor of MMP-10. These studies suggest that MMP-10 and possibly other MMP-10-activated MMPs are responsible for the phenotypes exhibited in the basement membrane, the basal keratinocyte layer, and the cornified layer of TCDD-treated organotypic cultures. Our studies reveal a novel mechanism by which the epithelial-stromal microenvironment is altered in a tissue-specific manner thereby inducing structural and functional pathology in the interfollicular epidermis of human skin.

Regulation of Bach2 by the aryl hydrocarbon receptor as a mechanism for suppression of B-cell differentiation by 2,3,7,8-tetrachlorodibenzo-p-dioxin.

Exposure to the aryl hydrocarbon receptor (AHR) agonist, 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) alters B-cell differentiation and suppresses antibody production. Previous genomic studies in mouse B cells identified Bach2 as a direct target of the AHR. Bach2 is known to repress expression of Prdm1, a key transcription factor involved in B-cell differentiation, by binding to Maf elements (MAREs) in the regulatory regions of the gene. Chromatin immunoprecipitation followed by quantitative PCR in TCDD-treated lipopolysaccharide (LPS)-activated B cells showed increased binding of the AHR within the first intron in the Bach2 gene. The binding was further confirmed by electrophoretic mobility shift assay (EMSA). TCDD also induced expression of Bach2 in activated as well as resting B cells from 2 to 24h post-treatment in a time- and concentration-dependent manner. Expression of Prdm1 was decreased by TCDD at 24h and was consistent with repression by Bach2. Increased DNA binding activity to the intron 5 MARE with increasing TCDD concentrations was observed by EMSA. Supershifts identified the presence of Bach2 in the DNA binding complex associated with the intron 5 MARE of Prdm1. Functional validation of the role of Bach2 in the suppression of B-cell differentiation by TCDD was performed using RNA interference (RNAi). Knockdown of Bach2 showed approximately 40% reversal in the TCDD-induced suppression of IgM secretion when compared to controls. The results suggest that the transcriptional regulation of Bach2 by the AHR is one of the mechanisms involved in the suppression of B-cell differentiation by TCDD.

An integrated genomic analysis of aryl hydrocarbon receptor-mediated inhibition of B-cell differentiation.

The aryl hydrocarbon receptor (AHR) agonist 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) alters differentiation of B cells and suppresses antibody production. A combination of whole-genome, microarray-based chromatin immunoprecipitation (ChIP-on-chip), and time course gene expression microarray analysis was performed on the mouse B-cell line CH12.LX following exposure to lipopolysaccharide (LPS) or LPS and TCDD to identify the primary and downstream transcriptional elements of B-cell differentiation that are altered by the AHR. ChIP-on-chip analysis identified 1893 regions with a significant increase in AHR binding with TCDD treatment. Transcription factor binding site analysis on the ChIP-on-chip data showed enrichment in AHR response elements. Other transcription factors showed significant coenrichment with AHR response elements. When ChIP-on-chip regions were compared with gene expression changes at the early time points, 78 genes were identified as potential direct targets of the AHR. AHR binding and expression changes were confirmed for a subset of genes in primary mouse B cells. Network analysis examining connections between the 78 potential AHR target genes and three transcription factors known to regulate B-cell differentiation indicated multiple paths for potential regulation by the AHR. Enrichment analysis on the differentially expressed genes at each time point evaluated the downstream impact of AHR-regulated gene expression changes on B-cell-related processes. AHR-mediated impairment of B-cell differentiation occurred at multiple nodes of the B-cell differentiation network and potentially through multiple mechanisms including direct cis-acting effects on key regulators of B-cell differentiation, indirect regulation of B-cell differentiation-related pathways, and transcriptional coregulation of target genes by AHR and other transcription factors.