Profiling the Toxcast Library with a Pluripotent Human (H9) Stem Cell Line-Based Biomarker Assay for Developmental Toxici- Ty[AQ2][AQ3]

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Profiling the Toxcast Library with a Pluripotent Human (H9) Stem Cell Line-Based Biomarker Assay for Developmental Toxici- Ty[AQ2][AQ3] 1 Profiling the ToxCast Library With a Pluripotent Human (H9) Stem Cell Line-Based Biomarker Assay for Developmental Toxici- ty[AQ2][AQ3] PROFILING THE TOXCAST LIBRARY[AQ1] ZURLINDEN et al. Todd J. Zurlinden * Katerine S. Saili * Nathaniel Rush * Parth Kothiya * Richard S. Judson * Keith A. Houck * E. Sidney Hunter † Nancy C. Baker ‡ Jessica A. Palmer § Russell S. Thomas * and Thomas B. Knudsen*,1[AQ5][AQ4] *. National Center for Computational Toxicology (NCCT) and †. National Health and Environmental Effects Research Laboratory (NHEERL), Office of Research and Development (ORD), U.S. En- vironmental Protection Agency (USEPA), Research Triangle Park, North Carolina 27711; ‡. Leidos, Research Triangle Park, North Carolina 27711; and §. Stemina Biomarker Discovery, Inc, Madison, Wisconsin 53719[AQ6] 1. To whom correspondence should be addressed at National Center for Computational Toxicology (B205-01), U.S. Environmental Protection Agency, Research Triangle Park, NC 27711. E-mail: [email protected].[AQ7] Disclaimer: The views expressed in this article are those of the authors and do not necessarily reflect the views or policies of the U.S. Environmental Protection Agency. Mention of trade names or commercial products does not con‐ stitute endorsement or recommendation for use. ABSTRACT The Stemina devTOX quickPredict platform is a human pluripotent stem cell-based assay that predicts the developmental toxicity potential based on changes in cellular metabolism following chemical exposure [Palmer, J. A., Smith, A. M., Egnash, L. A., Conard, K. R., West, P. R., Burrier, R. E., Donley, E. L. R., and Kirchner, F. R. (2013). Establishment and assessment of a new human embry- onic stem cell-based biomarker assay for developmental toxicity screening. Birth Defects Res. B Dev. Reprod. Toxicol. 98, 343– 363]. Using this assay, we screened 1065 ToxCast phase I and II chemicals in single-concentration or concentration-response for the targeted biomarker (ratio of ornithine to cystine secreted or consumed from the media). The dataset from the Stemina (STM) assay is annotated in the ToxCast portfolio as STM. Major findings from the analysis of ToxCast_STM dataset include (1) 19% of 1065 chemicals yielded a prediction of developmental toxicity, (2) assay performance reached 79%–82% accuracy with high spe- cificity (> 84%) but modest sensitivity (< 67%) when compared with in vivo animal models of human prenatal developmental toxicity, (3) sensitivity improved as more stringent weights of evidence requirements were applied to the animal studies, and (4) statistical analysis of the most potent chemical hits on specific biochemical targets in ToxCast revealed positive and negative associations with the STM response, providing insights into the mechanistic underpinnings of the targeted endpoint and its bio- logical domain. The results of this study will be useful to improving our ability to predict in vivo developmental toxicants based on in vitro data and in silico models. Keywords: predictive toxicology ; developmental toxicity ; embryonic stem cells In 2007, the National Research Council published Toxicity Testing in the 21st Century: A Vision and a Strategy (Na‐ tional Research Council, 2007). This report addressed the potential for automated high-throughput screening (HTS) and high-content screening (HCS) assays and technologies to identify chemically induced biological activity in hu‐ man cells and to develop predictive models of in vivo biological response that would ignite a shift from traditional animal endpoint-based testing to human pathway-based risk assessment (Collins et al., 2008). Concurrent with the NRC 2007 report, the U.S. Environmental Protection Agency (USEPA) launched the ToxCast research program that utilized statistical methods and machine learning algorithms in combination with HTS/HCS data for profiling biologi‐ © Copyrights 2019 cal pathways and building bioactivity signatures predictive of toxicity (Judson et al., 2010, 2016; Kavlock et al., 2012 Kavlock et al., 2012[AQ8]; Richard et al., 2016). An abundance of HTS/HCS data has since fueled the building and testing of integrative models for “encoding the toxicological blueprint of active substances that interact with liv‐ ing systems” ( Juberg et al., 2017 Juberg et al., 2017; Sturla et al., 2014). Impetus for the research and application of HTS/HCS assays is bolstered by the regulatory need to fill information gaps on potential hazards that chemicals might pose to human health and the environment and to identify and imple‐ ment appropriate health-protective risk management measures under the Registration, Evaluation, and Authorization of Chemicals (REACh) (European Parliament, Council of the European Union, 2006) and The Frank R. Lautenberg Chemical Safety for the 21st Century Act (amended Toxic Substances Control Act) in the United States (US Public Law 114–182, 2016). Under amended Toxic Substances Control Act, for example, the USEPA must encourage and facilitate “… the use of scientifically valid test methods and strategies that reduce or replace the use of vertebrate animals while providing information of equivalent or better scientific quality and relevance that will support regulato‐ ry decisions …” and consider the impacts of chemicals and chemical mixtures to “… potentially exposed or suscepti‐ ble subpopulation … who, due to either greater susceptibility or greater exposure, may be at greater risk than the general population of adverse health effects from exposure to a chemical substance or mixture, such as infants, chil‐ dren, pregnant women, workers, or the elderly.” (US Public Law 114–182, 2016). REACh regulation cites identifica‐ tion of derived no effect levels “for each relevant human population (e.g. workers, consumers and humans liable to exposure indirectly via the environment) and possibly for certain vulnerable sub-populations (e.g. children, pregnant women) …” and the need to “… to replace, reduce or refine testing on vertebrate animals” (European Parliament, Council of the European Union, 2006). These regulations highlight the need for in vitro assays and in silico models that can be used to evaluate the developmental toxicity potential of chemicals in screening and prioritization contexts, with less reliance on animal testing. The in vivo protocol commonly used to test for prenatal developmental toxicity (ie, OECD TG 414) is designed for a health-protective effects assessment based on observation of fetal malformations and variations in a study designed to produce a dose-response. The in vivo developmental studies are costly, animal resource intensive, and potentially different in cross-species responses (Knudsen and Daston, 2018; Leist et al., 2014). As such, HTS/HCS-based meth‐ odologies should consider novel in vitro data and in silico models that can effectively and efficaciously profile chemi‐ cals for critical effects on human development and as well point to mechanistic pathways. Some of the most promis‐ ing nonanimal alternatives exploit the self-organizing potential of embryonic stem cells (ESCs) to recapitulate devel‐ opmental processes that may be sensitive to chemical exposure (Bremer and Hartung, 2004; Luz and Tokar, 2018). Endpoints that provide mechanistic support for tissue-specific developmental processes include cardiomyocyte differ‐ entiation (Chandler et al., 2011; Genschow et al., 2002; Seiler and Spielmann, 2011), gene expression (Panzica-Kelly et al., 2013; Pennings et al., 2011), metabolic profiling ( Kleinstreuer et al., 2011 Kleinstreuer et al., 2011; Palmer et al., 2013; West et al., 2010), regulatory, gene-specific biomarkers (Kameoka et al., 2014; Le Coz et al., 2015), stem cell migration (Xing et al., 2015), axial patterning (Warkus and Marikawa, 2017), and histodifferentiation in 3D orga‐ noids (Huch and Koo, 2015). For example, the validated mEST (Genschow et al., 2002) monitors emergence of beat‐ ing cardiomyocytes from pluripotent murine ESCs as the targeted read-out (in parallel with cytotoxicity) to discrimi‐ nate nonteratogens from weak teratogens and strong teratogens. Because the cardiopoietic lineage is ultimately de‐ pendent on heterogeneous interactions with other cell lineages in the culture, either via “embryoid bodies” (Seiler and Spielmann, 2011) or dense monolayers (Chandler et al., 2011), the cardiogenic read-out is an effective surrogate for complex pathways in teratogenicity. These examples show the diversity of alternative test modalities amenable to ESC-based methodologies for developmental hazard prediction in embryogeny. Assays currently represented in the ToxCast portfolio evaluate hundreds of biochemical targets, dozens of signal‐ ing pathways, and a broad range of cellular effects. To increase the diversity of HTS assays used to predict develop‐ mental toxicants, we describe the addition of a human stem cell-based platform to the ToxCast portfolio based on the devTOX quickPredict (devTOXqP) platform (Palmer et al., 2013). This assay, contracted from Stemina Biomarker Discovery, utilizes undifferentiated H9 human embryonic stem cells (hESCs) and measures relative changes in 2 me‐ tabolites, ornithine (ORN) and cystine (CYSS), targeting the ORN/CYSS ratio as a biomarker for developmental tox‐ icity (Palmer et al., 2013, 2017). Ornithine is a nonproteogenic amino acid that functions in several biochemical path‐ ways including ammonia detoxification in the urea cycle, pyrimidine synthesis via ornithine transcarbamylase, and polyamine synthesis via ornithine decarboxylase. Ornithine
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