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Chemical Genomics Profiling of Environmental Chemical Modulation of Human Nuclear Receptors

Background: The large and increasing number of chemicals released into the environment demands more efficient and cost-effective approaches for assessing environmental chemical toxicity. The U.S. Tox21 program has responded to this challenge by proposing alternative strategies for toxicity testing,...

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Detalles Bibliográficos
Autores principales: Huang, Ruili, Xia, Menghang, Cho, Ming-Hsuang, Sakamuru, Srilatha, Shinn, Paul, Houck, Keith A., Dix, David J., Judson, Richard S., Witt, Kristine L., Kavlock, Robert J., Tice, Raymond R., Austin, Christopher P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: National Institute of Environmental Health Sciences 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3237348/
https://www.ncbi.nlm.nih.gov/pubmed/21543282
http://dx.doi.org/10.1289/ehp.1002952
Descripción
Sumario:Background: The large and increasing number of chemicals released into the environment demands more efficient and cost-effective approaches for assessing environmental chemical toxicity. The U.S. Tox21 program has responded to this challenge by proposing alternative strategies for toxicity testing, among which the quantitative high-throughput screening (qHTS) paradigm has been adopted as the primary tool for generating data from screening large chemical libraries using a wide spectrum of assays. Objectives: The goal of this study was to develop methods to evaluate the data generated from these assays to guide future assay selection and prioritization for the Tox21 program. Methods: We examined the data from the Tox21 pilot-phase collection of approximately 3,000 environmental chemicals profiled in qHTS format against a panel of 10 human nuclear receptors (AR, ERα, FXR, GR, LXRβ, PPARγ, PPARδ, RXRα, TRβ, and VDR) for reproducibility, concordance of biological activity profiles with sequence homology of the receptor ligand binding domains, and structure–activity relationships. Results: We determined the assays to be appropriate in terms of biological relevance. We found better concordance for replicate compounds for the agonist-mode than for the antagonist-mode assays, likely due to interference of cytotoxicity in the latter assays. This exercise also enabled us to formulate data-driven strategies for discriminating true signals from artifacts, and to prioritize assays based on data quality. Conclusions: The results demonstrate the feasibility of qHTS to identify the potential for environmentally relevant chemicals to interact with key toxicity pathways related to human disease induction.