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Integrated Model of Chemical Perturbations of a Biological Pathway Using 18 In Vitro High Throughput Screening Assays for the Estrogen Receptor

Judson, Richard S. and Magpantay, Felicia Maria and Chickarmane, Vijay and Haskell, Cymra and Tania, Nessy and Taylor, Jean and Xia, Menghang and Huang, Ruili and Rotroff, Daniel M. and Filer, Dayne L. and Houck, Keith A. and Martin, Matthew T. and Sipes, Nisha and Richard, Ann M. and Mansouri, Kamel and Setzer, R. Woodrow and Knudsen, Thomas B. and Crofton, Kevin M. and Thomas, Russell S. (2015) Integrated Model of Chemical Perturbations of a Biological Pathway Using 18 In Vitro High Throughput Screening Assays for the Estrogen Receptor. Toxicological Sciences, 148 (1). pp. 137-154. ISSN 1096-6080. PMCID PMC4635633. https://resolver.caltech.edu/CaltechAUTHORS:20150825-135943801

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Abstract

We demonstrate a computational network model that integrates 18 in vitro, high-throughput screening assays measuring estrogen receptor (ER) binding, dimerization, chromatin binding, transcriptional activation and ER-dependent cell proliferation. The network model uses activity patterns across the in vitro assays to predict whether a chemical is an ER agonist or antagonist, or is otherwise influencing the assays through a manner dependent on the physics and chemistry of the technology platform (“assay interference”). The method is applied to a library of 1812 commercial and environmental chemicals, including 45 ER positive and negative reference chemicals. Among the reference chemicals, the network model correctly identified the agonists and antagonists with the exception of very weak compounds whose activity was outside the concentration range tested. The model agonist score also correlated with the expected potency class of the active reference chemicals. Of the 1812 chemicals evaluated, 111 (6.1%) were predicted to be strongly ER active in agonist or antagonist mode. This dataset and model were also used to begin a systematic investigation of assay interference. The most prominent cause of false-positive activity (activity in an assay that is likely not due to interaction of the chemical with ER) is cytotoxicity. The model provides the ability to prioritize a large set of important environmental chemicals with human exposure potential for additional in vivo endocrine testing. Finally, this model is generalizable to any molecular pathway for which there are multiple upstream and downstream assays available.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1093/toxsci/kfv168 DOIArticle
https://academic.oup.com/toxsci/article-lookup/doi/10.1093/toxsci/kfv168PublisherArticle
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4635633PubMed CentralArticle
Additional Information:Published by Oxford University Press on behalf of the Society of Toxicology 2015. This work is written by US Government employees and is in the public domain in the US. Received April 14, 2015. Revision received July 6, 2015. Accepted July 23, 2015. First published online: August 13, 2015. The authors gratefully acknowledge the American Institute of Mathematics and National Science Foundation for support of this research through the “Modeling Problems Related to Our Environment” workshop held January 14-18, 2013 in Palo Alto, California. All other funding was provided by the U.S. EPA. The views expressed in this paper are those of the authors and do not necessarily reflect the views or policies of the U.S. Environmental Protection Agency.
Funders:
Funding AgencyGrant Number
American Institute of MathematicsUNSPECIFIED
NSFUNSPECIFIED
Environmental Protection Agency (EPA)UNSPECIFIED
Subject Keywords:estrogen receptor; EDSP; high-throughput screening; In vitro; prioritization; biological modeling
Issue or Number:1
PubMed Central ID:PMC4635633
Record Number:CaltechAUTHORS:20150825-135943801
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20150825-135943801
Official Citation:Richard S. Judson, Felicia Maria Magpantay, Vijay Chickarmane, Cymra Haskell, Nessy Tania, Jean Taylor, Menghang Xia, Ruili Huang, Daniel M. Rotroff, Dayne L. Filer, Keith A. Houck, Matthew T. Martin, Nisha Sipes, Ann M. Richard, Kamel Mansouri, R. Woodrow Setzer, Thomas B. Knudsen, Kevin M. Crofton, and Russell S. Thomas Integrated Model of Chemical Perturbations of a Biological Pathway Using 18 In Vitro High-Throughput Screening Assays for the Estrogen Receptor Toxicol. Sci. (2015) 148 (1): 137-154 first published online August 13, 2015 doi:10.1093/toxsci/kfv168
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:59893
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:25 Aug 2015 21:14
Last Modified:03 Oct 2019 08:51

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