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Selecting a Minimal set of Androgen Receptor Assays for Screening Chemicals
Citation:
Judson, R., K. Houck, K. Friedman, J. Brown, P. Browne, P. Johnston, D. Close, K. Mansouri, AND N. Kleinstreuer. Selecting a Minimal set of Androgen Receptor Assays for Screening Chemicals. REGULATORY TOXICOLOGY AND PHARMACOLOGY. Elsevier Science Ltd, New York, NY, 117(November 2020):104764, (2020). https://doi.org/10.1016/j.yrtph.2020.104764
Impact/Purpose:
This manuscript describes a pathway-based model for using multiple in vitro assays for androgen receptor (AR) activity to determine true AR activity in the face of assay interference and noise. A previously published paper (Kleinstreuer et al 2015) demonstrated that a model containing 12 AR assays could give good concordance with reference chemical activity and could exclude false positive activity due to assay interference. The present manuscript extends that work by evaluating “subset models” with fewer assays to find the most parsimonious model that can achieve acceptable performance. The result is that there are agonist mode models with as few as 6 assays and antagonist mode models with as few as 5 assays that can yield 95% balanced accuracy relative to the full model. The equivalent approach for estrogen receptor (ER) is under consideration by EPA and OECD for use as an integrated approach to testing and assessment (IATA). The results in the current manuscript will be used to support such an IATA approach for AR.
Description:
Screening certain environmental chemicals for their ability to interact with endocrine targets, including the androgen receptor (AR), is an important global concern. We previously developed a model using a battery of eleven in vitro AR assays to predict in vivo AR activity. Here we describe a revised mathematical modeling approach that also incorporates data from newly available assays and demonstrate that subsets of assays can provide close to the same level of predictivity. These subset models are evaluated against the full model using 1820 chemicals, as well as in vitro and in vivo reference chemicals from the literature. Agonist batteries of as few as six assays and antagonist batteries of as few as five assays can yield balanced accuracies of 95% or better relative to the full model. Balanced accuracy for predicting reference chemicals is 100%. An approach is outlined for researchers to develop their own subset batteries to accurately detect AR activity using assays that map to the pathway of key molecular and cellular events involved in chemical-mediated AR activation and transcriptional activity. This work indicates in vitro bioactivity and in silico predictions that map to the AR pathway could be used in an integrated approach to testing and assessment for identifying chemicals that interact directly with the mammalian AR.
URLs/Downloads:
DOI: Selecting a Minimal set of Androgen Receptor Assays for Screening Chemicals
https://pubmed.ncbi.nlm.nih.gov/32798611/