Profiling Bioactivity of the ToxCast Chemical Library Using BioMAP Primary Human Cell Systems

被引:83
作者
Houck, Keith A. [1 ]
Dix, David J. [1 ]
Judson, Richard S. [1 ]
Kavlock, Robert J. [1 ]
Yang, Jian [2 ]
Berg, Ellen L. [2 ]
机构
[1] US EPA, Natl Ctr Computat Toxicol, Off Res & Dev, Res Triangle Pk, NC 27711 USA
[2] BioSeek Inc, San Francisco, CA USA
基金
美国国家环境保护局;
关键词
toxicology; primary human cells; bioactivity profiling; chemical genetics; NETWORKS; ATRAZINE; MODELS; PROLIFERATION; GENOMEWIDE; MODULATION; ACTIVATION; EXPRESSION; FUNGICIDES; INHIBITORS;
D O I
10.1177/1087057109345525
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
The complexity of human biology has made prediction of health effects as a consequence of exposure to environmental chemicals especially challenging. Complex cell systems, such as the Biologically Multiplexed Activity Profiling (BioMAP) primary, human, cell-based disease models, leverage cellular regulatory networks to detect and distinguish chemicals with a broad range of target mechanisms and biological processes relevant to human toxicity. Here the authors use the BioMAP human cell systems to characterize effects relevant to human tissue and inflammatory disease biology following exposure to the 320 environmental chemicals in the Environmental Protection Agency's (EPA's) ToxCast phase I library. The ToxCast chemicals were assayed at 4 concentrations in 8 BioMAP cell systems, with a total of 87 assay endpoints resulting in more than 100,000 data points. Within the context of the BioMAP database, ToxCast compounds could be classified based on their ability to cause overt cytotoxicity in primary human cell types or according to toxicity mechanism class derived from comparisons to activity profiles of BioMAP reference compounds. ToxCast chemicals with similarity to inducers of mitochondrial dysfunction, CAMP elevators, inhibitors of tubulin function, inducers of endoplasmic reticulum stress, or NF kappa B pathway inhibitors were identified based on this BioMAP analysis. This data set is being combined with additional ToxCast data sets for development of predictive toxicity models at the EPA. (Journal of Biomolecular Screening 2009:1054-1066)
引用
收藏
页码:1054 / 1066
页数:13
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