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. 2010 Apr;118(4):485-92.
doi: 10.1289/ehp.0901392.

In vitro screening of environmental chemicals for targeted testing prioritization: the ToxCast project

Richard S Judson  1 , Keith A Houck, Robert J Kavlock, Thomas B Knudsen, Matthew T Martin, Holly M Mortensen, David M Reif, Daniel M Rotroff, Imran Shah, Ann M Richard, David J Dix
Affiliations

In vitro screening of environmental chemicals for targeted testing prioritization: the ToxCast project

Richard S Judson et al. Environ Health Perspect. 2010 Apr.

Abstract

Background: Chemical toxicity testing is being transformed by advances in biology and computer modeling, concerns over animal use, and the thousands of environmental chemicals lacking toxicity data. The U.S. Environmental Protection Agency's ToxCast program aims to address these concerns by screening and prioritizing chemicals for potential human toxicity using in vitro assays and in silico approaches.

Objectives: This project aims to evaluate the use of in vitro assays for understanding the types of molecular and pathway perturbations caused by environmental chemicals and to build initial prioritization models of in vivo toxicity.

Methods: We tested 309 mostly pesticide active chemicals in 467 assays across nine technologies, including high-throughput cell-free assays and cell-based assays, in multiple human primary cells and cell lines plus rat primary hepatocytes. Both individual and composite scores for effects on genes and pathways were analyzed.

Results: Chemicals displayed a broad spectrum of activity at the molecular and pathway levels. We saw many expected interactions, including endocrine and xenobiotic metabolism enzyme activity. Chemicals ranged in promiscuity across pathways, from no activity to affecting dozens of pathways. We found a statistically significant inverse association between the number of pathways perturbed by a chemical at low in vitro concentrations and the lowest in vivo dose at which a chemical causes toxicity. We also found associations between a small set of in vitro assays and rodent liver lesion formation.

Conclusions: This approach promises to provide meaningful data on the thousands of untested environmental chemicals and to guide targeted testing of environmental contaminants.

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Figures

Figure 1
Figure 1
Heat map of 624 assay measurements (including multiple time points where available) in ToxCast phase I data set. Assays are arranged left to right, and chemicals are arranged top to bottom. The color bar at the top indicates the assay type: red (cell-free HTS), violet (multiplexed transcription reporter), yellow (biologically multiplexed activity profiling), green (high-content cell imaging), blue (multiplexed gene expression), pink (cell-based HTS), black (phase I and II XME cytotoxicity), white (real-time cell electronic sensing), and orange (HTS genotoxicity). Data values are –log10(AC50/LEC), where light pink is inactive and darker reds indicate increased activity (lower AC50/LEC).
Figure 2
Figure 2
Distribution of number of hits per chemical as a function of AC50/LEC cutoff used to define a hit. (A) Distributions for all human assay measurements (out of 425) and the “direct” measurements from the cell-free HTS assays. The other assays are cell based and can potentially respond to multiple direct chemical interactions. (B) Number of hits per chemical for the gene and pathway perturbation scores. In each box and whisker plot, the heavy bar indicates the median, the boxes encompass the second and third quartiles, the whiskers extend to ±1.58 (interquartile range)/(number of assay-chemical hits), and the circles indicate outliers.
Figure 3
Figure 3
Distribution of number of hits against the 33 minimal pathways by chemical class (active at concentrations of < 30 μM). Only chemical classes with at least 10 chemicals are included. In each box and whisker plot, the heavy bar indicates the median, the boxes encompass the second and third quartiles, and the whiskers extend to ±1.58 (interquartile range)/(number of assay-chemical hits).
Figure 4
Figure 4
Plot of the minimum concentration at which a chemical caused cytotoxicity as a function of the number of minimal pathways in which the chemical was active at concentrations < 30 μM. Chemicals for which no cytotoxicity was observed were assigned an AC50 of 1 mM. The correlation coefficient is minimally sensitive to this default value. The line gives the fitted regression model.
Figure 5
Figure 5
Association between the number of minimal pathway hits (which we assume is inversely correlated with the minimum concentration at which significant pathway activity occurs for the chemical) and the lowest dose in vivo at which a significant toxicity end point is observed, in this case for the rat prenatal developmental bioassay. Each point represents a single chemical. The x-axis is the value resulting from the fitted model, which is 0.6 + 0.4 × log10(LD50) – 0.037 × (number of minimal pathway hits at concentrations < 30 μM). The y-axis is the minimum log10(concentration) at which toxicity is seen for this study type. This analysis was performed on the 153 chemicals for which we had all values.
Figure 6
Figure 6
Network of genes associated with the progression of rat liver tumor end points. Associations were calculated using Fisher’s exact test, with assay AC50/LEC values ≤ 100 μM set to 1 and those with > 100 μM set to 0. Only associations with a p-value < 0.01 are included. Links between genes (yellow) and in vivo end points (pink) are shown where there is a statistical association based on the in vitro assay results. The “Any lesion” category contains the “Preneoplastic” category, which in turn contains the “Neoplastic” lesions category. Disease or disorder classes (cyan) are linked to genes according to Goh et al. (2007).
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