Characterization of diversity in toxicity mechanism using in vitro cytotoxicity assays in quantitative high throughput screening - PubMed (original) (raw)

Characterization of diversity in toxicity mechanism using in vitro cytotoxicity assays in quantitative high throughput screening

Ruili Huang et al. Chem Res Toxicol. 2008 Mar.

Abstract

Assessing the potential health risks of environmental chemical compounds is an expensive undertaking that has motivated the development of new alternatives to traditional in vivo toxicological testing. One approach is to stage the evaluation, beginning with less expensive and higher throughput in vitro testing before progressing to more definitive trials. In vitro testing can be used to generate a hypothesis about a compound's mechanism of action, which can then be used to design an appropriate in vivo experiment. Here we begin to address the question of how to design such a battery of in vitro cell-based assays by combining data from two different types of assays, cell viability and caspase activation, with the aim of elucidating the mechanism of action. Because caspase activation is a transient event during apoptosis, it is not possible to design a single end-point assay protocol that would identify all instances of compound-induced caspase activation. Nevertheless, useful information about compound mechanism of action can be obtained from these assays in combination with cell viability data. Unsupervised clustering in combination with Dunn's cluster validity index is a robust method for identifying mechanisms of action without requiring any a priori knowledge about mechanisms of toxicity. The performance of this clustering method is evaluated by comparing the clustering results against literature annotations of compound mechanisms.

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Figures

Figure 1

A typical concentration-response for caspase activation (◊) and cell viability (□). Note the decrease in caspase activation at higher concentrations. The data shown is for hexachloropentadiene in the Jurkat human leukemia T cell line. Activity is shown as a percentage of control: -100% connotes complete cell killing, +100% connotes caspase activation equivalent to tamoxifen. Solid diamonds indicate that this data was not used for curve fitting purposes.

Figure 2

Hierarchical clustering of all caspase and viability assays based on similarity in the compound EC50/IC50 patterns. Caspase assay data and cell viability data generally cluster by assay type. The exception is the Jurkat cell line, where both assay types cluster together.

Figure 3

Activity distributions of the set of 1408 compounds in the 13 different cell types in terms of their caspase activity as compared to their activity in the corresponding viability assays. The number of compounds active in both caspase activation and cell viability is a small subset of the total number of active compounds. Many compounds exhibit activity only in the cell viability assay.

Figure 4

Number of compound mechanisms (clusters) revealed as a function of number of assays screened. Assays were selected from the pool of all caspase and viability assays. (a) As more assays are utilized for clustering, the average number of clusters identified increases. (b) A plot of the distribution of cluster number as a function of the number of assays shows the gradual convergence near 24 clusters as the number of assays increases (line color becomes darker).

Figure 4

Figure 5

Number of compound mechanisms revealed as a function of number of assays screened: effect of noise in data. Assays were selected from the pool of three caspase assays, NIH 3T3, H-4-II-E and BJ, each run in quadruplets. Merely providing more replicates of the same experiment does not increase the number of clusters identified.

Figure 6

Co-cluster rate of clusters generated using various number of assays with clusters generated using all 26 caspase activation and viability assays as a function of number of assays screened. The clusters generated using ≥6 assays are ~95% similar to clusters generated using all 26 assays.

Figure 7

Number of compound mechanisms covered as a function of number of compounds screened. All caspase and viability assays were used in the clustering. Compounds were selected from a pool of 293 compounds that were class 1-3 in at least three of the 26 assays. It appears that the identification of compound mechanisms is limited by the number of compounds in the present experiment; more compounds would likely help differentiate additional mechanisms.

References

1. Hogue C. EU Parliament Committee Beefs Up REACH. Chem. Eng. News. 2006 Online.
1. NTP . NTP, A National Toxicology Program for the 21st Century: A roadmap to achieve the NTP vision. National Toxicology Program / National Institute of Environmental Health Sciences; Research Triangle Park, NC: 2004.
1. Dix DJ, Houck KA, Martin MT, Richard AM, Setzer RW, Kavlock RJ. The ToxCast program for prioritizing toxicity testing of environmental chemicals. Toxicol. Sci. 2007;95:5–12. - PubMed
1. NRC . A Vision for Toxicity Testing in the 21st Century. The National Academies Press; Washington, DC: 2007.
1. O'Brien P,J, Irwin W, Diaz D, Howard-Cofield E, Krejsa CM, Slaughter MR, Gao B, Kaludercic N, Angeline A, Bernardi P, Brain P, Hougham C. High concordance of drug-induced human hepatotoxicity with in vitro cytotoxicity measured in a novel cell-based model using high content screening. Arch. Toxicol. 2006;80:580–604. - PubMed

Characterization of diversity in toxicity mechanism using in vitro cytotoxicity assays in quantitative high throughput screening - PubMed (original) (raw)