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Toxicogenomics in the assessment of immunotoxicity.

Baken KA, Vandebriel RJ, Pennings JL, Kleinjans JC, van Loveren H

Nutrition and Toxicology Research Institute Maastricht, Department of Health Risk Analysis and Toxicology (GRAT), Maastricht University, Maastricht, The Netherlands. kirsten.baken@rivm.nl

Microarray analysis is used for simultaneous measurement of expression of thousands of genes in a given sample and as such extends and deepens our understanding of biological processes. Application of the technique in toxicology is referred to as toxicogenomics. The examples of assessment of immunotoxicity by gene expression profiling presented and discussed here, show that microarray analysis is able to detect known and novel effects of a wide range of immunomodulating agents. Besides the elucidation of mechanisms of action, toxicogenomics is also applied to predict consequences of exposing biological systems to toxic agents. Successful attempts to classify compounds using signature gene expression profiles have been reported. These did, however, not specifically focus on immunotoxicity. Databases containing expression profiles can facilitate the applications of toxicogenomics. Platforms and methodologies for gene expression profiling may vary, however, hampering data compiling across different laboratories. Therefore, attention is paid to standardization of the generation, reporting, and management of microarray data. Obtained gene expression profiles should be anchored to pathological and functional endpoints for correct interpretation of results. These issues are also important when using toxicogenomics in risk assessment. The application of toxicogenomics in evaluation of immunotoxicity is thus not yet without challenges. It already contributes to the understanding of immunotoxic processes and the development of in vitro screening assays, though, and is therefore expected to be of value for mechanistic insight into immunotoxicity and hazard identification of existing and novel compounds.

Published 12 December 2006 in Methods, 41(1): 132-41.
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