ToxSci Advance Access originally published online on May 22, 2007
Toxicological Sciences 2007 99(1):289-302; doi:10.1093/toxsci/kfm131
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Acute Hepatotoxicity: A Predictive Model Based on Focused Illumina Microarrays
* Molecular Toxicology
Pathology and Histopathology
Institute of Toxicology, Merck KGaA, Darmstadt, 64293 Germany
1 To whom correspondence should be addressed at Institute of Toxicology – Molecular Toxicology, Merck KGaA, Frankfurter Str. 250, 64293 Darmstadt, Germany. Fax: +49-6151-912927. E-mail: philip.hewitt{at}merck.de.
Received February 28, 2007; accepted May 14, 2007
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Abstract |
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Drug-induced hepatotoxicity is a major issue for drug development, and toxicogenomics has the potential to predict toxicity during early toxicity screening. A bead-based Illumina oligonucleotide microarray containing 550 liver specific genes has been developed. We have established a predictive screening system for acute hepatotoxicity by analyzing differential gene expression profiles of well-known hepatotoxic and nonhepatotoxic compounds. Low and high doses of tetracycline, carbon tetrachloride (CCL4), 1-naphthylisothiocyanate (ANIT), erythromycin estolate, acetaminophen (AAP), or chloroform as hepatotoxicants, clofibrate, theophylline, naloxone, estradiol, quinidine, or dexamethasone as nonhepatotoxic compounds, were administered as a single dose to male Sprague–Dawley rats. After 6, 24, and 72 h, livers were taken for histopathological evaluation and for analysis of gene expression alterations. All hepatotoxic compounds tested generated individual gene expression profiles. Based on leave-one-out cross-validation analysis, gene expression profiling allowed the accurate discrimination of all model compounds, 24 h after high dose treatment. Even during the regeneration phase, 72 h after treatment, CCL4, ANIT, and AAP were predicted to be hepatotoxic, and only these three compounds showed histopathological changes at this time. Furthermore, we identified 64 potential marker genes responsible for class prediction, which reflected typical hepatotoxicity responses. These genes and pathways, commonly deregulated by hepatotoxicants, may be indicative of the early characterization of hepatotoxicity and possibly predictive of later hepatotoxicity onset. Two unknown test compounds were used for prevalidating the screening test system, with both being correctly predicted. We conclude that focused gene microarrays are sufficient to classify compounds with respect to toxicity prediction.
Key Words: gene expression changes; toxicogenomics; early prediction; screening model; Illumina microarray; rat in vivo model.
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