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Original

Microarray-based compendium of hepatic gene expression profiles for prototypical ADME gene-inducing compounds in rats and mice in vivo

, , , , , , , , , , , , , & show all
Pages 902-937 | Received 16 May 2005, Accepted 18 May 2006, Published online: 11 Aug 2009
 

Abstract

To examine species-specific aspects of the induction of absorption, distribution, metabolism and excretion (ADME)-related genes, we used 25 000 gene oligonucleotide microarrays to construct a rodent gene-response compendium that compared hepatic gene expression profiles and developed consensus aryl hydrocarbon receptor (AhR), constitutive androstane receptor (CAR) and pregnane X-receptor (PXR) ligand signatures relevant to drug clearance. Twenty-six inducer compounds were chosen from the literature. Rats and mice received one of six dose levels (log2 dose escalation, 32-fold dose range) of each compound daily for 3 days. Animals were necropsied 6–9 h after the last dose, and tissues were collected for RNA analysis. Hepatic gene expression profiles were obtained using Rosetta Resolver® expression analysis system, and ADME-related genes were extracted. Cross-talk among nuclear receptors or hepatoxicity at high dose levels resulted in large signatures (usually >1000 genes at p < 0.01) for most compounds. After ADME gene transcript enrichment, agglomerative clustering separated AhR ligands from CAR/PXR ligands, but it was difficult to distinguish CAR from PXR ligands. Consensus signatures were derived from groups of AhR, CAR and PXR ligands; and cross-talk among responding genes was determined. Many compounds had distinct log dose–response profiles, and relative potencies for ligands were established. Robust responses by CYP1A1, CYP2B10 (CAR responsive in mice) and CYP2B15 (CAR responsive in rats) and CYP3A1 (PXR responsive in rats) were used to benchmark the relative potency of different ligands and to determine the relative selectivity for AhR, CAR or PXR. By using a compendium of gene expression profiles, we defined species-specific induction patterns across the ADME transcriptome.

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