title: Microarray analysis in rat liver slices correctly predicts in vivo hepatotoxicity.
abstract: The microarray technology, developed for the simultaneous analysis of a large number of genes, may be useful for the detection of toxicity in an early stage of the development of new drugs. The effect of different hepatotoxins was analyzed at the gene expression level in the rat liver both in vivo and in vitro. As in vitro model system the precision-cut liver slice model was used, in which all liver cell types are present in their natural architecture. This is important since drug-induced toxicity often is a multi-cellular process involving not only hepatocytes but also other cell types such as Kupffer and stellate cells. As model toxic compounds lipopolysaccharide (LPS, inducing inflammation), paracetamol (necrosis), carbon tetrachloride (CCl(4), fibrosis and necrosis) and gliotoxin (apoptosis) were used. The aim of this study was to validate the rat liver slice system as in vitro model system for drug-induced toxicity studies. The results of the microarray studies show that the in vitro profiles of gene expression cluster per compound and incubation time, and when analyzed in a commercial gene expression database, can predict the toxicity and pathology observed in vivo. Each toxic compound induces a specific pattern of gene expression changes. In addition, some common genes were up- or down-regulated with all toxic compounds. These data show that the rat liver slice system can be an appropriate tool for the prediction of multi-cellular liver toxicity. The same experiments and analyses are currently performed for the prediction of human specific toxicity using human liver slices.
authors.affiliation: Department of Pharmacokinetics and Drug Delivery, Groningen Research Institute for Pharmacy, University of Groningen, The Netherlands. M.G.L.Elferink@rug.nl
authors.forename: M G L
authors.initials: MG
authors.lastname: Elferink
authors.forename: P
authors.initials: P
authors.lastname: Olinga
authors.forename: A L
authors.initials: AL
authors.lastname: Draaisma
authors.forename: M T
authors.initials: MT
authors.lastname: Merema
authors.forename: S
authors.initials: S
authors.lastname: Bauerschmidt
authors.forename: J
authors.initials: J
authors.lastname: Polman
authors.forename: W G
authors.initials: WG
authors.lastname: Schoonen
authors.forename: G M M
authors.initials: GM
authors.lastname: Groothuis
mesh_terms: D000082:Acetaminophen / Q000633:toxicity; D000818:Animals; D017209:Apoptosis / Q000187:drug effects; D002251:Carbon Tetrachloride / Q000633:toxicity; D015536:Down-Regulation / Q000187:drug effects; D005355:Fibrosis / Q000139:chemically induced; D005544:Forecasting; D005912:Gliotoxin / Q000633:toxicity; D007249:Inflammation / Q000139:chemically induced; D008070:Lipopolysaccharides / Q000633:toxicity; D008099:Liver / Q000187:drug effects* / Q000473:pathology; D008297:Male; D009336:Necrosis / Q000139:chemically induced; D020411:Oligonucleotide Array Sequence Analysis; D051381:Rats; D017208:Rats, Wistar; D013997:Time Factors; D018675:Toxicity Tests; D015854:Up-Regulation / Q000187:drug effects*
chemical_list: D008070:Lipopolysaccharides; D000082:Acetaminophen; D005912:Gliotoxin; D002251:Carbon Tetrachloride