Gene Expression Profiles Associated with Inflammation Fibrosis and Cholestasis in Mouse Liver after Griseofulvin

such as viruses, parasites, alcohol, hereditary metal overload, for example, Wilson disease, and xenobiotics may give rise to a constellation of abnormalities such as fatty change, apoptosis, necrosis, cholestasis, inflammation, and fibrosis as well as nodular regeneration and cirrhosis. As a paradigm for parenchymal wound healing in other tissues, chronic liver injury involves the activation of cytokines believed not only to mediate inflammation, necrosis, apoptosis, and fibrosis but also regeneration of liver tissue (Tilg and Diehl 2000). As with many diseases, progression reflects a combination of genetic and environmental factors, and the severity of the inflammatory process usually correlates with the rate of disease progression. In hereditary conditions such as hemachromatosis, a concurrent insult such as alcohol ingestion will increase injury and rate of progression to fibrosis (Friedman 1993). Other complicating factors include older age, immune status, male gender, and obesity (Friedman 1993; Tilg and Diehl 2000). Drug-induced liver injury also continues to be a significant problem (Bissell et al. 2001) where genetically determined differences in drugmetabolizing enzymes in the generation of toxic metabolites as well as in immune responses may be important (Lee 1995). However, the relative importance of these genetic factors and the way they might interact are not fully understood. One approach to help understand these factors and their interaction in the evolution of liver injury is through the use of gene expression profiles. Griseofulvin is an antifungal agent that, when administered chronically to mice, produces a variety of hepatic responses the chronology of which have been extensively studied (Knasmuller et al. 1997). Early cell proliferation leads to an increase in liver/body weight ratio, and alteration of the liver drug-metabolizing profile (Knasmuller et al. 1997). One of the earliest features of griseofulvin exposure is a hepatic porphyria characterized by the accumulation of protoporphyrin IX (De Matteis and Rimington 1963; Weston Hurst and Paget 1963). This porphyria is induced by the inhibition of ferrochelatase probably caused by a griseofulvin adduct of protoporphyrin IX produced in a cytochrome P450 (Cyp)-mediated suicide reaction (Bellingham et al. 1995). The changes in liver pathology with griseofulvin are similar to those found with human erythropoietic protoporphyria (EP)-associated liver failure that occurs in a subset of patients and probably depends on genetic and physiologic susceptibility factors to determine its onset (Bloomer et al. 1998; Cox et al. 1998; Kappas et al. 1995). Previous studies have used transcriptome data to categorize the toxicity of chemicals according to their gene expression profile, the premise being that those chemicals with a different type and/or mechanism of toxicity will produce different gene expression patterns. This approach was used by Waring et al. (2001) to distinguish 15 different hepatotoxins, a study which illustrated the utility of this approach. Similar studies have been carried out on smaller compound sets by Hamadeh et al. (2002a, 2002b). Working on the hypothesis that it is necessary using statistical analysis to determine only a relatively small number of gene expressions to differentiate toxicity profiles, Thomas et al. (2001) used 12 transcripts to differentiate a set of 12 hepatotoxins. This approach is potentially reductionist, however, and although successful on 12 previously characterized hepatotoxins, there is no guarantee that it works on novel agents using such a small number of genes. None of the above studies have addressed the potential influence of cellular response, altered organ homeostasis, and resulting pathologic change on gene expression profiles. This issue was addressed later by Hamadeh et al. (2002c), who were able to associate gene expression profiles with pathologic change in the liver after methapyrilene exposure. By making a correlation between gene expression profiles and pathologic change, these authors were able to demonstrate the ability of gene expression profile data to inform and enhance rather than replace the pathologic analysis. The application of gene expression profiles in toxicology and pathology has been recently reviewed (Gant 2002).