Clustering of hepatotoxins based on mechanism of toxicity using gene expression profiles

Abstract

Microarray technology, which allows one to quantitate the expression of thousands of genes simultaneously, has begun to have a major impact on many different areas of drug discovery and development. The question remains of whether microarray analysis and gene expression signature profiles can be applied to the field of toxicology. To date, there are very few published studies showing the use of microarrays in toxicology and important questions remain regarding the predictability and accuracy of applying gene expression profiles to toxicology. To begin to address these questions, we have treated rats with 15 different known hepatotoxins, including allyl alcohol, amiodarone, Aroclor 1254, arsenic, carbamazepine, carbon tetrachloride, diethylnitrosamine, dimethylformamide, diquat, etoposide, indomethacin, methapyrilene, methotrexate, monocrotaline, and 3-methylcholanthrene. These agents cause a variety of hepatocellular injuries including necrosis, DNA damage, cirrhosis, hypertrophy, and hepatic carcinoma. Gene expression analysis was done on RNA from the livers of treated rats and was compared against vehicle-treated controls. The gene expression results were clustered and compared to the histopathology findings and clinical chemistry values. Our results show strong correlation between the histopathology, clinical chemistry, and gene expression profiles induced by the agents. In addition, genes were identified whose regulation correlated strongly with effects on clinical chemistry parameters. Overall, the results suggest that microarray assays may prove to be a highly sensitive technique for safety screening of drug candidates and for the classification of environmental toxins.