The liver pharmacological and xenobiotic gene response repertoire.

We have used a supervised classification approach to systematically mine a large microarray database derived from livers of compound-treated rats. Thirty-four distinct signatures (classifiers) for pharmacological and toxicological end points can be identified. Just 200 genes are sufficient to classify these end points. Signatures were enriched in xenobiotic and immune response genes and contain un-annotated genes, indicating that not all key genes in the liver xenobiotic responses have been characterized. Many signatures with equal classification capabilities but with no gene in common can be derived for the same phenotypic end point. The analysis of the union of all genes present in these signatures can reveal the underlying biology of that end point as illustrated here using liver fibrosis signatures. Our approach using the whole genome and a diverse set of compounds allows a comprehensive view of most pharmacological and toxicological questions and is applicable to other situations such as disease and development.

Toxicogenomics in drug discovery and development: mechanistic analysis of compound/class-dependent effects using the DrugMatrix database.

A range of genomics technologies are increasingly becoming integrated with existing scientific disciplines to broaden and strengthen existing capabilities and open new avenues of research in drug discovery and development. Examples of these new research fields are proteomics, pharmacogenomics, metabolomics and toxicogenomics. Here we review the application of toxicogenomics to improve the evaluation of drug safety, mechanism of action and toxicity in the drug discovery and development process.

Development of a large-scale chemogenomics database to improve drug candidate selection and to understand mechanisms of chemical toxicity and action.

Successful drug discovery requires accurate decision making in order to advance the best candidates from initial lead identification to final approval. Chemogenomics, the use of genomic tools in pharmacology and toxicology, offers a promising enhancement to traditional methods of target identification/validation, lead identification, efficacy evaluation, and toxicity assessment. To realize the value of chemogenomics information, a contextual database is needed to relate the physiological outcomes induced by diverse compounds to the gene expression patterns measured in the same animals. Massively parallel gene expression characterization coupled with traditional assessments of drug candidates provides additional, important mechanistic information, and therefore a means to increase the accuracy of critical decisions. A large-scale chemogenomics database developed from in vivo treated rats provides the context and supporting data to enhance and accelerate accurate interpretation of mechanisms of toxicity and pharmacology of chemicals and drugs. To date, approximately 600 different compounds, including more than 400 FDA approved drugs, 60 drugs approved in Europe and Japan, 25 withdrawn drugs, and 100 toxicants, have been profiled in up to 7 different tissues of rats (representing over 3200 different drug-dose-time-tissue combinations). Accomplishing this task required evaluating and improving a number of in vivo and microarray protocols, including over 80 rigorous quality control steps. The utility of pairing clinical pathology assessments with gene expression data is illustrated using three anti-neoplastic drugs: carmustine, methotrexate, and thioguanine, which had similar effects on the blood compartment, but diverse effects on hepatotoxicity. We will demonstrate that gene expression events monitored in the liver can be used to predict pathological events occurring in that tissue as well as in hematopoietic tissues.