ABSTRACT
Nuwasyir and colleagues (1) in 1999 defined ‘toxicogenomics’ as the intersection of toxicology and genomics. They proposed that the goal of this new discipline is to identify potential toxicants and to clarify their mechanism of action with the help of genomics resources. Since then, major efforts have been undertaken to establish data sets that include a diversity of compounds and environmental stressors. This will eventually allow classification of unknown or novel compounds into mechanistic groups. By doing so, researchers hope to achieve toxicant or toxicant-group-specific genomic signatures which indicate exposure and initiation of toxic events. This might not only be valid for known and already well-defined toxicants, but perhaps more importantly, for unknown toxicants or compounds under development. Achieving this goal would allow identification of potential toxicity prior to indications of overt toxicity for novel compounds and could allow for very sensitive exposure monitoring. Several groups have undertaken efforts to classify compounds based on gene expression data. One of the first classification studies in toxicogenomics was published by Waring et al. in 2001 (2). Here the authors retrieved gene expression data from livers of rats exposed to 15 different hepatotoxicants and showed correlations between differentially expressed genes, histopathological and clinical chemistry changes. They also demonstrated that gene expression analysis allows for the identification of mechanistically related compounds and reveals a higher degree of similarity between RNA derived from animals treated with the same compound than to those exposed to other hepatotoxicants. Hamadeh and colleagues in 2002 performed the first toxicological classification study that included blinded samples. In this study, the authors first determined gene expression patterns for three different peroxisome proliferators and one barbiturate (3). This data was utilized as a training set and identified discriminating signatures between compounds. Coded RNA samples from animals exposed to either a barbiturate or peroxisome proliferators were subjected to gene expression
analysis. This study demonstrated that it was possible to predict the class of compound to which the rats were exposed based on gene expression profiles for those blinded liver RNA samples (4).
