Overview of an interlaboratory collaboration on evaluating the effects of model hepatotoxicants on hepatic gene...

DNA microarrays and related tools offer promise for identification of pathways involved in toxic responses to xenobiotics. To be useful for risk assessment, experimental data must be challenged for reliability and interlaboratory reproducibility. Toward this goal, the Hepatotoxicity Working Group of the International Life Sciences Institute (ILSI) Health and Environmental Sciences Institute (HESI) Technical Committee on Application of Genomics to Mechanism-Based Risk Assessment evaluated and compared biological and gene expression responses in rats exposed to two model hepatotoxins--clofibrate and methapyrilene. This collaborative effort provided an unprecedented opportunity for the working group to evaluate and compare multiple biological, genomic, and toxicological parameters across different laboratories and microarray platforms. Many of the results from this collaboration are presented in accompanying articles in this mini-monograph, whereas others have been published previously. (Italic)In vivo(/Italic) studies for both compounds were conducted in two laboratories using a standard experimental protocol, and RNA samples were distributed to 16 laboratories for analysis on six microarray platforms. Histopathology, clinical chemistry, and organ weight changes were consistent with reported effects. Gene expression results demonstrated reasonable agreement between laboratories and across platforms. Discrepancies in expression profiles of some individual genes were largely due to platform differences and approaches to data analysis rather than to biological or interlaboratory variability. Despite these discrepancies there was overall agreement in the biological pathways affected by these compounds, demonstrating that transcriptional profiling is reproducible between laboratories and can reliably identify affected pathways necessary to provide mechanistic insight. This effort represents an important first step toward the use of transcriptional profiling in risk assessment.