Title: Multicenter study of acetaminophen hepatotoxicity reveals the importance of biological endpoints in genomic analyses.

Authors: Beyer, Richard P; Fry, Rebecca C; Lasarev, Michael R; McConnachie, Lisa A; Meira, Lisiane B; Palmer, Valerie S; Powell, Christine L; Ross, Pamela K; Bammler, Theo K; Bradford, Blair U; Cranson, Alex B; Cunningham, Michael L; Fannin, Rickie D; Higgins, Gregory M; Hurban, Patrick; Kayton, Robert J; Kerr, Kathleen F; Kosyk, Oksana; Lobenhofer, Edward K; Sieber, Stella O; Vliet, Portia A; Weis, Brenda K; Wolfinger, Russel; Woods, Courtney G; Freedman, Jonathan H; Linney, Elwood; Kaufmann, William K; Kavanagh, Terrance J; Paules, Richard S; Rusyn, Ivan; Samson, Leona D; Spencer, Peter S; Suk, William; Tennant, Raymond J; Zarbl, Helmut; Members of the Toxicogenomics Research Consortium

Published In Toxicol Sci, (2007 Sep)

Abstract: Gene expression profiling is a widely used technique with data from the majority of published microarray studies being publicly available. These data are being used for meta-analyses and in silico discovery; however, the comparability of toxicogenomic data generated in multiple laboratories has not been critically evaluated. Using the power of prospective multilaboratory investigations, seven centers individually conducted a common toxicogenomics experiment designed to advance understanding of molecular pathways perturbed in liver by an acute toxic dose of N-acetyl-p-aminophenol (APAP) and to uncover reproducible genomic signatures of APAP-induced toxicity. The nonhepatotoxic APAP isomer N-acetyl-m-aminophenol was used to identify gene expression changes unique to APAP. Our data show that c-Myc is induced by APAP and that c-Myc-centered interactomes are the most significant networks of proteins associated with liver injury. Furthermore, sources of error and data variability among Centers and methods to accommodate this variability were identified by coupling gene expression with extensive toxicological evaluation of the toxic responses. We show that phenotypic anchoring of gene expression data is required for biologically meaningful analysis of toxicogenomic experiments.

PubMed ID: 17562736

MeSH Terms: Acetaminophen/toxicity*; Analgesics, Non-Narcotic/toxicity*; Animals; DNA-Binding Proteins/biosynthesis; DNA-Binding Proteins/genetics; Endpoint Determination; Gene Expression Profiling/methods*; Gene Expression/drug effects*; Genomic Islands; Genomics/methods*; Isomerism; Liver/drug effects*; Liver/metabolism; Male; Mice; Mice, Inbred C57BL; Phenotype; Reproducibility of Results; Salivary alpha-Amylases; Transcription Factors/biosynthesis; Transcription Factors/genetics