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
University of Washington, and Fred Hutchinson Cancer Research Center, Seattle, Washington 98195, USA.
Toxicol Sci. 2007 Sep;99(1):326-37. doi: 10.1093/toxsci/kfm150. Epub 2007 Jun 11.
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.
基因表达谱分析是一种广泛应用的技术，大多数已发表的微阵列研究数据均可公开获取。这些数据正被用于荟萃分析和计算机模拟发现；然而，多个实验室生成的毒理基因组学数据的可比性尚未得到严格评估。利用前瞻性多实验室研究的力量，七个中心各自开展了一项共同的毒理基因组学实验，旨在增进对急性毒性剂量的对乙酰氨基酚（APAP）所致肝脏中分子通路扰动的理解，并揭示APAP诱导毒性的可重复基因组特征。使用非肝毒性的APAP异构体N - 乙酰 - 间氨基酚来鉴定APAP特有的基因表达变化。我们的数据表明，APAP可诱导c - Myc，且以c - Myc为中心的相互作用组是与肝损伤相关的最显著的蛋白质网络。此外，通过将基因表达与对毒性反应的广泛毒理学评估相结合，确定了各中心之间的误差来源和数据变异性以及适应这种变异性的方法。我们表明，毒理基因组学实验的生物学意义分析需要基因表达数据的表型锚定。
