急性肝毒性:基于聚焦Illumina微阵列的预测模型

Acute hepatotoxicity: a predictive model based on focused illumina microarrays.

作者信息

Zidek Nadine, Hellmann Juergen, Kramer Peter-Juergen, Hewitt Philip G

机构信息

Molecular Toxicology, Institute of Toxicology, Merck KGaA, Darmstadt, Germany.

出版信息

Toxicol Sci. 2007 Sep;99(1):289-302. doi: 10.1093/toxsci/kfm131. Epub 2007 May 22.

Abstract

Drug-induced hepatotoxicity is a major issue for drug development, and toxicogenomics has the potential to predict toxicity during early toxicity screening. A bead-based Illumina oligonucleotide microarray containing 550 liver specific genes has been developed. We have established a predictive screening system for acute hepatotoxicity by analyzing differential gene expression profiles of well-known hepatotoxic and nonhepatotoxic compounds. Low and high doses of tetracycline, carbon tetrachloride (CCL4), 1-naphthylisothiocyanate (ANIT), erythromycin estolate, acetaminophen (AAP), or chloroform as hepatotoxicants, clofibrate, theophylline, naloxone, estradiol, quinidine, or dexamethasone as nonhepatotoxic compounds, were administered as a single dose to male Sprague-Dawley rats. After 6, 24, and 72 h, livers were taken for histopathological evaluation and for analysis of gene expression alterations. All hepatotoxic compounds tested generated individual gene expression profiles. Based on leave-one-out cross-validation analysis, gene expression profiling allowed the accurate discrimination of all model compounds, 24 h after high dose treatment. Even during the regeneration phase, 72 h after treatment, CCL4, ANIT, and AAP were predicted to be hepatotoxic, and only these three compounds showed histopathological changes at this time. Furthermore, we identified 64 potential marker genes responsible for class prediction, which reflected typical hepatotoxicity responses. These genes and pathways, commonly deregulated by hepatotoxicants, may be indicative of the early characterization of hepatotoxicity and possibly predictive of later hepatotoxicity onset. Two unknown test compounds were used for prevalidating the screening test system, with both being correctly predicted. We conclude that focused gene microarrays are sufficient to classify compounds with respect to toxicity prediction.

摘要

药物性肝毒性是药物研发中的一个主要问题,而毒理基因组学有潜力在早期毒性筛查中预测毒性。一种包含550个肝脏特异性基因的基于微珠的Illumina寡核苷酸微阵列已被开发出来。我们通过分析知名肝毒性和非肝毒性化合物的差异基因表达谱,建立了一种急性肝毒性的预测筛查系统。将低剂量和高剂量的四环素、四氯化碳(CCL4)、1-萘基异硫氰酸酯(ANIT)、琥乙红霉素、对乙酰氨基酚(AAP)或氯仿作为肝毒性物质,将氯贝丁酯、茶碱、纳洛酮、雌二醇、奎尼丁或地塞米松作为非肝毒性化合物,以单剂量给予雄性Sprague-Dawley大鼠。在6、24和72小时后,取出肝脏进行组织病理学评估和基因表达变化分析。所有测试的肝毒性化合物都产生了各自的基因表达谱。基于留一法交叉验证分析,基因表达谱分析能够在高剂量处理24小时后准确区分所有模型化合物。即使在处理后72小时的再生阶段,CCL4、ANIT和AAP也被预测为具有肝毒性,并且只有这三种化合物在此时显示出组织病理学变化。此外,我们鉴定出64个负责类别预测的潜在标记基因,它们反映了典型的肝毒性反应。这些通常被肝毒性物质失调的基因和途径,可能指示肝毒性的早期特征,并有可能预测后期肝毒性的发生。使用两种未知的测试化合物对筛查测试系统进行预验证,两种化合物均被正确预测。我们得出结论,聚焦基因微阵列足以对化合物进行毒性预测分类。

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