Studies to develop the prediction system for drug metabolism, pharmacokineties and toxicity.

我们利用大鼠药物反应芯片研究了肝毒性化学物质给药与基因表达谱之间的关系。从典型的肝毒性大鼠中分离肝脏mRNA，并进行含有1,097个药物反应基因的DMA芯片。所有测试的化学物质都产生了一种特定的基因表达模式。APAP与其他化学物质的聚类不同。从血清生化标记谱中，我们确定了10个上调基因和10个下调基因作为肝毒性的潜在标记。通过QT聚类，我们确定了每种化学物质的主要上调和下调表达模式。有趣的是，这些表达模式与生化标记谱的表达模式具有良好的相关性。总之，我们鉴定出了20种潜在毒性标记物，化学物质给药的表达谱分析可以推测出与毒性水平无关的毒性时间点，而且这种表达谱分析也可以作为检测潜在肝毒性的工具之一。我们采用典型肝毒性药物硫代乙酰胺（TA），构建肝毒性模型大鼠，同时测定基因表达谱，并寻找剂量与时间的相关性。给药后血清AST和ALT呈剂量依赖性升高，并在24小时达到最大值。各剂量组的分层聚类分析显示2个主要聚类。此外，各剂量组的分层聚类分析显示与所有剂量组相同的模式。此外，QT聚类分析获得的基因表达多数与TA毒性最大时间点相同。我们以前的研究中选择的个体基因表达谱与它们的剂量无关。这些发现表明，在没有发生毒性的情况下，潜在的毒性作用与它们的剂量无关，遵循特定基因表达谱和一般基因表达谱可以作为毒性的敏感标志。少

We investigated whether there is relationship in gene expression profiles of hepatotoxic chemicals administration by using Rat Drug Response Chip. Liver mRNA was isolated from the typical hepatotoxicant-administered rats and performed DMA microarray containing 1,097 drug response genes. All the tested chemicals generated a specific gene expression patterns. APAP was sorted different cluster from other chemicals. From serum biochemical markers profiles, we identified up-regulated 10 genes and down-regulated 10 genes as a potential marker of hepatotoxicity. By using QT clustering, we identified major up-regulated and down-regulated expression patterns from each chemical. Interestingly, these means of expression patterns had good correlation with expression patterns from biochemical markers profiles. In conclusion, we identified 20 potential toxicity markers and expression profile analysis of chemicals administration can guess toxic time point with independent of toxicity level and using … More this expression profile analysis was also available to be one of the tools of detecting potential hepatotoxicant.We used typical hepatotoxicant thioacetamide (TA), constructed liver toxicity model rats to perform simultaneous measurement of gene expression profiles and to find correlation between dosage and time. Serum AST and ALT were increased by TA administration with dose dependent manner and reached the maximal value at 24 hours. Hierarchical clustering analysis of all dosage groups showed 2 major clusters. Moreover, hierarchical clustering analysis of each dosage group showed the same pattern as shown in all dosage groups. Furthermore, gene expression majority obtained by QT clustering analysis had the same maximal time point of TA toxicity. Individual gene expression profiles selected our previous studies were independent on their dosage. These finding suggest that potential toxic effects in the absense of the occurrence of toxicity are independent on their dosage, and following specific gene expression profiles and general gene expression profiles can be a sensitive marker of toxicity. Less