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基于代谢组学的顺铂类药物固有毒性预测

Predicting idiopathic toxicity of cisplatin by a pharmacometabonomic approach.

机构信息

Department of Biochemistry, Inha University Hospital and Center for Advanced Medical Education by BK21 project, College of Medicine, Inha University, Shinheung-dong 3ga, Chung-gu, Incheon, Korea.

出版信息

Kidney Int. 2011 Mar;79(5):529-37. doi: 10.1038/ki.2010.440. Epub 2010 Oct 27.

DOI:10.1038/ki.2010.440
PMID:20980974
Abstract

Cisplatin has been one of the most widely used anticancer agents, but its nephrotoxicity remains a dose-limiting complication. Here, we evaluated the idiopathic nature and the predose prediction of cisplatin-induced nephrotoxicity using a nuclear magnetic resonance (NMR)-based pharmacometabonomic approach. Cisplatin produced serious toxic responses in some animals (toxic group), but had little effect in others (nontoxic group), as judged by hematological and histological results. The individual metabolic profiles, assessed by urine NMR spectra, showed large differences between the post-administration profiles of the two groups, indicating the relevance of the NMR approach. Importantly, multivariate analysis of the NMR data showed that the toxic and nontoxic groups can be differentiated based on the pretreatment metabolite profiles. Leave-one-out analysis, performed to evaluate the practical performance of our approach, gave a 66% accuracy rate in predicting toxic responses based on the pretreatment metabolite profiles. Hence, we provide a working model that can explain the idiopathic toxicity mechanism based on marker metabolites found by NMR analysis consistent with tissue NADH measurements. Thus, a pharmacometabonomic approach using pretreatment metabolite profiles may help expedite personalized chemotherapy of anticancer drugs.

摘要

顺铂是最广泛使用的抗癌药物之一,但肾毒性仍是其剂量限制的并发症。在这里,我们使用基于核磁共振(NMR)的代谢组学方法来评估顺铂诱导的肾毒性的特发性和预测。顺铂在一些动物中产生严重的毒性反应(毒性组),而在另一些动物中则几乎没有影响(非毒性组),这可以从血液学和组织学结果判断。通过尿液 NMR 谱评估的个体代谢谱,显示两组给药后的谱之间存在很大差异,表明 NMR 方法的相关性。重要的是,对 NMR 数据的多变量分析表明,基于预处理代谢物谱可以区分毒性和非毒性组。为了评估我们方法的实际性能而进行的留一法分析表明,基于预处理代谢物谱预测毒性反应的准确率为 66%。因此,我们提供了一个工作模型,该模型可以基于 NMR 分析发现的与组织 NADH 测量一致的标志物代谢物来解释特发性毒性机制。因此,使用预处理代谢物谱的代谢组学方法可能有助于加快抗癌药物的个体化化疗。

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