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用于预测化学物质致癌潜力的定量构效关系(QSAR)模型的开发 I. 作为致癌潜力估计值的替代毒性指标

Development of quantitative structure-activity relationship (QSAR) models to predict the carcinogenic potency of chemicals I. Alternative toxicity measures as an estimator of carcinogenic potency.

作者信息

Venkatapathy Raghuraman, Wang Ching Yi, Bruce Robert Mark, Moudgal Chandrika

机构信息

Pegasus Technical Services, Inc., 46 E. Hollister St., Cincinnati, OH 45219, USA.

出版信息

Toxicol Appl Pharmacol. 2009 Jan 15;234(2):209-21. doi: 10.1016/j.taap.2008.09.028. Epub 2008 Oct 15.

Abstract

Determining the carcinogenicity and carcinogenic potency of new chemicals is both a labor-intensive and time-consuming process. In order to expedite the screening process, there is a need to identify alternative toxicity measures that may be used as surrogates for carcinogenic potency. Alternative toxicity measures for carcinogenic potency currently being used in the literature include lethal dose (dose that kills 50% of a study population [LD(50)]), lowest-observed-adverse-effect-level (LOAEL) and maximum tolerated dose (MTD). The purpose of this study was to investigate the correlation between tumor dose (TD(50)) and three alternative toxicity measures as an estimator of carcinogenic potency. A second aim of this study was to develop a Classification and Regression Tree (CART) between TD(50) and estimated/experimental predictor variables to predict the carcinogenic potency of new chemicals. Rat TD(50)s of 590 structurally diverse chemicals were obtained from the Cancer Potency Database, and the three alternative toxicity measures considered in this study were estimated using TOPKAT, a toxicity estimation software. Though poor correlations were obtained between carcinogenic potency and the three alternative toxicity (both experimental and TOPKAT) measures for the CPDB chemicals, a CART developed using experimental data with no missing values as predictor variables provided reasonable estimates of TD(50) for nine chemicals that were part of an external validation set. However, if experimental values for the three alternative measures, mutagenicity and logP are not available in the literature, then either the CART developed using missing experimental values or estimated values may be used for making a prediction.

摘要

确定新化学物质的致癌性和致癌强度是一个既耗费人力又耗时的过程。为了加快筛选过程,有必要确定可作为致癌强度替代指标的其他毒性测量方法。目前文献中使用的致癌强度替代毒性测量方法包括致死剂量(杀死50%研究群体的剂量[LD(50)])、最低观察到有害作用水平(LOAEL)和最大耐受剂量(MTD)。本研究的目的是调查肿瘤剂量(TD(50))与三种替代毒性测量方法之间的相关性,以此作为致癌强度的估计指标。本研究的第二个目的是在TD(50)与估计/实验预测变量之间建立分类回归树(CART),以预测新化学物质的致癌强度。从癌症强度数据库获取了590种结构各异化学物质的大鼠TD(50),并使用毒性估计软件TOPKAT估计了本研究中考虑的三种替代毒性测量方法。尽管对于CPDB化学物质,致癌强度与三种替代毒性测量方法(实验和TOPKAT)之间的相关性较差,但使用无缺失值的实验数据作为预测变量建立的CART对作为外部验证集一部分的9种化学物质的TD(50)提供了合理估计。然而,如果文献中没有三种替代测量方法、致突变性和logP的实验值,那么可以使用使用缺失实验值或估计值建立的CART进行预测。

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