Toxicogenomics discrimination of potential hepatocarcinogenicity of non‐genotoxic compounds in rat liver
Toxicogenomics discrimination of potential hepatocarcinogenicity of non‐genotoxic compounds in rat liver
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大鼠肝脏中非基因毒性化合物潜在肝癌性的毒理基因组学判别
DOI：
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发表时间：
2012
影响因子：
3.3
通讯作者：
Y. Ohno
中科院分区：
文献类型：
--
作者：
Fumihiro Yamada;K. Sumida;T. Uehara;Yuji Morikawa;H. Yamada;T. Urushidani;Y. Ohno
化合物的长期致癌性试验非常耗时和昂贵，需要许多试验动物，而艾姆斯试验基于任何致突变物质也可能产生致癌潜力的假设，可用作短期筛选试验，但存在重大缺陷。尽管事实上，90%的艾姆斯试验阳性的化合物在实验室动物中引起癌症，但很大比例的艾姆斯试验阴性的化合物也是致癌物;也就是说，致癌性和阴性艾姆斯试验结果之间没有良好的相关性。作为这两种方法的替代，我们尝试应用毒理基因组学来预测体内诱导的基因表达谱的化合物的致癌性。为了建立我们的模型，雄性Sprague-Dawley大鼠经口给予测试化合物（12种肝癌物质和26种非肝癌物质）28天。通过支持向量机（SVM）将化合物分为“用于训练”和“用于测试”（随机分配20例）分析肝脏基因表达数据，允许测试一组标记基因以预测肝癌性。通过与训练数据和测试数据的一致率对所建立的预测模型进行了验证，取得了较好的效果。我们将获得新的基因表达数据，并继续验证我们的模型。版权所有© 2012约翰威利父子有限公司.
Long‐term carcinogenicity testing of a compound is exceedingly time‐consuming and costly, and requires many test animals, whereas the Ames test, which is based on the assumption that any substance that is mutagenic may also exert carcinogenic potential, is useful as a short‐term screening assay but has major drawbacks. Although, in fact, 90% of compounds that give a positive Ames test cause cancer in laboratory animals, a good proportion of compounds that give a negative Ames test are also carcinogens; that is, there is no good correlation between carcinogenicity and negative Ames test results. As an alternative to these two approaches, we have tried applying toxicogenomics to predict the carcinogenicity of a compound from the gene expression profile induced in vivo. To establish our model, male Sprague–Dawley rats were orally administered test compounds (12 hepatocarcinogens and 26 non‐hepatocarcinogens) for 28 days. Analysis of liver gene expression data by Support Vector Machines (SVM) dividing compounds into ‘for training’ and ‘for test’ (20 cases assigned randomly) allowed a set of marker genes to be tested for prediction of hepatocarcinogenicity. The developed prediction model was then validated with reference to the concordance rate with training data and test data, and a good performance was obtained. We will have new gene expression data and continue the validation of our model. Copyright © 2012 John Wiley & Sons, Ltd.
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影响因子：
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作者：
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DOI：
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发表时间：
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期刊：
International journal of molecular medicine.
影响因子：
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影响因子：
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作者：
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