Identification of toxicologically predictive gene sets using cDNA microarrays
Identification of toxicologically predictive gene sets using cDNA microarrays
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DOI：
10.1124/mol.60.6.1189
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发表时间：
2001-12-01
影响因子：
3.6
通讯作者：
Bradfield, CA
中科院分区：
文献类型：
--
作者：
Thomas, RS;Rank, DR;Bradfield, CA
我们开发了一种根据毒物对mRNA转录本的影响对其进行分类的方法。小鼠暴露于24个模型治疗后，检测了肝脏基因表达的变化，这些治疗分为五个毒理学研究良好的类别：过氧化物体增殖剂、芳烃受体激动剂、非共面多氯联苯、炎剂和低氧诱导剂。使用基于相关性的方法和概率方法对1200份记录进行分析，分类准确率在50%到70%之间。然而，通过使用前向参数选择方案，确定了12个转录本的诊断集，该转录本基于留一交叉验证提供了估计100%的预测准确性。将这一方法扩展到更多受监管关注的化学品，可能会成为毒理学测试新时代的重要筛查步骤。
We have developed an approach to classify toxicants based upon their influence on profiles of mRNA transcripts. Changes in liver gene expression were examined after exposure of mice to 24 model treatments that fall into five well-studied toxicological categories: peroxisome proliferators, aryl hydrocarbon receptor agonists, noncoplanar polychlorinated biphenyls, inflammatory agents, and hypoxia-inducing agents. Analysis of 1200 transcripts using both a correlation-based approach and a probabilistic approach resulted in a classification accuracy of between 50 and 70%. However, with the use of a forward parameter selection scheme, a diagnostic set of 12 transcripts was identified that provided an estimated 100% predictive accuracy based on leave-one-out cross-validation. Expansion of this approach to additional chemicals of regulatory concern could serve as an important screening step in a new era of toxicological testing.