Department of Health Risk Analysis and Toxicology, Faculty of Health, Medicine and Life Sciences, Maastricht University, 6200 MD Maastricht, The Netherlands.
Toxicol Sci. 2009 Dec;112(2):374-84. doi: 10.1093/toxsci/kfp229. Epub 2009 Sep 21.
Assessing the potential carcinogenicity of chemicals for humans represents an ongoing challenge. Chronic rodent bioassays predict human cancer risk at only limited reliability and are simultaneously expensive and long lasting. In order to seek for alternatives, the ability of a transcriptomics-based primary mouse hepatocyte model to classify carcinogens by their modes of action was evaluated. As it is obvious that exposure will induce a cascade of gene expression modifications, in particular, the influence of exposure time in vitro on discriminating genotoxic (GTX) carcinogens from nongenotoxic (NGTX) carcinogens class discrimination was investigated. Primary mouse hepatocytes from male C57Bl6 mice were treated for 12, 24, 36, and 48 h with two GTX and two NGTX carcinogens. For validation, two additional GTX compounds were studied at 24 and 48 h. Immunostaining of gammaH2AX foci was applied in order to phenotypically verify DNA damage. It confirmed significant induction of DNA damage after treatment with GTX compounds but not with NGTX compounds. Whole-genome gene expression modifications were analyzed by means of Affymetrix microarrays. When using differentially expressed genes from data sets normalized by Robust Multi-array Average, the two classes and various compounds were better separated from each other by hierarchical clustering when increasing the treatment period. Discrimination of GTX and NGTX carcinogens by Prediction Analysis of Microarray improved with time and resulted in correct classification of the validation compounds. The present study shows that gene expression profiling in primary mouse hepatocytes is promising for discriminating GTX from NGTX compounds and that this discrimination improves with increasing treatment period.
评估化学物质对人类的潜在致癌性是一个持续存在的挑战。慢性啮齿动物生物测定预测人类癌症风险的可靠性有限，同时成本高且耗时长久。为了寻求替代方法，评估了基于转录组的原代小鼠肝细胞模型根据作用模式对致癌物进行分类的能力。由于暴露显然会诱导一系列基因表达修饰，特别是研究了体外暴露时间对区分遗传毒性（GTX）致癌物和非遗传毒性（NGTX）致癌物的分类判别影响。用两种 GTX 和两种 NGTX 致癌物分别处理雄性 C57Bl6 小鼠的原代肝细胞 12、24、36 和 48 小时。为了验证，还在 24 和 48 小时研究了另外两种 GTX 化合物。通过免疫染色γH2AX 焦点来表型验证 DNA 损伤。它证实了 GTX 化合物处理后明显诱导了 DNA 损伤，但 NGTX 化合物没有。通过 Affymetrix 微阵列分析全基因组基因表达修饰。当使用通过 Robust Multi-array Average 进行标准化的数据集的差异表达基因时，通过层次聚类，当处理时间增加时，两类和各种化合物彼此之间的分离更好。通过微阵列预测分析对 GTX 和 NGTX 致癌物的区分随着时间的推移而改善，并导致验证化合物的正确分类。本研究表明，原代小鼠肝细胞中的基因表达谱有望区分 GTX 和 NGTX 化合物，并且这种区分随着处理时间的增加而提高。
