...
首页> 外文期刊>Carcinogenesis >A transcriptomics-based in vitro assay for predicting chemical genotoxicity in vivo
【24h】

A transcriptomics-based in vitro assay for predicting chemical genotoxicity in vivo

机译:基于转录组学的体外测定方法,用于预测体内化学遗传毒性

获取原文
获取原文并翻译 | 示例

摘要

The lack of accurate in vitro assays for predicting in vivo toxicity of chemicals together with new legislations demanding replacement and reduction of animal testing has triggered the development of alternative methods. This study aimed at developing a transcriptomics-based in vitro prediction assay for in vivo genotoxicity. Transcriptomics changes induced in the human liver cell line HepG2 by 34 compounds after treatment for 12, 24, and 48h were used for the selection of gene-sets that are capable of discriminating between in vivo genotoxins (GTX) and in vivo nongenotoxins (NGTX). By combining transcriptomics with publicly available results for these chemicals from standard in vitro genotoxicity studies, we developed several prediction models. These models were validated by using an additional set of 28 chemicals. The best prediction was achieved after stratification of chemicals according to results from the Ames bacterial gene mutation assay prior to transcriptomics evaluation after 24h of treatment. A total of 33 genes were selected for discriminating GTX from NGTX for Ames-positive chemicals and 22 for Ames-negative chemicals. Overall, this method resulted in 89% accuracy and 91% specificity, thereby clearly outperforming the standard in vitro test battery. Transcription factor network analysis revealed HNF3a, HNF4a, HNF6, androgen receptor, and SP1 as main factors regulating the expression of classifiers for Ames-positive chemicals. Thus, the classical bacterial gene mutation assay in combination with in vitro transcriptomics in HepG2 is proposed as an upgraded in vitro approach for predicting in vivo genotoxicity of chemicals holding a great promise for reducing animal experimentations on genotoxicity.
机译:缺乏用于预测化学物质体内毒性的准确体外测定方法,以及要求替换和减少动物试验的新法规,引发了替代方法的发展。这项研究旨在开发一种基于转录组学的体外体内遗传毒性体外预测测定方法。在处理12、24和48小时后,由34种化合物在人肝细胞系HepG2中诱导的转录组学变化用于选择能够区分体内基因毒素(GTX)和体内基因毒素(NGTX)的基因组。 。通过将转录组学与标准化学物质体外遗传毒性研究中这些化学药品的可公开获得的结果相结合,我们开发了几种预测模型。这些模型通过使用另一组28种化学物质进行了验证。根据Ames细菌基因突变测定的结果对化合物进行化学分层后的最佳预测是在治疗24小时后进行转录组学评估之前。总共选择了33个基因用于区分Ames阳性化学药品和NGTX中的GTX,以及22个用于识别Ames阴性化学药品的基因。总体而言,该方法的准确度为89%,特异性为91%,因此明显优于标准的体外测试电池。转录因子网络分析表明,HNF3a,HNF4a,HNF6,雄激素受体和SP1是调节Ames阳性化学物质分类器表达的主要因素。因此,将经典的细菌基因突变测定法与HepG2中的体外转录组学相结合,提出了一种升级的体外方法,用于预测化学物质的体内遗传毒性,对减少动物对遗传毒性的实验具有广阔的前景。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号