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文献优化基因表达整合用于毒理基因组数据集的器官特异性评估。

Literature optimized integration of gene expression for organ-specific evaluation of toxicogenomics datasets.

机构信息

Faculty of Biology, Biozentrum I, Mainz, Germany.

Experimentelle Nephrologie, Universitätsklinikum Jena, KIM III, Jena, Germany.

出版信息

PLoS One. 2019 Jan 14;14(1):e0210467. doi: 10.1371/journal.pone.0210467. eCollection 2019.

Abstract

The study of drug toxicity in human organs is complicated by their complex inter-relations and by the obvious difficulty to testing drug effects on biologically relevant material. Animal models and human cell cultures offer alternatives for systematic and large-scale profiling of drug effects on gene expression level, as typically found in the so-called toxicogenomics datasets. However, the complexity of these data, which includes variable drug doses, time points, and experimental setups, makes it difficult to choose and integrate the data, and to evaluate the appropriateness of one or another model system to study drug toxicity (of particular drugs) of particular human organs. Here, we define a protocol to integrate drug-wise rankings of gene expression changes in toxicogenomics data, which we apply to the TG-GATEs dataset, to prioritize genes for association to drug toxicity in liver or kidney. Contrast of the results with sets of known human genes associated to drug toxicity in the literature allows to compare different rank aggregation approaches for the task at hand. Collectively, ranks from multiple models point to genes not previously associated to toxicity, notably, the PCNA clamp associated factor (PCLAF), and genes regulated by the master regulator of the antioxidant response NFE2L2, such as NQO1 and SRXN1. In addition, comparing gene ranks from different models allowed us to evaluate striking differences in terms of toxicity-associated genes between human and rat hepatocytes or between rat liver and rat hepatocytes. We interpret these results to point to the different molecular functions associated to organ toxicity that are best described by each model. We conclude that the expected production of toxicogenomics panels with larger numbers of drugs and models, in combination with the ongoing increase of the experimental literature in organ toxicity, will lead to increasingly better associations of genes for organism toxicity.

摘要

研究人类器官的药物毒性受到其复杂的相互关系和明显难以测试药物对生物相关物质的影响的限制。动物模型和人类细胞培养提供了替代方法,可以系统地大规模分析药物对基因表达水平的影响,这通常在所谓的毒代基因组学数据集中发现。然而,这些数据的复杂性,包括不同的药物剂量、时间点和实验设置,使得选择和整合数据变得困难,并且难以评估一个或另一个模型系统是否适合研究特定人类器官的特定药物毒性(特别是药物)。在这里,我们定义了一个整合毒代基因组学数据中基因表达变化的药物排序的方案,我们将其应用于 TG-GATEs 数据集,以优先考虑与肝脏或肾脏药物毒性相关的基因。将结果与文献中与药物毒性相关的已知人类基因集进行对比,可比较手头任务的不同排名聚合方法。来自多个模型的综合排名指向以前未与毒性相关的基因,特别是 PCNA 夹钳相关因子(PCLAF)和受抗氧化反应主调节因子 NFE2L2 调节的基因,例如 NQO1 和 SRXN1。此外,比较不同模型的基因排名使我们能够评估人类和大鼠肝细胞或大鼠肝脏和大鼠肝细胞之间与毒性相关的基因之间的显著差异。我们解释这些结果表明,每个模型都最好地描述了与器官毒性相关的不同分子功能。我们得出结论,随着毒代基因组学面板中药物和模型数量的增加,以及器官毒性实验文献的不断增加,将越来越能够更好地将基因与机体毒性相关联。

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