Department of Toxicogenomics, Maastricht University, PO Box 616, 6200 MD Maastricht, The Netherlands; Netherlands Toxicogenomics Centre, Maastricht, The Netherlands.
Department of Toxicogenomics, Maastricht University, PO Box 616, 6200 MD Maastricht, The Netherlands.
Toxicol In Vitro. 2017 Oct;44:322-329. doi: 10.1016/j.tiv.2017.07.024. Epub 2017 Aug 1.
Drug-induced liver injury remains the most common cause of acute liver failure and a frequently indicated reason for withdrawal of drugs. For the purpose of evaluating the relevance of liver cell models for assessing hepatotoxic risks in intact humans, we here aimed to benchmark 'omics-derived mechanistic data from three in vitro models for parenchymal liver function, intended for the investigation of drug-induced cholestasis, against 'omics data from cholestatic patients. Transcriptomic changes in HepG2 cells, primary mouse hepatocytes and primary human hepatocytes exposed to known cholestatic compounds were analyzed using microarrays. Some of the differentially expressed genes in HepG2 cells were also differentially expressed into the same direction in human cholestasis. The overlap between drug-induced transcriptomic responses in primary mouse hepatocytes and primary human hepatocytes appeared limited and no genes overlapping with in vivo cholestasis were found. Thereupon, a pathway for drug-induced cholestasis was used to map the drug-induced transcriptomic modifications involved in bile salt homeostasis. Indications of an adaptive response to prevent and reduce intracellular bile salt accumulation were observed in vivo as well as in the in vitro liver models. Furthermore, drug-specific changes were found, which may be indicative for their cholestatic properties. Furthermore, connectivity mapping was applied in order to investigate the predictive value of the in vitro models for in vivo cholestasis. This analysis resulted in a positive connection score for most compounds, which may indicate that for identifying cholestatic compounds the focus should be on gene expression signatures rather than on differentially expressed genes.
药物性肝损伤仍然是急性肝衰竭的最常见原因，也是药物撤药的常见原因。为了评估肝细胞模型在评估完整人体中肝毒性风险的相关性，我们旨在将三种用于研究药物性胆汁淤积的实质肝功能的体外模型的“组学”衍生的机制数据与胆汁淤积患者的“组学”数据进行基准比较。使用微阵列分析了暴露于已知胆汁淤积化合物的 HepG2 细胞、原代小鼠肝细胞和原代人肝细胞中的转录组变化。HepG2 细胞中一些差异表达的基因在人类胆汁淤积中也朝着相同的方向表达。原代小鼠肝细胞和原代人肝细胞中药物诱导的转录组反应之间的重叠似乎有限，并且没有发现与体内胆汁淤积重叠的基因。因此，使用药物诱导的胆汁淤积途径来映射参与胆汁盐稳态的药物诱导的转录组修饰。在体内以及体外肝模型中均观察到了预防和减少细胞内胆汁盐积累的适应性反应的迹象。此外，还发现了药物特异性变化，这可能表明其具有胆汁淤积特性。此外，还应用了连接映射，以研究体外模型对体内胆汁淤积的预测价值。该分析导致大多数化合物的连接评分呈阳性，这可能表明，要识别胆汁淤积化合物，重点应放在基因表达特征上，而不是差异表达的基因上。
