Oppelt Angela, Kaschek Daniel, Huppelschoten Suzanna, Sison-Young Rowena, Zhang Fang, Buck-Wiese Marie, Herrmann Franziska, Malkusch Sebastian, Krüger Carmen L, Meub Mara, Merkt Benjamin, Zimmermann Lea, Schofield Amy, Jones Robert P, Malik Hassan, Schilling Marcel, Heilemann Mike, van de Water Bob, Goldring Christopher E, Park B Kevin, Timmer Jens, Klingmüller Ursula
1Division Systems Biology of Signal Transduction, German Cancer Research Center (DKFZ), Heidelberg, Germany.
2Institute of Physics, University of Freiburg, Freiburg, Germany.
NPJ Syst Biol Appl. 2018 Jun 11;4:23. doi: 10.1038/s41540-018-0058-z. eCollection 2018.
Drug-induced liver injury (DILI) has become a major problem for patients and for clinicians, academics and the pharmaceutical industry. To date, existing hepatotoxicity test systems are only poorly predictive and the underlying mechanisms are still unclear. One of the factors known to amplify hepatotoxicity is the tumor necrosis factor alpha (TNFα), especially due to its synergy with commonly used drugs such as diclofenac. However, the exact mechanism of how diclofenac in combination with TNFα induces liver injury remains elusive. Here, we combined time-resolved immunoblotting and live-cell imaging data of HepG2 cells and primary human hepatocytes (PHH) with dynamic pathway modeling using ordinary differential equations (ODEs) to describe the complex structure of TNFα-induced NFκB signal transduction and integrated the perturbations of the pathway caused by diclofenac. The resulting mathematical model was used to systematically identify parameters affected by diclofenac. These analyses showed that more than one regulatory module of TNFα-induced NFκB signal transduction is affected by diclofenac, suggesting that hepatotoxicity is the integrated consequence of multiple changes in hepatocytes and that multiple factors define toxicity thresholds. Applying our mathematical modeling approach to other DILI-causing compounds representing different putative DILI mechanism classes enabled us to quantify their impact on pathway activation, highlighting the potential of the dynamic pathway model as a quantitative tool for the analysis of DILI compounds.
药物性肝损伤(DILI)已成为患者、临床医生、学者和制药行业面临的一个主要问题。迄今为止,现有的肝毒性测试系统预测能力很差,其潜在机制仍不清楚。已知放大肝毒性的因素之一是肿瘤坏死因子α(TNFα),特别是由于它与双氯芬酸等常用药物具有协同作用。然而,双氯芬酸与TNFα联合诱导肝损伤的确切机制仍然难以捉摸。在这里,我们将HepG2细胞和原代人肝细胞(PHH)的时间分辨免疫印迹和活细胞成像数据与使用常微分方程(ODEs)的动态通路建模相结合,以描述TNFα诱导的NFκB信号转导的复杂结构,并整合了双氯芬酸引起的通路扰动。所得的数学模型用于系统地识别受双氯芬酸影响的参数。这些分析表明,TNFα诱导的NFκB信号转导的不止一个调节模块受双氯芬酸影响,这表明肝毒性是肝细胞多种变化的综合结果,并且多种因素决定毒性阈值。将我们的数学建模方法应用于代表不同假定DILI机制类别的其他导致DILI的化合物,使我们能够量化它们对通路激活的影响,突出了动态通路模型作为分析DILI化合物的定量工具的潜力。