Model-based identification of TNF alpha-induced IKK beta-mediated and I kappa B alpha-mediated regulation of NF kappa B signal transduction as a tool to quantify the impact of drug-induced liver injury compounds

Drug-induced liver injury: mathematical model quantifies impact of liver-damaging drugs Drug-induced liver injury (DILI) is one of the most important obstacles during drug development. More than 1000 drugs have been identified to damage the liver, but the current test systems are poor in predicting DILI. A team of cell biologists, theoretical physicists, and clinical pharmacologists combined experimental data generated in cultured liver cells with mathematical modeling to quantify the impact of the anti-inflammatory drug diclofenac. The analysis demonstrated that diclofenac induces multiple changes in the signal transduction network activated by the tumor necrosis factor alpha (TNFα), one of the known factors to amplify liver toxicity. Data of other liver injury-causing compounds were integrated into the mathematical model and their impact was quantified, thereby demonstrating the potential use of the mathematical model for the further analysis of other compounds in order to improve DILI test systems

Quantitative High Content Imaging of Cellular Adaptive Stress Response Pathways in Toxicity for Chemical Safety Assessment

Over the past decade, major leaps forward have been made on the mechanistic understanding and identification of adaptive stress response landscapes underlying toxic insult using transcriptomics approaches. However, for predictive purposes of adverse outcome several major limitations in these approaches exist. First, the limited number of samples that can be analyzed reduces the in depth analysis of concentration–time course relationships for toxic stress responses. Second these transcriptomics analysis have been based on the whole cell population, thereby inevitably preventing single cell analysis. Third, transcriptomics is based on the transcript level, totally ignoring (post)­translational regulation. We believe these limitations are circumvented with the application of high content analysis of relevant toxicant-induced adaptive stress signaling pathways using bacterial artificial chromosome (BAC) green fluorescent protein (GFP) reporter cell-based assays. The goal is to establish a platform that incorporates all adaptive stress pathways that are relevant for toxicity, with a focus on drug-induced liver injury. In addition, cellular stress responses typically follow cell perturbations at the subcellular organelle level. Therefore, we complement our reporter line panel with reporters for specific organelle morphometry and function. Here, we review the approaches of high content imaging of cellular adaptive stress responses to chemicals and the application in the mechanistic understanding and prediction of chemical toxicity at a systems toxicology level

Quantitative High Content Imaging of Cellular Adaptive Stress Response Pathways in Toxicity for Chemical Safety Assessment

Over the past decade, major leaps forward have been made on the mechanistic understanding and identification of adaptive stress response landscapes underlying toxic insult using transcriptomics approaches. However, for predictive purposes of adverse outcome several major limitations in these approaches exist. First, the limited number of samples that can be analyzed reduces the in depth analysis of concentration–time course relationships for toxic stress responses. Second these transcriptomics analysis have been based on the whole cell population, thereby inevitably preventing single cell analysis. Third, transcriptomics is based on the transcript level, totally ignoring (post)­translational regulation. We believe these limitations are circumvented with the application of high content analysis of relevant toxicant-induced adaptive stress signaling pathways using bacterial artificial chromosome (BAC) green fluorescent protein (GFP) reporter cell-based assays. The goal is to establish a platform that incorporates all adaptive stress pathways that are relevant for toxicity, with a focus on drug-induced liver injury. In addition, cellular stress responses typically follow cell perturbations at the subcellular organelle level. Therefore, we complement our reporter line panel with reporters for specific organelle morphometry and function. Here, we review the approaches of high content imaging of cellular adaptive stress responses to chemicals and the application in the mechanistic understanding and prediction of chemical toxicity at a systems toxicology level

The hepatotoxic fluoroquinolone trovafloxacin disturbs TNF- and LPS-induced p65 nuclear translocation in vivo and in vitro

Idiosyncratic drug-induced liver injury (IDILI) is a severe disease that cannot be detected during drug development. It has been shown that hepatotoxicity of some compounds associated with IDILI becomes apparent when these are combined in vivo and in vitro with LPS or TNF. Among these compounds trovafloxacin (TVX) induced apoptosis in the liver and increased pro-inflammatory cytokines in mice exposed to LPS/TNF. The hepatocyte survival and the cytokine release after TNF/LPS stimulation relies on a pulsatile activation of NF-κB. We set out to evaluate the dynamic activation of NF-κB in response to TVX + TNF or LPS models, both in mouse and human cells. Remarkably, TVX prolonged the first translocation of NF-κB induced by TNF both in vivo and in vitro. The prolonged p65 translocation caused by TVX was associated with an increased phosphorylation of IKK and MAPKs and accumulation of inhibitors of NF-κB such as IκBα and A20 in HepG2. Coherently, TVX suppressed further TNF-induced NF-κB translocations in HepG2 leading to decreased transcription of ICAM-1 and inhibitors of apoptosis. TVX prolonged LPS-induced NF-κB translocation in RAW264.7 macrophages increasing the secretion of TNF. In summary, this study presents new, relevant insights into the mechanism of TVX-induced liver injury underlining the resemblance between mouse and human models. In this study we convincingly show that regularly used toxicity models provide a coherent view of relevant pathways for IDILI. We propose that assessment of the kinetics of activation of NF-κB and MAPKs is an appropriate tool for the identification of hepatotoxic compounds during drug development

The hepatotoxic fluoroquinolone trovafloxacin disturbs TNF- and LPS-induced p65 nuclear translocation in vivo and in vitro

Idiosyncratic drug-induced liver injury (IDILI) is a severe disease that cannot be detected during drug development. It has been shown that hepatotoxicity of some compounds associated with IDILI becomes apparent when these are combined in vivo and in vitro with LPS or TNF. Among these compounds trovafloxacin (TVX) induced apoptosis in the liver and increased pro-inflammatory cytokines in mice exposed to LPS/TNF. The hepatocyte survival and the cytokine release after TNF/LPS stimulation relies on a pulsatile activation of NF-κB. We set out to evaluate the dynamic activation of NF-κB in response to TVX + TNF or LPS models, both in mouse and human cells. Remarkably, TVX prolonged the first translocation of NF-κB induced by TNF both in vivo and in vitro. The prolonged p65 translocation caused by TVX was associated with an increased phosphorylation of IKK and MAPKs and accumulation of inhibitors of NF-κB such as IκBα and A20 in HepG2. Coherently, TVX suppressed further TNF-induced NF-κB translocations in HepG2 leading to decreased transcription of ICAM-1 and inhibitors of apoptosis. TVX prolonged LPS-induced NF-κB translocation in RAW264.7 macrophages increasing the secretion of TNF. In summary, this study presents new, relevant insights into the mechanism of TVX-induced liver injury underlining the resemblance between mouse and human models. In this study we convincingly show that regularly used toxicity models provide a coherent view of relevant pathways for IDILI. We propose that assessment of the kinetics of activation of NF-κB and MAPKs is an appropriate tool for the identification of hepatotoxic compounds during drug development.Toxicolog

Model-based identification of TNFα-induced IKKβ-mediated and IκBα-mediated regulation of NFκB signal transduction as a tool to quantify the impact of drug-induced liver injury compounds

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