Connexin-based signaling and drug-induced hepatotoxicity.
Ontology highlight
ABSTRACT:
SUBMITTER: Maes M
PROVIDER: S-EPMC5562166 | biostudies-other | 2017 Feb
REPOSITORIES: biostudies-other
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Project description:Quantitative structure-activity relationship (QSAR) modeling and toxicogenomics are typically used independently as predictive tools in toxicology. In this study, we evaluated the power of several statistical models for predicting drug hepatotoxicity in rats using different descriptors of drug molecules, namely, their chemical descriptors and toxicogenomics profiles. The records were taken from the Toxicogenomics Project rat liver microarray database containing information on 127 drugs ( http://toxico.nibio.go.jp/datalist.html ). The model end point was hepatotoxicity in the rat following 28 days of continuous exposure, established by liver histopathology and serum chemistry. First, we developed multiple conventional QSAR classification models using a comprehensive set of chemical descriptors and several classification methods (k nearest neighbor, support vector machines, random forests, and distance weighted discrimination). With chemical descriptors alone, external predictivity (correct classification rate, CCR) from 5-fold external cross-validation was 61%. Next, the same classification methods were employed to build models using only toxicogenomics data (24 h after a single exposure) treated as biological descriptors. The optimized models used only 85 selected toxicogenomics descriptors and had CCR as high as 76%. Finally, hybrid models combining both chemical descriptors and transcripts were developed; their CCRs were between 68 and 77%. Although the accuracy of hybrid models did not exceed that of the models based on toxicogenomics data alone, the use of both chemical and biological descriptors enriched the interpretation of the models. In addition to finding 85 transcripts that were predictive and highly relevant to the mechanisms of drug-induced liver injury, chemical structural alerts for hepatotoxicity were identified. These results suggest that concurrent exploration of the chemical features and acute treatment-induced changes in transcript levels will both enrich the mechanistic understanding of subchronic liver injury and afford models capable of accurate prediction of hepatotoxicity from chemical structure and short-term assay results.
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Project description:Liver dysfunction is a common side effect associated with the treatment of dasatinib and its mechanism is poorly understood. Autophagy has been thought to be a potent survival or death factor for liver dysfunction, which may shed the light on a novel strategy for the intervention of hepatotoxicity caused by dasatinib. In this study, we show for the first time that autophagy is induced, which is consistent with the formation of liver damage. Autophagy inhibition exacerbated dasatinib-induced liver failure, suggesting that autophagy acted as a self-defense mechanism to promote survival. Oxidative stress has been shown to be an important stimulus for autophagy and hepatotoxicity. Interestingly, dasatinib increased the activity of p38, which is a critical modulator of the oxidative stress related to liver injury and autophagy. p38 silencing significantly blocked LC3-II induction and p62 reduction by dasatinib, which was accompanied by increased caspase-3 and PARP cleavage, indicating that autophagy alleviated dasatinib-induced hepatotoxicity via p38 signaling. Finally, the p38 agonist isoproterenol hydrochloride (ISO) alleviated dasatinib-induced liver failure by enhancing autophagy without affecting the anticancer activity of dasatinib. Thus, this study revealed that p38-activated autophagy promoted survival during liver injury, which may provide novel approaches for managing the clinical applications of dasatinib.
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Project description:Drug-induced hepatotoxicity is a leading cause of attrition of candidate drugs in drug development. Therefore new screening methods are necessary which predict these hazards more accurate and earlier in the drug development process. Of all in vitro hepatotoxicity models, primary human hepatocytes are considered as 'the gold standard'. However, the use of these hepatocytes is hindered by their scarcity and major inter-individual variation. These limitations may be overcome with use of primary mouse hepatocytes. Within this context changes in protein expressions in primary mouse hepatocytes, after exposure to cyclosporin A were studied using differential gel electrophoresis. Thereafter, the mRNA expression levels of these deregulated proteins from cyclosporin A-treated cells were analyzed. Cyclosporin A induced ER stress and altered the ER-Golgi transport, which may alter vesicle mediated transport and protein secretion. Moreover are the differentially expressed proteins observed upon challenge by cyclosporin A, associated with cholestatic mechanisms. For each biological experiment, one hybridization was conducted and one sample per array. In total, 6 arrays were used for 2 different conditions (Csa or control at 48 hours).
2013-04-01 | E-GEOD-33742 | biostudies-arrayexpress
Project description:Increased medical application of psychotropic drugs raised attention concerning their toxicological effects. In fact, more than 160 psychotropic drugs including antidepressants and antipsychotics, have been shown to cause liver side effects, but the underlying mechanisms are still poorly understood. Here, we discovered that fluoxetine, a common antidepressant, was specifically sensed by NLRP3 inflammasome, whose subsequent activation resulted in the maturation of caspase-1 and IL-1β, as well as gasdermin D (GSDMD) cleavage, which could be completely abrogated by a selective NLRP3 inhibitor MCC950 or Nlrp3 knockout (Nlrp3-/-). Mechanistically, mitochondrial damage and the subsequent mitochondrial reactive oxygen species (mtROS) accumulation were crucial upstream signaling events in fluoxetine-triggered NLRP3 inflammasome activation. In fluoxetine hepatotoxicity models, mice showed the alterations of aminotransferase levels, hepatic inflammation and hepatocyte death in an NLRP3-dependent manner, and MCC950 pretreatment could reverse these side effects of fluoxetine. Notably, we also found that multiple antidepressants, such as amitriptyline, paroxetine, and imipramine, and antipsychotics, such as asenapine, could specifically trigger the NLRP3 inflammasome activation. Collectively, our findings implicate multiple psychotropic drugs may act as danger signals sensed by the NLRP3 inflammasome and result in hepatic injury.
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Project description:Drug-induced hepatotoxicity is a leading cause of attrition of candidate drugs in drug development. Therefore new screening methods are necessary which predict these hazards more accurate and earlier in the drug development process. Of all in vitro hepatotoxicity models, primary human hepatocytes are considered as 'the gold standard'. However, the use of these hepatocytes is hindered by their scarcity and major inter-individual variation. These limitations may be overcome with use of primary mouse hepatocytes. Within this context changes in protein expressions in primary mouse hepatocytes, after exposure to cyclosporin A were studied using differential gel electrophoresis. Thereafter, the mRNA expression levels of these deregulated proteins from cyclosporin A-treated cells were analyzed. Cyclosporin A induced ER stress and altered the ER-Golgi transport, which may alter vesicle mediated transport and protein secretion. Moreover are the differentially expressed proteins observed upon challenge by cyclosporin A, associated with cholestatic mechanisms.
2013-04-01 | GSE33742 | GEO
Project description:BackgroundDrug-induced liver injury (DILI) is a critical issue in drug development because DILI causes failures in clinical trials and the withdrawal of approved drugs from the market. There have been many attempts to predict the risk of DILI based on in vivo and in silico identification of hepatotoxic compounds. In the current study, we propose the in silico prediction model predicting DILI using weighted molecular fingerprints.ResultsIn this study, we used 881 bits of molecular fingerprint and used as features describing presence or absence of each substructure of compounds. Then, the Bayesian probability of each substructure was calculated and labeled (positive or negative for DILI), and a weighted fingerprint was determined from the ratio of DILI-positive to DILI-negative probability values. Using weighted fingerprint features, the prediction models were trained and evaluated with the Random Forest (RF) and Support Vector Machine (SVM) algorithms. The constructed models yielded accuracies of 73.8% and 72.6%, AUCs of 0.791 and 0.768 in cross-validation. In independent tests, models achieved accuracies of 60.1% and 61.1% for RF and SVM, respectively. The results validated that weighted features helped increase overall performance of prediction models. The constructed models were further applied to the prediction of natural compounds in herbs to identify DILI potential, and 13,996 unique herbal compounds were predicted as DILI-positive with the SVM model.ConclusionsThe prediction models with weighted features increased the performance compared to non-weighted models. Moreover, we predicted the DILI potential of herbs with the best performed model, and the prediction results suggest that many herbal compounds could have potential to be DILI. We can thus infer that taking natural products without detailed references about the relevant pathways may be dangerous. Considering the frequency of use of compounds in natural herbs and their increased application in drug development, DILI labeling would be very important.
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Project description:The role of small heterodimer partner (SHP) in regulation of xenobiotic detoxification remains elusive. Here, we uncover a critical role for SHP in circadian regulation of cytochromes P450 (CYPs) and drug-induced hepatotoxicity. Methods: The mRNA and protein levels of CYPs in the livers of wild-type and SHP-/- mice were measured by quantitative real-time polymerase chain reaction and Western blotting, respectively. Regulation of CYP by SHP was investigated using luciferase reporter, mobility shift, chromatin immunoprecipitation, and/or co-immunoprecipitation assays. Results: The circadian rhythmicities of xenobiotic-detoxifying CYP mRNAs and proteins were disrupted in SHP-deficient mice. Of note, SHP ablation up-regulated Cyp2c38 and Cyp2c39, whereas it down-regulated all other CYP genes. Moreover, SHP regulated the expression of CYP genes through different mechanisms. SHP repressed Lrh-1/Hnf4α to down-regulate Cyp2c38, E4bp4 to up-regulate Cyp2a5, Dec2/HNF1α axis to up-regulate Cyp1a2, Cyp2e1 and Cyp3a11, and Rev-erbα to up-regulate Cyp2b10, Cyp4a10 and Cyp4a14. Furthermore, SHP ablation sensitized mice to theophylline (or mitoxantrone)-induced toxicity. Higher level of toxicity was correlated with down-regulated metabolism and clearance of theophylline (or mitoxantrone). In contrast, SHP ablation blunted the circadian rhythmicity of acetaminophen-induced hepatotoxicity and alleviated the toxicity by down-regulating Cyp2e1-mediated metabolism and reducing formation of the toxic metabolite. Toxicity alleviation by SHP ablation was also observed for aflatoxin B1 due to reduced formation of the toxic epoxide metabolite. Conclusion: SHP participates in circadian regulation of CYP enzymes, thereby impacting xenobiotic metabolism and drug-induced hepatotoxicity.
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