tranilast and Chemical-and-Drug-Induced-Liver-Injury

Drug-induced organ toxicity is a frequently encountered obstacle in the field of medical practice that limits the use of numerous pharmacologically valuable drugs. Methotrexate (MTX)-induced organ toxicity is unfortunately the rate-limiting factor for its clinical application. In the current study, MTX injection induced significant renal and hepatic toxicities manifested on functional, biochemical, and histopathological scales. This was associated with a significant elevation in both renal and hepatic contents of TNF-related apoptosis-inducing ligand (TRAIL) and caspase-8, biomarkers of tissue apoptosis. Inline, immunohistochemical analysis confirmed that tissue increased expression of Ki67 as a biomarker of tissue regeneration in both organs. Tranilast (TRAN) is a small molecular weight anti-inflammatory and antiallergic agent. TRAN's coadministration with MTX in the current study induced a significant tissue recovery via modulation of TRAIL/caspase-8 signaling and modulation of apoptosis-induced tissue proliferation confirmed by quantification of Ki67 expression. In conclusion, TRAN can be proposed as an effective drug to attenuate MTX-induced organ toxicity via modulation of apoptosis-induced tissue proliferation pathway.

Topics: Animals; Apoptosis; Biomarkers; Caspase 8; Cell Proliferation; Chemical and Drug Induced Liver Injury; Ki-67 Antigen; Kidney; Liver; Liver Regeneration; Male; Methotrexate; Mice; ortho-Aminobenzoates; Oxidative Stress; Signal Transduction; TNF-Related Apoptosis-Inducing Ligand

The bile salt export pump (BSEP) is expressed at the canalicular domain of hepatocytes, where it serves as the primary route of elimination for monovalent bile acids (BAs) into the bile canaliculi. The most compelling evidence linking dysfunction in BA transport with liver injury in humans is found with carriers of mutations that render BSEP nonfunctional. Based on mounting evidence, there appears to be a strong association between drug-induced BSEP interference and liver injury in humans; however, causality has not been established. For this reason, drug-induced BSEP interference is best considered a susceptibility factor for liver injury as other host- or drug-related properties may contribute to the development of hepatotoxicity. To better understand the association between BSEP interference and liver injury in humans, over 600 marketed or withdrawn drugs were evaluated in BSEP expressing membrane vesicles. The example of a compound that failed during phase 1 human trials is also described, AMG 009. AMG 009 showed evidence of liver injury in humans that was not predicted by preclinical safety studies, and BSEP inhibition was implicated. For 109 of the drugs with some effect on in vitro BSEP function, clinical use, associations with hepatotoxicity, pharmacokinetic data, and other information were annotated. A steady state concentration (C(ss)) for each of these annotated drugs was estimated, and a ratio between this value and measured IC₅₀ potency values were calculated in an attempt to relate exposure to in vitro potencies. When factoring for exposure, 95% of the annotated compounds with a C(ss)/BSEP IC₅₀ ratio ≥ 0.1 were associated with some form of liver injury. We then investigated the relationship between clinical evidence of liver injury and effects to multidrug resistance-associated proteins (MRPs) believed to play a role in BA homeostasis. The effect of 600+ drugs on MRP2, MRP3, and MRP4 function was also evaluated in membrane vesicle assays. Drugs with a C(ss)/BSEP IC₅₀ ratio ≥ 0.1 and a C(ss)/MRP IC₅₀ ratio ≥ 0.1 had almost a 100% correlation with some evidence of liver injury in humans. These data suggest that integration of exposure data, and knowledge of an effect to not only BSEP but also one or more of the MRPs, is a useful tool for informing the potential for liver injury due to altered BA transport.

Topics: Animals; ATP Binding Cassette Transporter, Subfamily B; ATP Binding Cassette Transporter, Subfamily B, Member 11; ATP-Binding Cassette Transporters; Biological Transport; Chemical and Drug Induced Liver Injury; Cluster Analysis; Drug-Related Side Effects and Adverse Reactions; Humans; Liver; Male; Multidrug Resistance-Associated Proteins; Pharmacokinetics; Rats; Rats, Sprague-Dawley; Recombinant Proteins; Risk Assessment; Risk Factors; Toxicity Tests

Drug-induced liver injury is one of the main causes of drug attrition. The ability to predict the liver effects of drug candidates from their chemical structures is critical to help guide experimental drug discovery projects toward safer medicines. In this study, we have compiled a data set of 951 compounds reported to produce a wide range of effects in the liver in different species, comprising humans, rodents, and nonrodents. The liver effects for this data set were obtained as assertional metadata, generated from MEDLINE abstracts using a unique combination of lexical and linguistic methods and ontological rules. We have analyzed this data set using conventional cheminformatics approaches and addressed several questions pertaining to cross-species concordance of liver effects, chemical determinants of liver effects in humans, and the prediction of whether a given compound is likely to cause a liver effect in humans. We found that the concordance of liver effects was relatively low (ca. 39-44%) between different species, raising the possibility that species specificity could depend on specific features of chemical structure. Compounds were clustered by their chemical similarity, and similar compounds were examined for the expected similarity of their species-dependent liver effect profiles. In most cases, similar profiles were observed for members of the same cluster, but some compounds appeared as outliers. The outliers were the subject of focused assertion regeneration from MEDLINE as well as other data sources. In some cases, additional biological assertions were identified, which were in line with expectations based on compounds' chemical similarities. The assertions were further converted to binary annotations of underlying chemicals (i.e., liver effect vs no liver effect), and binary quantitative structure-activity relationship (QSAR) models were generated to predict whether a compound would be expected to produce liver effects in humans. Despite the apparent heterogeneity of data, models have shown good predictive power assessed by external 5-fold cross-validation procedures. The external predictive power of binary QSAR models was further confirmed by their application to compounds that were retrieved or studied after the model was developed. To the best of our knowledge, this is the first study for chemical toxicity prediction that applied QSAR modeling and other cheminformatics techniques to observational data generated by the means of automate

Topics: Animals; Chemical and Drug Induced Liver Injury; Cluster Analysis; Databases, Factual; Humans; MEDLINE; Mice; Models, Chemical; Molecular Conformation; Quantitative Structure-Activity Relationship

Topics: Aged; Anti-Inflammatory Agents, Non-Steroidal; Chemical and Drug Induced Liver Injury; Female; Humans; Male; Middle Aged; ortho-Aminobenzoates