Systems Toxicology Research Articles

Quantitative Systems Toxicology Identifies Independent Mechanisms for Hepatotoxicity and Bilirubin Elevations Due to AKR1C3 Inhibitor BAY1128688.

BAY1128688 is a selective inhibitor of AKR1C3, investigated recently in a trial that was prematurely terminated due to drug-induced liver injury. These unexpected observations prompted use of the quantitative systems toxicology model, DILIsym, to determine possible mechanisms of hepatotoxicity. Using mechanistic in vitro toxicity data as well as clinical exposure data, DILIsym predicted the potential for BAY1128688 to cause liver toxicity (elevations in serum alanine aminotransferase (ALT)) and elevations in serum bilirubin. Initial simulations overpredicted hepatotoxicity and bilirubin elevations, so the BAY1128688 representation within DILIsym underwent optimization. The liver partition coefficient Kp was altered to align simulated bilirubin elevations with those observed clinically. Altering the mode of bile acid canalicular and basolateral efflux inhibition was necessary to accurately predict ALT elevations. Optimization results support that bilirubin elevations observed early during treatment are due to altered bilirubin metabolism and transporter inhibition, which is independent of liver injury. The modeling further supports that on-treatment ALT elevations result from inhibition of bile acid transporters, particularly the bile salt excretory pump, leading to accumulation of toxic bile acids. The predicted dose-dependent intrinsic hepatotoxicity may increase patient susceptibility to an adaptive immune response, accounting for ALT elevations observed after completion of treatment. These BAY1128688 simulations provide insight into the mechanisms behind hepatotoxicity and bilirubin elevations and may inform the potential risk posed by future compounds.

Assessing liver effects of Cannabidiol and Valproate alone and in Combination using Quantitative Systems Toxicology.

In clinical trials of cannabidiol (CBD) for the treatment of seizures in patients with Dravet syndrome, Lennox-Gastaut syndrome, and tuberous sclerosis complex, elevations in serum alanine aminotransferase (ALT) >3× the upper limit of normal (ULN) were observed in some patents, but the incidence was much greater in patients who were receiving treatment with valproate (VPA) before starting CBD. To explore potential mechanisms underlying this interaction, we used DILIsym®, a quantitative systems toxicology (QST) model, to predict ALT elevations in a simulated human population treated with CBD alone, VPA alone, and when CBD dosing was starting during treatment with VPA. We gathered in vitro data assessing the potential for CBD, the two major CBD metabolites, and VPA to cause hepatotoxicity via inhibition of bile acid transporters, mitochondrial dysfunction, and production of reactive oxygen species (ROS). Physiologically-based pharmacokinetic (PBPK) models for CBD and VPA were used to predict liver exposure. DILIsym simulations predicted dose-dependent ALT elevations from CBD treatment and this was predominantly driven by ROS production from the parent molecule. DILIsym also predicted VPA treatment to cause ALT elevations which were transient when mitochondrial biogenesis was incorporated into the model. Contrary to the clinical experience, simulation of two weeks treatment with VPA prior to introduction of CBD treatment did not predict an increase the incidence of ALT elevations relative to CBD treatment alone. We conclude that the marked increased incidence of CBD-associated ALT elevations in patients already receiving VPA is unlikely to involve the three major mechanisms of direct hepatotoxicity.

Assessing network-based methods in the context of system toxicology.

Introduction: Network-based methods are promising approaches in systems toxicology because they can be used to predict the effects of drugs and chemicals on health, to elucidate the mode of action of compounds, and to identify biomarkers of toxicity. Over the years, the network biology community has developed a wide range of methods, and users are faced with the task of choosing the most appropriate method for their own application. Furthermore, the advantages and limitations of each method are difficult to determine without a proper standard and comparative evaluation of their performance. This study aims to evaluate different network-based methods that can be used to gain biological insight into the mechanisms of drug toxicity, using valproic acid (VPA)-induced liver steatosis as a benchmark. Methods: We provide a comprehensive analysis of the results produced by each method and highlight the fact that the experimental design (how the method is applied) is relevant in addition to the method specifications. We also contribute with a systematic methodology to analyse the results of the methods individually and in a comparative manner. Results: Our results show that the evaluated tools differ in their performance against the benchmark and in their ability to provide novel insights into the mechanism of adverse effects of the drug. We also suggest that aggregation of the results provided by different methods provides a more confident set of candidate genes and processes to further the knowledge of the drug's mechanism of action. Discussion: By providing a detailed and systematic analysis of the results of different network-based tools, we aim to assist users in making informed decisions about the most appropriate method for systems toxicology applications.

The Combination of a Human Biomimetic Liver Microphysiology System with BIOLOGXsym, a Quantitative Systems Toxicology (QST) Modeling Platform for Macromolecules, Provides Mechanistic Understanding of Tocilizumab- and GGF2-Induced Liver Injury.

Biologics address a range of unmet clinical needs, but the occurrence of biologics-induced liver injury remains a major challenge. Development of cimaglermin alfa (GGF2) was terminated due to transient elevations in serum aminotransferases and total bilirubin. Tocilizumab has been reported to induce transient aminotransferase elevations, requiring frequent monitoring. To evaluate the clinical risk of biologics-induced liver injury, a novel quantitative systems toxicology modeling platform, BIOLOGXsym™, representing relevant liver biochemistry and the mechanistic effects of biologics on liver pathophysiology, was developed in conjunction with clinically relevant data from a human biomimetic liver microphysiology system. Phenotypic and mechanistic toxicity data and metabolomics analysis from the Liver Acinus Microphysiology System showed that tocilizumab and GGF2 increased high mobility group box 1, indicating hepatic injury and stress. Tocilizumab exposure was associated with increased oxidative stress and extracellular/tissue remodeling, and GGF2 decreased bile acid secretion. BIOLOGXsym simulations, leveraging the in vivo exposure predicted by physiologically-based pharmacokinetic modeling and mechanistic toxicity data from the Liver Acinus Microphysiology System, reproduced the clinically observed liver signals of tocilizumab and GGF2, demonstrating that mechanistic toxicity data from microphysiology systems can be successfully integrated into a quantitative systems toxicology model to identify liabilities of biologics-induced liver injury and provide mechanistic insights into observed liver safety signals.

Mechanistic Insights into the Biological Effects of Engineered Nanomaterials: A Focus on Gold Nanoparticles.

Nanotechnology has great potential to significantly advance the biomedical field for the benefit of human health. However, the limited understanding of nano-bio interactions leading to unknowns about the potential adverse health effects of engineered nanomaterials and to the poor efficacy of nanomedicines has hindered their use and commercialization. This is well evidenced considering gold nanoparticles, one of the most promising nanomaterials for biomedical applications. Thus, a fundamental understanding of nano-bio interactions is of interest to nanotoxicology and nanomedicine, enabling the development of safe-by-design nanomaterials and improving the efficacy of nanomedicines. In this review, we introduce the advanced approaches currently applied in nano-bio interaction studies-omics and systems toxicology-to provide insights into the biological effects of nanomaterials at the molecular level. We highlight the use of omics and systems toxicology studies focusing on the assessment of the mechanisms underlying the in vitro biological responses to gold nanoparticles. First, the great potential of gold-based nanoplatforms to improve healthcare along with the main challenges for their clinical translation are presented. We then discuss the current limitations in the translation of omics data to support risk assessment of engineered nanomaterials.

Investigating bile acid-mediated cholestatic drug-induced liver injury using a mechanistic model of multidrug resistance protein 3 (MDR3) inhibition.

Inhibition of the canalicular phospholipid floppase multidrug resistance protein 3 (MDR3) has been implicated in cholestatic drug-induced liver injury (DILI), which is clinically characterized by disrupted bile flow and damage to the biliary epithelium. Reduction in phospholipid excretion, as a consequence of MDR3 inhibition, decreases the formation of mixed micelles consisting of bile acids and phospholipids in the bile duct, resulting in a surplus of free bile acids that can damage the bile duct epithelial cells, i.e., cholangiocytes. Cholangiocytes may compensate for biliary increases in bile acid monomers via the cholehepatic shunt pathway or bicarbonate secretion, thereby influencing viability or progression to toxicity. To address the unmet need to predict drug-induced bile duct injury in humans, DILIsym, a quantitative systems toxicology model of DILI, was extended by representing key features of the bile duct, cholangiocyte functionality, bile acid and phospholipid disposition, and cholestatic hepatotoxicity. A virtual, healthy representative subject and population (n = 285) were calibrated and validated utilizing a variety of clinical data. Sensitivity analyses were performed for 1) the cholehepatic shunt pathway, 2) biliary bicarbonate concentrations and 3) modes of MDR3 inhibition. Simulations showed that an increase in shunting may decrease the biliary bile acid burden, but raise the hepatocellular concentrations of bile acids. Elevating the biliary concentration of bicarbonate may decrease bile acid shunting, but increase bile flow rate. In contrast to competitive inhibition, simulations demonstrated that non-competitive and mixed inhibition of MDR3 had a profound impact on phospholipid efflux, elevations in the biliary bile acid-to-phospholipid ratio, cholangiocyte toxicity, and adaptation pathways. The model with its extended bile acid homeostasis representation was furthermore able to predict DILI liability for compounds with previously studied interactions with bile acid transport. The cholestatic liver injury submodel in DILIsym accounts for several processes pertinent to bile duct viability and toxicity and hence, is useful for predictions of MDR3 inhibition-mediated cholestatic DILI in humans.

Toxicogenomics scoring system: TGSS, a novel integrated risk assessment model for chemical carcinogenicity prediction

BackgroundGiven the increasing exposure of humans to environmental chemicals and the limitations of conventional toxicity test, there is an urgent need to develop next-generation risk assessment methods. ObjectivesThis study aims to establish a novel computational system named Toxicogenomics Scoring System (TGSS) to predict the carcinogenicity of chemicals coupling chemical-gene interactions with multiple cancer transcriptomic datasets. MethodsChemical-related gene signatures were derived from chemical-gene interaction data from the Comparative Toxicogenomics Database (CTD). For each cancer type in TCGA, genes were ranked by their effects on tumorigenesis, which is based on the differential expression between tumor and normal samples. Next, we developed carcinogenicity scores (C-scores) using pre-ranked GSEA to quantify the correlation between chemical-related gene signatures and ranked gene lists. Then we established TGSS by systematically evaluating the C-scores in multiple chemical-tumor pairs. Furthermore, we examined the performance of our approach by ROC curves or prognostic analyses in TCGA and multiple independent cancer cohorts. ResultsForty-six environmental chemicals were finally included in the study. C-score was calculated for each chemical-tumor pair. The C-scores of IARC Group 3 chemicals were significantly lower than those of chemicals in Group 1 (P-value = 0.02) and Group 2 (P-values = 7.49 ×10−5). ROC curves analysis indicated that C-score could distinguish “high-risk chemicals” from the other compounds (AUC = 0.67) with a specificity and sensitivity of 0.86 and 0.57. The results of survival analysis were also in line with the assessed carcinogenicity in TGSS for the chemicals in Group 1. Finally, consistent results were further validated in independent cancer cohorts. ConclusionTGSS highlighted the great potential of integrating chemical-gene interactions with gene-cancer relationships to predict the carcinogenic risk of chemicals, which would be valuable for systems toxicology.

Metabolomics- and systems toxicology-based hepatotoxicity mechanism of Sophorae Tonkinensis Radix et Rhizoma in rats.

Drug-induced liver injury (DILI) is a major challenge to the development and clinical application of drugs, especially limits the global application of Chinese herbal medicines, because the material basis and mechanisms of some Chinese herbal medicines are not well clear. In this study, a comprehensive method integrating metabolomics and systems toxicology (SysT) was used to investigate how the main substances in Sophorae Tonkinensis Radix et Rhizoma (STRER) influence the metabolic pathways and molecular mechanisms of hepatotoxicity. Through a 28-day continuous oral administration toxicity study combined with serum metabolomics analyses, the aqueous, ethanol-precipitation and dichloromethane extracts of STRER exhibited significant hepatotoxic effects. In addition, 19 differential metabolites with a time-dose-effect relationship were identified in rats. The primary bile acid biosynthesis pathway was significantly altered, which was consistent with the findings of the SysT analysis. Furthermore, through the quantification of bile acids in serum, 16 differential bile acids were identified as being significantly changed; moreover, 21 relevant targets which intersected with the hepatotoxic targets of STRER were identified. Molecular docking was used to confirm the validation of bindings between targets and corresponding compounds, and finally, six important compounds and 14 potential targets were identified to be involved in STRER-induced liver injury in relation to bile acid metabolism.

Mathematical Representation of Drug Induced Crystal Nephropathy Using a Quantitative Systems Toxicology Approach

Mathematical Representation of Drug Induced Crystal Nephropathy Using a Quantitative Systems Toxicology Approach

Introduction to the Theme "Development of New Drugs: Moving from the Bench to Bedside and Improved Patient Care".

Investigations in pharmacology and toxicology range from molecular studies to clinical care. Studies in basic and clinical pharmacology and in preclinical and clinical toxicology are all essential in bringing new knowledge and new drugs into clinical use. The 30 reviews in Volume 63 of the Annual Review of Pharmacology and Toxicology explore topics across this spectrum. Examples include "Zebrafish as a Mainstream Model for In Vivo Systems Pharmacology and Toxicology" and "Artificial Intelligence and Machine Learning for Lead-to-Candidate Decision-Making and Beyond." Other reviews discuss components important for drug discovery and development and the use of pharmaceuticals in a variety of diseases. Air pollution continues to increase globally; accordingly, "Air Pollution-Related Neurotoxicity Across the Life Span" is a timely and forward-thinking review. Volume 63 also explores the use of contemporary technologies such as electronic health records, pharmacogenetics, and new drug delivery systems that help enhance and improve the utility of new therapies.

Zebrafish as a Mainstream Model for In Vivo Systems Pharmacology and Toxicology.

Pharmacology and toxicology are part of a much broader effort to understand the relationship between chemistry and biology. While biomedicine has necessarily focused on specific cases, typically of direct human relevance, there are real advantages in pursuing more systematic approaches to characterizing how health and disease are influenced by small molecules and other interventions. In this context, the zebrafish is now established as the representative screenable vertebrate and, through ongoing advances in the available scale of genome editing and automated phenotyping, is beginning to address systems-level solutions to some biomedical problems. The addition of broader efforts to integrate information content across preclinical model organisms and the incorporation of rigorous analytics, including closed-loop deep learning, will facilitate efforts to create systems pharmacology and toxicology with the ability to continuously optimize chemical biological interactions around societal needs. In this review, we outline progress toward this goal.

Systems assessment of statins hazard: Integrating in silico prediction, developmental toxicity profile and transcriptomics in zebrafish

Statins are prescribed widely as lipid-lowering agents. However, statins are associated with an increased harmful risk on public health and the ecosystem. Little is known about statins’ toxicity on biological development and the underlying molecular mechanisms. We exposed zebrafish embryos to a series of statins to evaluate their development toxicity. Statins-induced embryonic developmental defects in a concentration-dependent manner. 72 h LC50 values for lovastatin, simvastatin, fluvastatin, atorvastatin, rosuvastatin, and pravastatin were 0.01 μM, 0.04 μM, 1.93 μM, 37.28 μM, 79.29 μM, and 2170 μM, respectively. Moreover, the expression of genes involved in heart contraction, calcium ion binding, transcription factors, nucleus, and G protein-coupled receptor signaling pathway was altered by statins. The early growth response gene (egr4) and transcription factor genes (fosab and fosb) were screened as potential toxicity targets due to their significant upregulation based on protein-protein interaction (PPI) and drug-gene interaction network analysis. Finally, the ecotoxicity profile of statins was predicted by in silico method, and statins were high or moderate risk to aquatic organisms. We provide a systems toxicology strategy to explore the toxicity of statins and illustrate the potential mechanisms of action.

High-resolution quadrupole time-of-flight mass spectrometry, a powerful technique to include in analytical scheme for the identification of drugs and chemicals in seizures: A case study

A seizure containing 37 items was analyzed with laboratory identification scheme for drugs and chemicals in seized products applying accredited methods based on gas chromatography mass spectrometry (GC-MS) and liquid chromatography with photodiode-array detection (UPLC-PDA), a category A technique combined with category B and C techniques. No identification was obtained for 1 item [analogue of lysergic acid diethylamide (LSD)] and none detected or identified by GC-MS and/or UPLC-PDA for 8 items. All items were subsequently analyzed using ultra performance liquid chromatography quadrupole time-of-flight mass spectrometry (UPLC-Q-Tof) to investigate whether it is appropriate to include this technique in laboratory identification scheme for seized materials. The seizure consisted of individual packages containing blotter papers, capsules and powders, respectively. The powders were present in sealed alu-bags labeled ‘not for human consumption’ and Falcon® tubes, presumably purchased as ‘research chemical’. Methanolic solutions were analyzed. The GC-MS method was described elsewere (Coopman V. Toxicol Anal Clin 2018;30:75–79). Automated library search was performed against NIST, SWGDRUG and CAYMAN mass spectral library and mass spectra published in scientific literature were consulted. The UPLC-PDA analysis was performed with a Waters Acquity UPLC H-Class system. The compounds were separeted on an Acquity UPLC C18 column using gradient elution with a mobile phase consisting of 0.1% (v/v) formic acid aqueous solution and 0.1% (v/v) formic acid in acetonitrile, and photodiode-arra y detection. Automated library search was performed with Empower™ 3 software against in-house and Waters library. A Waters Acquity UPLC I-Class with Xevo G2-XS QTof was used, equipped with UNIFI® scientific information system and Forensic Toxicology Screening Application from Waters with data acquisition parameters for accurate mass analysis in positive and negative mode. Analogues of LSD (1P-LSD, ETH-LAD, AL-LAD) and a designer benzodiazepine (clonazolam) respectively, were identified in blotter paper by UPLC-PDA, GC-MS and confirmed by UPLC-Q-Tof. The unknown analogue of LSD was identified as ALD-52 by UPLC-Q-Tof. 4-fluoromethylphenidate (4F-MPH), N-ethyldeschloroketamine (O-PCE) and mirtagynine were identified in powder by UPLC-PDA, GC-MS and UPLC-Q-Tof. O-PCE was not present in the Forensic Toxicology Screening Application library and was therefore not automatically identified. Salicylic acid, caffeine, trazodone, pseudoephedrine, melatonin and ETH-LAD respectively, were identified in tablet or capsule with routine laboratory identification scheme and confirmed by UPLC-Q-Tof. In a capsule found to contain pseudoephedrine and unknown, a library hit was found for the designer drug N-methyl-2-aminoindane (NM-2AI) by UPLC-Q-Tof. Laboratory identification scheme for the identification of drugs and chemicals in seizures is based on GC-MS and UPLC-PDA, a category A technique and category B, C techniques (SWGDRUG recommendations). Not all drugs and chemicals were detected with both techniques. When identification is obtained with one or any of the applied techniques, a more extensive analysis is recommended. UPLC-Q-Tof is a sensitive and powerful technique, appropriate to include in laboratory identification scheme for seized materials when identification is obtained with one or any of the applied techniques or if the presence of low concentration, a NPS or designer drugs is suspected, allowing confirmation or identification.

Hair Dye Ingredients and Potential Health Risks from Exposure to Hair Dyeing.

Given the worldwide popularity of hair dyeing, there is an urgent need to understand the toxicities and risks associated with exposure to chemicals found in hair dye formulations. Hair dyes are categorized as oxidative and nonoxidative in terms of their chemical composition and ingredients. For several decades, the expert panel’s Cosmetic Ingredient Review (CIR) has assessed the safety of many of the chemicals used in hair dyes; however, a comprehensive review of hair dye ingredients and the risk of exposure to hair dyeing has not been documented. Herein, we review the safety of the various chemicals in oxidative and nonoxidative hair dyes, toxicities associated with hair dyeing, and the carcinogenic risks related to hair dyeing. While many compounds are considered safe for users at the concentrations in hair dyes, there are conflicting data about a large number of hair dye formulations. The CIR expert panel has ratified a number of coloring ingredients for hair dyes and banned a series of chemicals as carcinogenic to animals and unsafe for this application. The use of these chemicals as raw materials for producing hair dyes may result in the synthesis of other contaminants with potential toxicities and increased risk of carcinogenesis. It is an open question whether personal or occupational hair dyeing increases the risk of cancer; however, in specific subpopulations, a positive association between hair dye use and cancer occurrence has been reported. To address this question, a better understanding of the chemical and mechanistic basis of the reported toxicities of hair dye mixtures and individual hair dye ingredients is needed. It is anticipated that in-depth chemical and systems toxicology studies harnessing modern and emerging techniques can shed light on this public health concern in the future.

Comparing the Liver Safety Profiles of 4 Next-Generation CGRP Receptor Antagonists to the Hepatotoxic CGRP Inhibitor Telcagepant Using Quantitative Systems Toxicology Modeling

Calcitonin gene-related peptide (CGRP) signaling inhibitors have shown efficacy in both the acute and preventive treatment of migraine. Telcagepant, a first-generation CGRP receptor antagonist, was effective but failed in clinical trials due to hepatotoxicity. Subsequently, although 4 next-generation CGRP receptor antagonists (rimegepant, zavegepant, atogepant, and ubrogepant) were being advanced into late-stage clinical trials, due to telcagepant’s failure, more confidence in the liver safety of these compounds was needed. DILIsym v6A, a quantitative systems toxicology (QST) model of drug-induced liver injury (DILI), was used to model all 5 compounds and thus to compare the 4 next-generation CGRP receptor antagonists to telcagepant. In vitro experiments were performed to measure the potential for each compound to inhibit bile acid transporters, produce oxidative stress, and cause mitochondrial dysfunction. Physiologically based pharmacokinetic models were produced for each compound in order to appropriately estimate liver exposure. DILIsym predicted clinical elevations of liver enzymes and bilirubin for telcagepant, correctly predicting the observed DILI liability of the first-generation compound. By contrast, DILIsym predicted that each of the 4 next-generation compounds would be significantly less likely to cause DILI than telcagepant. Subsequent clinical trials have validated these predictions for each of the 4 compounds, and all 3 of the compounds submitted to FDA to date (rimegepant, ubrogepant, and atogepant) have since been approved by the FDA with no warning for hepatotoxicity. This work demonstrates the potential for QST modeling to prospectively differentiate between hepatotoxic and nonhepatotoxic molecules within the same class.

Accurate in silico simulation of the rabbit Purkinje fiber electrophysiological assay to facilitate early pharmaceutical cardiosafety assessment: Dream or reality?

As a branch of quantitative systems toxicology, in silico simulations are of growing attractiveness to guide preclinical cardiosafety risk assessments. Traditionally, a cascade of in vitro/in vivo assays has been applied in pharmaceutical research to screen out molecules at risk for cardiac side effects and prevent subsequent risk for patients. Drug cardiosafety assessments typically employ early mechanistic, hazard-oriented in silico/in vitro assays for compound inhibition of cardiac ion channels, followed by induced pluripotent stem cells (iPSCs) or tissue-based models such as the rabbit Purkinje fiber assay, which includes the major mechanisms contributing to action potential (AP) genesis. Additionally, multiscale simulation techniques based on mathematical models have become available, which are performed in silico ‘at the heart’ of compound triage to substitute Purkinje tests and increase translatability through mechanistic interpretability. To adhere to the 3R principle and reduce animal experiments, we performed a comparative benchmark and investigated a variety of mathematical cardiac AP models, including a newly developed minimalistic model specifically tailored to the AP of rabbit Purkinje cells, for their ability to substitute experiments. The simulated changes in AP duration (dAPD90) at increasing drug concentrations were compared to experimental results from 588 internal Purkinje fiber studies covering 555 different drugs with diverse modes of action. Using our minimalistic model, 80% of the Purkinje experiments could be quantitatively reproduced. This result allows for significant saving of experimental effort in early research and justifies the embedding of electrophysiological simulations into the DMTA (Design, Make, Test, Analyze) cycle in pharmaceutical compound optimization.

Screening of ToxCast Chemicals Responsible for Human Adverse Outcomes with Exposure to Ambient Air.

Air pollution poses a major threat to global public health. Although there have been a few investigations into the relationships between organic pollutants and adverse outcomes, the responsible components and molecular mechanisms may be ignored. In this study, a suspect screening method combining comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry (GC × GC-TOF MS) with the Toxicity Forecaster (ToxCast) database was applied to analyze complex hydrophobic compounds in ambient air and prospectively figure out toxicologically significant compounds. Seventy-six ToxCast compounds were screened, including seven pollutants receiving less attention and five chemicals never published in the air previously. Given the concentrations, bioactivities, as well as absorption, distribution, metabolism, and excretion properties in vivo, 29 contaminants were assigned high priority since they had active biological effects in the vascular, lung, liver, kidney, prostate, and bone tissues. Phenotypic linkages of key pollutants to potential mechanistic pathways were explored by systems toxicology. A total of 267 chemical-effect pathways involving 29 toxicants and 31 molecular targets were mapped in bipartite network, in which 12 key pathogenic pathways were clarified, which not only provided evidence supporting the previous hypothesis but also provided new insights into the molecular targets. The results would facilitate the development of pollutant priority control, population intervention, and clinical therapeutic strategies so as to substantially reduce human health hazards induced by urban air.

The Negative Bidirectional Interaction Between Climate Change and the Prevalence and Care of Liver Disease: A Joint BSG, BASL, EASL, and AASLD Commentary

The Negative Bidirectional Interaction Between Climate Change and the Prevalence and Care of Liver Disease: A Joint BSG, BASL, EASL, and AASLD Commentary

Mechanism of hepatobiliary toxicity of the LPA1 antagonist BMS-986020 developed to treat idiopathic pulmonary fibrosis: Contrasts with BMS-986234 and BMS-986278

In a Phase 2 clinical trial, BMS-986020, a lysophosphatidic acid receptor-1 (LPA1) antagonist, produced hepatobiliary toxicity (increased ALT, AST, and ALP; cholecystitis) and increases in plasma bile acids (BA). Nonclinical investigations conducted to identify a potential mechanism(s) for this toxicity examined BMS-986020 and two LPA1 antagonists structurally distinct from BMS-986020 (BMS-986234 and BMS-986278). BMS-986020 inhibited hepatic BA efflux transporters BSEP (IC50 1.8 μM), MRP3 (IC50 22 μM), and MRP4 (IC50 6.2 μM) and inhibited BA canalicular efflux in human hepatocytes (68% at 10 μM). BMS-986020 inhibited mitochondrial function (basal and maximal respiration, ATP production, and spare capacity) in human hepatocytes and cholangiocytes at ≥10 μM and inhibited phospholipid efflux in human hepatocytes (MDR3 IC50 7.5 μM). A quantitative systems toxicology analysis (DILIsym®), considering pharmacokinetics, BA homeostasis, mitochondrial function, oxidative phosphorylation, and reactive intermediates performed for BMS-986020 recapitulated clinical findings ascribing the effects to BA transporter and mitochondrial electron transport chain inhibition. BMS-986234 and BMS-986278 minimally inhibited hepatic BA transporters (IC50 ≥20 μM) and did not inhibit MDR3 activity (IC50 >100 μM), nor did BMS-986234 inhibit BA efflux (≤50 μM) or mitochondrial function (≤30 μM) (BMS-986278 not evaluated). Multiple mechanisms may be involved in the clinical toxicity observed with BMS-986020. The data indicate that this toxicity was unrelated to LPA1 antagonism since the mechanisms that likely influenced the adverse clinical outcome of BMS-986020 were not observed with equipotent LPA1 antagonists BMS-986234 and BMS-986278. This conclusion is consistent with the lack of hepatobiliary toxicity in nonclinical and clinical safety studies with BMS-986278.

Unravelling Mechanisms of Doxorubicin-Induced Toxicity in 3D Human Intestinal Organoids.

Doxorubicin is widely used in the treatment of different cancers, and its side effects can be severe in many tissues, including the intestines. Symptoms such as diarrhoea and abdominal pain caused by intestinal inflammation lead to the interruption of chemotherapy. Nevertheless, the molecular mechanisms associated with doxorubicin intestinal toxicity have been poorly explored. This study aims to investigate such mechanisms by exposing 3D small intestine and colon organoids to doxorubicin and to evaluate transcriptomic responses in relation to viability and apoptosis as physiological endpoints. The in vitro concentrations and dosing regimens of doxorubicin were selected based on physiologically based pharmacokinetic model simulations of treatment regimens recommended for cancer patients. Cytotoxicity and cell morphology were evaluated as well as gene expression and biological pathways affected by doxorubicin. In both types of organoids, cell cycle, the p53 signalling pathway, and oxidative stress were the most affected pathways. However, significant differences between colon and SI organoids were evident, particularly in essential metabolic pathways. Short time-series expression miner was used to further explore temporal changes in gene profiles, which identified distinct tissue responses. Finally, in silico proteomics revealed important proteins involved in doxorubicin metabolism and cellular processes that were in line with the transcriptomic responses, including cell cycle and senescence, transport of molecules, and mitochondria impairment. This study provides new insight into doxorubicin-induced effects on the gene expression levels in the intestines. Currently, we are exploring the potential use of these data in establishing quantitative systems toxicology models for the prediction of drug-induced gastrointestinal toxicity.