Drug-induced liver injury classification model based on in vitro human transcriptomics and in vivo rat clinical chemistry data

2014 ◽  
Vol 2 (4) ◽  
pp. 63-70 ◽  
Author(s):  
Danyel Jennen ◽  
Jan Polman ◽  
Mark Bessem ◽  
Maarten Coonen ◽  
Joost van Delft ◽  
...  
Keyword(s):  
Liver Injury ◽  
Clinical Chemistry ◽  
Classification Model ◽  
Drug Induced ◽  
Drug Induced Liver Injury ◽  
Chemistry Data ◽  
Model Based ◽  
Injury Classification

scholarly journals Current Perspective: 3D Spheroid Models Utilizing Human-Based Cells for Investigating Metabolism-Dependent Drug-Induced Liver Injury

2020 ◽  
Vol 2 ◽  
Author(s):  
Christopher R. Cox ◽  
Stephen Lynch ◽  
Christopher Goldring ◽  
Parveen Sharma
Keyword(s):  
Liver Injury ◽  
Pharmaceutical Companies ◽  
Drug Induced ◽  
Drug Induced Liver Injury ◽  
Current Perspective ◽  
Dosing Regimens ◽  
Underlying Mechanisms ◽  
Approved Drugs

Drug-induced liver injury (DILI) remains a leading cause for the withdrawal of approved drugs. This has significant financial implications for pharmaceutical companies, places increasing strain on global health services, and causes harm to patients. For these reasons, it is essential that in-vitro liver models are capable of detecting DILI-positive compounds and their underlying mechanisms, prior to their approval and administration to patients or volunteers in clinical trials. Metabolism-dependent DILI is an important mechanism of drug-induced toxicity, which often involves the CYP450 family of enzymes, and is associated with the production of a chemically reactive metabolite and/or inefficient removal and accumulation of potentially toxic compounds. Unfortunately, many of the traditional in-vitro liver models fall short of their in-vivo counterparts, failing to recapitulate the mature hepatocyte phenotype, becoming metabolically incompetent, and lacking the longevity to investigate and detect metabolism-dependent DILI and those associated with chronic and repeat dosing regimens. Nevertheless, evidence is gathering to indicate that growing cells in 3D formats can increase the complexity of these models, promoting a more mature-hepatocyte phenotype and increasing their longevity, in vitro. This review will discuss the use of 3D in vitro models, namely spheroids, organoids, and perfusion-based systems to establish suitable liver models to investigate metabolism-dependent DILI.

scholarly journals TAMH: A Useful In Vitro Model for Assessing Hepatotoxic Mechanisms

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Madison Davis ◽  
Brendan D. Stamper
Keyword(s):  
Liver Injury ◽  
Transforming Growth Factor ◽  
Chemical Exposure ◽  
Health Concern ◽  
Hepatocellular Injury ◽  
Drug Induced ◽  
Endogenous Factors ◽  
Drug Induced Liver Injury

In vitro models for hepatotoxicity can be useful tools to predict in vivo responses. In this review, we discuss the use of the transforming growth factor-αtransgenic mouse hepatocyte (TAMH) cell line, which is an attractive model to study drug-induced liver injury due to its ability to retain a stable phenotype and express drug-metabolizing enzymes. Hepatotoxicity involves damage to the liver and is often associated with chemical exposure. Since the liver is a major site for drug metabolism, drug-induced liver injury is a serious health concern for certain agents. At the molecular level, various mechanisms may protect or harm the liver during drug-induced hepatocellular injury including signaling pathways and endogenous factors (e.g., Bcl-2, GSH, Nrf2, or MAPK). The interplay between these and other pathways in the hepatocyte can change upon drug or drug metabolite exposure leading to intracellular stress and eventually cell death and liver injury. This review focuses on mechanistic studies investigating drug-induced toxicity in the TAMH line and how alterations to hepatotoxic mechanisms in this model relate to the in vivo situation. The agents discussed herein include acetaminophen (APAP), tetrafluoroethylcysteine (TFEC), flutamide, PD0325901, lapatinib, and flupirtine.

scholarly journals miR-15a-3p Protects Against Isoniazid-Induced Liver Injury via Suppressing N-Acetyltransferase 2 Expression

2021 ◽  
Vol 8 ◽  
Author(s):  
Xinmei Li ◽  
Heng Zhang ◽  
Lin Xu ◽  
Yuan Jin ◽  
Jiao Luo ◽  
...  
Keyword(s):  
Liver Injury ◽  
Drug Efficacy ◽  
Mature Mirnas ◽  
Drug Induced ◽  
Drug Induced Liver Injury ◽  
Expression Activity ◽  
Underlying Mechanisms ◽  
Line Drug

Isoniazid (INH), an effective first-line drug for tuberculosis treatment, has been reported to be associated with hepatotoxicity for decades, but the underlying mechanisms are poorly understood. N-acetyltransferase 2 (NAT2) is a Phase II enzyme that specifically catalyzes the acetylation of INH, and NAT2 expression/activity play pivotal roles in INH metabolism, drug efficacy, and toxicity. In this study, we systematically investigated the regulatory roles of microRNA (miRNA) in NAT2 expression and INH-induced liver injury via a series of in silico, in vitro, and in vivo analyses. Four mature miRNAs, including hsa-miR-15a-3p, hsa-miR-628-5p, hsa-miR-1262, and hsa-miR-3132, were predicted to target the NAT2 transcript, and a negative correlation was observed between hsa-miR-15a-3p and NAT2 transcripts in liver samples. Further experiments serially revealed that hsa-miR-15a-3p was able to interact with the 3′-untranslated region (UTR) of NAT2 directly, suppressed the endogenous NAT2 expression, and then inhibited INH-induced NAT2 overexpression as well as INH-induced liver injury, both in liver cells and mouse model. In summary, our results identified hsa-miR-15a-3p as a novel epigenetic factor modulating NAT2 expression and as a protective module against INH-induced liver injury, and provided new clues to elucidate the epigenetic regulatory mechanisms concerning drug-induced liver injury (DILI).

Modulation of NRF2/ARE pathway- and cell death-related genes during drug-induced liver injury

2021 ◽  
pp. 096032712110279
Author(s):  
BY Ghanim ◽  
MI Ahmad ◽  
QM Abdallah ◽  
LA Qatouseh ◽  
NA Qinna
Keyword(s):  
Cell Death ◽  
Liver Injury ◽  
Antioxidant Response ◽  
Drug Induced ◽  
Drug Induced Liver Injury ◽  
Severity Of Injury ◽  
Primary Mouse ◽  
Dose Dependent

Transcriptional factor NRF2 is an emerging tool in reviewing mechanistic behavior of drug-specific injury pathways. Drug-induced liver injury (DILI) represents a major clinical concern that often manifests oxidative stress and cell death. Despite the pivotal role of NRF2 pathway in liver pathologies, it is questioned whether NRF2 activation or regulatory efficiency could be hindered in by the severity of DILI and progression of cell death. In this study, we evaluate NRF2 as a biomarker to DILI in comparison to severity of injury as well as explore stress mediating factors affecting Nrf2 expression. In vivo DILI model was established in C57BL/6 mice by acetaminophen (APAP) at different toxic doses, confirmed by dose-dependent liver pathological changes and accompanied with in vitro time- and dose-dependent depletion of GSH and SOD in isolated primary mouse hepatocytes. Increase in liver NRF2 translocation and cytosolic content was observed in 70 mg/kg APAP-treated mice. At this subtoxic dose, liver Nrf2 transcription was increased in mice by 18.3-fold, a prominent downregulation was seen in ARE (antioxidant response element) genes; Hmox1, Nqo1 and Glcm, and apoptotic Bcl2 regulating genes. In addition, upregulation in necrosis inducer Parp2 was associated to downregulation in Hmgb1. Collectively, expression of genes related to cell survival were regulated at mild APAP hepatotoxicity. By increasing APAP dose, hemorrhagic necrosis and impaired genetic transcription in both Nrf2 and several other genes were evident. In conclusion, NRF2/ARE system and cell death modulation is halted by the increase of chemical stress and found directly associated with DILI severity.

scholarly journals (+)-Clausenamide protects against drug-induced liver injury by inhibiting hepatocyte ferroptosis

2020 ◽  
Vol 11 (9) ◽  
Author(s):  
Min Wang ◽  
Chun-Yu Liu ◽  
Tian Wang ◽  
Hong-Min Yu ◽  
Shu-Hua Ouyang ◽  
...  
Keyword(s):  
Liver Injury ◽  
Liver Damage ◽  
Mouse Liver ◽  
Mrna Level ◽  
Intervention Strategy ◽  
Drug Induced ◽  
Drug Induced Liver Injury ◽  
Underlying Mechanisms

Abstract Drug-induced liver injury is the major cause of acute liver failure. However, the underlying mechanisms seem to be multifaceted and remain poorly understood, resulting in few effective therapies. Here, we report a novel mechanism that contributes to acetaminophen-induced hepatotoxicity through the induction of ferroptosis, a distinctive form of programmed cell death. We subsequently identified therapies protective against acetaminophen-induced liver damage and found that (+)-clausenamide ((+)-CLA), an active alkaloid isolated from the leaves of Clausena lansium (Lour.) Skeels, inhibited acetaminophen-induced hepatocyte ferroptosis both in vivo and in vitro. Consistently, (+)-CLA significantly alleviated acetaminophen-induced or erastin-induced hepatic pathological damages, hepatic dysfunctions and excessive production of lipid peroxidation both in cultured hepatic cell lines and mouse liver. Furthermore, treatment with (+)-CLA reduced the mRNA level of prostaglandin endoperoxide synthase 2 while it increased the protein level of glutathione peroxidase 4 in hepatocytes and mouse liver, confirming that the inhibition of ferroptosis contributes to the protective effect of (+)-CLA on drug-induced liver damage. We further revealed that (+)-CLA specifically reacted with the Cys-151 residue of Keap1, which blocked Nrf2 ubiquitylation and resulted in an increased Nrf2 stability, thereby leading to the activation of the Keap1–Nrf2 pathway to prevent drug-induced hepatocyte ferroptosis. Our studies illustrate the innovative mechanisms of acetaminophen-induced liver damage and present a novel intervention strategy to treat drug overdose by using (+)-CLA.

scholarly journals Recent Advances in Models of Immune-Mediated Drug-Induced Liver Injury

2021 ◽  
Vol 3 ◽  
Author(s):  
Farah Tasnim ◽  
Xiaozhong Huang ◽  
Christopher Zhe Wei Lee ◽  
Florent Ginhoux ◽  
Hanry Yu
Keyword(s):  
T Cells ◽  
Liver Injury ◽  
Complex Disease ◽  
Cell Contact ◽  
Drug Induced ◽  
Drug Induced Liver Injury ◽  
Immune Mediated ◽  
Cell Cell

Hepatic inflammation is a key feature of a variety of liver diseases including drug-induced liver injury (DILI), orchestrated by the innate immune response (Kupffer cells, monocytes, neutrophils, dendritic cells) and the adaptive immune system (T cells and natural killer T cells). In contrast to acute DILI, prediction of immune-mediated DILI (im-DILI) has been more challenging due to complex disease pathogenesis, lack of reliable models and limited knowledge of underlying mechanisms. This review summarizes in vivo and in vitro systems that have been used to model im-DILI. In particular, the review focuses on state-of-the-art in vitro human-based multicellular models which have been developed to supplement the use of in vivo models due to interspecies variation and increasing ethical concerns regarding animal use. Advantages of the co-cultures in maintaining hepatocyte functions and importantly, introducing heterotypic cell-cell interactions to mimic inflammatory hepatic microenvironment are discussed. Challenges regarding cell source and incorporation of different cells with physical cell-cell contact are outlined and potential solutions are proposed. It is likely that better understanding of the interplay of immune cells in liver models will allow for the development of more accurate systems to better predict hepatotoxicity and stratification of drugs that can cause immune-mediated effects.

scholarly journals Computational Models Using Multiple Machine Learning Algorithms for Predicting Drug Hepatotoxicity with the DILIrank Dataset

2020 ◽  
Author(s):  
Robert Ancuceanu ◽  
Marilena Viorica Hovanet ◽  
Adriana Iuliana Anghel ◽  
Florentina Furtunescu ◽  
Monica Neagu ◽  
...  
Keyword(s):  
Machine Learning ◽  
Liver Injury ◽  
Computational Models ◽  
Liver Toxicity ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Drug Induced ◽  
Reference Drug ◽  
Drug Induced Liver Injury

Drug induced liver injury (DILI) remains one of the challenges in the safety profile of both authorized drugs and candidate drugs and predicting hepatotoxicity from the chemical structure of a substance remains a challenge worth pursuing, being also coherent with the current tendency for replacing non-clinical tests with in vitro or in silico alternatives. In 2016 a group of researchers from FDA published an improved annotated list of drugs with respect to their DILI risk, constituting “the largest reference drug list ranked by the risk for developing drug-induced liver injury in humans”, DILIrank. This paper is one of the few attempting to predict liver toxicity using the DILIrank dataset. Molecular descriptors were computed with the Dragon 7.0 software, and a variety of feature selection and machine learning algorithms were implemented in the R computing environment. Nested (double) cross-validation was used to externally validate the models selected. A number of 78 models with reasonable performance have been selected and stacked through several approaches, including the building of multiple meta-models. The performance of the stacked models was slightly superior to other models published. The models were applied in a virtual screening exercise on over 100,000 compounds from the ZINC database and about 20% of them were predicted to be non-hepatotoxic.

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