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Updated: Mar 25, 2026
Murine Precision-Cut Liver Slices as an Ex Vivo Model of Liver Biology
Published on: March 14, 2020
Classification of Cholestatic and Necrotic Hepatotoxicants Using Transcriptomics on Human Precision-Cut Liver Slices
Suresh Vatakuti, Jeroen L A Pennings1, Emilia Gore
1National Institute for Public Health and the Environment , Bilthoven, The Netherlands.
Abstract:
Human toxicity screening is an important stage in the development of safe drug candidates. Hepatotoxicity is one of the major reasons for the withdrawal of drugs from the market because the liver is the major organ involved in drug metabolism, and it can generate toxic metabolites. There is a need to screen molecules for drug-induced hepatotoxicity in humans at an earlier stage. Transcriptomics is a technique widely used to screen molecules for toxicity and to unravel toxicity mechanisms. To date, the majority of such studies were performed using animals or animal cells, with concomitant difficulty in interpretation due to species differences, or in human hepatoma cell lines or cultured hepatocytes, suffering from the lack of physiological expression of enzymes and transporters and lack of nonparenchymal cells. The aim of this study was to classify known hepatotoxicants on their phenotype of toxicity in humans using gene expression profiles ex vivo in human precision-cut liver slices (PCLS). Hepatotoxicants known to induce either necrosis (n = 5) or cholestasis (n = 5) were used at concentrations inducing low (<30%) and medium (30-50%) cytotoxicity, based on ATP content. Random forest and support vector machine algorithms were used to classify hepatotoxicants using a leave-one-compound-out cross-validation method. Optimized biomarker sets were compared to derive a consensus list of markers. Classification correctly predicted the toxicity phenotype with an accuracy of 70-80%. The classification is slightly better for the low than for the medium cytotoxicity. The consensus list of markers includes endoplasmic reticulum stress genes, such as C2ORF30, DNAJB9, DNAJC12, SRP72, TMED7, and UBA5, and a sodium/bile acid cotransporter (SLC10A7). This study shows that human PCLS are a useful model to predict the phenotype of drug-induced hepatotoxicity. Additional compounds should be included to confirm the consensus list of markers, which could then be used to develop a biomarker PCR-array for hepatotoxicity screening.
Insights
Human precision-cut liver slices (PCLS) effectively predict drug-induced liver toxicity phenotypes. Gene expression profiling identified key biomarkers for hepatotoxicity screening, improving early-stage drug safety assessment.
Area of Science:
- Toxicology
- Genomics
- Drug Development
Background:
- Hepatotoxicity is a primary cause of drug withdrawal, necessitating early screening methods.
- Current toxicity screening models (animal, cell lines) have limitations in human relevance.
- Transcriptomics offers insights into toxicity mechanisms but requires physiologically relevant models.
Purpose of the Study:
- To classify known hepatotoxicants based on their toxicity phenotype in humans.
- To utilize gene expression profiles from human precision-cut liver slices (PCLS) for toxicity classification.
- To identify novel biomarkers for predicting drug-induced liver injury.
Main Methods:
- Hepatotoxicants inducing necrosis or cholestasis were tested in human PCLS at varying cytotoxicity levels.
- Gene expression profiles were analyzed using Random Forest and Support Vector Machine algorithms.
- A leave-one-compound-out cross-validation method was employed for classification accuracy.
Main Results:
- The classification model accurately predicted toxicity phenotypes with 70-80% accuracy.
- Classification performance was slightly better for low cytotoxicity compared to medium cytotoxicity.
- A consensus list of biomarkers, including endoplasmic reticulum stress genes and SLC10A7, was identified.
Conclusions:
- Human PCLS represent a valuable model for predicting drug-induced hepatotoxicity phenotypes.
- The identified consensus biomarkers could form the basis for a novel hepatotoxicity screening tool.
- Further validation with additional compounds is recommended to refine the biomarker set for a PCR-array.
