Literature DB >> 26881866

Classification of Cholestatic and Necrotic Hepatotoxicants Using Transcriptomics on Human Precision-Cut Liver Slices.

Suresh Vatakuti, Jeroen L A Pennings1, Emilia Gore, Peter Olinga, Geny M M Groothuis.   

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.

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Year:  2016        PMID: 26881866     DOI: 10.1021/acs.chemrestox.5b00491

Source DB:  PubMed          Journal:  Chem Res Toxicol        ISSN: 0893-228X            Impact factor:   3.739


  5 in total

1.  Metformin Disrupts Bile Acid Efflux by Repressing Bile Salt Export Pump Expression.

Authors:  Brandy Garzel; Tao Hu; Linhao Li; Yuanfu Lu; Scott Heyward; James Polli; Lei Zhang; Shiew-Mei Huang; Jean-Pierre Raufman; Hongbing Wang
Journal:  Pharm Res       Date:  2020-01-06       Impact factor: 4.200

Review 2.  Best Practices and Progress in Precision-Cut Liver Slice Cultures.

Authors:  Liza Dewyse; Hendrik Reynaert; Leo A van Grunsven
Journal:  Int J Mol Sci       Date:  2021-07-01       Impact factor: 5.923

3.  Integration of metabolomics and transcriptomics in nanotoxicity studies.

Authors:  Tae Hwan Shin; Da Yeon Lee; Hyeon-Seong Lee; Hyung Jin Park; Moon Suk Jin; Man-Jeong Paik; Balachandran Manavalan; Jung-Soon Mo; Gwang Lee
Journal:  BMB Rep       Date:  2018-01       Impact factor: 4.778

4.  Improved Precision-Cut Liver Slice Cultures for Testing Drug-Induced Liver Fibrosis.

Authors:  Liza Dewyse; Vincent De Smet; Stefaan Verhulst; Nathalie Eysackers; Rastislav Kunda; Nouredin Messaoudi; Hendrik Reynaert; Leo A van Grunsven
Journal:  Front Med (Lausanne)       Date:  2022-03-30

5.  Validation of precision-cut liver slices to study drug-induced cholestasis: a transcriptomics approach.

Authors:  Suresh Vatakuti; Peter Olinga; Jeroen L A Pennings; Geny M M Groothuis
Journal:  Arch Toxicol       Date:  2016-06-25       Impact factor: 5.153

  5 in total

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