Comparing in vitro human liver models to in vivo human liver using RNA-Seq

Rajinder Gupta; Yannick Schrooders; Duncan Hauser; Marcel van Herwijnen; Wiebke Albrecht; Bas Ter Braak; Tim Brecklinghaus; Jose V Castell; Leroy Elenschneider; Sylvia Escher; Patrick Guye; Jan G Hengstler; Ahmed Ghallab; Tanja Hansen; Marcel Leist; Richard Maclennan; Wolfgang Moritz; Laia Tolosa; Tine Tricot; Catherine Verfaillie; Paul Walker; Bob van de Water; Jos Kleinjans; Florian Caiment

doi:10.1007/s00204-020-02937-6

Comparing in vitro human liver models to in vivo human liver using RNA-Seq

Arch Toxicol. 2021 Feb;95(2):573-589. doi: 10.1007/s00204-020-02937-6. Epub 2020 Oct 27.

Authors

Rajinder Gupta¹, Yannick Schrooders¹, Duncan Hauser¹, Marcel van Herwijnen¹, Wiebke Albrecht², Bas Ter Braak³, Tim Brecklinghaus², Jose V Castell⁴, Leroy Elenschneider⁵, Sylvia Escher⁵, Patrick Guye⁶, Jan G Hengstler², Ahmed Ghallab^{2

7}, Tanja Hansen⁵, Marcel Leist⁸, Richard Maclennan⁹, Wolfgang Moritz⁶, Laia Tolosa¹⁰, Tine Tricot¹¹, Catherine Verfaillie¹¹, Paul Walker⁹, Bob van de Water³, Jos Kleinjans¹, Florian Caiment¹²

Affiliations

¹ Department of Toxicogenomics, School of Oncology and Developmental Biology (GROW), Maastricht University, Maastricht, The Netherlands.
² Leibniz Research Centre for Working Environment and Human Factors, Technical University of Dortmund (IfADo), Dortmund, Germany.
³ Division of Drug Discovery and Safety, Leiden Academic Centre for Drug Research, Leiden University, PO Box 9503, 2300 RA, Leiden, The Netherlands.
⁴ Instituto de Investigación Sanitaria La Fe, Experimental Hepatology Unit, Valencia, Spain.
⁵ Fraunhofer Institute for Toxicology and Experimental Medicine Preclinical Pharmacology and In-Vitro Toxicology, Nikolai-Fuchs-Straße 1, 30625, Hannover, Germany.
⁶ InSphero AG, Wagistrasse 27, 8952, Schlieren, Switzerland.
⁷ Department of Forensic Medicine and Toxicology, Faculty of Veterinary Medicine, South Valley University, Qena, 83523, Egypt.
⁸ In Vitro Toxicology and Biomedicine, Department Inaugurated, Doerenkamp-Zbinden Foundation, University of Konstanz, Konstanz, Germany.
⁹ Cyprotex Discovery, No 24 Mereside, Alderley Park, Cheshire, SK10 4TG, UK.
¹⁰ Instituto de Investigación Sanitaria La Fe, Unidad Hepatología Experimental, Valencia, Spain.
¹¹ Stem Cell Institute, Department of Development and Regeneration, KU Leuven, Herestraat 49, 3000, Leuven, Belgium.
¹² Department of Toxicogenomics, School of Oncology and Developmental Biology (GROW), Maastricht University, Maastricht, The Netherlands. florian.caiment@maastrichtuniversity.nl.

Abstract

The liver plays an important role in xenobiotic metabolism and represents a primary target for toxic substances. Many different in vitro cell models have been developed in the past decades. In this study, we used RNA-sequencing (RNA-Seq) to analyze the following human in vitro liver cell models in comparison to human liver tissue: cancer-derived cell lines (HepG2, HepaRG 3D), induced pluripotent stem cell-derived hepatocyte-like cells (iPSC-HLCs), cancerous human liver-derived assays (hPCLiS, human precision cut liver slices), non-cancerous human liver-derived assays (PHH, primary human hepatocytes) and 3D liver microtissues. First, using CellNet, we analyzed whether these liver in vitro cell models were indeed classified as liver, based on their baseline expression profile and gene regulatory networks (GRN). More comprehensive analyses using non-differentially expressed genes (non-DEGs) and differential transcript usage (DTU) were applied to assess the coverage for important liver pathways. Through different analyses, we noticed that 3D liver microtissues exhibited a high similarity with in vivo liver, in terms of CellNet (C/T score: 0.98), non-DEGs (10,363) and pathway coverage (highest for 19 out of 20 liver specific pathways shown) at the beginning of the incubation period (0 h) followed by a decrease during long-term incubation for 168 and 336 h. PHH also showed a high degree of similarity with human liver tissue and allowed stable conditions for a short-term cultivation period of 24 h. Using the same metrics, HepG2 cells illustrated the lowest similarity (C/T: 0.51, non-DEGs: 5623, and pathways coverage: least for 7 out of 20) with human liver tissue. The HepG2 are widely used in hepatotoxicity studies, however, due to their lower similarity, they should be used with caution. HepaRG models, iPSC-HLCs, and hPCLiS ranged clearly behind microtissues and PHH but showed higher similarity to human liver tissue than HepG2 cells. In conclusion, this study offers a resource of RNA-Seq data of several biological replicates of human liver cell models in vitro compared to human liver tissue.

Keywords: CellNet; In vitro liver; In vivo liver; Non-DEGs; Non-DEGsDTU−; Pathway coverage; RNA-seq.

Publication types

Comparative Study
Research Support, Non-U.S. Gov't

MeSH terms

Cell Differentiation
Cell Line, Tumor
Cells, Cultured
Computational Biology / methods*
Gene Expression Profiling
Gene Expression Regulation
Gene Regulatory Networks
Hep G2 Cells
Hepatocytes / metabolism*
High-Throughput Nucleotide Sequencing
Humans
In Vitro Techniques
Induced Pluripotent Stem Cells / metabolism
Liver / metabolism*
Liver Neoplasms / metabolism*
Models, Biological
RNA-Seq
Transcriptome*