Evidence map›Paper›PMID 33106934›Full record

ArticleArchives of toxicology2021

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 and 14 more

Open access · hybridAbstract readComparative Study
In one paragraph

Article in Archives of toxicology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
55citing papers in PubMed, 1 pooled it
5.7field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

55 citing papers in PubMed, 1 synthesis or guideline pooled it, 90 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Systematic comparison of temporal hepatotoxicant-induced gene network responses across 3 liver test systems.Toxicological sciences : an official journal of the Society of Toxicology · 2026
    Article
  5. Article
  6. Article
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  8. Article
  9. Epithelial Reprogramming and Transition during Pulmonary Bioengineering.bioRxiv : the preprint server for biology · 2026
    Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. Experimental Models to Investigate PNPLA3 in Liver Steatosis.Liver international : official journal of the International Association for the Study of the Liver · 2025
    Review
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

24 authors at 9 institutions in 6 countries.

Rajinder GuptaDepartment of Toxicogenomics, School of Oncology and Developmental Biology (GROW), Maastricht University, Maastricht, The Netherlands.ORCID http://orcid.org/0000-0003-3342-2122
Yannick SchroodersDepartment of Toxicogenomics, School of Oncology and Developmental Biology (GROW), Maastricht University, Maastricht, The Netherlands.
Duncan HauserDepartment of Toxicogenomics, School of Oncology and Developmental Biology (GROW), Maastricht University, Maastricht, The Netherlands.
Marcel van HerwijnenDepartment of Toxicogenomics, School of Oncology and Developmental Biology (GROW), Maastricht University, Maastricht, The Netherlands.
Wiebke AlbrechtLeibniz Research Centre for Working Environment and Human Factors, Technical University of Dortmund (IfADo), Dortmund, Germany.
Bas Ter BraakDivision of Drug Discovery and Safety, Leiden Academic Centre for Drug Research, Leiden University, PO Box 9503, 2300 RA, Leiden, The Netherlands.
Tim BrecklinghausLeibniz Research Centre for Working Environment and Human Factors, Technical University of Dortmund (IfADo), Dortmund, Germany.
Jose V CastellInstituto de Investigación Sanitaria La Fe, Experimental Hepatology Unit, Valencia, Spain.
Leroy ElenschneiderFraunhofer Institute for Toxicology and Experimental Medicine Preclinical Pharmacology and In-Vitro Toxicology, Nikolai-Fuchs-Straße 1, 30625, Hannover, Germany.
Sylvia EscherFraunhofer Institute for Toxicology and Experimental Medicine Preclinical Pharmacology and In-Vitro Toxicology, Nikolai-Fuchs-Straße 1, 30625, Hannover, Germany.
Patrick GuyeInSphero AG, Wagistrasse 27, 8952, Schlieren, Switzerland.
Jan G HengstlerLeibniz Research Centre for Working Environment and Human Factors, Technical University of Dortmund (IfADo), Dortmund, Germany.
Ahmed GhallabLeibniz Research Centre for Working Environment and Human Factors, Technical University of Dortmund (IfADo), Dortmund, Germany.
Tanja HansenFraunhofer Institute for Toxicology and Experimental Medicine Preclinical Pharmacology and In-Vitro Toxicology, Nikolai-Fuchs-Straße 1, 30625, Hannover, Germany.
Marcel LeistIn Vitro Toxicology and Biomedicine, Department Inaugurated, Doerenkamp-Zbinden Foundation, University of Konstanz, Konstanz, Germany.
Richard MaclennanCyprotex Discovery, No 24 Mereside, Alderley Park, Cheshire, SK10 4TG, UK.
Wolfgang MoritzInSphero AG, Wagistrasse 27, 8952, Schlieren, Switzerland.
Laia TolosaInstituto de Investigación Sanitaria La Fe, Unidad Hepatología Experimental, Valencia, Spain.
Tine TricotStem Cell Institute, Department of Development and Regeneration, KU Leuven, Herestraat 49, 3000, Leuven, Belgium.
Catherine VerfaillieStem Cell Institute, Department of Development and Regeneration, KU Leuven, Herestraat 49, 3000, Leuven, Belgium.
Paul WalkerCyprotex Discovery, No 24 Mereside, Alderley Park, Cheshire, SK10 4TG, UK.
Bob van de WaterDivision of Drug Discovery and Safety, Leiden Academic Centre for Drug Research, Leiden University, PO Box 9503, 2300 RA, Leiden, The Netherlands.
Jos KleinjansDepartment of Toxicogenomics, School of Oncology and Developmental Biology (GROW), Maastricht University, Maastricht, The Netherlands.
Florian CaimentDepartment of Toxicogenomics, School of Oncology and Developmental Biology (GROW), Maastricht University, Maastricht, The Netherlands. florian.caiment@maastrichtuniversity.nl.
Maastricht University · NLFraunhofer Institute for Toxicology and Experimental Medicine · DETU Dortmund University · DEC4X Discovery (United Kingdom) · GBInstituto de Investigación Sanitaria La Fe · ESKU Leuven · BELeiden University · NLSouth Valley University · EGUniversity of Konstanz · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

TranscriptomeCell DifferentiationCell Line, TumorCells, CulturedComputational BiologyGene Expression ProfilingGene Expression RegulationGene Regulatory NetworksHepatocytesHep G2 CellsHigh-Throughput Nucleotide SequencingHumansInduced Pluripotent Stem CellsIn Vitro TechniquesLiverLiver NeoplasmsCellNetIn vitro liverIn vivo liverNon-DEGsNon-DEGsDTU−Pathway coverageRNA-seq

Identifiers

PMID33106934
PMCPMC7870774
OpenAlexW3093748727

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.