Evidence map›Paper›PMID 38015832›Full record

ArticleToxicological sciences : an official journal of the Society of Toxicology2024

A network-based transcriptomic landscape of HepG2 cells uncovering causal gene-cytotoxicity interactions underlying drug-induced liver injury.

Lukas S Wijaya, Attila Gabor, Iris E Pot, Luca van de Have, Julio Saez-Rodriguez, James L Stevens, Sylvia E Le Dévédec, Giulia Callegaro, Bob van de Water

Open access · hybridAbstract read
In one paragraph

Article in Toxicological sciences : an official journal of the Society of Toxicology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
2.2field-weighted citation impact, top 13% 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

8 citing papers in PubMed, 9 citations in OpenAlex.

  1. 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
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Review
  8. 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

9 authors at 3 institutions in 2 countries.

Lukas S WijayaLeiden Academic Centre for Drug Research (LACDR), Faculty of Science, Leiden University, 2333 Leiden, The Netherlands.
Attila GaborInstitute for Computational Biomedicine, Faculty of Medicine, Heidelberg University, 69120 Heidelberg, Germany.
Iris E PotLeiden Academic Centre for Drug Research (LACDR), Faculty of Science, Leiden University, 2333 Leiden, The Netherlands.
Luca van de HaveLeiden Academic Centre for Drug Research (LACDR), Faculty of Science, Leiden University, 2333 Leiden, The Netherlands.
Julio Saez-RodriguezInstitute for Computational Biomedicine, Faculty of Medicine, Heidelberg University, 69120 Heidelberg, Germany.
James L StevensLeiden Academic Centre for Drug Research (LACDR), Faculty of Science, Leiden University, 2333 Leiden, The Netherlands.
Sylvia E Le DévédecLeiden Academic Centre for Drug Research (LACDR), Faculty of Science, Leiden University, 2333 Leiden, The Netherlands.
Giulia CallegaroLeiden Academic Centre for Drug Research (LACDR), Faculty of Science, Leiden University, 2333 Leiden, The Netherlands.
Bob van de WaterLeiden Academic Centre for Drug Research (LACDR), Faculty of Science, Leiden University, 2333 Leiden, The Netherlands.
Leiden University · NLCentre for Human Drug Research · NLUniversity Hospital Heidelberg · DE

Funding

EC Horizon2020 EU-ToxRisk 681002EC Horizon2020 Risk-Hunt3R 96453EU-EFPIA Innovative Medicines Initiative 2 116030European Union's Horizon 2020
6 · The paper itself

Abstract

Drug-induced liver injury (DILI) remains the main reason for drug development attritions largely due to poor mechanistic understanding. Toxicogenomic to interrogate the mechanism of DILI has been broadly performed. Gene coregulation network-based transcriptome analysis is a bioinformatics approach that potentially contributes to improve mechanistic interpretation of toxicogenomic data. Here we performed an extensive concentration time course response-toxicogenomic study in the HepG2 cell line exposed to 20 DILI compounds, 7 reference compounds for stress response pathways, and 10 agonists for cytokines and growth factor receptors. We performed whole transcriptome targeted RNA sequencing to more than 500 conditions and applied weighted gene coregulated network analysis to the transcriptomics data followed by the identification of gene coregulated networks (modules) that were strongly modulated upon the exposure of DILI compounds. Preservation analysis on the module responses of HepG2 and PHH demonstrated highly preserved adaptive stress response gene coregulated networks. We correlated gene coregulated networks with cell death onset and causal relationships of 67 critical target genes of these modules with the onset of cell death was evaluated using RNA interference screening. We identified GTPBP2, HSPA1B, IRF1, SIRT1, and TSC22D3 as essential modulators of DILI compound-induced cell death. These genes were also induced by DILI compounds in PHH. Altogether, we demonstrate the application of large transcriptome datasets combined with network-based analysis and biological validation to uncover the candidate determinants of DILI.

Indexed as

Chemical and Drug Induced Liver InjuryTranscriptomeGene Expression ProfilingGene Regulatory NetworksHep G2 CellsHumansbiomarkerscytotoxicityhepatotoxicityhigh throughputtoxicogenomicsWGCNA

Identifiers

PMID38015832
PMCPMC10901150
OpenAlexW4389076851

What OpenQuestion 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 OpenQuestion graph.