Data mining reveals a network of early-response genes as a consensus signature of drug-induced in vitro and in vivo toxicity
Open accessAbstract
Gene signatures of drug-induced toxicity are of broad interest, but they are often identified from small-scale, single-time point experiments, and are therefore of limited applicability. To address this issue, we performed multivariate analysis of gene expression, cell-based assays, and histopathological data in the TG-GATEs (Toxicogenomics Project-Genomics Assisted Toxicity Evaluation system) database. Data mining highlights four genes-EGR1, ATF3, GDF15 and FGF21-that are induced 2 h after drug administration in human and rat primary hepatocytes poised to eventually undergo cytotoxicity-induced cell death. Modelling and simulation reveals that these early stress-response genes form a functional network with evolutionarily conserved structure and intrinsic dynamics. This is underlined by the fact that early induction of this network in vivo predicts drug-induced liver and kidney pathology with high accuracy. Our findings demonstrate the value of early gene-expression signatures in predicting and understanding compound-induced toxicity. The identified network can empower first-line tests that reduce animal use and costs of safety evaluation.
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Although the number of affected genes is small at induction, much greater gene expression changes occur 24 h after induction.
“Although the number of affected genes is small at the induction, much greater gene expression changes will occur 24 h after induction [136].”
From Machine Learning Based Toxicity Prediction: From Chemical Structural Description to Transcriptome Analysis (2018) · cites this paper as [136]
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- Authors
- Zhang, J. D., Berntenis, N., Roth, A., & Ebeling, M.
- Affiliations
- F. Hoffmann-La Roche AG (CH)
- Corresponding author
- Zhang, J D
- Ebeling, M
- ORCID
- Venue
- The Pharmacogenomics Journal
- Published
- 2013-11-12
- Volume
- 14
- Issue
- 3
- Pages
- 208-216
- ISSN
- 1470-269X (ISSN-L)
- 1473-1150
- PMC
- PMC4034126
- OpenAlex
- W2005132453
- Cited by
- 79
- References
- 74
- Citations by year
- 2026: 5 · 2025: 3 · 2023: 3 · 2022: 6 · 2021: 4 · 2020: 4 · 2019: 10 · 2018: 5 · 2017: 14 · 2016: 9 · 2015: 11 · 2014: 5
- FWCI
- 9.11
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- The Pharmacogenomics Journal (publishedVersion, cc-by-nc-sa)
- PubMed Central (publishedVersion, cc-by-nc-sa)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Pharmacology › Drug-Induced Hepatotoxicity and Protection
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
- Health Sciences › Veterinary › Small Animals › Animal testing and alternatives
- Keywords
- drug toxicity, early response genes, gene expression signatures, hepatotoxicity, nephrotoxicity, EGR1, ATF3, GDF15, FGF21, primary hepatocytes, histopathology, animal-free toxicity testing, predictive biomarkers
- MeSH terms
- Humans, Genes, Immediate-Early, Toxicity Tests, Gene Expression Profiling, Data Mining, In Vitro Techniques
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