ArticleThe pharmacogenomics journal2014
Data mining reveals a network of early-response genes as a consensus signature of drug-induced in vitro and in vivo toxicity.
Article in The pharmacogenomics journal, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers, 1 of them a synthesis that pooled it.
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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.
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Who cites it
40 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pooled it
- Discrimination of Steatotic and Non-Steatotic Chemicals Through Transcriptome Analysis in Primary Human Hepatocytes.International journal of molecular sciences · 2026Article
- Single-cell transcriptomics of acetaminophen-induced responses in human 2D and 3D liver microtissues.Archives of toxicology · 2026Article
- Assessment of Drug-Induced Liver Injury through Cell Morphology and Gene Expression Analysis.Chemical research in toxicology · 2023Article
- Harnessing male germline epigenomics for the genetic improvement in cattle.Journal of animal science and biotechnology · 2023Review
- SOPHIE: Generative Neural Networks Separate Common and Specific Transcriptional Responses.Genomics, proteomics & bioinformatics · 2022Article
- Deriving time-concordant event cascades from gene expression data: A case study for Drug-Induced Liver Injury (DILI).PLoS computational biology · 2022Article
- Article title: Transcriptional profiling efficacy to define biological activity similarity for cosmetic ingredients' safety assessment based on next-generation read-across.Frontiers in toxicology · 2022Article
- Egr1 confers protection against acetaminophen‑induced hepatotoxicity via transcriptional upregulating of Acaa2.International journal of biological sciences · 2022Article
- Tissue heterogeneity is prevalent in gene expression studies.NAR genomics and bioinformatics · 2021Article
- An Introduction to Machine Learning.Clinical pharmacology and therapeutics · 2020Review
- Gadolinium labelled nanoliposomes as the platform for MRI theranostics: in vitro safety study in liver cells and macrophages.Scientific reports · 2020Article
- Screening of Cellular Stress Responses Induced by Ambient Aerosol Ultrafine Particle Fraction PM0.5 in A549 Cells.International journal of molecular sciences · 2019Article
- Unsupervised identification of disease states from high-dimensional physiological and histopathological profiles.Molecular systems biology · 2019Article
- Literature optimized integration of gene expression for organ-specific evaluation of toxicogenomics datasets.PloS one · 2019Article
- Assessing Chemical-Induced Liver InjuryFrontiers in genetics · 2019Article
- Imidazo[1,2-Molecules (Basel, Switzerland) · 2018Article
- Machine Learning Based Toxicity Prediction: From Chemical Structural Description to Transcriptome Analysis.International journal of molecular sciences · 2018Review
- A Sensitive In Vitro Approach to Assess the Hybridization-Dependent Toxic Potential of High Affinity Gapmer Oligonucleotides.Molecular therapy. Nucleic acids · 2018Article
- The sbv IMPROVER Systems Toxicology Computational Challenge: Identification of Human and Species-Independent Blood Response Markers as Predictors of Smoking Exposure and Cessation Status.Computational toxicology (Amsterdam, Netherlands) · 2018Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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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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.