ArticleBMC genomics2015
Identification of in vitro and in vivo disconnects using transcriptomic data.
Article in BMC genomics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Knockdown of p53 Enhances LncRNA A2M-AS1 Inhibition of Pancreatic Cancer Progression via Regulating MAPK Pathway.Cancer medicine · 2025Article
- MHC-I and PD-L1 Expression is Associated with Decreased Tumor Outgrowth and is Radiotherapy-inducible in the Murine Head and Neck Squamous Cell Carcinoma Model MOC1.Molecular imaging and biology · 2024Article
- Accurate clinical toxicity prediction using multi-task deep neural nets and contrastive molecular explanations.Scientific reports · 2023Article
- High-throughput toxicogenomic screening of chemicals in the environment using metabolically competent hepatic cell cultures.NPJ systems biology and applications · 2021Article
- Concordance between Thioacetamide-Induced Liver Injury in Rat and Human In Vitro Gene Expression Data.International journal of molecular sciences · 2020Article
- Brief update on endocytosis of nanomedicines.Advanced drug delivery reviews · 2019Review
- Integration of metabolomics and transcriptomics in nanotoxicity studies.BMB reports · 2018Article
- Transcriptomics in toxicology.Food and chemical toxicology : an international journal published for the British Industrial Biological Research Association · 2017Review
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIntegrating transcriptomic experiments within drug development is increasingly advocated for the early detection of toxicity. This is partly to reduce costs related to drug failures in the late, and expensive phases of clinical trials. Such an approach has proven useful both in the study of toxicology and carcinogenicity. However, general lack of translation of in vitro findings to in vivo systems remains one of the bottle necks in drug development. This paper proposes a method for identifying disconnected genes between in vitro and in vivo toxicogenomic rat experiments. The analytical framework is based on the joint modeling of dose-dependent in vitro and in vivo data using a fractional polynomial framework and biclustering algorithm.
resultsMost disconnected genes identified belonged to known pathways, such as drug metabolism and oxidative stress due to reactive metabolites, bilirubin increase, glutathion depletion and phospholipidosis. We also identified compounds that were likely to induce disconnect in gene expression between in vitro and in vivo toxicogenomic rat experiments. These compounds include: sulindac and diclofenac (both linked to liver damage), naphtyl isothiocyanate (linked to hepatoxocity), indomethacin and naproxen (linked to gastrointestinal problem and damage of intestines).
conclusionThe results confirmed that there are important discrepancies between in vitro and in vivo toxicogenomic experiments. However, the contribution of this paper is to provide a tool to identify genes that are disconnected between the two systems. Pathway analysis of disconnected genes may improve our understanding of uncertainties in the mechanism of actions of drug candidates in humans, especially concerning the early detection of toxicity.
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