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Literature optimized integration of gene expression for organ-specific evaluation of toxicogenomics datasets

The study of drug toxicity in human organs is complicated by their complex inter-relations and by the obvious difficulty to testing drug effects on biologically relevant material. Animal models and human cell cultures offer alternatives for systematic and large-scale profiling of drug effects on gen...

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Autores principales: Taškova, Katerina, Fontaine, Jean-Fred, Mrowka, Ralf, Andrade-Navarro, Miguel A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6331104/
https://www.ncbi.nlm.nih.gov/pubmed/30640953
http://dx.doi.org/10.1371/journal.pone.0210467
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author Taškova, Katerina
Fontaine, Jean-Fred
Mrowka, Ralf
Andrade-Navarro, Miguel A.
author_facet Taškova, Katerina
Fontaine, Jean-Fred
Mrowka, Ralf
Andrade-Navarro, Miguel A.
author_sort Taškova, Katerina
collection PubMed
description The study of drug toxicity in human organs is complicated by their complex inter-relations and by the obvious difficulty to testing drug effects on biologically relevant material. Animal models and human cell cultures offer alternatives for systematic and large-scale profiling of drug effects on gene expression level, as typically found in the so-called toxicogenomics datasets. However, the complexity of these data, which includes variable drug doses, time points, and experimental setups, makes it difficult to choose and integrate the data, and to evaluate the appropriateness of one or another model system to study drug toxicity (of particular drugs) of particular human organs. Here, we define a protocol to integrate drug-wise rankings of gene expression changes in toxicogenomics data, which we apply to the TG-GATEs dataset, to prioritize genes for association to drug toxicity in liver or kidney. Contrast of the results with sets of known human genes associated to drug toxicity in the literature allows to compare different rank aggregation approaches for the task at hand. Collectively, ranks from multiple models point to genes not previously associated to toxicity, notably, the PCNA clamp associated factor (PCLAF), and genes regulated by the master regulator of the antioxidant response NFE2L2, such as NQO1 and SRXN1. In addition, comparing gene ranks from different models allowed us to evaluate striking differences in terms of toxicity-associated genes between human and rat hepatocytes or between rat liver and rat hepatocytes. We interpret these results to point to the different molecular functions associated to organ toxicity that are best described by each model. We conclude that the expected production of toxicogenomics panels with larger numbers of drugs and models, in combination with the ongoing increase of the experimental literature in organ toxicity, will lead to increasingly better associations of genes for organism toxicity.
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spelling pubmed-63311042019-02-01 Literature optimized integration of gene expression for organ-specific evaluation of toxicogenomics datasets Taškova, Katerina Fontaine, Jean-Fred Mrowka, Ralf Andrade-Navarro, Miguel A. PLoS One Research Article The study of drug toxicity in human organs is complicated by their complex inter-relations and by the obvious difficulty to testing drug effects on biologically relevant material. Animal models and human cell cultures offer alternatives for systematic and large-scale profiling of drug effects on gene expression level, as typically found in the so-called toxicogenomics datasets. However, the complexity of these data, which includes variable drug doses, time points, and experimental setups, makes it difficult to choose and integrate the data, and to evaluate the appropriateness of one or another model system to study drug toxicity (of particular drugs) of particular human organs. Here, we define a protocol to integrate drug-wise rankings of gene expression changes in toxicogenomics data, which we apply to the TG-GATEs dataset, to prioritize genes for association to drug toxicity in liver or kidney. Contrast of the results with sets of known human genes associated to drug toxicity in the literature allows to compare different rank aggregation approaches for the task at hand. Collectively, ranks from multiple models point to genes not previously associated to toxicity, notably, the PCNA clamp associated factor (PCLAF), and genes regulated by the master regulator of the antioxidant response NFE2L2, such as NQO1 and SRXN1. In addition, comparing gene ranks from different models allowed us to evaluate striking differences in terms of toxicity-associated genes between human and rat hepatocytes or between rat liver and rat hepatocytes. We interpret these results to point to the different molecular functions associated to organ toxicity that are best described by each model. We conclude that the expected production of toxicogenomics panels with larger numbers of drugs and models, in combination with the ongoing increase of the experimental literature in organ toxicity, will lead to increasingly better associations of genes for organism toxicity. Public Library of Science 2019-01-14 /pmc/articles/PMC6331104/ /pubmed/30640953 http://dx.doi.org/10.1371/journal.pone.0210467 Text en © 2019 Taškova et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Taškova, Katerina
Fontaine, Jean-Fred
Mrowka, Ralf
Andrade-Navarro, Miguel A.
Literature optimized integration of gene expression for organ-specific evaluation of toxicogenomics datasets
title Literature optimized integration of gene expression for organ-specific evaluation of toxicogenomics datasets
title_full Literature optimized integration of gene expression for organ-specific evaluation of toxicogenomics datasets
title_fullStr Literature optimized integration of gene expression for organ-specific evaluation of toxicogenomics datasets
title_full_unstemmed Literature optimized integration of gene expression for organ-specific evaluation of toxicogenomics datasets
title_short Literature optimized integration of gene expression for organ-specific evaluation of toxicogenomics datasets
title_sort literature optimized integration of gene expression for organ-specific evaluation of toxicogenomics datasets
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6331104/
https://www.ncbi.nlm.nih.gov/pubmed/30640953
http://dx.doi.org/10.1371/journal.pone.0210467
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