Please use this identifier to cite or link to this item: http://doi.org/10.25358/openscience-767
Authors: Taškova, Katerina
Fontaine, Jean-Fred
Mrowka, Ralf
Andrade, Miguel
Title: Literature optimized integration of gene expression for organ-specific evaluation of toxicogenomics datasets
Online publication date: 12-Apr-2019
Year of first publication: 2019
Language: english
Abstract: 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.
DDC: 570 Biowissenschaften
570 Life sciences
Institution: Johannes Gutenberg-Universität Mainz
Department: FB 10 Biologie
Place: Mainz
ROR: https://ror.org/023b0x485
DOI: http://doi.org/10.25358/openscience-767
URN: urn:nbn:de:hebis:77-publ-590292
Version: Published version
Publication type: Zeitschriftenaufsatz
License: CC BY
Information on rights of use: https://creativecommons.org/licenses/by/4.0/
Journal: PLOS ONE
14
1
Pages or article number: e0210467
Publisher: PLOS
Publisher place: San Francisco, California, US
Issue date: 2019
ISSN: 1932-6203
Publisher URL: http://dx.doi.org/10.1371/journal.pone.0210467
Publisher DOI: 10.1371/journal.pone.0210467
Annotation: Andrade, Miguel veröffentlicht unter: Andrade-Navarro, Miguel A.
Appears in collections:JGU-Publikationen

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