Dataset Information

Use of deep learning methods to translate drug-induced gene expression changes from rat to human primary hepatocytes.

ABSTRACT: In clinical trials, animal and cell line models are often used to evaluate the potential toxic effects of a novel compound or candidate drug before progressing to human trials. However, relating the results of animal and in vitro model exposures to relevant clinical outcomes in the human in vivo system still proves challenging, relying on often putative orthologs. In recent years, multiple studies have demonstrated that the repeated dose rodent bioassay, the current gold standard in the field, lacks sufficient sensitivity and specificity in predicting toxic effects of pharmaceuticals in humans. In this study, we evaluate the potential of deep learning techniques to translate the pattern of gene expression measured following an exposure in rodents to humans, circumventing the current reliance on orthologs, and also from in vitro to in vivo experimental designs. Of the applied deep learning architectures applied in this study the convolutional neural network (CNN) and a deep artificial neural network with bottleneck architecture significantly outperform classical machine learning techniques in predicting the time series of gene expression in primary human hepatocytes given a measured time series of gene expression from primary rat hepatocytes following exposure in vitro to a previously unseen compound across multiple toxicologically relevant gene sets. With a reduction in average mean absolute error across 76 genes that have been shown to be predictive for identifying carcinogenicity from 0.0172 for a random regression forest to 0.0166 for the CNN model (p < 0.05). These deep learning architecture also perform well when applied to predict time series of in vivo gene expression given measured time series of in vitro gene expression for rats.

SUBMITTER: O'Donovan SD

PROVIDER: S-EPMC7418976 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Use of deep learning methods to translate drug-induced gene expression changes from rat to human primary hepatocytes.

O'Donovan Shauna D SD Driessens Kurt K Lopatta Daniel D Wimmenauer Florian F Lukas Alexander A Neeven Jelmer J Stumm Tobias T Smirnov Evgueni E Lenz Michael M Ertaylan Gokhan G Jennen Danyel G J DGJ van Riel Natal A W NAW Cavill Rachel R Peeters Ralf L M RLM de Kok Theo M C M TMCM

PloS one 20200811 8

In clinical trials, animal and cell line models are often used to evaluate the potential toxic effects of a novel compound or candidate drug before progressing to human trials. However, relating the results of animal and in vitro model exposures to relevant clinical outcomes in the human in vivo system still proves challenging, relying on often putative orthologs. In recent years, multiple studies have demonstrated that the repeated dose rodent bioassay, the current gold standard in the field, l ...[more]

PMID: 32780735

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Project description:UnlabelledAngiotensin II (AT-II) is a pro-fibrotic compound that acts via membrane-bound receptors (AT-1R/AT-2R) and thereby activates hepatic stellate cells (HSCs). AT-II receptor blockers (ARBs) are thus important candidates in the treatment of liver fibrosis. However, multiple case reports suggest that AT-1R blockers may induce hepatocyte injury. Therefore, we investigated the effect of AT-II and its receptor blockers on cytokine-, oxidative stress- and bile salt-induced cell death in hepatocytes. Primary rat hepatocytes were exposed to TNF-α/Actinomycin D, the ROS-generating agent menadione or the bile salts: glycochenodeoxycholic acid (GCDCA) and tauro-lithocholic acid-3 sulfate (TLCS), to induce apoptosis. AT-II (100 nmol/L) was added 10 minutes prior to the cell death-inducing agent. AT-1R antagonists (Sartans) and the AT-2R antagonist PD123319 were used at 1 µmol/L. Apoptosis (caspase-3 activity, acridine orange staining) and necrosis (Sytox green staining) were quantified. Expression of CHOP (marker for ER stress) and AT-II receptor mRNAs were quantified by Q-PCR. AT-II dose-dependently reduced GCDCA-induced apoptosis of hepatocytes (-50%, p<0.05) without inducing necrosis. In addition, AT-II reduced TLCS-induced apoptosis of hepatocytes (-50%, p<0.05). However, AT-II did not suppress TNF/Act-D and menadione-induced apoptosis. Only the AT-1R antagonists abolished the protective effect of AT-II against GCDCA-induced apoptosis. AT-II increased phosphorylation of ERK and a significant reversal of the protective effect of AT-II was observed when signaling kinases, including ERK, were inhibited. Moreover, AT-II prevented the GCDCA-induced expression of CHOP (the marker of the ER-mediated apoptosis).ConclusionAngiotensin II protects hepatocytes from bile salt-induced apoptosis through a combined activation of PI3-kinase, MAPKs, PKC pathways and inhibition of bile salt-induced ER stress. Our results suggest a mechanism for the observed hepatocyte-toxicity of Sartans (angiotensin receptor blockers, ARBs) in some patients with chronic liver injury.

Dataset Information

Use of deep learning methods to translate drug-induced gene expression changes from rat to human primary hepatocytes.

Publications

Use of deep learning methods to translate drug-induced gene expression changes from rat to human primary hepatocytes.

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