The human hepatocyte TXG-MAPr: gene co-expression network modules to support mechanism-based risk assessment

Archives of Toxicology, vol. 95, pp. 3745–3775

Abstract

Mechanism-based risk assessment is urged to advance and fully permeate into current safety assessment practices, possibly at early phases of drug safety testing. Toxicogenomics is a promising source of mechanisms-revealing data, but interpretative analysis tools specific for the testing systems (e.g. hepatocytes) are lacking. In this study, we present the TXG-MAPr webtool (available at https://txg-mapr.eu/WGCNA_PHH/TGGATEs_PHH/ ), an R-Shiny-based implementation of weighted gene co-expression network analysis (WGCNA) obtained from the Primary Human Hepatocytes (PHH) TG-GATEs dataset. The 398 gene co-expression networks (modules) were annotated with functional information (pathway enrichment, transcription factor) to reveal their mechanistic interpretation. Several well-known stress response pathways were captured in the modules, were perturbed by specific stressors and showed preservation in rat systems (rat primary hepatocytes and rat in vivo liver), with the exception of DNA damage and oxidative stress responses. A subset of 87 well-annotated and preserved modules was used to evaluate mechanisms of toxicity of endoplasmic reticulum (ER) stress and oxidative stress inducers, including cyclosporine A, tunicamycin and acetaminophen. In addition, module responses can be calculated from external datasets obtained with different hepatocyte cells and platforms, including targeted RNA-seq data, therefore, imputing biological responses from a limited gene set. As another application, donors' sensitivity towards tunicamycin was investigated with the TXG-MAPr, identifying higher basal level of intrinsic immune response in donors with pre-existing liver pathology. In conclusion, we demonstrated that gene co-expression analysis coupled to an interactive visualization environment, the TXG-MAPr, is a promising approach to achieve mechanistic relevant, cross-species and cross-platform evaluation of toxicogenomic data.

Authors 15

1. Giulia Callegaro Aachen Leiden Academic Centre for Drug Research

   Leiden University

   Affiliation as printed

   Leiden Academic Centre for Drug Research, Leiden University, Einsteinweg 55, 2333 CC, Leiden, The Netherlands

2. Steven J. Kunnen Aachen Leiden Academic Centre for Drug Research

   Leiden University

   Affiliation as printed

   Leiden Academic Centre for Drug Research, Leiden University, Einsteinweg 55, 2333 CC, Leiden, The Netherlands

3. Panuwat Trairatphisan

   Heidelberg University · University Hospital Heidelberg · AbbVie (Germany)

   Affiliation as printed

   AbbVie Deutschland, GmbH & Co KG, Ludwigshafen, Germany

   Faculty of Medicine, Heidelberg University, Heidelberg University Hospital, Institute for Computational Biomedicine, BioQuant, 69120, Heidelberg, Germany

4. Solène Grosdidier

   Erasmus MC

   Affiliation as printed

   Erasmus Medical Centre, Rotterdam, The Netherlands

5. Marije Niemeijer Aachen Leiden Academic Centre for Drug Research

   Leiden University

   Affiliation as printed

   Leiden Academic Centre for Drug Research, Leiden University, Einsteinweg 55, 2333 CC, Leiden, The Netherlands

6. Wouter den Hollander Aachen Leiden Academic Centre for Drug Research

   Leiden University

   Affiliation as printed

   Leiden Academic Centre for Drug Research, Leiden University, Einsteinweg 55, 2333 CC, Leiden, The Netherlands

7. Emre Güney

   Universitat Pompeu Fabra · Hospital del Mar Research Institute

   Affiliation as printed

   Hospital del Mar Research Institute (IMIM), Pompeu Fabra University (UPF), Barcelona, Spain

8. Janet Piñero

   Universitat Pompeu Fabra · Hospital del Mar Research Institute

   Affiliation as printed

   Hospital del Mar Research Institute (IMIM), Pompeu Fabra University (UPF), Barcelona, Spain

9. Laura Ines Furlong

   Universitat Pompeu Fabra · Hospital del Mar Research Institute

   Affiliation as printed

   Hospital del Mar Research Institute (IMIM), Pompeu Fabra University (UPF), Barcelona, Spain

10. Yue Webster

    Eli Lilly (United States)

    Affiliation as printed

    Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, IN, USA

11. Julio Sáez-Rodríguez

    Heidelberg University · University Hospital Heidelberg

    Affiliation as printed

    Faculty of Medicine, Heidelberg University, Heidelberg University Hospital, Institute for Computational Biomedicine, BioQuant, 69120, Heidelberg, Germany

12. Jeffrey J. Sutherland

    Eli Lilly (United States)

    Affiliation as printed

    Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, IN, USA

13. Jennifer E. Mollon

    AbbVie (Germany)

    Affiliation as printed

    AbbVie Deutschland, GmbH & Co KG, Ludwigshafen, Germany

14. James L. Stevens corresponding Aachen Leiden Academic Centre for Drug Research

    Leiden University · Eli Lilly (United States)

    Affiliation as printed

    Leiden Academic Centre for Drug Research, Leiden University, Einsteinweg 55, 2333 CC, Leiden, The Netherlands. j.l.stevens@lacdr.leidenuniv.nl

    Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, IN, USA. j.l.stevens@lacdr.leidenuniv.nl

    Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, IN, USA

15. Bob van de Water corresponding Aachen Leiden Academic Centre for Drug Research

    Leiden University

    Affiliation as printed

    Leiden Academic Centre for Drug Research, Leiden University, Einsteinweg 55, 2333 CC, Leiden, The Netherlands. b.water@lacdr.leidenuniv.nl

    Leiden Academic Centre for Drug Research, Leiden University, Einsteinweg 55, 2333 CC, Leiden, The Netherlands