Network integration and modelling of dynamic drug responses at multi-omics levels
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Published:2020-10-15
Issue:1
Volume:3
Page:
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ISSN:2399-3642
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Container-title:Communications Biology
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language:en
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Short-container-title:Commun Biol
Author:
Selevsek Nathalie, Caiment Florian, Nudischer RamonaORCID, Gmuender Hans, Agarkova Irina, Atkinson Francis L., Bachmann Ivo, Baier Vanessa, Barel GalORCID, Bauer Chris, Boerno Stefan, Bosc NicolasORCID, Clayton Olivia, Cordes Henrik, Deeb Sally, Gotta Stefano, Guye Patrick, Hersey Anne, Hunter Fiona M. I.ORCID, Kunz Laura, Lewalle AlexORCID, Lienhard MatthiasORCID, Merken Jort, Minguet Jasmine, Oliveira BernardoORCID, Pluess Carla, Sarkans UgisORCID, Schrooders Yannick, Schuchhardt Johannes, Smit InesORCID, Thiel Christoph, Timmermann Bernd, Verheijen Marcha, Wittenberger TimoORCID, Wolski Witold, Zerck Alexandra, Heymans Stephane, Kuepfer Lars, Roth Adrian, Schlapbach Ralph, Niederer Steven, Herwig RalfORCID, Kleinjans Jos
Abstract
AbstractUncovering cellular responses from heterogeneous genomic data is crucial for molecular medicine in particular for drug safety. This can be realized by integrating the molecular activities in networks of interacting proteins. As proof-of-concept we challenge network modeling with time-resolved proteome, transcriptome and methylome measurements in iPSC-derived human 3D cardiac microtissues to elucidate adverse mechanisms of anthracycline cardiotoxicity measured with four different drugs (doxorubicin, epirubicin, idarubicin and daunorubicin). Dynamic molecular analysis at in vivo drug exposure levels reveal a network of 175 disease-associated proteins and identify common modules of anthracycline cardiotoxicity in vitro, related to mitochondrial and sarcomere function as well as remodeling of extracellular matrix. These in vitro-identified modules are transferable and are evaluated with biopsies of cardiomyopathy patients. This to our knowledge most comprehensive study on anthracycline cardiotoxicity demonstrates a reproducible workflow for molecular medicine and serves as a template for detecting adverse drug responses from complex omics data.
Funder
EC | EC Seventh Framework Programm | FP7 Health
Publisher
Springer Science and Business Media LLC
Subject
General Agricultural and Biological Sciences,General Biochemistry, Genetics and Molecular Biology,Medicine (miscellaneous)
Reference87 articles.
1. Ebrahim, A. et al. (2016) Multi-omic data integration enables discovery of hidden biological regularities. Nat. Commun. 7, 13091 (2016). 2. Lenneman, C. G. & Sawyer, D. B. Cardio-oncology. An update on cardiotoxicity of cancer-related treatment. Circ. Res. 118, 1008–1020 (2016). 3. Cook, D. et al. Lessons learned from the fate of AstraZeneca’s drug pipeline: a five-dimensional framework. Nat. Rev. Drug Discov. 13, 419–431 (2014). 4. Siramshetty, V. B. et al. R. WITHDRAWN—a resource for withdrawn and discontinued drugs. Nucleic Acids Res. 44, D1080–D1086 (2016). 5. Onakpoya, I. J., Heneghan, C. J. & Aronson, J. K. Post-marketing withdrawal of 462 medicinal products because of adverse drug reactions: a systematic review of the world literature. BMC Med. 14, 10 (2016).
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