Network integration and modelling of dynamic drug responses at multi-omics levels

Nathalie Selevsek, Florian Caiment, Ramona Nudischer, Hans Gmuender, Irina Agarkova, Francis L. Atkinson, Ivo Bachmann, Vanessa Baier, Gal Barel, Chris Bauer, Stefan Boerno, Nicolas Bosc, Olivia Clayton, Henrik Cordes, Sally Deeb, Stefano Gotta, Patrick Guye, Anne Hersey, Fiona M. I. Hunter, Laura KunzAlex Lewalle, Matthias Lienhard, Jort Merken, Jasmine Minguet, Bernardo Oliveira, Carla Pluess, Ugis Sarkans, Yannick Schrooders, Johannes Schuchhardt, Ines Smit, Christoph Thiel, Bernd Timmermann, Marcha Verheijen, Timo Wittenberger, Witold Wolski, Alexandra Zerck, Stephane Heymans, Lars Kuepfer, Adrian Roth, Ralph Schlapbach, Steven Niederer, Ralf Herwig*, Jos Kleinjans

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review


Uncovering 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. Using a network propagation approach with integrated multi-omic data, Selevsek et al. develop a reproducible workflow for identifying drug toxicity effects in cellular systems. This is demonstrated with the analysis of anthracycline cardiotoxicity in cardiac microtissues under the effect of multiple drugs.

Original languageEnglish
Article number573
Number of pages15
JournalCommunications Biology
Issue number1
Publication statusPublished - 15 Oct 2020


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