Network integration and modelling of dynamic drug responses at multi-omics levels
Nathalie Selevsek, Florian Caiment, Ramona Nudischer, Hans Gmuender, Irina Agarkova, Francis Atkinson, Ivo Bachmann, Vanessa Baier, Gal Barel, Chris Bauer, Stefan Boerno, Nicolas Bosc, Olivia Clayton, Henrik Cordes, Sally J. Deeb, Stefano Gotta, Patrick Guye, Anne Hersey, Fiona Hunter, Laura Kunz, Alexandre Lewalle, Matthias Lienhard, Jort J. Merken, Jasmine Minguet, Bernardo Lino de Oliveira, Carla Pluess, Uğis Sarkans, Yannick Schrooders, Johannes Schuchhardt, Ines Smit, Christoph Thiel, Bernd Timmermann, Marcha Verheijen, Timo Wittenberger, Witold Wolski, Alexandra Zerck, Stéphane Heymans, Lars Kuepfer, Adrian Roth, Ralph Schlapbach, Steven Niederer, Ralf Herwig, Jos Kleinjans
Abstract
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.