Network integration and modelling of dynamic drug responses at multi-omics levels.
Nathalie SelevsekFlorian CaimentRamona NudischerHans GmuenderIrina AgarkovaFrancis L AtkinsonIvo BachmannVanessa BaierGal BarelChris BauerStefan BoernoNicolas BoscOlivia ClaytonHenrik CordesSally DeebStefano GottaPatrick GuyeAnne HerseyFiona M I HunterLaura KunzAlex LewalleMatthias LienhardJort MerkenJasmine MinguetBernardo Lino de OliveiraCarla PluessSiddhant TripathiYannick SchroodersJohannes SchuchhardtInes A SmitChristoph ThielBernd TimmermannMarcha VerheijenTimo WittenbergerWitold WolskiAlexandra ZerckStephane HeymansLars KuepferAdrian RothRalph SchlapbachSteven NiedererRalf HerwigJos KleinjansPublished in: Communications biology (2020)
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.
Keyphrases
- adverse drug
- electronic health record
- extracellular matrix
- single cell
- drug induced
- end stage renal disease
- ejection fraction
- network analysis
- newly diagnosed
- endothelial cells
- emergency department
- heart failure
- healthcare
- big data
- rna seq
- genome wide
- gene expression
- single molecule
- peritoneal dialysis
- left ventricular
- dna methylation
- artificial intelligence
- data analysis
- copy number
- high resolution
- molecularly imprinted
- protein kinase
- deep learning