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Dissecting cancer resistance to therapies with cell-type-specific dynamic logic models

View ORCID ProfileFederica Eduati, Victoria Doldàn-Martelli, Bertram Klinger, View ORCID ProfileThomas Cokelaer, Anja Sieber, Fiona Kogera, View ORCID ProfileMathurin Dorel, View ORCID ProfileMathew J Garnett, View ORCID ProfileNils Blüthgen, View ORCID ProfileJulio Saez-Rodriguez
doi: https://doi.org/10.1101/094755
Federica Eduati
1European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, UK
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  • ORCID record for Federica Eduati
Victoria Doldàn-Martelli
1European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, UK
2Departamento de Física de la Materia Condensada, Condensed Matter Physics Center (IFIMAC) and Instituto Nicolás Cabrera, Facultad de Ciencias, Universidad Autónoma de Madrid, Madrid, Spain
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Bertram Klinger
3institute of Pathology, Charité - Universitätsmedizin Berlin, Berlin, Germany
4Integrative Research Institute (IRI) Life Sciences and Institute for Theoretical Biology, Humboldt-Universität zu Berlin, Berlin, Germany
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Thomas Cokelaer
1European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, UK
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Anja Sieber
3institute of Pathology, Charité - Universitätsmedizin Berlin, Berlin, Germany
4Integrative Research Institute (IRI) Life Sciences and Institute for Theoretical Biology, Humboldt-Universität zu Berlin, Berlin, Germany
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Fiona Kogera
5Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire, UK
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Mathurin Dorel
3institute of Pathology, Charité - Universitätsmedizin Berlin, Berlin, Germany
4Integrative Research Institute (IRI) Life Sciences and Institute for Theoretical Biology, Humboldt-Universität zu Berlin, Berlin, Germany
6Berlin Institute of Health (BIH), Berlin, Germany
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Mathew J Garnett
5Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire, UK
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Nils Blüthgen
3institute of Pathology, Charité - Universitätsmedizin Berlin, Berlin, Germany
4Integrative Research Institute (IRI) Life Sciences and Institute for Theoretical Biology, Humboldt-Universität zu Berlin, Berlin, Germany
6Berlin Institute of Health (BIH), Berlin, Germany
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  • For correspondence: nils.bluethgen@charite.de saezrodriguez@gmail.com
Julio Saez-Rodriguez
1European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, UK
7Joint Research Centre for Computational Biomedicine (JRC-COMBINE), RWTH Aachen University, Faculty of Medicine, Aachen, Germany
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  • For correspondence: nils.bluethgen@charite.de saezrodriguez@gmail.com
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Abstract

Therapies targeting specific molecular processes, in particular kinases, are major strategies to treat cancer. Genomic features are commonly used as biomarkers for drug sensitivity, but our ability to stratify patients based on these features is still limited. As response to kinase inhibitors is a dynamic process affecting largely signal transduction, we investigated the association between cell-specific dynamic signaling pathways and drug sensitivity. We measured 14 phosphoproteins under 43 different perturbed conditions (combination of 5 stimuli and 7 inhibitors) for 14 colorectal cancer cell-lines, and built cell-line-specific dynamic logic models of the underlying signaling network. Model parameters, representing pathway dynamics, were used as features to predict sensitivity to a panel of 27 drugs. This analysis revealed associations between cell-specific signaling pathways and drug sensitivity for 14 of the drugs, 9 of which have no genomic biomarker. Following one of these associations, we validated a drug combination predicted to overcome resistance to MEK inhibitors by co-blockade of GSK3. These results underscore the value of perturbation-based studies to find biomarkers and combination therapies complementing those based on a static genomic characterization.

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Posted December 16, 2016.
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Dissecting cancer resistance to therapies with cell-type-specific dynamic logic models
Federica Eduati, Victoria Doldàn-Martelli, Bertram Klinger, Thomas Cokelaer, Anja Sieber, Fiona Kogera, Mathurin Dorel, Mathew J Garnett, Nils Blüthgen, Julio Saez-Rodriguez
bioRxiv 094755; doi: https://doi.org/10.1101/094755
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Dissecting cancer resistance to therapies with cell-type-specific dynamic logic models
Federica Eduati, Victoria Doldàn-Martelli, Bertram Klinger, Thomas Cokelaer, Anja Sieber, Fiona Kogera, Mathurin Dorel, Mathew J Garnett, Nils Blüthgen, Julio Saez-Rodriguez
bioRxiv 094755; doi: https://doi.org/10.1101/094755

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