Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

Prediction of combination therapies based on topological modeling of the immune signaling network in Multiple Sclerosis

View ORCID ProfileMarti Bernardo-Faura, View ORCID ProfileMelanie Rinas, View ORCID ProfileJakob Wirbel, View ORCID ProfileInna Pertsovskaya, Vicky Pliaka, View ORCID ProfileDimitris E Messinis, Gemma Vila, Theodore Sakellaropoulos, View ORCID ProfileWolfgang Faigle, View ORCID ProfilePernilla Stridh, Janina R. Behrens, View ORCID ProfileTomas Olsson, Roland Martin, View ORCID ProfileFriedemann Paul, View ORCID ProfileLeonidas G Alexopoulos, View ORCID ProfilePablo Villoslada, View ORCID ProfileJulio Saez-Rodriguez
doi: https://doi.org/10.1101/541458
Marti Bernardo-Faura
1European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK
2Centre for Research in Agricultural Genomics (CRAG), Bellaterra, Barcelona, Spain
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Marti Bernardo-Faura
Melanie Rinas
3Joint Research Center for Computational Biomedicine (JRC-COMBINE), RWTH-Aachen University, Faculty of Medicine, Aachen, Germany
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Melanie Rinas
Jakob Wirbel
1European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK
3Joint Research Center for Computational Biomedicine (JRC-COMBINE), RWTH-Aachen University, Faculty of Medicine, Aachen, Germany
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Jakob Wirbel
Inna Pertsovskaya
4Institut d’ Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), Barcelona, Spain
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Inna Pertsovskaya
Vicky Pliaka
5National Technical University of Athens, Greece
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Dimitris E Messinis
6ProtATonce Ltd, Athens, Greece
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Dimitris E Messinis
Gemma Vila
4Institut d’ Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), Barcelona, Spain
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Theodore Sakellaropoulos
5National Technical University of Athens, Greece
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Wolfgang Faigle
7University of Zurich, Switzerland
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Wolfgang Faigle
Pernilla Stridh
8Department of Neurology, Karolinska University Hospital, Sweden and Department of Clinical Neuroscience, Karolinska Institutet, Sweden.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Pernilla Stridh
Janina R. Behrens
9NeuroCure Clinical Research Center and Department of Neurology, Charité University Medicine Berlin, Berlin, Germany
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Tomas Olsson
8Department of Neurology, Karolinska University Hospital, Sweden and Department of Clinical Neuroscience, Karolinska Institutet, Sweden.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Tomas Olsson
Roland Martin
7University of Zurich, Switzerland
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Friedemann Paul
9NeuroCure Clinical Research Center and Department of Neurology, Charité University Medicine Berlin, Berlin, Germany
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Friedemann Paul
Leonidas G Alexopoulos
5National Technical University of Athens, Greece
6ProtATonce Ltd, Athens, Greece
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Leonidas G Alexopoulos
  • For correspondence: saezrodriguez@gmail.com pvilloslada@clinic.ub.es leo@mail.ntua.gr
Pablo Villoslada
4Institut d’ Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), Barcelona, Spain
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Pablo Villoslada
  • For correspondence: saezrodriguez@gmail.com pvilloslada@clinic.ub.es leo@mail.ntua.gr
Julio Saez-Rodriguez
1European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK
3Joint Research Center for Computational Biomedicine (JRC-COMBINE), RWTH-Aachen University, Faculty of Medicine, Aachen, Germany
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Julio Saez-Rodriguez
  • For correspondence: saezrodriguez@gmail.com pvilloslada@clinic.ub.es leo@mail.ntua.gr
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Supplementary material
  • Preview PDF
Loading

Abstract

Signal transduction deregulation is a hallmark of many complex diseases, including Multiple Sclerosis (MS). Here, we performed ex vivo multiplexed phosphoproteomic assays in PBMCs from 180 MS patients either untreated or treated with fingolimod, natalizumab, interferon-beta, glatiramer acetate or the experimental therapy epigallocatechin gallate (EGCG), and from 60 matched healthy controls. Fitting a bespoke literature-derived network of MS-related pathways using logic modeling yielded a signaling network specific for each patient. Patient models were merged to characterize healthy-, disease- and drug-specific signaling networks. We defined a co-druggability score based on the topology for each drug’s network. We used this score to identify kinase interactions whose activity could be reverted to a "healthy-like" status by combination therapy. We predicted several combinations with approved MS drugs. Specifically, TAK1 kinase, involved in TGF-B, toll-like receptor, B-cell receptor and response to inflammation pathways was found to be highly deregulated and co-druggable with four MS drugs. One of these predicted combinations, Fingolimod with a TAK1 inhibitor, was validated in an animal model of MS. Our approach based on patient-specific signaling networks enables prediction of targets for combination therapy for MS and other complex diseases.

One sentence summary A new approach to predict combination therapies based on modeling signaling architecture using phosphoproteomics from patients with Multiple Sclerosis characterizes deregulated signaling pathways and reveals new therapeutic targets and drug combinations.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
Back to top
PreviousNext
Posted February 05, 2019.
Download PDF

Supplementary Material

Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
Prediction of combination therapies based on topological modeling of the immune signaling network in Multiple Sclerosis
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
Prediction of combination therapies based on topological modeling of the immune signaling network in Multiple Sclerosis
Marti Bernardo-Faura, Melanie Rinas, Jakob Wirbel, Inna Pertsovskaya, Vicky Pliaka, Dimitris E Messinis, Gemma Vila, Theodore Sakellaropoulos, Wolfgang Faigle, Pernilla Stridh, Janina R. Behrens, Tomas Olsson, Roland Martin, Friedemann Paul, Leonidas G Alexopoulos, Pablo Villoslada, Julio Saez-Rodriguez
bioRxiv 541458; doi: https://doi.org/10.1101/541458
Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo
Citation Tools
Prediction of combination therapies based on topological modeling of the immune signaling network in Multiple Sclerosis
Marti Bernardo-Faura, Melanie Rinas, Jakob Wirbel, Inna Pertsovskaya, Vicky Pliaka, Dimitris E Messinis, Gemma Vila, Theodore Sakellaropoulos, Wolfgang Faigle, Pernilla Stridh, Janina R. Behrens, Tomas Olsson, Roland Martin, Friedemann Paul, Leonidas G Alexopoulos, Pablo Villoslada, Julio Saez-Rodriguez
bioRxiv 541458; doi: https://doi.org/10.1101/541458

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Systems Biology
Subject Areas
All Articles
  • Animal Behavior and Cognition (2524)
  • Biochemistry (4971)
  • Bioengineering (3478)
  • Bioinformatics (15198)
  • Biophysics (6890)
  • Cancer Biology (5385)
  • Cell Biology (7727)
  • Clinical Trials (138)
  • Developmental Biology (4525)
  • Ecology (7143)
  • Epidemiology (2059)
  • Evolutionary Biology (10217)
  • Genetics (7507)
  • Genomics (9776)
  • Immunology (4835)
  • Microbiology (13197)
  • Molecular Biology (5136)
  • Neuroscience (29405)
  • Paleontology (203)
  • Pathology (836)
  • Pharmacology and Toxicology (1462)
  • Physiology (2134)
  • Plant Biology (4739)
  • Scientific Communication and Education (1008)
  • Synthetic Biology (1338)
  • Systems Biology (4008)
  • Zoology (768)