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

Integrative pharmacogenomics to infer large-scale drug taxonomy

Nehme El-Hachem, Deena M.A. Gendoo, Laleh Soltan Ghoraie, Zhaleh Safikhani, Petr Smirnov, Christina Chung, Kenan Deng, Ailsa Fang, Erin Birkwood, Chantal Ho, Ruth Isserlin, Gary D. Bader, Anna Goldenberg, Benjamin Haibe-Kains
doi: https://doi.org/10.1101/046219
Nehme El-Hachem
1Integrative Computational Systems Biology, Institut de Recherches Cliniques de Montréal, Montreal, Quebec, Canada
2Department of Biomedical Sciences. Université de Montréal, Montreal, Quebec, Canada
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Deena M.A. Gendoo
3Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
4Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Laleh Soltan Ghoraie
3Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
4Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Zhaleh Safikhani
3Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
4Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Petr Smirnov
3Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Christina Chung
5Department of Computer Science, University of Toronto, Toronto, Ontario, Canada
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Kenan Deng
5Department of Computer Science, University of Toronto, Toronto, Ontario, Canada
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Ailsa Fang
5Department of Computer Science, University of Toronto, Toronto, Ontario, Canada
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Erin Birkwood
6School of Computer Science, McGill University, Montreal, Quebec, Canada
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Chantal Ho
5Department of Computer Science, University of Toronto, Toronto, Ontario, Canada
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Ruth Isserlin
5Department of Computer Science, University of Toronto, Toronto, Ontario, Canada
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Gary D. Bader
5Department of Computer Science, University of Toronto, Toronto, Ontario, Canada
6School of Computer Science, McGill University, Montreal, Quebec, Canada
7The Donnelly Centre, Toronto, Ontario, Canada
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Anna Goldenberg
7The Donnelly Centre, Toronto, Ontario, Canada
8The Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Benjamin Haibe-Kains
3Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
4Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
5Department of Computer Science, University of Toronto, Toronto, Ontario, Canada
9Hospital for Sick Children, Toronto, Ontario, Canada
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Supplementary material
  • Preview PDF
Loading

ABSTRACT

Identification of drug targets and mechanism of action (MoA) for new and uncharacterlzed drugs is important for optimization of drug efficacy. Current MoA prediction approaches largely rely on prior information including side effects, therapeutic indication and/or chemo-informatics. Such information is not transferable or applicable for newly identified, previously uncharacterlzed small molecules. Therefore, a shift in the paradigm of MoA predictions is necessary towards development of unbiased approaches that can elucidate drug relationships and efficiently classify new compounds with basic input data. We propose a new integrative computational pharmacogenomlc approach, referred to as Drug Network Fusion (DNF), to infer scalable drug taxonomies that relies only on basic drug characteristics towards elucidating drug-drug relationships. DNF is the first framework to integrate drug structural information, high-throughput drug perturbation and drug sensitivity profiles, enabling drug classification of new experimental compounds with minimal prior information. We demonstrate that the DNF taxonomy succeeds in identifying pertinent and novel drug-drug relationships, making it suitable for investigating experimental drugs with potential new targets or MoA. We highlight how the scalability of DNF facilitates identification of key drug relationships across different drug categories, and poses as a flexible tool for potential clinical applications in precision medicine. Our results support DNF as a valuable resource to the cancer research community by providing new hypotheses on the compound MoA and potential insights for drug repurposlng.

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 January 05, 2017.
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.
Integrative pharmacogenomics to infer large-scale drug taxonomy
(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
Integrative pharmacogenomics to infer large-scale drug taxonomy
Nehme El-Hachem, Deena M.A. Gendoo, Laleh Soltan Ghoraie, Zhaleh Safikhani, Petr Smirnov, Christina Chung, Kenan Deng, Ailsa Fang, Erin Birkwood, Chantal Ho, Ruth Isserlin, Gary D. Bader, Anna Goldenberg, Benjamin Haibe-Kains
bioRxiv 046219; doi: https://doi.org/10.1101/046219
Digg logo Reddit logo Twitter logo Facebook logo Google logo LinkedIn logo Mendeley logo
Citation Tools
Integrative pharmacogenomics to infer large-scale drug taxonomy
Nehme El-Hachem, Deena M.A. Gendoo, Laleh Soltan Ghoraie, Zhaleh Safikhani, Petr Smirnov, Christina Chung, Kenan Deng, Ailsa Fang, Erin Birkwood, Chantal Ho, Ruth Isserlin, Gary D. Bader, Anna Goldenberg, Benjamin Haibe-Kains
bioRxiv 046219; doi: https://doi.org/10.1101/046219

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

  • Bioinformatics
Subject Areas
All Articles
  • Animal Behavior and Cognition (3514)
  • Biochemistry (7365)
  • Bioengineering (5342)
  • Bioinformatics (20318)
  • Biophysics (10041)
  • Cancer Biology (7773)
  • Cell Biology (11348)
  • Clinical Trials (138)
  • Developmental Biology (6450)
  • Ecology (9979)
  • Epidemiology (2065)
  • Evolutionary Biology (13354)
  • Genetics (9370)
  • Genomics (12607)
  • Immunology (7724)
  • Microbiology (19087)
  • Molecular Biology (7459)
  • Neuroscience (41134)
  • Paleontology (300)
  • Pathology (1235)
  • Pharmacology and Toxicology (2142)
  • Physiology (3177)
  • Plant Biology (6878)
  • Scientific Communication and Education (1276)
  • Synthetic Biology (1900)
  • Systems Biology (5328)
  • Zoology (1091)