1. Cancer Biology
  2. Computational and Systems Biology

shinyDepMap, a tool to identify targetable cancer genes and their functional connections from Cancer Dependency Map data

  1. Kenichi Shimada  Is a corresponding author
  2. John A Bachman
  3. Jeremy L Muhlich
  4. Timothy J Mitchison
  1. Harvard Medical School, United States
https://doi.org/10.7554/eLife.57116
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  1. Kenichi Shimada
  2. John A Bachman
  3. Jeremy L Muhlich
  4. Timothy J Mitchison
(2021)
shinyDepMap, a tool to identify targetable cancer genes and their functional connections from Cancer Dependency Map data
eLife 10:e57116.
https://doi.org/10.7554/eLife.57116
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Abstract

Individual cancers rely on distinct essential genes for their survival. The Cancer Dependency Map (DepMap) is an ongoing project to uncover these gene dependencies in hundreds of cancer cell lines. To make this drug discovery resource more accessible to the scientific community we built an easy-to-use browser, shinyDepMap (https://labsyspharm.shinyapps.io/depmap). shinyDepMap combines CRISPR and shRNA data to determine, for each gene, the growth reduction caused by knockout/knockdown and the selectivity of this effect across cell lines. The tool also clusters genes with similar dependencies, revealing functional relationships. shinyDepMap can be used to 1) predict the efficacy and selectivity of drugs targeting particular genes; 2) identify maximally sensitive cell lines for testing a drug; 3) target hop, i.e., navigate from an undruggable protein with the desired selectivity profile, such as an activated oncogene, to more druggable targets with a similar profile; and 4) identify novel pathways driving cancer cell growth and survival.

Data availability

Data files have been provided for Figures 1, 3, 4, and 5 on FigShare: https://figshare.com/projects/shinyDepMap_Source_Data/97382 (DOIs: 10.6084/m9.figshare.13653251.v1, 10.6084/m9.figshare.13653257.v1, 10.6084/m9.figshare.13653260.v1, 10.6084/m9.figshare.13653266.v1, 10.6084/m9.figshare.13653272.v1, 10.6084/m9.figshare.13653278.v1, 10.6084/m9.figshare.13653281.v2)

The following data sets were generated
The following previously published data sets were used

Article and author information

Author details

  1. Kenichi Shimada

    Department of Systems Biology and Laboratory of Systems Pharmacology, Harvard Medical School, Boston, United States
    For correspondence
    kenichi_shimada@hms.harvard.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8540-9785

  2. John A Bachman

    Department of Systems Biology and Laboratory of Systems Pharmacology, Harvard Medical School, Boston, United States
    Competing interests
    The authors declare that no competing interests exist.

  3. Jeremy L Muhlich

    Laboratory of Systems Pharmacology, Harvard Medical School, Boston, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-0811-637X

  4. Timothy J Mitchison

    Department of Systems Biology, Harvard Medical School, Boston, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7781-1897

Funding

Japan Society for the Promotion of Science (H29-814)

  • Kenichi Shimada

National Institute of General Medical Sciences (R35GM131753)

  • Timothy J Mitchison

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

© 2021, Shimada et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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  1. Kenichi Shimada
  2. John A Bachman
  3. Jeremy L Muhlich
  4. Timothy J Mitchison
(2021)
shinyDepMap, a tool to identify targetable cancer genes and their functional connections from Cancer Dependency Map data
eLife 10:e57116.
https://doi.org/10.7554/eLife.57116

Share this article

https://doi.org/10.7554/eLife.57116

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