IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v8y2017i1d10.1038_ncomms14423.html
   My bibliography  Save this article

Haploinsufficiency networks identify targetable patterns of allelic deficiency in low mutation ovarian cancer

Author

Listed:
  • Joe Ryan Delaney

    (UCSD School of Medicine and UCSD Moores Cancer Center)

  • Chandni B. Patel

    (UCSD School of Medicine and UCSD Moores Cancer Center)

  • Katelyn McCabe Willis

    (UCSD School of Medicine and UCSD Moores Cancer Center)

  • Mina Haghighiabyaneh

    (UCSD School of Medicine and UCSD Moores Cancer Center)

  • Joshua Axelrod

    (UCSD School of Medicine and UCSD Moores Cancer Center)

  • Isabelle Tancioni

    (UCSD School of Medicine and UCSD Moores Cancer Center)

  • Dan Lu

    (UCSD School of Medicine and UCSD Moores Cancer Center)

  • Jaidev Bapat

    (UCSD School of Medicine and UCSD Moores Cancer Center)

  • Shanique Young

    (UCSD School of Medicine and UCSD Moores Cancer Center)

  • Octavia Cadassou

    (UCSD School of Medicine and UCSD Moores Cancer Center
    Centre de recherche en Cancérologie, INSERM 1052, CNRS 5286, Centre Léon Bérard, Université de Lyon)

  • Alena Bartakova

    (UCSD School of Medicine and UCSD Moores Cancer Center)

  • Parthiv Sheth

    (UCSD School of Medicine and UCSD Moores Cancer Center)

  • Carley Haft

    (UCSD School of Medicine and UCSD Moores Cancer Center)

  • Sandra Hui

    (UCSD School of Medicine and UCSD Moores Cancer Center)

  • Cheryl Saenz

    (UCSD School of Medicine and UCSD Moores Cancer Center)

  • David D. Schlaepfer

    (UCSD School of Medicine and UCSD Moores Cancer Center)

  • Olivier Harismendy

    (UCSD School of Medicine and UCSD Moores Cancer Center)

  • Dwayne G. Stupack

    (UCSD School of Medicine and UCSD Moores Cancer Center)

Abstract

Identification of specific oncogenic gene changes has enabled the modern generation of targeted cancer therapeutics. In high-grade serous ovarian cancer (OV), the bulk of genetic changes is not somatic point mutations, but rather somatic copy-number alterations (SCNAs). The impact of SCNAs on tumour biology remains poorly understood. Here we build haploinsufficiency network analyses to identify which SCNA patterns are most disruptive in OV. Of all KEGG pathways (N=187), autophagy is the most significantly disrupted by coincident gene deletions. Compared with 20 other cancer types, OV is most severely disrupted in autophagy and in compensatory proteostasis pathways. Network analysis prioritizes MAP1LC3B (LC3) and BECN1 as most impactful. Knockdown of LC3 and BECN1 expression confers sensitivity to cells undergoing autophagic stress independent of platinum resistance status. The results support the use of pathway network tools to evaluate how the copy-number landscape of a tumour may guide therapy.

Suggested Citation

  • Joe Ryan Delaney & Chandni B. Patel & Katelyn McCabe Willis & Mina Haghighiabyaneh & Joshua Axelrod & Isabelle Tancioni & Dan Lu & Jaidev Bapat & Shanique Young & Octavia Cadassou & Alena Bartakova & , 2017. "Haploinsufficiency networks identify targetable patterns of allelic deficiency in low mutation ovarian cancer," Nature Communications, Nature, vol. 8(1), pages 1-11, April.
    • Handle: RePEc:nat:natcom:v:8:y:2017:i:1:d:10.1038_ncomms14423
    DOI: 10.1038/ncomms14423
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/ncomms14423
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1038/ncomms14423?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:8:y:2017:i:1:d:10.1038_ncomms14423. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.