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

Cancers accumulate multiple single copy number alterations, but their impact is unclear. Here, the authors computationally demonstrate a disruption of genes associated with autophagy in ovarian cancer, show impact on autophagic flux, and note the efficacy of autophagy drugs in preclinical models.

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Autores principales: 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, Parthiv Sheth, Carley Haft, Sandra Hui, Cheryl Saenz, David D. Schlaepfer, Olivier Harismendy, Dwayne G. Stupack
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Publicado: Nature Portfolio 2017
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Acceso en línea:https://doaj.org/article/4693ab4669b34978ad4a226632a7b4a7
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spelling oai:doaj.org-article:4693ab4669b34978ad4a226632a7b4a72021-12-02T15:39:00ZHaploinsufficiency networks identify targetable patterns of allelic deficiency in low mutation ovarian cancer10.1038/ncomms144232041-1723https://doaj.org/article/4693ab4669b34978ad4a226632a7b4a72017-02-01T00:00:00Zhttps://doi.org/10.1038/ncomms14423https://doaj.org/toc/2041-1723Cancers accumulate multiple single copy number alterations, but their impact is unclear. Here, the authors computationally demonstrate a disruption of genes associated with autophagy in ovarian cancer, show impact on autophagic flux, and note the efficacy of autophagy drugs in preclinical models.Joe Ryan DelaneyChandni B. PatelKatelyn McCabe WillisMina HaghighiabyanehJoshua AxelrodIsabelle TancioniDan LuJaidev BapatShanique YoungOctavia CadassouAlena BartakovaParthiv ShethCarley HaftSandra HuiCheryl SaenzDavid D. SchlaepferOlivier HarismendyDwayne G. StupackNature PortfolioarticleScienceQENNature Communications, Vol 8, Iss 1, Pp 1-11 (2017)
institution DOAJ
collection DOAJ
language EN
topic Science
Q
spellingShingle Science
Q
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
Parthiv Sheth
Carley Haft
Sandra Hui
Cheryl Saenz
David D. Schlaepfer
Olivier Harismendy
Dwayne G. Stupack
Haploinsufficiency networks identify targetable patterns of allelic deficiency in low mutation ovarian cancer
description Cancers accumulate multiple single copy number alterations, but their impact is unclear. Here, the authors computationally demonstrate a disruption of genes associated with autophagy in ovarian cancer, show impact on autophagic flux, and note the efficacy of autophagy drugs in preclinical models.
format article
author 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
Parthiv Sheth
Carley Haft
Sandra Hui
Cheryl Saenz
David D. Schlaepfer
Olivier Harismendy
Dwayne G. Stupack
author_facet 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
Parthiv Sheth
Carley Haft
Sandra Hui
Cheryl Saenz
David D. Schlaepfer
Olivier Harismendy
Dwayne G. Stupack
author_sort Joe Ryan Delaney
title Haploinsufficiency networks identify targetable patterns of allelic deficiency in low mutation ovarian cancer
title_short Haploinsufficiency networks identify targetable patterns of allelic deficiency in low mutation ovarian cancer
title_full Haploinsufficiency networks identify targetable patterns of allelic deficiency in low mutation ovarian cancer
title_fullStr Haploinsufficiency networks identify targetable patterns of allelic deficiency in low mutation ovarian cancer
title_full_unstemmed Haploinsufficiency networks identify targetable patterns of allelic deficiency in low mutation ovarian cancer
title_sort haploinsufficiency networks identify targetable patterns of allelic deficiency in low mutation ovarian cancer
publisher Nature Portfolio
publishDate 2017
url https://doaj.org/article/4693ab4669b34978ad4a226632a7b4a7
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