Systematic discovery of mutation-specific synthetic lethals by mining pan-cancer human primary tumor data

There are no robust methods for systematically identifying mutation-specific synthetic lethal (SL) partners in cancer. Here, the authors develop a computational algorithm that uses pan-cancer data to detect mutation-andcancer-specific SL partners and they validate a novel SL interaction between muta...

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Autores principales:	Subarna Sinha, Daniel Thomas, Steven Chan, Yang Gao, Diede Brunen, Damoun Torabi, Andreas Reinisch, David Hernandez, Andy Chan, Erinn B. Rankin, Rene Bernards, Ravindra Majeti, David L. Dill
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/e49e620b8adf451f9e5a7aa02173d0b8
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spelling	oai:doaj.org-article:e49e620b8adf451f9e5a7aa02173d0b82021-12-02T17:06:19ZSystematic discovery of mutation-specific synthetic lethals by mining pan-cancer human primary tumor data10.1038/ncomms155802041-1723https://doaj.org/article/e49e620b8adf451f9e5a7aa02173d0b82017-05-01T00:00:00Zhttps://doi.org/10.1038/ncomms15580https://doaj.org/toc/2041-1723There are no robust methods for systematically identifying mutation-specific synthetic lethal (SL) partners in cancer. Here, the authors develop a computational algorithm that uses pan-cancer data to detect mutation-andcancer-specific SL partners and they validate a novel SL interaction between mutant IDH and loss of ACACA in leukaemia.Subarna SinhaDaniel ThomasSteven ChanYang GaoDiede BrunenDamoun TorabiAndreas ReinischDavid HernandezAndy ChanErinn B. RankinRene BernardsRavindra MajetiDavid L. DillNature PortfolioarticleScienceQENNature Communications, Vol 8, Iss 1, Pp 1-13 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Subarna Sinha Daniel Thomas Steven Chan Yang Gao Diede Brunen Damoun Torabi Andreas Reinisch David Hernandez Andy Chan Erinn B. Rankin Rene Bernards Ravindra Majeti David L. Dill Systematic discovery of mutation-specific synthetic lethals by mining pan-cancer human primary tumor data
description	There are no robust methods for systematically identifying mutation-specific synthetic lethal (SL) partners in cancer. Here, the authors develop a computational algorithm that uses pan-cancer data to detect mutation-andcancer-specific SL partners and they validate a novel SL interaction between mutant IDH and loss of ACACA in leukaemia.
format	article
author	Subarna Sinha Daniel Thomas Steven Chan Yang Gao Diede Brunen Damoun Torabi Andreas Reinisch David Hernandez Andy Chan Erinn B. Rankin Rene Bernards Ravindra Majeti David L. Dill
author_facet	Subarna Sinha Daniel Thomas Steven Chan Yang Gao Diede Brunen Damoun Torabi Andreas Reinisch David Hernandez Andy Chan Erinn B. Rankin Rene Bernards Ravindra Majeti David L. Dill
author_sort	Subarna Sinha
title	Systematic discovery of mutation-specific synthetic lethals by mining pan-cancer human primary tumor data
title_short	Systematic discovery of mutation-specific synthetic lethals by mining pan-cancer human primary tumor data
title_full	Systematic discovery of mutation-specific synthetic lethals by mining pan-cancer human primary tumor data
title_fullStr	Systematic discovery of mutation-specific synthetic lethals by mining pan-cancer human primary tumor data
title_full_unstemmed	Systematic discovery of mutation-specific synthetic lethals by mining pan-cancer human primary tumor data
title_sort	systematic discovery of mutation-specific synthetic lethals by mining pan-cancer human primary tumor data
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/e49e620b8adf451f9e5a7aa02173d0b8
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Systematic discovery of mutation-specific synthetic lethals by mining pan-cancer human primary tumor data

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