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

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
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Science
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Acceso en línea:https://doaj.org/article/e49e620b8adf451f9e5a7aa02173d0b8
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Sumario: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.

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