Large-Scale Profiling of Kinase Dependencies in Cancer Cell Lines

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Title: Large-Scale Profiling of Kinase Dependencies in Cancer Cell Lines
Authors: Campbell, James
Ryan, Colm J.
Brough, Rachel
et al.
Permanent link: http://hdl.handle.net/10197/9764
Date: 15-Mar-2016
Online since: 2019-04-02T08:13:50Z
Abstract: One approach to identifying cancer-specific vulnerabilities and therapeutic targets is to profile genetic dependencies in cancer cell lines. Here, we describe data from a series of siRNA screens that identify the kinase genetic dependencies in 117 cancer cell lines from ten cancer types. By integrating the siRNA screen data with molecular profiling data, including exome sequencing data, we show how vulnerabilities/genetic dependencies that are associated with mutations in specific cancer driver genes can be identified. By integrating additional data sets into this analysis, including protein-protein interaction data, we also demonstrate that the genetic dependencies associated with many cancer driver genes form dense connections on functional interaction networks. We demonstrate the utility of this resource by using it to predict the drug sensitivity of genetically or histologically defined subsets of tumor cell lines, including an increased sensitivity of osteosarcoma cell lines to FGFR inhibitors and SMAD4 mutant tumor cells to mitotic inhibitors.
Funding Details: European Commission - Seventh Framework Programme (FP7)
Health Research Board
Science Foundation Ireland
Wellcome Trust
Type of material: Journal Article
Publisher: Elsevier
Journal: Cell Reports
Volume: 14
Issue: 10
Start page: 2490
End page: 2501
Copyright (published version): 2016 Elsevier
Keywords: Cancer cell linesIntegrating genotype dataKinase dependenciesProtein interaction dataGenetic dependenciesMutant cell linesKinome siRNA screening
DOI: 10.1016/j.celrep.2016.02.023
Language: en
Status of Item: Peer reviewed
Appears in Collections:SBI Research Collection

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