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.
|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
|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 lines; Integrating genotype data; Kinase dependencies; Protein interaction data; Genetic dependencies; Mutant cell lines; Kinome 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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