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Large-Scale Profiling of Kinase Dependencies in Cancer Cell Lines

Campbell, J, Ryan, CJ, Brough, R, Bajrami, I, Pemberton, HN, Chong, IY, Costa-Cabral, S, Frankum, J, Gulati, A, Holme, H, and others. (2016) Large-Scale Profiling of Kinase Dependencies in Cancer Cell Lines. Cell Reports, 14 (10). pp. 2490-2501. ISSN 2211-1247. (doi:10.1016/j.celrep.2016.02.023) (KAR id:61503)

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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.

Item Type: Article
DOI/Identification number: 10.1016/j.celrep.2016.02.023
Additional information: This is an open access article under the Creative Commons Attribution Licence (
Divisions: Divisions > Division of Natural Sciences > School of Biosciences
Depositing User: Tim Fenton
Date Deposited: 21 Apr 2017 13:46 UTC
Last Modified: 29 May 2019 18:59 UTC
Resource URI: (The current URI for this page, for reference purposes)
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