Large-Scale Profiling of Kinase Dependencies in Cancer Cell Lines

James Campbell, Colm J Ryan, Rachel Brough, Ilirjana Bajrami, Helen Pemberton, Irene Y Chong, Sara Costa-Cabral, Jessica Frankum, Aditi Gulati, Harriet Holme, Rowan Miller, Sophie Postel-Vinay, Rumana Rafiq, Wenbin Wei, Chris T Williamson, David A. Quigley, Joe Tym, Bissan Al-Lazikani, Timothy Fenton, Rachael NatrajanSandra J Strauss, Alan Ashworth, Christopher J. Lord

Research output: Contribution to journalArticlepeer-review

67 Citations (Scopus)
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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.

Original languageEnglish
Pages (from-to)2490-2501
Number of pages12
JournalCell Reports
Volume14
Issue number10
Early online date3 Mar 2016
DOIs
Publication statusE-pub ahead of print - 3 Mar 2016

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