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Large-Scale Profiling of Kinase Dependencies in Cancer Cell Lines
Author(s)
Date Issued
2016-03-15
Date Available
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.
Sponsorship
European Commission - Seventh Framework Programme (FP7)
Health Research Board
Science Foundation Ireland
Wellcome Trust
Other Sponsorship
Cancer Research UK
Breast Cancer Now
National Health Service
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
Language
English
Status of Item
Peer reviewed
This item is made available under a Creative Commons License
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Name
Large Scale Profiling of Kinase Dependencies in Cancer Cell Lines CRyan TBC.pdf
Size
6.49 MB
Format
Adobe PDF
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