Large-Scale Profiling of Kinase Dependencies in Cancer Cell Lines.
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Authors
Campbell, J
Ryan, CJ
Brough, R
Bajrami, I
Pemberton, HN
Chong, IY
Costa-Cabral, S
Frankum, J
Gulati, A
Holme, H
Miller, R
Postel-Vinay, S
Rafiq, R
Wei, W
Williamson, CT
Quigley, DA
Tym, J
Al-Lazikani, B
Fenton, T
Natrajan, R
Strauss, SJ
Ashworth, A
Lord, CJ
Ryan, CJ
Brough, R
Bajrami, I
Pemberton, HN
Chong, IY
Costa-Cabral, S
Frankum, J
Gulati, A
Holme, H
Miller, R
Postel-Vinay, S
Rafiq, R
Wei, W
Williamson, CT
Quigley, DA
Tym, J
Al-Lazikani, B
Fenton, T
Natrajan, R
Strauss, SJ
Ashworth, A
Lord, CJ
Document Type
Journal Article
Date
2016-03-15
Date Accepted
2016-02-01
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.
Citation
Cell reports, 2016, 14 (10), pp. 2490 - 2501
Source Title
Publisher
CELL PRESS
ISSN
2211-1247
eISSN
2211-1247
Research Team
Computational Biology and Chemogenomics
Ashworth Collaborators
Functional Genomics
Gene Function
Ashworth Collaborators
Functional Genomics
Gene Function