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Approaches to identify kinase dependencies in cancer signalling networks
Author(s) -
Dermit Maria,
Dokal Arran,
Cutillas Pedro R.
Publication year - 2017
Publication title -
febs letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.593
H-Index - 257
eISSN - 1873-3468
pISSN - 0014-5793
DOI - 10.1002/1873-3468.12748
Subject(s) - signalling , cancer , kinase , computational biology , biology , chemistry , cancer research , computer science , microbiology and biotechnology , genetics
Cells integrate extracellular signals into appropriate responses through a complex network of biochemical reactions driven by the activity of protein and lipid kinases, among other proteins. In order to understand this complexity, new approaches, both experimental and computational, have recently been developed with the aim to identify regulatory kinases and infer their activation status in the context of their signalling network. Here, we review such approaches with particular focus on those based on phosphoproteomics. Integration of kinase activity measurements inferred from phosphoproteomics data with other ‘omics’ datasets is starting to be used to identify regulatory nodes in biochemical networks. These methodologies may in the future be used to identify patient‐specific targets and thus advance personalised cancer medicine.