| Literature DB >> 31227600 |
Osama A Arshad1, Vincent Danna1, Vladislav A Petyuk1, Paul D Piehowski1, Tao Liu1, Karin D Rodland2, Jason E McDermott3.
Abstract
Phosphorylation of proteins is a key way cells regulate function, both at the individual protein level and at the level of signaling pathways. Kinases are responsible for phosphorylation of substrates, generally on serine, threonine, or tyrosine residues. Though particular sequence patterns can be identified that dictate whether a residue will be phosphorylated by a specific kinase, these patterns are not highly predictive of phosphorylation. The availability of large scale proteomic and phosphoproteomic data sets generated using mass-spectrometry-based approaches provides an opportunity to study the important relationship between kinase activity, substrate specificity, and phosphorylation. In this study, we analyze relationships between protein abundance and phosphopeptide abundance across more than 150 tumor samples and show that phosphorylation at specific phosphosites is not well correlated with overall kinase abundance. However, individual kinases show a clear and statistically significant difference in correlation among known phosphosite targets for that kinase and randomly selected phosphosites. We further investigate relationships between phosphorylation of known activating or inhibitory sites on kinases and phosphorylation of their target phosphosites. Combined with motif-based analysis, this approach can predict novel kinase targets and show which subsets of a kinase's target repertoire are specifically active in one condition versus another.Entities:
Keywords: Breast cancer; Cancer Biology; Computational Biology; Ovarian cancer; Phosphoproteome; Phosphorylation; iTRAQ
Mesh:
Substances:
Year: 2019 PMID: 31227600 PMCID: PMC6692771 DOI: 10.1074/mcp.RA119.001540
Source DB: PubMed Journal: Mol Cell Proteomics ISSN: 1535-9476 Impact factor: 5.911