Final Report Summary - KINOMEDRIFT (Specificity Drift in The Kinome During Cancer Development and Evolution)
Cellular processes such as cell growth, death and motility are controlled by complex networks of cellular signals. These cellular signals are initiated and maintained by a specialized set of enzymes called kinases. Kinases act on other proteins in the cell by phosphorylating specific residues contained in those proteins leading to changes in their function. While it is well know that many proteins in a cell can be, and are, phosphorylated the exact sites of phosphorylation recognized by each kinase, and the affect this may have on protein function is currently unknown. Using three different biochemical techniques we have determined the phosphorylation events that are caused by each protein kinase; using protein kinase assays we have discovered the preferential protein sequence kinases phosphorylate, and using global mass spectrometry approaches we have determined which proteins interact with each kinase and which proteins are phosphorylated by each kinase. By integrating these three data sets, we can computationally model the targets of each kinase.
A second aspect of our research centers on cancer mutations. It is well known that genetic mutations in kinases can lead to the development of cancer. However our understanding of how best to treat these cancers is still lacking. To this end we have developed a novel computational platform, ReKINect, to investigated how kinase mutations alter cell signaling networks using information from cancer genome sequencing projects in conjunction with proteomics data. Using this platform we were able to explain and validate the role of mutations in cancer that were, until now, impossible to interpret. We hope that moving forward these observations will lead to a better understanding of the role of mutations in cancer and subsequent improvements in treatment strategies against cancer.
A second aspect of our research centers on cancer mutations. It is well known that genetic mutations in kinases can lead to the development of cancer. However our understanding of how best to treat these cancers is still lacking. To this end we have developed a novel computational platform, ReKINect, to investigated how kinase mutations alter cell signaling networks using information from cancer genome sequencing projects in conjunction with proteomics data. Using this platform we were able to explain and validate the role of mutations in cancer that were, until now, impossible to interpret. We hope that moving forward these observations will lead to a better understanding of the role of mutations in cancer and subsequent improvements in treatment strategies against cancer.