title: HUMAN KINASES DISPLAY MUTATIONAL HOTSPOTS AT COGNATE POSITIONS WITHIN CANCER.
abstract: The discovery of driver genes is a major pursuit of cancer genomics, usually based on observing the same mutation in different patients. But the heterogeneity of cancer pathways plus the high background mutational frequency of tumor cells often cloud the distinction between less frequent drivers and innocent passenger mutations. Here, to overcome these disadvantages, we grouped together mutations from close kinase paralogs under the hypothesis that cognate mutations may functionally favor cancer cells in similar ways. Indeed, we find that kinase paralogs often bear mutations to the same substituted amino acid at the same aligned positions and with a large predicted Evolutionary Action. Functionally, these high Evolutionary Action, non-random mutations affect known kinase motifs, but strikingly, they do so differently among different kinase types and cancers, consistent with differences in selective pressures. Taken together, these results suggest that cancer pathways may flexibly distribute a dependence on a given functional mutation among multiple close kinase paralogs. The recognition of this "mutational delocalization" of cancer drivers among groups of paralogs is a new phenomena that may help better identify relevant mechanisms and therefore eventually guide personalized therapy.
authors.affiliation: Structural Computational Biology and Molecular Biophysics, Baylor College of Medicine, One Baylor Plaza Houston, TX, 77030, USA†The authors gratefully acknowledge support from the National Institutes of Health (GM066099 and GM079656), from the National Science Foundation (DBI-1356569), and from DARPA (N66001-15-C-4042), Jonathan.Gallion@bcm.edu.
authors.forename: Jonathan
authors.initials: J
authors.lastname: Gallion
authors.forename: Angela D
authors.initials: AD
authors.lastname: Wilkins
authors.forename: Olivier
authors.initials: O
authors.lastname: Lichtarge
mesh_terms: D019295:Computational Biology; D019143:Evolution, Molecular; D006801:Humans; D008958:Models, Molecular; D009154:Mutation; D009369:Neoplasms / Q000145:classification / Q000201:enzymology* / Q000235:genetics*; D010770:Phosphotransferases / Q000737:chemistry / Q000235:genetics* / Q000378:metabolism; D011487:Protein Conformation
chemical_list: D010770:Phosphotransferases