Literature DB >> 19626714

Cancer-associated mutations are preferentially distributed in protein kinase functional sites.

Jose M G Izarzugaza1, Oliver C Redfern, Christine A Orengo, Alfonso Valencia.   

Abstract

Protein kinases are a superfamily involved in many crucial cellular processes, including signal transmission and regulation of cell cycle. As a consequence of this role, kinases have been reported to be associated with many types of cancer and are considered as potential therapeutic targets. We analyzed the distribution of pathogenic somatic point mutations (drivers) in the protein kinase superfamily with respect to their location in the protein, such as in structural, evolutionary, and functionally relevant regions. We find these driver mutations are more clearly associated with key protein features than other somatic mutations (passengers) that have not been directly linked to tumor progression. This observation fits well with the expected implication of the alterations in protein kinase function in cancer pathogenicity. To explain the relevance of the detected association of cancer driver mutations at the molecular level in the human kinome, we compare these with genetically inherited mutations (SNPs). We find that the subset of nonsynonymous SNPs that are associated to disease, but sufficiently mild to the point of being widespread in the population, tend to avoid those key protein regions, where they could be more detrimental for protein function. This tendency contrasts with the one detected for cancer associated-driver-mutations, which seems to be more directly implicated in the alteration of protein function. The detailed analysis of protein kinase groups and a number of relevant examples, confirm the relation between cancer associated-driver-mutations and key regions for protein kinase structure and function. 2009 Wiley-Liss, Inc.

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Year:  2009        PMID: 19626714     DOI: 10.1002/prot.22512

Source DB:  PubMed          Journal:  Proteins        ISSN: 0887-3585


  18 in total

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2.  Identification of cancer driver genes based on nucleotide context.

Authors:  Felix Dietlein; Donate Weghorn; Amaro Taylor-Weiner; André Richters; Brendan Reardon; David Liu; Eric S Lander; Eliezer M Van Allen; Shamil R Sunyaev
Journal:  Nat Genet       Date:  2020-02-03       Impact factor: 38.330

3.  Exome Sequencing Reveals AMER1 as a Frequently Mutated Gene in Colorectal Cancer.

Authors:  Rebeca Sanz-Pamplona; Adriana Lopez-Doriga; Laia Paré-Brunet; Kira Lázaro; Fernando Bellido; M Henar Alonso; Susanna Aussó; Elisabet Guinó; Sergi Beltrán; Francesc Castro-Giner; Marta Gut; Xavier Sanjuan; Adria Closa; David Cordero; Francisco D Morón-Duran; Antonio Soriano; Ramón Salazar; Laura Valle; Victor Moreno
Journal:  Clin Cancer Res       Date:  2015-06-12       Impact factor: 12.531

4.  Oncogenic potential is related to activating effect of cancer single and double somatic mutations in receptor tyrosine kinases.

Authors:  Kosuke Hashimoto; Igor B Rogozin; Anna R Panchenko
Journal:  Hum Mutat       Date:  2012-07-16       Impact factor: 4.878

Review 5.  Molecular mechanisms of disease-causing missense mutations.

Authors:  Shannon Stefl; Hafumi Nishi; Marharyta Petukh; Anna R Panchenko; Emil Alexov
Journal:  J Mol Biol       Date:  2013-07-16       Impact factor: 5.469

Review 6.  Human genomic disease variants: a neutral evolutionary explanation.

Authors:  Joel T Dudley; Yuseob Kim; Li Liu; Glenn J Markov; Kristyn Gerold; Rong Chen; Atul J Butte; Sudhir Kumar
Journal:  Genome Res       Date:  2012-06-04       Impact factor: 9.043

7.  Characterization of pathogenic germline mutations in human protein kinases.

Authors:  Jose M G Izarzugaza; Lisa E M Hopcroft; Anja Baresic; Christine A Orengo; Andrew C R Martin; Alfonso Valencia
Journal:  BMC Bioinformatics       Date:  2011-07-05       Impact factor: 3.169

8.  An integrated approach to the interpretation of single amino acid polymorphisms within the framework of CATH and Gene3D.

Authors:  Jose M G Izarzugaza; Anja Baresic; Lisa E M McMillan; Corin Yeats; Andrew B Clegg; Christine A Orengo; Andrew C R Martin; Alfonso Valencia
Journal:  BMC Bioinformatics       Date:  2009-08-27       Impact factor: 3.169

9.  Sequence and structure signatures of cancer mutation hotspots in protein kinases.

Authors:  Anshuman Dixit; Lin Yi; Ragul Gowthaman; Ali Torkamani; Nicholas J Schork; Gennady M Verkhivker
Journal:  PLoS One       Date:  2009-10-16       Impact factor: 3.240

Review 10.  Getting personalized cancer genome analysis into the clinic: the challenges in bioinformatics.

Authors:  Alfonso Valencia; Manuel Hidalgo
Journal:  Genome Med       Date:  2012-07-30       Impact factor: 11.117

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