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Prediction of Cancer Driver Mutations in Protein Kinases

¹ Graduate Program in Biomedical Sciences and ² Center for Human Genetics and Genomics, University of California, San Diego, San Diego, California and ³ Scripps Genomic Medicine and The Scripps Research Institute, La Jolla, California

Requests for reprints: Nicholas J. Schork, Scripps Genomic Medicine, The Scripps Research Institute, MEM-275A, 10550 North Torrey Pines Road, La Jolla, CA 92037. Phone: 858-784-2308; Fax: 858-784-2910; E-mail: nschork{at}scripps.edu.

Key Words: Drivers • Passengers • Protein Kinases • Prediction • Somatic Mutations

A large number of somatic mutations accumulate during the process of tumorigenesis. A subset of these mutations contribute to tumor progression (known as "driver" mutations) whereas the majority of these mutations are effectively neutral (known as "passenger" mutations). The ability to differentiate between drivers and passengers will be critical to the success of upcoming large-scale cancer DNA resequencing projects. Here we show a method capable of discriminating between drivers and passengers in the most frequently cancer-associated protein family, protein kinases. We apply this method to multiple cancer data sets, validating its accuracy by showing that it is capable of identifying known drivers, has excellent agreement with previous statistical estimates of the frequency of drivers, and provides strong evidence that predicted drivers are under positive selection by various sequence and structural analyses. Furthermore, we identify particular positions in protein kinases that seem to play a role in oncogenesis. Finally, we provide a ranked list of candidate driver mutations. [Cancer Res 2008;68(6):1675–82]

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