Genetic and structural variation in the gastric cancer kinome revealed through targeted deep sequencing

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Abstract

Genetic alterations in kinases have been linked to multiple human pathologies. To explore the landscape of kinase genetic variation in gastric cancer (GC), we used targeted, paired-end deep sequencing to analyze 532 protein and phosphoinositide kinases in 14 GC cell lines. We identified 10,604 single-nucleotide variants (SNV) in kinase exons including greater than 300 novel nonsynonymous SNVs. Family-wise analysis of the nonsynonymous SNVs revealed a significant enrichment in mitogen-activated protein kinase (MAPK)-related genes (P < 0.01), suggesting a preferential involvement of this kinase family in GC. A potential antioncogenic role for MAP2K4, a gene exhibiting recurrent alterations in 2 lines, was functionally supported by siRNA knockdown and overexpression studies in wild-type and MAP2K4 variant lines. The deep sequencing data also revealed novel, large-scale structural rearrangement events involving kinases including gene fusions involving CDK12 and the ERBB2 receptor tyrosine kinase in MKN7 cells. Integrating SNVs and copy number alterations, we identified Hs746T as a cell line exhibiting both splice-site mutations and genomic amplification of MET, resulting in MET protein overexpression. When applied to primary GCs, we identified somatic mutations in 8 kinases, 4 of which were recurrently altered in both primary tumors and cell lines (MAP3K6, STK31, FER, and CDKL5). These results demonstrate that how targeted deep sequencing approaches can deliver unprecedented multilevel characterization of a medically and pharmacologically relevant gene family. The catalog of kinome genetic variants assembled here may broaden our knowledge on kinases and provide useful information on genetic alterations in GC. ©2010 AACR.

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Zang, Z. J., Ong, C. K., Cutcutache, I., Yu, W., Zhang, S. L., Huang, D., … Tan, P. (2011). Genetic and structural variation in the gastric cancer kinome revealed through targeted deep sequencing. Cancer Research, 71(1), 29–39. https://doi.org/10.1158/0008-5472.CAN-10-1749

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