Abstract
Protein kinases are key regulators of various biological processes, such as control of cell growth, metabolism, differentiation and apoptosis. Therefore, protein kinases have been an important class of targets for anticancer drugs. Health-related disparities such as differential drug response have been observed between human populations. A survey of the human kinases and their ligand genes for those containing population-specific genetic variants could provide new insights into the mechanisms of these health disparities and suggest novel targets for ethnicity-specific personalized medicine. Using the International HapMap Project genotypic data on single-nucleotide polymorphisms (SNPs), the protein kinase complement of the human genome (kinome) and some experimentally verified ligand genes were scanned for the existence of population-specific SNPs (eSNPs). In general, protein kinases were found to contain a much higher proportion of eSNPs than the whole genome background, indicating a stronger pressure for adaptation in individual populations. In contrast, the proportion of ligand genes containing eSNPs was not different from that of the whole genome background. Although with some important limitations, our results suggest that human kinases are more likely to be under recent positive selection than ligands. Our findings suggest that the health-related disparities associated with kinase signaling pathways are more likely to be driven by the genetic variation in the kinase genes than their cognate ligands. Illustrating the role of molecular evolution in the genetic variation of the human kinome could provide a promising route to understand the ethnic differences in cancer and facilitate the realization of ethnicity-based individualized medicine.
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References
Hunter, T. Signaling—2000 and beyond. Cell 100, 113–127 (2000).
Manning, G., Whyte, D. B., Martinez, R., Hunter, T. & Sudarsanam, S. The protein kinase complement of the human genome. Science 298, 1912–1934 (2002).
Fabbro, D., Ruetz, S., Buchdunger, E., Cowan-Jacob, S. W., Fendrich, G., Liebetanz, J. et al. Protein kinases as targets for anticancer agents: from inhibitors to useful drugs. Pharmacol. Ther. 93, 79–98 (2002).
Dassonville, O., Bozec, A., Fischel, J. L. & Milano, G. EGFR targeting therapies: monoclonal antibodies versus tyrosine kinase inhibitors. Similarities and differences. Crit. Rev. Oncol. Hematol. 62, 53–61 (2007).
Harari, P. M., Allen, G. W. & Bonner, J. A. Biology of interactions: antiepidermal growth factor receptor agents. J. Clin. Oncol. 25, 4057–4065 (2007).
Ratain, M. J., Eisen, T., Stadler, W. M., Flaherty, K. T., Kaye, S. B., Rosner, G. L. et al. Phase II placebo-controlled randomized discontinuation trial of sorafenib in patients with metastatic renal cell carcinoma. J. Clin. Oncol. 24, 2505–2512 (2006).
Escudier, B., Eisen, T., Stadler, W. M., Szczylik, C., Oudard, S., Siebels, M. et al. Sorafenib in advanced clear-cell renal-cell carcinoma. N. Engl. J. Med. 356, 125–134 (2007).
Cohen, P. Protein kinases—the major drug targets of the twenty-first century? Nat. Rev. Drug. Discov. 1, 309–315 (2002).
Fejerman, L. & Ziv, E. Population differences in breast cancer severity. Pharmacogenomics 9, 323–333 (2008).
Taron, M., Ichinose, Y., Rosell, R., Mok, T., Massuti, B., Zamora, L. et al. Activating mutations in the tyrosine kinase domain of the epidermal growth factor receptor are associated with improved survival in gefitinib-treated chemorefractory lung adenocarcinomas. Clin. Cancer. Res. 11, 5878–5885 (2005).
Liu, W., Wu, X., Zhang, W., Montenegro, R. C., Fackenthal, D. L., Spitz, J. A. et al. Relationship of EGFR mutations, expression, amplification, and polymorphisms to epidermal growth factor receptor inhibitors in the NCI60 cell lines. Clin. Cancer. Res. 13, 6788–6795 (2007).
Gomase, V. S. & Tagore, S. Kinomics. Curr. Drug. Metab. 9, 255–258 (2008).
The International HapMap Consortium. The International HapMap Project. Nature 426, 789–796 (2003).
The International HapMap Consortium. A haplotype map of the human genome. Nature 437, 1299–1320 (2005).
Frazer, K. A., Ballinger, D. G., Cox, D. R., Hinds, D. A., Stuve, L. L., Gibbs, R. A. et al. A second generation human haplotype map of over 3.1 million SNPs. Nature 449, 851–861 (2007).
Zhang, W., Ratain, M. J. & Dolan, M. E. The HapMap resource is providing new insights into ourselves and its application to pharmacogenomics. Bioinform. Biol. Insights 2, 15–23 (2008).
Voight, B. F., Kudaravalli, S., Wen, X. & Pritchard, J. K. A map of recent positive selection in the human genome. PLoS Biol. 4, e72 (2006).
Zhang, W. & Dolan, M. E. Exploring the evolutionary history of the differentially expressed genes between human populations: action of recent positive selection. Evol. Bioinform. 4, 171–179 (2008).
Graeber, T. G. & Eisenberg, D. Bioinformatic identification of potential autocrine signaling loops in cancers from gene expression profiles. Nat. Genet. 29, 295–300 (2001).
Salwinski, L., Miller, C. S., Smith, A. J., Pettit, F. K., Bowie, J. U. & Eisenberg, D. The Database of Interacting Proteins: 2004 update. Nucleic Acids Res. 32, D449–D451 (2004).
Park, J., Hwang, S., Lee, Y. S., Kim, S. C. & Lee, D. SNP@Ethnos: a database of ethnically variant single-nucleotide polymorphisms. Nucleic Acids Res. 35, D711–D715 (2007).
Tibshirani, R., Hastie, T., Narasimhan, B. & Chu, G. Diagnosis of multiple cancer types by shrunken centroids of gene expression. Proc. Natl Acad. Sci. USA 99, 6567–6572 (2002).
Benjamini, Y. & Hochberg, Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. B (57), 289–300 (1995).
Dausset, J., Cann, H., Cohen, D., Lathrop, M., Lalouel, J. M. & White, R. Centre d’etude du polymorphisme humain (CEPH): collaborative genetic mapping of the human genome. Genomics 6, 575–577 (1990).
Zhang, W. & Dolan, M. E. On the challenges of the HapMap resource. Bioinformation 2, 238–239 (2008).
The 1000 Genomes Project Meeting Report: a workshop to plan a deep catalog of human genetic variation (http://www.1000genomes.org) (2007).
Mardis, E. R. The impact of next-generation sequencing technology on genetics. Trends Genet. 24, 133–141 (2008).
Mardis, E. R. Next-generation DNA sequencing methods. Annu. Rev. Genomics Hum. Genet. 9, 387–402 (2008).
Zhang, W. & Dolan, M. E. Beyond the HapMap genotypic data: prospects of deep resequencing projects. Curr. Bioinformatics 3, 178–182 (2008).
Acknowledgements
This Pharmacogenetics of Anticancer Agents Research (PAAR) Group (http://www.pharmacogenetics.org/) study was supported by the NIH/NIGMS grant U01GM61393. Data will be deposited into PharmGKB (supported by the NIH/NIGMS Pharmacogenetics Research Network and Database grant U01GM61374, http://www.pharmgkb.org/). We are grateful to Drs Anna Di Rienzo, Chang Sun and Wanqing Liu for their helpful discussions.
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Zhang, W., Catenacci, D., Duan, S. et al. A survey of the population genetic variation in the human kinome. J Hum Genet 54, 488–492 (2009). https://doi.org/10.1038/jhg.2009.72
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DOI: https://doi.org/10.1038/jhg.2009.72
