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Journal Article

The structural impact of cancer-associated missense mutations in oncogenes and tumor suppressors

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Stehr,  H.
Independent Junior Research Groups (OWL), Max Planck Institute for Molecular Genetics, Max Planck Society;

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Duarte,  J. M.
Independent Junior Research Groups (OWL), Max Planck Institute for Molecular Genetics, Max Planck Society;

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Wierling,  C.
Systems Biology (Christoph Wierling), Dept. of Vertebrate Genomics (Head: Hans Lehrach), Max Planck Institute for Molecular Genetics, Max Planck Society;

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Lehrach,  H.
Dept. of Vertebrate Genomics (Head: Hans Lehrach), Max Planck Institute for Molecular Genetics, Max Planck Society;

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Lappe,  M.
Independent Junior Research Groups (OWL), Max Planck Institute for Molecular Genetics, Max Planck Society;

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Citation

Stehr, H., Jang, S. H., Duarte, J. M., Wierling, C., Lehrach, H., Lappe, M., et al. (2011). The structural impact of cancer-associated missense mutations in oncogenes and tumor suppressors. Molecular Cancer, 10, 54. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/21575214 http://www.molecular-cancer.com/content/pdf/1476-4598-10-54.pdf.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0010-7902-2
Abstract
BACKGROUND: Current large-scale cancer sequencing projects have identified large numbers of somatic mutations covering an increasing number of different cancer tissues and patients. However, the characterization of these mutations at the structural and functional level remains a challenge. RESULTS: We present results from an analysis of the structural impact of frequent missense cancer mutations using an automated method. We find that inactivation of tumor suppressors in cancer correlates frequently with destabilizing mutations preferably in the core of the protein, while enhanced activity of oncogenes is often linked to specific mutations at functional sites. Furthermore, our results show that this alteration of oncogenic activity is often associated with mutations at ATP or GTP binding sites. CONCLUSIONS: With our findings we can confirm and statistically validate the hypotheses for the gain-of-function and loss-of-function mechanisms of oncogenes and tumor suppressors, respectively. We show that the distinct mutational patterns can potentially be used to pre-classify newly identified cancer-associated genes with yet unknown function.