Comprehensive assessment of cancer missense mutation clustering in protein structures
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- Atanas Kamburov
- Department of Pathology and Cancer Center, Massachusetts General Hospital, Boston, MA 02114;
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- Michael S. Lawrence
- Broad Institute of MIT and Harvard, Cambridge, MA 02142;
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- Paz Polak
- Department of Pathology and Cancer Center, Massachusetts General Hospital, Boston, MA 02114;
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- Ignaty Leshchiner
- Broad Institute of MIT and Harvard, Cambridge, MA 02142;
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- Kasper Lage
- Harvard Medical School, Boston, MA 02115;
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- Todd R. Golub
- Broad Institute of MIT and Harvard, Cambridge, MA 02142;
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- Eric S. Lander
- Broad Institute of MIT and Harvard, Cambridge, MA 02142;
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- Gad Getz
- Department of Pathology and Cancer Center, Massachusetts General Hospital, Boston, MA 02114;
書誌事項
- 公開日
- 2015-09-21
- 権利情報
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- http://www.pnas.org/site/misc/userlicense.xhtml
- DOI
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- 10.1073/pnas.1516373112
- 公開者
- Proceedings of the National Academy of Sciences
この論文をさがす
説明
<jats:title>Significance</jats:title><jats:p>Tumor sequencing efforts have enabled the identification of cancer genes based on an excess of mutations in the gene or clustering of mutations along the (one-dimensional) DNA sequence of the gene. Here, we show that this approach can be extended to identify cancer genes based on clustering of mutations relative to the 3D structure of the protein product. By analyzing the PanCancer compendium of somatic mutations in nearly 5,000 tumors, we identified known cancer genes and previously unidentified candidates based on clustering of missense mutations in protein structures or at interfaces with binding partners. In addition, we found that 3D clustering is present in both oncoproteins and tumor suppressors—contrary to the view that such clustering is a hallmark of oncoproteins.</jats:p>
収録刊行物
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- Proceedings of the National Academy of Sciences
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Proceedings of the National Academy of Sciences 112 (40), E5486-, 2015-09-21
Proceedings of the National Academy of Sciences