Emerging landscape of oncogenic signatures across human cancers

Chris Sander and colleagues have extracted significant functional events from 12 tumor types. Tumors can be classified as being driven largely by either mutation or copy number changes, and, within this division, subclasses of cross-tissue patterns of events are discerned that suggest sets of combin...

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Veröffentlicht in:Nature genetics 2013-10, Vol.45 (10), p.1127-1133
Hauptverfasser: Ciriello, Giovanni, Miller, Martin L, Aksoy, Bülent Arman, Senbabaoglu, Yasin, Schultz, Nikolaus, Sander, Chris
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Sprache:eng
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Zusammenfassung:Chris Sander and colleagues have extracted significant functional events from 12 tumor types. Tumors can be classified as being driven largely by either mutation or copy number changes, and, within this division, subclasses of cross-tissue patterns of events are discerned that suggest sets of combinatorial therapies. Cancer therapy is challenged by the diversity of molecular implementations of oncogenic processes and by the resulting variation in therapeutic responses. Projects such as The Cancer Genome Atlas (TCGA) provide molecular tumor maps in unprecedented detail. The interpretation of these maps remains a major challenge. Here we distilled thousands of genetic and epigenetic features altered in cancers to ∼500 selected functional events (SFEs). Using this simplified description, we derived a hierarchical classification of 3,299 TCGA tumors from 12 cancer types. The top classes are dominated by either mutations (M class) or copy number changes (C class). This distinction is clearest at the extremes of genomic instability, indicating the presence of different oncogenic processes. The full hierarchy shows functional event patterns characteristic of multiple cross-tissue groups of tumors, termed oncogenic signature classes. Targetable functional events in a tumor class are suggestive of class-specific combination therapy. These results may assist in the definition of clinical trials to match actionable oncogenic signatures with personalized therapies.
ISSN:1061-4036
1546-1718
DOI:10.1038/ng.2762