Deciphering Signatures of Mutational Processes Operative in Human Cancer

The genome of a cancer cell carries somatic mutations that are the cumulative consequences of the DNA damage and repair processes operative during the cellular lineage between the fertilized egg and the cancer cell. Remarkably, these mutational processes are poorly characterized. Global sequencing i...

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Bibliographic Details
Published in:Cell reports (Cambridge) 2013-01, Vol.3 (1), p.246-259
Main Authors: Alexandrov, Ludmil B., Nik-Zainal, Serena, Wedge, David C., Campbell, Peter J., Stratton, Michael R.
Format: Article
Language:eng
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Summary:The genome of a cancer cell carries somatic mutations that are the cumulative consequences of the DNA damage and repair processes operative during the cellular lineage between the fertilized egg and the cancer cell. Remarkably, these mutational processes are poorly characterized. Global sequencing initiatives are yielding catalogs of somatic mutations from thousands of cancers, thus providing the unique opportunity to decipher the signatures of mutational processes operative in human cancer. However, until now there have been no theoretical models describing the signatures of mutational processes operative in cancer genomes and no systematic computational approaches are available to decipher these mutational signatures. Here, by modeling mutational processes as a blind source separation problem, we introduce a computational framework that effectively addresses these questions. Our approach provides a basis for characterizing mutational signatures from cancer-derived somatic mutational catalogs, paving the way to insights into the pathogenetic mechanism underlying all cancers. [Display omitted] ► Theoretical model describing mutational processes operative in cancer genomes ► Computational framework for deciphering signatures of mutational processes ► Extensive evaluation of the computational framework with simulated data ► Application to mutational catalogs of breast cancer genomes and exomes Stratton and colleagues provide a theoretical model and computational framework that bridge the gap between mutational catalogs derived from cancer genomes and the signatures of mutational processes contained in these catalogs. They extensively evaluate their framework with simulated and real data, demonstrating that it allows incorporation of a wide variety of different mutation types. The framework is robust to a large range of different parameters and applicable to mutational catalogs derived from genome and exome sequencing.
ISSN:2211-1247
2211-1247