Dataset Information

Complex landscapes of somatic rearrangement in human breast cancer genomes.

ABSTRACT: Multiple somatic rearrangements are often found in cancer genomes; however, the underlying processes of rearrangement and their contribution to cancer development are poorly characterized. Here we use a paired-end sequencing strategy to identify somatic rearrangements in breast cancer genomes. There are more rearrangements in some breast cancers than previously appreciated. Rearrangements are more frequent over gene footprints and most are intrachromosomal. Multiple rearrangement architectures are present, but tandem duplications are particularly common in some cancers, perhaps reflecting a specific defect in DNA maintenance. Short overlapping sequences at most rearrangement junctions indicate that these have been mediated by non-homologous end-joining DNA repair, although varying sequence patterns indicate that multiple processes of this type are operative. Several expressed in-frame fusion genes were identified but none was recurrent. The study provides a new perspective on cancer genomes, highlighting the diversity of somatic rearrangements and their potential contribution to cancer development.

SUBMITTER: Stephens PJ

PROVIDER: S-EPMC3398135 | biostudies-literature | 2009 Dec

REPOSITORIES: biostudies-literature

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Complex landscapes of somatic rearrangement in human breast cancer genomes.

Stephens Philip J PJ McBride David J DJ Lin Meng-Lay ML Varela Ignacio I Pleasance Erin D ED Simpson Jared T JT Stebbings Lucy A LA Leroy Catherine C Edkins Sarah S Mudie Laura J LJ Greenman Chris D CD Jia Mingming M Latimer Calli C Teague Jon W JW Lau King Wai KW Burton John J Quail Michael A MA Swerdlow Harold H Churcher Carol C Natrajan Rachael R Sieuwerts Anieta M AM Martens John W M JW Silver Daniel P DP Langerød Anita A Russnes Hege E G HE Foekens John A JA Reis-Filho Jorge S JS van 't Veer Laura L Richardson Andrea L AL Børresen-Dale Anne-Lise AL Campbell Peter J PJ Futreal P Andrew PA Stratton Michael R MR

Nature 20091201 7276

Multiple somatic rearrangements are often found in cancer genomes; however, the underlying processes of rearrangement and their contribution to cancer development are poorly characterized. Here we use a paired-end sequencing strategy to identify somatic rearrangements in breast cancer genomes. There are more rearrangements in some breast cancers than previously appreciated. Rearrangements are more frequent over gene footprints and most are intrachromosomal. Multiple rearrangement architectures a ...[more]

PMID: 20033038

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Project description:BackgroundLarge-scale tumor sequencing projects are now underway to identify genetic mutations that drive tumor initiation and development. Most studies take a gene-based approach to identifying driver mutations, highlighting genes mutated in a large percentage of tumor samples as those likely to contain driver mutations. However, this gene-based approach usually does not consider the position of the mutation within the gene or the functional context the position of the mutation provides. Here we introduce a novel method for mapping mutations to distinct protein domains, not just individual genes, in which they occur, thus providing the functional context for how the mutation contributes to disease. Furthermore, aggregating mutations from all genes containing a specific protein domain enables the identification of mutations that are rare at the gene level, but that occur frequently within the specified domain. These highly mutated domains potentially reveal disruptions of protein function necessary for cancer development.ResultsWe mapped somatic mutations from the protein coding regions of 100 colon adenocarcinoma tumor samples to the genes and protein domains in which they occurred, and constructed topographical maps to depict the "mutational landscapes" of gene and domain mutation frequencies. We found significant mutation frequency in a number of genes previously known to be somatically mutated in colon cancer patients including APC, TP53 and KRAS. In addition, we found significant mutation frequency within specific domains located in these genes, as well as within other domains contained in genes having low mutation frequencies. These domain "peaks" were enriched with functions important to cancer development including kinase activity, DNA binding and repair, and signal transduction.ConclusionsUsing our method to create the domain landscapes of mutations in colon cancer, we were able to identify somatic mutations with high potential to drive cancer development. Interestingly, the majority of the genes involved have a low mutation frequency. Therefore, the method shows good potential for identifying rare driver mutations in current, large-scale tumor sequencing projects. In addition, mapping mutations to specific domains provides the necessary functional context for understanding how the mutations contribute to the disease, and may reveal novel or more refined gene and domain target regions for drug development.

Dataset Information

Complex landscapes of somatic rearrangement in human breast cancer genomes.

Publications

Complex landscapes of somatic rearrangement in human breast cancer genomes.

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