high-throughput gene mutation profiling

Definition: Somatic mutation theory of cancer is a theory on the pathogenesis of cancer that essentially postulates that cancer in somatic cells arises from mutations. More recently, the theory has been adapted to specifically implicate mutations in oncogenes or tumour suppressor genes.

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.

Mutational signature

Somatic mutation patterns in tumor cells can serve as a source of information on the processes that have gone awry in cancers and, in some cases, the environmental exposures to blame for these genetic glitches. Though, routinely finding such mutational signatures has been tricky.

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.

By modeling mutational processes as a blind source separation problem, it has been introduced a computational framework that effectively addresses these questions. (DOI:10.1016/j.celrep.2012.12.008 )

This 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.

In a study, the Sanger Institute’s Michael Stratton and colleagues presented their computational strategy for sifting through the sets of base substitutions, insertions and deletions, rearrangements, and copy-number shifts found within the growing collection of cancer genome sequences to identify potentially informative mutational signatures. (DOI:10.1016/j.celrep.2012.12.008 )

After applying this approach to simulated cancer sequence data, the researchers demonstrated its feasibility for finding mutational signatures in breast cancer using data from whole-genome and exome sequencing studies of the disease.

This approach provides a basis for characterizing mutational signatures from cancer-derived somatic mutation catalogs, paving the way to insights into the pathogenetic mechanisms underlying all cancers.

Types

 cancer driver mutations
 cancer passenger mutations

See also

 oncogenesis/tumorigenesis
 cancer-associated somatic mutations
 DNA mutations/genic mutations
 high-throughput oncogene mutation profiling

Reviews

 Futreal PA. Backseat drivers take the wheel. Cancer Cell. 2007 Dec;12(6):493-4. PMID: 18068625

References

 Deciphering Signatures of Mutational Processes Operative in Human Cancer. Cell Reports, 10 January 2013. DOI:10.1016/j.celrep.2012.12.008

 15763568, 15661527, 16869737, 16140923, 15608510

 Greenman C, Stephens P, Smith R, Dalgliesh GL et al. Patterns of somatic mutation in human cancer genomes. Nature. 2007 Mar 8;446(7132):153-8. PMID: 17344846

 Dalgliesh GL, Futreal PA. The continuing search for cancer-causing somatic mutations. Breast Cancer Res. 2007;9(1):101. PMID: 17319975

 Futreal PA, Wooster R, Stratton MR. Somatic mutations in human cancer: insights from resequencing the protein kinase gene family. Cold Spring Harb Symp Quant Biol. 2005;70:43-9. PMID: 16869737

 Greenman C, Wooster R, Futreal PA, Stratton MR, Easton DF.Statistical analysis of pathogenicity of somatic mutations in cancer. Genetics. 2006 Aug;173(4):2187-98. PMID: 16783027

 Davies H, Hunter C, Smith R, Stephens P et al. Somatic mutations of the protein kinase gene family in human lung cancer. Cancer Res. 2005 Sep 1;65(17):7591-5. PMID: 16140923

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 Ley TJ, Minx PJ, Walter MJ, Ries RE, Sun H, McLellan M, DiPersio JF, Link DC, Tomasson MH, Graubert TA, McLeod H, Khoury H, Watson M, Shannon W, Trinkaus K, Heath S, Vardiman JW, Caligiuri MA, Bloomfield CD, Milbrandt JD, Mardis ER, Wilson RK. A pilot study of high-throughput, sequence-based mutational profiling of primary human acute myeloid leukemia cell genomes. Proc Natl Acad Sci U S A. 2003 Nov 25;100(24):14275-80. PMID: 14614138