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University of Cambridge > Talks.cam > CRI Reading Group on Cancer Systems Biology > SNP arrays in heterogeneous tissue: highly accurate collection of both germline and somatic genetic information from unpaired single tumor samples.
SNP arrays in heterogeneous tissue: highly accurate collection of both germline and somatic genetic information from unpaired single tumor samples.Add to your list(s) Download to your calendar using vCal
If you have a question about this talk, please contact Stefan Gräf. http://www.ncbi.nlm.nih.gov/pubmed/18355774 Am J Hum Genet. 2008 Apr;82(4):903-15. Epub 2008 Mar 20. SNP arrays in heterogeneous tissue: highly accurate collection of both germline and somatic genetic information from unpaired single tumor samples. Assié G, LaFramboise T, Platzer P, Bertherat J, Stratakis CA, Eng C. Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, Ohio 44195, USA . SNP arrays provide reliable genotypes and can detect chromosomal aberrations at a high resolution. However, tissue heterogeneity is currently a major limitation for somatic tissue analysis. We have developed SOMATI Cs, an original program for accurate analysis of heterogeneous tissue samples. Fifty-four samples (42 tumors and 12 normal tissues) were processed through Illumina Beadarrays and then analyzed with SOMATI Cs. We demonstrate that tissue heterogeneity-related limitations not only can be overcome but can also be turned into an advantage. First, admixture of normal cells with tumor can be used as an internal reference, thereby enabling highly sensitive detection of somatic deletions without having corresponding normal tissue. Second, the presence of normal cells allows for discrimination of somatic from germline aberrations, and the proportion of cells in the tissue sample that are harboring the somatic events can be assessed. Third, relatively early versus late somatic events can also be distinguished, assuming that late events occur only in subsets of cancer cells. Finally, admixture by normal cells allows inference of germline genotypes from a cancer sample. All this information can be obtained from any cancer sample containing a proportion of 40-75% of cancer cells. SOMATI Cs is a ready-to-use open-source program that integrates all of these features into a simple format, comprehensively describing each chromosomal event. This talk is part of the CRI Reading Group on Cancer Systems Biology series. This talk is included in these lists:Note that ex-directory lists are not shown. |
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