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Somatic cell genetic alterations are a hallmark of tumor development and progression. Although various technologies have been developed and utilized to identify genetic aberrations, identifying genetic translocations at the chromosomal level is still a challenging task. High density SNP microarrays are useful to measure DNA copy number variation (CNV) across the genome. Utilizing SNP array data of cancer cell lines and patient samples, we evaluated the CNV and copy number breakpoints for several known fusion genes implicated in tumorigenesis. This analysis demonstrated the potential utility of SNP array data for the prediction of genetic aberrations via translocations based on identifying copy number breakpoints within the target genes. Genome-wide analysis was also performed to identify genes harboring copy number breakpoints across 820 cancer cell lines. Candidate oncogenes were identified that are linked to potential translocations in specific cancer cell lines.
Pubmed ID: 22259228
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Functional genomics data repository supporting MIAME-compliant data submissions. Includes microarray-based experiments measuring the abundance of mRNA, genomic DNA, and protein molecules, as well as non-array-based technologies such as serial analysis of gene expression (SAGE) and mass spectrometry proteomic technology. Array- and sequence-based data are accepted. Collection of curated gene expression DataSets, as well as original Series and Platform records. The database can be searched using keywords, organism, DataSet type and authors. DataSet records contain additional resources including cluster tools and differential expression queries.
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