Over seven years ago, in 2005, Tomlins and colleagues reported an interesting discovery of gene
fusions in PC that is one of the most prevalent epithelial malignancies in the world. By analyzing
DNA microarray data with a specific unconventional bioinformatics approach called the cancer
outlier profile analysis (COPA) algorithm (described in Tomlins et al. 2005), they discovered
recurrent TMPRSS2:ETS (E-twenty six) translocations in PC. They performed COPA analysis in
Oncomine 3.0 with 132 different gene expression data sets (10,486 microarray experiments). Instead
of using cancer samples and analyzing them with common analytical methods to search for
activation of genes (e.g. t test) they used COPA for the search of genes that have marked
overexpression profiles (outlier profiles) in specific cancer types. Furthermore, Tomlins and coworkers
found that ERG (21q22.3) and ETV1 (7p21.2), which encode ETS oncogenic transcription
factors, had the strongest outlier profiles in several data sets observed in PC and the respective genes
were among the top 10 outlier genes in six different PC profiling studies.
Over seven years ago, in 2005, Tomlins and colleagues reported an interesting discovery of genefusions in PC that is one of the most prevalent epithelial malignancies in the world. By analyzingDNA microarray data with a specific unconventional bioinformatics approach called the canceroutlier profile analysis (COPA) algorithm (described in Tomlins et al. 2005), they discoveredrecurrent TMPRSS2:ETS (E-twenty six) translocations in PC. They performed COPA analysis inOncomine 3.0 with 132 different gene expression data sets (10,486 microarray experiments). Insteadof using cancer samples and analyzing them with common analytical methods to search foractivation of genes (e.g. t test) they used COPA for the search of genes that have markedoverexpression profiles (outlier profiles) in specific cancer types. Furthermore, Tomlins and coworkersfound that ERG (21q22.3) and ETV1 (7p21.2), which encode ETS oncogenic transcriptionfactors, had the strongest outlier profiles in several data sets observed in PC and the respective geneswere among the top 10 outlier genes in six different PC profiling studies.
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