Abstract
Tomlins et al. [6] used a novel bioinformatic approach to search for genes that are expressed more frequently in prostate cancer than in normal tissue. Their ‘cancer outlier profile analysis’ was aimed at accentuating and identifying outlier profiles on the basis of the median gene expression profile and median absolute deviation of the gene expression profile. The search concentrated on genes known to cause cancer and led to the identification of genes encoding two ETS transcription factors, ERG and ETV1, as frequent outliers. The authors argued that enhanced expression of both genes would be redundant. This hypothesis was confirmed by showing that increased expression of the two transcription factors is mutually exclusive.
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