Overexpression of AQP1 has recently been shown to be an independent prognostic factor in pleural mesothelioma favoring survival. This paper presents a data mining and bioinformatics approach towards the evaluation of the gene expression profile of AQP1 in malignant pleural mesothelioma and of AQP1 associated markers in the context of mesothelioma disease phenotype, CDKN2A gene deletion, sex and asbestos exposure. The data generated were thus again subjected to differential expression profile analysis. Here we report that AQP1 is overexpressed in epithelioid mesothelioma and identify TRIP6 and EFEMP2 as candidate genes for further investigation in mesothelioma.
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