Description
Genetically engineered mouse models of cancer represent valuable biological tools that can be used to filter genome-wide expression datasets generated from human prostate tumours, and identify gene expression alterations that are functionally important to cancer development and progression. In this study, we have generated RNASeq data from tumours arising in two established mouse models of prostate cancer, PB-Cre/PtenloxP/loxP and p53loxP/loxPRbloxP/loxP, and integrated this with published human prostate cancer expression data to pinpoint cancer-associated gene expression changes that are conserved between the two species. In order to identify potential therapeutic targets, we then filtered this information for genes that are either known or predicted to be druggable. Using this approach, we identified the serine/threonine kinase MELK as a potential therapeutic target in prostate cancer. MELK was overexpressed in both human and murine prostate cancers, and high expression of MELK was associated with biochemical recurrence in prostate cancer patients. Overall design: 92 Samples