Description
While early stages of clear cell renal cell carcinoma (ccRCC) are curable, survival outcome for metastatic ccRCC remains poor. The purpose of the current study was to apply a new individualized bioinformatics analysis (IBA) strategy to these transcriptome data in conjunction with Gene Set Enrichment Analysis of the Connectivity Map (C-MAP) database to identify and reposition FDA-approved drugs for anti-cancer therapy. We demonstrated that one of the drugs predicted to revert the RCC gene signature towards normal kidney, pentamidine, is effective against RCC cells in culture and in a RCC xenograft model. Most importantly, pentamidine slows tumor growth in the 786-O human ccRCC xenograft mouse model. To determine which genes are regulated by pentamidine in a human RCC cell line, 786-O, we treated these cells with pentamidine and performed transcriptional profiling analysis.