The team used a computational approach to organise the genes identified by transcriptional profiling into networks with central nodes. Comparison with a gene set describing metabolic syndrome revealed a high overlap between the central nodes of cancer and metabolic syndrome. Inflammatory factors such as IFN-γ, IL-1β, IL-6, and NF-κB as well as insulin and low-density lipoprotein (LDL) appeared as central nodes in cancer gene networks, suggesting the importance of inflammatory processes in both cancer and metabolic diseases and also a link between protein and lipid metabolism and cellular transformation. Lipid-related genes that had not previously been linked to cancer included OLR1, SNAP23, VAMP4, SCD1, SREBP1 and GALNT2.
The similarities between the pathways in cancer and metabolic diseases led the team to test whether drugs used to treat inflammation or aspects of metabolic disease might also affect cellular transformation and tumorigenicity. Four of the compounds that performed best in the cell experiments, metformin, sulindac, simvastatin, and cerulenin were tested for their ability to suppress tumour growth in nude mice: tumour growth was completely suppressed by metformin and sulindac and significantly delayed by cerulenin and simvastatin, suggesting that drugs designed to combat metabolic diseases may also be useful in treating some types of cancer.
The study is published in Cancer Cell.