Pan-cancer analysis of transcriptional metabolic dysregulation using The Cancer Genome Atlas

• DOI: 10.1038/s41467-018-07232-8
• Publication Date: 2018-12-10T17:07:12Z
• Authors: S. R. Rosario; M. D. Long; H. C. Affronti; A. M. Rowsam; K. H. Eng; D. J. Smiraglia
• Keywords: Metabolic pathway

Understanding metabolic dysregulation in different disease settings is vital for the safe and effective incorporation of metabolism-targeted therapeutics clinic. Here, using transcriptomic data 10,704 tumor normal samples from The Cancer Genome Atlas, across 26 sites, we present a novel bioinformatics pipeline that distinguishes tissues, based on differential gene expression 114 pathways. We confirm pathway separate patient populations, demonstrating robustness our approach. Bootstrapping simulations were then applied to assess biological significance these alterations. provide distinct examples types analysis can be accomplished with this tool understand cancer specific dysregulation, highlighting pathways interest, patterns flux, both common rare sites. Further, show Master Metabolic Transcriptional Regulators explain why differences exist, segregate predict responders therapeutics.