Coping with Nose-bleeds

Abstract

The importance of FDG PET in imaging head and neck squamous cell carcinoma (HNSCC) has grown in recent decades. Since PET has prognostic values, and provides functional and molecular information in HNSCC, the genetic and biologic backgrounds associated with PET parameters are of great interests. Here, as a systems biology approach, we aimed to investigate gene networks associated with tumor metabolism and their biological function using RNA sequence and FDG PET data. <b>Methods:</b> Using RNA sequence data of HNSCC downloaded from TCGA data portal, we constructed gene coexpression network. PET parameters including lesion-to-blood pool ratio, metabolic tumor volume and tumor lesion glycolysis were calculated. The Pearson’s correlation test was performed between module eigengene - the first principal component of modules’ expression profile - and the PET parameters. The significantly correlated module was functionally annotated with gene ontology terms and its hub genes were identified. Survival analysis of the significantly correlated module was performed. <b>Results:</b> We identified nine coexpression network modules from the preprocessed RNA sequence data. A network module was significantly correlated with total lesion glycolysis as well as maximum and mean FDG uptake. Expression profiles of hub genes of the network was inversely correlated with FDG uptake. The significantly annotated gene ontology terms of the module were associated with immune cell activation and aggregation. The module demonstrated significant association with overall survival, and the group with higher module eigengene showed better survival than the other groups with statistical significance (<i>P</i> = 0.022) <b>Conclusion:</b> We showed that a gene network which accounts for immune cell microenvironment was associated with FDG uptake as well as prognosis in HNSCC. Our result supports the idea that competition for glucose between cancer cell and immune cell plays an important role in cancer progression associated with hypermetabolic feature. In the future, PET parameters could be used as a surrogate marker of HNSCC for estimating molecular status of immune cell microenvironment.