Tumor Metabolic Features Identified by F-FDG PET Correlate with Gene Networks of Immune Cell Microenvironment in Head and Neck Cancer.

The importance of F-FDG PET in imaging head and neck squamous cell carcinoma (HNSCC) has grown in recent decades. Because PET has prognostic values, and provides functional and molecular information in HNSCC, the genetic and biologic backgrounds associated with PET parameters are of great interest. Here, as a systems biology approach, we aimed to investigate gene networks associated with tumor metabolism and their biologic function using RNA sequence and F-FDG PET data. Using RNA sequence data of HNSCC downloaded from The Cancer Genome Atlas data portal, we constructed a gene coexpression network. PET parameters including lesion-to-blood-pool ratio, metabolic tumor volume, and tumor lesion glycolysis were calculated. The Pearson 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. We identified 9 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 F-FDG uptake. The expression profiles of hub genes of the network were inversely correlated with F-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 ( = 0.022). We showed that a gene network that accounts for immune cell microenvironment was associated with F-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 features. In the future, PET parameters could be used as a surrogate marker of HNSCC for estimating molecular status of immune cell microenvironment.