Investigation of an FGFR-Signaling-Related Prognostic Model and Immune Landscape in Head and Neck Squamous Cell Carcinoma - Chen, Qi; Chu, Ling; Li, Xinyu; Li, Hao; Zhang, Ying; Cao, Qingtai; Zhuang, Quan (Frontiers in Cell and Developmental Biology, 2022)
Background There is accumulating evidence on the clinical importance of fibroblast growth factor receptor (FGFR) signal, hypoxia and glycolysis in the immune microenvironment of head and neck squamous cell carcinoma (HNSCC), yet reliable prognostic signatures based on combination of fibrosis signal, hypoxia and glycolysis have not been systematically investigated. Herein, we are committed to establish a fibrosis-hypoxia-glycolysis-related prediction model for the prognosis and related immune infiltration of HNSCC. Methods Fibrotic signal status was estimated with microarray data of a discovery cohort from the TCGA database using UMAP algorithm. Hypoxia, glycolysis and immune-cell infiltration scores were imputed using ssGSEA algorithm. The Cox regression with the LASSO method was applied to define prognostic genes and develop a fibrosis-hypoxia-glycolysis-related gene signature. Immunohistochemistry (IHC) was conducted to identify the expression of specific genes in prognostic model. Protein expression of several signature genes were evaluated in HPA. An independent cohort from GEO database was used for external validation. Another scRNA-seq dataset was used to clarify the related immune infiltration of HNSCC. Results Six genes, including AREG, THBS1, SEMA3C, ANO1, IGHG2, EPHX3, were identified to construct a prognostic model for risk stratification, which was mostly validated in the independent cohort. Multivariate analysis revealed that risk score calculated by our prognostic model were identified as an independent adverse prognostic factor (p < 0.001). Activated B cell, immature B cell, activated CD4+ T cell, activated CD8+ T cell, effector memory CD8+ T cell, MDSC and mast cell were identified as key immune cells between high-risk and low-risk groups. Immunohistochemical results showed that the expression of SEMA3C, IGHG2 slightly higher in HNSCC tissue than normal head and neck squamous cell tissue. THBS1, ANO1 and EPHX3 were verified by immunohistochemical in HPA. By using single-cell analysis, FGFR-related genes and highly expressed DEGs in low-survival patients were more active in monocytes than in other immune cells. Conclusion Fibrosis-hypoxia-glycolysis-related prediction model provides risk estimation for better prognoses to patients diagnosed with HNSCC.