Objective. This study is aimed at investigating the regulating mechanisms of the interferon regulatory factor (IRF) family genes in head and neck squamous cell carcinoma. Methods. Based on the HNSC data in the ‘The Cancer Genome Atlas (TCGA)’ database, the expression pattern of IRF family genes was investigated. The association of IRFs family genes and survival outcomes were analyzed by Kaplan–Meier plotter web portal. The relation of IRF genes and tumor stages was evaluated by using stage plots and based on GEPIA portal. 50 genes interacting with IRFs were identified using the NetworkAnalyst’s protein-protein interaction (PPI) network construction tool. The top 200 correlated genes with similar expression patterns in HNSC were obtained by the similar gene detection module of GEPIA. Furthermore, functional enrichment analysis was performed to determine the biological functions enriched by the interacting and correlated genes. The potential implication of IRFs in tumor immunity was investigated in terms of tumor-infiltrating immune cells, a pair of immune checkpoint genes (CD274 and PDCD1), and ESTIMATE-Stromal-Immune score. Results. The unpaired sample analysis shows that all of the IRF family genes were highly expressed in HNSC tumor samples compared to control samples. The survival analysis results showed that the overexpression of IRF1, IRF4, IRF5, IRF6, IRF8, and IRF9 was associated with better overall survival in HNSC, while the other IRFs genes (IRF2, IRF3. and IRF7) did not show prognostic values for overall survival outcome of HNSC. Four genes (STAT1, STAT2, FOXP3, and SPI1) were overlapping among 50 interacted genes in the PPI network and top 200 correlated genes identified by GEPIA. The 50 interacting genes in the PPI network and top 200 correlated genes were integrated into 246 genes. These 246 genes were found to be overrepresented in multiple KEGG pathways, e.g., Th17 cell differentiation, T cell receptor signaling pathway, cytokine-cytokine receptor interaction, natural killer (NK) cell-mediated cytotoxicity, FOXO signaling, PI3K-Akt signaling, and ErbB signaling. Most correlations between IRF gene members and TIICs were positive. The strongest positive correlation was identified between IRF8 and T cells ( r = 0.849 , p < 0.001 ). The majority of correlation between IRF family genes and ESTIMATE-Stromal-Immune score was found to be positive. The highest positive correlation was found to be between IRF8 and Immune score ( r = 0.874 , p = 1.09 E − 158 ). Most correlations between IRFs and two immunoinhibitor genes (CD274 and PDCD1) were positive. IRF1 and PDCD1 were found to show the highest positive correlation ( r = 0.764 , p < 2.2 e − 16 ). Conclusions. The current analysis showed IRFs were differentially expressed in HNSC, indicated significant prognostic values, were involved in tumor immunity-related signaling pathways, and significantly regulated tumor-infiltrating immune cells. IRF family genes could be potential therapeutic biomarkers in targeting tumor immunity of head and neck cancer.
Objective To identify the genetic mechanisms underlying lipid metabolism-mediated tumor immunity in head and neck squamous carcinoma (HNSC). Materials and methods RNA sequencing data and clinical characteristics of HNSC patients were procured from The Cancer Genome Atlas (TCGA) database. Lipid metabolism-related genes were collected from KEGG and MSigDB databases. Immune cells and immune-related genes were obtained from the TISIDB database. The differentially expressed genes (DEGs) in HNSC were identified and weighted correlation network analysis (WGCNA) was performed to identify the significant gene modules. Lasso regression analysis was performed to identify hub genes. The differential gene expression pattern, diagnostic values, relationships with clinical features, prognostic values, relationships with tumor mutation burden (TMB), and signaling pathways involved, were each investigated. Results One thousand six hundred sixty-eight DEGs were identified as dysregulated between HNSC tumor samples and healthy control head and neck samples. WGCNA analysis and Lasso regression analysis identified 8 hub genes, including 3 immune-related genes (PLA2G2D, TNFAIP8L2 and CYP27A1) and 5 lipid metabolism-related genes (FOXP3, IL21R, ITGAL, TRAF1 and WIPF1). Except CYP27A1, the other hub genes were upregulated in HNSC as compared with healthy control samples, and a low expression of these hub genes indicated a higher risk of death in HNSC. Except PLA2G2D, all other hub genes were significantly and negatively related with TMB in HNSC. The hub genes were implicated in several immune-related signaling pathways including T cell receptor signaling, Th17 cell differentiation, and natural killer (NK) cell mediated cytotoxicity. Conclusion Three immune genes (PLA2G2D, TNFAIP8L2, and CYP27A1) and immune-related pathways (T cell receptor signaling, Th17 cell differentiation, and natural killer (NK) cell mediated cytotoxicity) were predicted to play significant roles in the lipid metabolism-mediated tumor immunity in HNSC.
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