Immune Cluster and PPI Network Analyses Identified CXCR3 as a Key Node of Immunoregulation in Head and Neck Cancer

Abstract

The tumor microenvironment (TME) is significantly associated with clinical outcomes and therapeutic efficacy. However, the landscape of the head and neck cancer (HNC) microenvironment is not fully understood. Therefore, we divided HNCs into three classes according to differences in the TME to determine effective personalized treatments. We explored the immune landscape of head and neck cancer by analysing the gene expression profile of 501 cases from the Cancer Genome Atlas (TCGA) data portal and validated our findings in 270 cases from the Gene Expression Omnibus (GEO) database. The levels of immune components in the tumor microenvironment were evaluated via single-sample gene set enrichment (ssGSEA) analysis. The HNCs were clustered into an Immunity-H group, Immunity-M group and Immunity-L group according to 40 immune components in the tumor microenvironment. DNA damage and HLA genes play an important role in immune regulation. The patients in the Immunity-H group had a favourable survival compared with patients in the Immunity-M group and the Immunity-L group. The patients in the Immunity-H group and Immunity-M group could benefit from radiotherapy. In addition, the Immunity-L group showed the lowest immunophenoscore and had poor response to anti-PD-1 treatment. CXCR3 was demonstrated to be downregulated in the Immunity-L group, which was related to shorter OS in the TCGA and GEO databases, suggesting CXCR3 as a potential therapeutic target. Taken together, our findings proposed three new microenvironment-related phenotypes of HNCs and suggested that CXCR3 played a major role in immune regulation and could be a novel therapeutic target, providing a reference for clinical decisions and research directions in the future.

Identification of Molecular Subtypes and Prognostic Characteristics of Adrenocortical Carcinoma Based on Unsupervised Clustering

“…The KEGG analysis comprises pathways such as cytokine-cytokine receptor interaction, viral protein interaction with cytokine and cytokine receptor, the chemokine signaling pathway, and neuroactive ligand-receptor interaction, among others. Our findings are also supported by molecular typing using IRGs in head and neck cancer [46]. To summarize, the findings of these enrichment analyses emphasize the contrasting functional characteristics of high-risk and low-risk groups, specifically in relation to immune responses, cell signaling, and potentially viral interactions.…”

Novel application of the ferroptosis-related genes risk model associated with disulfidptosis in hepatocellular carcinoma prognosis and immune infiltration

“…For univariate Cox regression analysis, we utilized the R “forestplot” package and identified DE-DRG-FRGs with a p -value less than 0.01, which were considered independent prognostic factors associated with overall survival (OS) in HCC ( He, Yang & Jin, 2022 ). To explore the protein-protein interactions (PPI) among DE-DRG-FRGs associated with OS, we constructed a network using the STRING website ( ) ( Wang et al, 2021 ).…”