The m6A and immune regulatory gene signature predicts the prognosis and correlates with immune infiltration of head and neck squamous cell carcinoma

m6A 和免疫调节基因特征可预测头颈部鳞状细胞癌的预后,并与免疫浸润相关。

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Abstract

Recent investigations have underscored the epigenetic modulation of the immune response; however, the interplay between RNA N6-methyladenosine (m(6)A) modification and immunomodulation in head and neck squamous cell carcinoma (HNSC) remains relatively unexplored. To bridge this knowledge gap, we undertook an extensive examination of the potential contributions of m(6)A modification and immunomodulation in HNSC. We amalgamated and deduplicated 27 m(6)A -related genes (m6AGs) and 1342 immune regulation-related genes (IMRGs), resulting in a comprehensive dataset encompassing 1358 genes. This dataset was scrutinized for m(6)A modification and immunomodulatory patterns within HNSC specimens. Employing Cox regression analysis and the Least Absolute Shrinkage and Selection Operator (LASSO) technique, we developed a prognostic risk model for m(6)A regulator-mediated methylation modification and immunomodulation-related differentially expressed genes (m6A&IMRDEGs). Our differential expression analysis delineated 29 m6A&IMRDEGs, and Weighted Gene Co-expression Network Analysis (WGCNA) elucidated two module genes (IL11 and MMP13) subjected to correlation analysis. The prognostic prediction models revealed that the clinical predictive efficacy peaked for 1-year forecasts, followed sequentially by 3-year and 5-year predictions. The risk scores derived from the model adeptly categorized HNSC patients into high- and low-risk cohorts, with the high-risk group exhibiting a more unfavorable prognosis. Protein-Protein Interaction (PPI) analysis identified 7 hub genes implicated in m(6)A and immune regulation, namely BPIFB1, BPIFB2, GP2, MUC5B, MUC7, PIP, and SCGB3A1. Furthermore, we noted marked disparities in the expression profiles of 18 immune cell types between the high- and low-risk groups. Our results substantiate that the clustering subpopulations and risk models associated with m(6)A and immune regulatory genes portend a poor prognosis in HNSC. The risk score emerges as a potent prognostic biomarker and predictive metric for HNSC patients. A thorough assessment of m(6)A and immune regulatory genes in HNSC will augment our comprehension of the tumor immune microenvironment and facilitate the advancement of HNSC therapeutics.

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