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Gene Model Related to m6A Predicts the Prognostic Effect of Immune Infiltration on Head and Neck Squamous Cell Carcinoma
Author(s) -
Ya-Ping Deng,
Kehua Li,
Fengwu Tan,
Hanbo Liu
Publication year - 2021
Publication title -
journal of oncology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.228
H-Index - 54
eISSN - 1687-8469
pISSN - 1687-8450
DOI - 10.1155/2021/1814266
Subject(s) - immune system , head and neck squamous cell carcinoma , medicine , proportional hazards model , oncology , tumor microenvironment , gene , lasso (programming language) , immune checkpoint , kegg , transcriptome , cancer research , immunotherapy , head and neck cancer , gene expression , cancer , biology , immunology , genetics , world wide web , computer science
Head and neck squamous cell carcinoma (HNSCC) is a highly aggressive solid tumor. Because most studies have focused on the intrinsic carcinogenic pathways of tumors, we focused on the relationship between N6-methyladenosine (m6A) and the prognosis of HNSCC in the tumor immune microenvironment. We downloaded RNA-seq data from the TCGA dataset and used univariate Cox regression to screen m6A-related lncRNAs. The expression value of LASSO-screened genes was the sum of LASSO regression coefficients. We then evaluated relationships between the risk score and cellular components or cellular immune response. Differences in immune response under various algorithms were visualized with heat maps. The GSVA package in R was used to analyze GO, BP, KEGG, and hallmark gene sets of immune checkpoint clusters and immune checkpoint scores. The GSEA analysis was performed with the cluster profile package, yielding 21 m6A genes. Related lncRNAs were screened with Pearson's correlations, and the resulting 442 lncRNAs were screened using single-factor analysis. Eight lncRNAs closely related to prognosis were identified through survival random forest. Survival analysis showed that patients with a high risk score had a poor prognosis. Low- and high-risk-score groups differed significantly in m6A gene expression. Prognostic scores from different algorithms were significantly correlated with B cells, T cells, and memory cells in the immune microenvironment. Expression of immune checkpoints and signal pathways differed significantly across risk-score groups, suggesting that m6A could mediate lncRNA-induced immune system dysfunction and affect HNSCC development. A comprehensive study of tumor-cell immune characteristics should provide more insight into the complex immune microenvironment, thus contributing to the development of new immunotherapeutic agents.

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