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ABSTRACT: Background
Numerous studies have shown that the aging microenvironment played a huge impact on tumor progression. However, the clinical prognostic value of aging-related risk signatures and their effects on the tumor immune microenvironment (TIME) in head and neck squamous cell carcinoma (HNSCC) remains largely unclear. This study aimed to identify novel prognostic signatures based on aging-related genes (AGs) and reveal the landscape of the TIME in HNSCC.Methods
Differentially expressed AGs were identified using the gene set enrichment analysis (GSEA). The prognostic risk model of AGs was established by univariate and multivariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses. The independent prognostic value of the risk mod
SUBMITTER: Chen F
PROVIDER: S-EPMC9127417 | biostudies-literature | 2022
REPOSITORIES: biostudies-literature