Translational cancer research · 2026
Comprehensive analysis and validation of the prognostic value of glycosylation- and mitophagy-related genes for head and neck squamous cell carcinoma.
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Lu Qiaoling, Ying Li, Ling Lang, Hui Wu, Wang Xinbin
Аннотация
BACKGROUND: The treatment of head and neck squamous cell carcinoma (HNSCC) is particularly difficult because of its aggressive nature, complex anatomical location, and high recurrence and metastasis rates. This study investigated the relationship between glycosylation and mitophagy-related genes in HNSCC.
METHODS: We used bioinformatics tools to analyze data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Specifically, we analyzed differentially expressed genes (DEGs), mutations, copy number variations (CNVs), Gene Ontology (GO) enrichment, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment. Univariate and multivariate Cox regression analyses and Least Absolute Shrinkage and Selection Operator (LASSO) regression were performed to develop prognostic models, which were validated using GEO datasets.
RESULTS: We identified six key genes (PPARG, PIP, BIRC5, AR, ITGA5, and ENO2) significantly differentially expressed in HNSCC samples compared with controls. BIRC5, ITGA5, and ENO2 showed high diagnostic accuracy, whereas PPARG, PIP, and AR showed moderate accuracy. Enrichment analysis linked the extracellular matrix-receptor interaction pathway to HNSCC. Our prognostic model showed that the low-risk group exhibited longer survival. Immune analysis revealed a correlation between ITGA5 and CD8+ T cells in low-risk patients and AR in high-risk patients.
CONCLUSIONS: These findings highlight the diagnostic and prognostic potential of glycosylation- and mitophagy-related genes, laying the foundation for individualized HNSCC treatment.
METHODS: We used bioinformatics tools to analyze data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Specifically, we analyzed differentially expressed genes (DEGs), mutations, copy number variations (CNVs), Gene Ontology (GO) enrichment, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment. Univariate and multivariate Cox regression analyses and Least Absolute Shrinkage and Selection Operator (LASSO) regression were performed to develop prognostic models, which were validated using GEO datasets.
RESULTS: We identified six key genes (PPARG, PIP, BIRC5, AR, ITGA5, and ENO2) significantly differentially expressed in HNSCC samples compared with controls. BIRC5, ITGA5, and ENO2 showed high diagnostic accuracy, whereas PPARG, PIP, and AR showed moderate accuracy. Enrichment analysis linked the extracellular matrix-receptor interaction pathway to HNSCC. Our prognostic model showed that the low-risk group exhibited longer survival. Immune analysis revealed a correlation between ITGA5 and CD8+ T cells in low-risk patients and AR in high-risk patients.
CONCLUSIONS: These findings highlight the diagnostic and prognostic potential of glycosylation- and mitophagy-related genes, laying the foundation for individualized HNSCC treatment.