biostudies-literatureDai YNational Natural Science Foundation of China (General Program)Graduate Innovation Fund of Jilin UniversityScience and Technology Department of Jilin Provincee42665https://www.ebi.ac.uk/biostudies/studies/S-EPMC12173340biostudies-literatureUnknown104(24)Hypoxia and lactate metabolism are both distinctive characteristics of cancerous cells. Head and neck squamous cell carcinoma (HNSCC) is one of the most prevalent forms of cancer. The objective of this study was to construct a prognostic model of genes related to hypoxia and lactate metabolism in order to facilitate the study of the prognosis, tumor immune microenvironment and therapeutic response of patients with HNSCC. The RNA-seq and clinical data for HNSCC were obtained from The Cancer Genome Atlas database and gene expression omnibus. The hypoxia- and lactate metabolism-related genes were obtained from the Molecular Signatures Database. The identification of differentially expressed genes was conducted using the "limma" R package. Subsequently, protein-protein interaction networks of MedicineDevelopment and experimental verification of a prognosis model for hypoxia- and lactate metabolism-associated genes in HNSCC.PMC12173340Grant No. 82370934Grant No.2024CX143Grant No.ZKJCKJT2024A044, No.ZKJCKJT2024A052Li YZou JLiu ZWang RSui XChen XDai YXin JfalseDevelopment and experimental verification of a prognosis model for hypoxia- and lactate metabolism-associated genes in HNSCC.Hypoxia and lactate metabolism are both distinctive characteristics of cancerous cells. Head and neck squamous cell carcinoma (HNSCC) is one of the most prevalent forms of cancer. The objective of this study was to construct a prognostic model of genes related to hypoxia and lactate metabolism in order to facilitate the study of the prognosis, tumor immune microenvironment and therapeutic response of patients with HNSCC. The RNA-seq and clinical data for HNSCC were obtained from The Cancer Genome Atlas database and gene expression omnibus. The hypoxia- and lactate metabolism-related genes were obtained from the Molecular Signatures Database. The identification of differentially expressed genes was conducted using the "limma" R package. Subsequently, protein-protein interaction networks of 2025-01-01T00:00:00Z2025 Jun2026-06-03T07:45:32.093Z2026-04-26T03:09:57.365ZS-EPMC121733404052779010.1097/MD.0000000000042665