Abstract
BACKGROUND: Increasing evidence has shown that hypoxia is a biomarker of tumor proliferation and metastasis. This research aimed to identify a hypoxia-associated gene prognostic index (HAGPI) in head and neck squamous cell carcinoma (HNSCC) and based on HAGPI-defined subgroups to predict prognosis and response to immune checkpoint inhibitors therapy. METHODS: RNA-sequencing transcriptomic data for patients with HNSCC were downloaded from The Cancer Genome Atlas (TCGA). Protein-protein interaction network analysis was performed to select hypoxia-related hub genes. Univariate and multivariate cox regression analyses were used to identify hub genes to develop the HAGPI. Afterward expression data were imported into CIBERSORT to evaluate the relative proportion of 22 immune cells and compared the relative proportions of immune cells between the 2 HAGPI subgroups. The relationship between immunopheno score (IPS) and HAGPI was validated for immune checkpoint inhibitors (ICIs) response in TCGA cohorts. RESULTS: The HAGPI was constructed based on HS3ST1, HK1, PGK1, STC2, SERPINE1, PKLR genes. In high-HAGPI patients, the primary and secondary endpoint events in TCGA and GEO cohorts were significantly lower than low-HAGPI groups (P < .05). HAGPI-high patients exhibited a poorer prognosis than HAGPI-low patients did. The abundance of M2 macrophages and NK cell were significantly enhanced in the high-HAGPI while T cells regulatory and T cells CD8, were markedly elevated in the low-HAGPI. Meanwhile, patients in the low-HAGPI patients had higher levels of immunosuppressant expression and less aggressive phenotypes. Furthermore, IPS analysis showed that the low-HAGPI group with higher IPS represented a more immunogenic phenotype. CONCLUSION: The current study developed and verified a HAPGI model that can be considered as an independent prognostic biomarker and elucidated the tumor immune microenvironment of HNSCC.