4.5 Article

A novel hypoxia-associated gene signature for prognosis prediction in head and neck squamous cell carcinoma

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BMC ORAL HEALTH
卷 23, 期 1, 页码 -

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BMC
DOI: 10.1186/s12903-023-03489-8

关键词

Hypoxia; HNSCC; TCGA; Prognostic; Biomarker

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An 8 hypoxia-associated gene signature was established as a novel independent prognostic indicator for HNSCC patients. The nomogram combining the risk score and clinical stage showed enhanced predictive performance compared to the risk model alone. Significant differences in immune cell infiltration levels and metabolic pathways were found between high and low risk subgroups.
BackgroundHead and neck squamous cell carcinoma (HNSCC) is the most common malignant tumor of head and neck, which seriously threatens human life and health. However, the mechanism of hypoxia-associated genes (HAGs) in HNSCC remains unelucidated. This study aims to establish a hypoxia-associated gene signature and the nomogram for predicting the prognosis of patients with HNSCC.MethodsPrevious literature reports provided a list of HAGs. The TCGA database provided genetic and clinical information on HNSCC patients. First, a hypoxia-associated gene risk model was constructed for predicting overall survival (OS) in HNSCC patients and externally validated in four GEO datasets (GSE27020, GSE41613, GSE42743, and GSE117973). Then, immune status and metabolic pathways were analyzed. A nomogram was constructed and assessed the predictive value. Finally, experimental validation of the core genes was performed by qRT-PCR.ResultsA HNSCC prognostic model was constructed based on 8 HAGs. This risk model was validated in four external datasets and exhibited high predictive value in various clinical subgroups. Significant differences in immune cell infiltration levels and metabolic pathways were found between high and low risk subgroups. The nomogram was highly accurate for predicting OS in HNSCC patients.ConclusionsThe 8 hypoxia-associated gene signature can serve as novel independent prognostic indicators in HNSCC patients. The nomogram combining the risk score and clinical stage enhanced predictive performance in predicting OS compared to the risk model and clinical characteristics alone.

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