Skip to content
2000
Volume 25, Issue 11
  • ISSN: 1386-2073
  • E-ISSN: 1875-5402

Abstract

Background: The occurrence of oxidative stress is an important hallmark of tumorigenesis and the development of cancers, including head and neck squamous cell carcinoma (HNSCC). The purpose of this study was to identify a robust oxidative stress-related prognostic model in HNSCC. Methods: Oxidative stress genes related to the prognosis of HNSCC were identified through multiple bioinformatics methods. Results: The expression profile of differential genes related to oxidative stress and functional enrichment analysis were obtained from the HNSCC cohort of The Cancer Genome Atlas (TCGAHNSC). Then, the HNSCC prognostic risk model was constructed of thirteen screened genes through univariate Cox analysis, the least absolute shrinkage and selection operator (LASSO) Cox regression, and multivariate Cox analysis. Kaplan–Meier curve indicated that the low-risk group had a better survival outcome than the high-risk group. The clinical utility of the risk model was validated in the GSE41613 dataset. The risk score was an independent prognostic indicator in the training and validation sets. In addition, the risk score was in a positive correlation with tumor stage, lymph node infiltration, and the status of the primary site. Gene set enrichment analysis (GSEA) illustrated that many biological processes associated with immunity were significantly enriched in the low-risk group of the training cohort. Conclusion: The oxidative stress-related risk signature was a promising predictor for the prognosis of HNSCC patients, which might assist in making individualized therapy programs.

Loading

Article metrics loading...

/content/journals/cchts/10.2174/1386207325666211207154436
2022-09-01
2024-12-23
Loading full text...

Full text loading...

/content/journals/cchts/10.2174/1386207325666211207154436
Loading
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error
Please enter a valid_number test