Identification and Analysis of Senescence-Related Genes in Head and Neck Squamous Cell Carcinoma by a Comprehensive Bioinformatics Approach. (17th October 2022)

• Record Type: Journal Article
• Authors: Deng, Lin; Mi, Jinglin; Ruan, Xiaolan; Zhang, Guozhen; Pan, Yufei; Wang, Rensheng
• Other Names: Ali Sheikh Md Sayed Academic Editor.
• Is Part Of: Mediators of inflammation. Volume 2022(2022)
• Publication Date: 2022-10-17
• Subjects: Inflammation -- Mediators -- Periodicals; Biological response modifiers -- Periodicals; Inflammation (Pathologie) -- Médiateurs; Immunomodulateurs; Biological response modifiers; Inflammation -- Mediators; Immunology; Autacoids; Immunologic Factors; Cell Adhesion Molecules; Cell Communication; Cytokines; Inflammation; Periodicals; Electronic journals; 616.0473
• DOI: 10.1155/2022/4007469
• Languages: English
• ISSNs: 0962-9351

Abstract

Abstract : Head and neck cancer is the sixth most frequent cancer all over the world, with the majority of subtypes of head and neck squamous cell carcinoma (HNSCC). Cellular senescence-associated genes have been confirmed to play a critical role in cancer and have the potential to be prognostic biomarkers for cancer. Clinical information of HNSCC samples and expression data were acquired from public databases. Expression profiles of genes related to cellular senescence were used to identify molecular subtypes by consensus clustering. To screen differentially expressed genes (DEGs) between different subtypes, differential analysis was performed. We used the univariate Cox regression to identify prognostic DEGs and performed least absolute shrinkage and selection operator (LASSO) to optimize and construct a prognostic model. CIBERSORT, ESTIMATE, and TIDE tools were applied to estimate immune characteristics. Four molecular subtypes were established based on cellular senescence-associated genes. Differential prognosis was observed among different subtypes with C4 having the longest overall survival and C1 having the worst prognosis. C4 subtype also showed the highest immune infiltration. We screened a total of eight cellular senescence prognosis-related genes and established a cellular senescence-related signature score (CSRS.Score) that could stratify samples into high-CSRS.Score and low-CSRS.Score groups. The high-CSRS.Score group had worse prognosis, lower immune infiltration, and lower response to immunotherapy. We further improved the prognostic model and survival prediction by combining CSRS.Score with clinicopathological features using a decision tree model, which had high predictive accuracy and survival prediction. This study demonstrated an important role of cellular senescence in HNSCC. The identified eight cellular senescence-associated genes have the potential to provide ideas for adjuvant treatment and personalized treatment of HNSCC patients.