Development of a Cellular Senescence-Related Risk Model as a Prognostic Biomarker and Immunotherapy Response in Lung Squamous Cell Carcinoma

OBJECTIVE: To identify cellular senescence-associated genes in lung squamous cell carcinoma (LUSC) and explore their relationship with tumour microenvironment, immunotherapy response, and prognosis. STUDY DESIGN: An observational study. Place and Duration of the Study: Department of Thoracic Surgery, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Hubei, China, from September to October 2023. METHODOLOGY: Prognostic genes and clinical information of LUSC were derived from the Cancer Genome Atlas (TCGA). Subsequently, R packages were used to obtain differentially expressed genes (DEGs) associated with cellular senescence prognosis. In addition, univariate and least absolute shrinkage and selection operator (LASSO) Cox regression analyses were used to construct cellular senescence-related gene signatures to determine the degree of risk. Sensitivity to immune checkpoint inhibitors (ICI) was evaluated according to the median risk score, which served as an independent prognostic factor. RESULTS: By univariate Cox regression analysis of gene expression data and overall survival data in the TCGA-LUSC cohort, 11 DEGs associated with prognostic cellular senescence were identified. The ageing prognostic models include genes of IGFBP1, SERPINE1, SIX1, and TRPM8. Tumour immune dysfunction and exclusion (TIDE) score and tumour mutation burden (TMB) score were better in the low-risk group, with advantages in terms of prognostic and immunotherapy response rate. CONCLUSION: The results suggest that senescence-related determinants are involved in the tumour microenvironment through senescence-related secretory phenotypes and can be used as reliable biomarkers for LUSC immunotherapy and prognosis. KEY WORDS: Cellular senescence, Lung squamous cell carcinoma, Tumour microenvironment, Immunotherapy, Prognosis.