Systematic Profiling of Immune Risk Model to Predict Survival and Immunotherapy Response in Head and Neck Squamous Cell Carcinoma

Background and purpose: Head and neck squamous carcinoma (HNSCC), characterized by immunosuppression, is a group of highly heterogeneous cancers. Although immunotherapy exerts a promising influence on HNSCC, the response rate remains low and varies in assorted primary sites. The immunological mechanisms underlying HNSCC pathogenesis and treatment response are not fully understood. The aim of this study was to develop a differential expressed genes (DEGs) based risk model that may predict immunotherapy efficacy and stratify prognosis of HNSCC patients. Materials and methods: We downloaded the expression profiles of HNSCC patients from the Cancer Genome Atlas (TCGA) database. The tumor microenvironment and immune response were estimated by Cell type identification by estimating relative subset of known RNA transcripts (CIBERSORT) and immunophenoscore (IPS). The differential expression pattern based on human papillomavirus (HPV) status was identified. A DEGs based prognostic risk model was developed and validated. All statistical analysis was performed with R software (version 3.6.3). Results: By using the TCGA database, we identified DKK1, HBEGF, RNASE7, TNFRSF12A, INHBA, PIK3R3 as DEGs that were associated with patients’ overall survival (OS) and stratified patients into high-risk and low-risk subgroups based on a DEGs based prognostic risk model. Significant difference of overall survival was found between high-risk and low-risk patients (1.64 vs 2.18 years, P =0.0017). In multivariate Cox analysis, the risk model was an independent prognostic factor for OS (HR=1.06, 95% CI [1.02-1.10], P =0.004). Higher degree of CD8+ T cell and regulatory cells (Tregs) were observed in low-risk group and associated with a favorable prognosis. The IPS analysis suggested that the low-risk patients possessed a higher IPS score and a higher immunoreactivity phenotype, which were correlated with better immunotherapy response. Conclusion: Collectively, we established a reliable DEGs based risk model with potential prognostic value and capacity to predict the immunophenotype of HNSCC patients.