Single-cell analysis of tumor microenvironment immune homeostasis and identification of prognostic biomarkers in head and neck squamous cell carcinoma.

Background: Head and neck squamous cell carcinoma (HNSCC) is the eighth most common cancer globally, characterized by its diverse primary sites and immunosuppressive tumor microenvironment (TME). The TME impairs anti-tumor immunity, with T cells playing a critical role. However, T cells often become "exhausted," diminishing their anti-tumor function. Understanding the dynamic changes within the HNSCC TME is crucial for identifying therapeutic targets. To delineate immune homeostasis within the HNSCC TME at single-cell resolution and to identify robust prognostic biomarkers for patient risk stratification. Methods: This study utilized single-cell RNA sequencing (scRNA-seq) data from the Gene Expression Omnibus (GEO) to analyze the cellular composition and intercellular interactions in the HNSCC TME. We focused on the heterogeneity and differentiation trajectories of T cell subsets. Key genes involved in T-cell differentiation were identified and validated using data from The Cancer Genome Atlas-HNSCC (TCGA-HNSC) project. A prognostic risk model was constructed based on these genes. Results: The study revealed that the differentiation trajectory of T cells from naïve to exhausted states is regulated by genes such as Conclusions: This study provides valuable insights into the immune dynamics of HNSCC and identifies a prognostic risk model based on key immune-related genes, aiding in personalized treatment strategies. The findings offer a novel approach for precise prognostic evaluation and targeted therapy development in HNSCC, advancing clinical management and patient outcomes.