Cancer-Associated Fibroblast Heterogeneity Shapes Prognosis and Immune Landscapes in Head and Neck Squamous Cell...

Background/Objectives: Head and neck squamous cell carcinoma (HNSCC) is a biologically heterogeneous malignancy with poor outcomes in advanced disease. Increasing evidence indicates that the tumor microenvironment, particularly cancer-associated fibroblasts (CAFs), plays an important role in tumor progression and immune regulation. However, the diversity of CAF subsets and their clinical relevance in HNSCC remain incompletely understood. This study aimed to characterize CAF heterogeneity and assess the prognostic significance of CAF subset-specific transcriptional programs. Methods: Single-cell RNA sequencing data from HNSCC tumors were analyzed to identify CAF subsets based on differentially expressed genes. CAF subset-specific gene signatures were used to construct prognostic risk models for overall survival (OS) and progression-free survival (PFS) in The Cancer Genome Atlas HNSCC cohort, with validation in an independent dataset. CAF-driven prognostic groups were defined, and their immune landscapes and biological pathways were evaluated. Bulk RNA sequencing of primary CAF cultures was performed for validation. Results: Six CAF subsets were identified, including myofibroblastic (myCAF), inflammatory (iCAF), antigen-presenting, and extracellular matrix-related CAFs. Risk scores derived from inflammatory CAF subsets consistently predicted shorter OS across independent cohorts, whereas PFS prediction showed greater cohort dependency. CAF-based stratification identified patient subgroups with distinct immune profiles and pathway enrichment patterns. These results were supported by validation analyses and by bulk RNA sequencing of primary CAFs, demonstrating preservation of myCAF- and iCAF-like transcriptional programs ex vivo. Conclusions: CAF heterogeneity has important prognostic and immunological implications in HNSCC. Inflammatory CAF-related transcriptional programs represent robust markers of patient survival and may complement tumor-intrinsic biomarkers.