From Bulk to Spatially Resolved Single-Cell Omics: Shaping Future Prognostic and Predictive Stratification in Head and Neck Squamous Cell Carcinoma

Head and neck squamous cell carcinoma (HNSCC) is characterized by marked intratumoral heterogeneity and complex tumor–immune–stromal interactions, which shape therapeutic response and clinical outcome. Despite extensive transcriptomic efforts, bulk RNA sequencing has faced significant limitations, often failing to generate robust prognostic or predictive biomarkers, highlighting the need for approaches capable of resolving the cellular and spatial complexity of the tumor ecosystem. Single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) have refined our understanding of HNSCC biology by enabling high-resolution mapping of malignant, stem-like, immune, and stromal compartments. Three major spatial domains have been defined in HNSCC: tumor core (TC), tumor invasion front (TIF), and leading edge (LE). Each ecosystem exhibits distinct cellular programs that promote immune evasion, tumor dissemination, and therapy resistance, particularly in high-risk clinical settings. In this Review, we integrate recent single-cell and spatial studies and propose a translational framework linking ecosystem architecture with clinical stratification across resectable locally advanced (r-LAD), unresectable locally advanced (u-LAD), and recurrent/metastatic (R/M) disease. We further discuss how spatially resolved transcriptomic approaches may support biomarker discovery and hypothesis generation for risk stratification and trial design, while emphasizing that clinical implementation remains limited by cohort size, methodological heterogeneity, and the need for large-scale prospective validation. Finally, we outline key methodological and translational challenges that must be addressed before these technologies can reliably inform precision oncology and decision-making in HNSCC.