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Updated: Jan 9, 2026
Isolation and Characterization of a Head and Neck Squamous Cell Carcinoma Subpopulation Having Stem Cell Characteristics
Published on: May 11, 2016
Identification and prognostic assessment of clonal and functional heterogeneity in head and neck squamous cell
Yibo Guo1,2, Xiuyin Wu3, Yi Xu4
1Department of Oral and Maxillofacial Surgery, Zhongshan Hospital, Fudan University, Shanghai, China.
Background:
Head and neck squamous cell carcinoma (HNSCC) ranks sixth in incidence and seventh in mortality among cancers in China, affecting 750,000 individuals worldwide and resulting in over 300,000 deaths each year. The intratumoral heterogeneity of HNSCC poses significant challenges for prognosis and therapeutic interventions. This study aimed to investigate clonal heterogeneity and functional regulatory factors in HNSCC and establish a robust prognostic signature.
Methods:
Single-cell and bulk RNA sequencing datasets were integrated to identify clonal subpopulations and functional states in HNSCC. Comprehensive analyses, including clonality assessment, pseudotime trajectory, and functional annotation, were employed to characterize intratumoral heterogeneity. The prognostic significance of these findings was evaluated through survival analyses. Subsequently, a prognostic signature was developed and its robustness was validated across multiple independent patient cohorts.
Results:
Distinct clonal subpopulations were identified within HNSCC tumors, characterized by specific transcriptional profiles associated with stemness, proliferation, and epithelial-mesenchymal transition (EMT). Increased clonal and functional heterogeneity correlated significantly with worse patient survival. A novel prognostic signature, based on heterogeneity, exhibited strong predictive capabilities across multiple cohorts. The signature's utility was further confirmed in an internal cohort, in which the risk score was associated with the aggressiveness of the tumor phenotypes.
Conclusions:
This study identifies intratumoral clonal and functional heterogeneity as key drivers of poor prognosis in HNSCC. We found that increased heterogeneity, characterized by distinct cellular states, correlates significantly with worse patient survival. Consequently, we developed and validated a novel prognostic signature derived from genes governing the intercellular communication between these heterogeneous populations. This signature provides a robust tool for patient risk stratification and highlights novel therapeutic targets to overcome treatment resistance, offering valuable insights for personalized management of HNSCC.
