ArticleFrontiers in immunology2021
Molecular Subtypes Based on Cell Differentiation Trajectories in Head and Neck Squamous Cell Carcinoma: Differential Prognosis and Immunotherapeutic Responses.
Article in Frontiers in immunology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Application of artificial intelligence in head and neck squamous cell carcinoma.Annals of medicine · 2026Review
- Radiomics-based machine learning models decipher heterogeneity of anoikis-related molecular subtypes for prognostic stratification in head and neck squamous cell carcinoma.Translational cancer research · 2026Article
- A unified single-cell atlas of HNSCC: Toward characterizing HPV- and sex-associated TME variability.iScience · 2026Article
- Artificial Intelligence-Enabled Multi-Omics for Predicting Immune Checkpoint Inhibitor Response and Resistance.Journal of multidisciplinary healthcare · 2026Review
- Single-Cell and Spatial Transcriptomic Profiling of Penile Squamous Cell Carcinoma Reveals Dynamics of Tumor Differentiation and Immune Microenvironment.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Review
- Enhancing immunotherapy outcomes by targeted remodeling of the tumor microenvironment via combined cGAS-STING pathway strategies.Frontiers in immunology · 2024Review
- Application of single-cell RNA sequencing in head and neck squamous cell carcinoma.Chinese journal of cancer research = Chung-kuo yen cheng yen chiu · 2023Article
- Article
- Automated Nuclear Segmentation in Head and Neck Squamous Cell Carcinoma Pathology Reveals Relationships between Cytometric Features and ESTIMATE Stromal and Immune Scores.The American journal of pathology · 2022Article
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Authors and funding
8 authors.
Funding
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Abstract
Objective: Head and neck squamous cell carcinoma (HNSCC) is one of the most common and lethal malignant tumors. We aimed to investigate the HNSCC cell differentiation trajectories and the corresponding clinical relevance. Methods: Based on HNSCC cell differentiation-related genes (HDRGs) identified by single-cell sequencing analysis, the molecular subtypes and corresponding immunity, metabolism, and stemness characteristics of 866 HNSCC cases were comprehensively analyzed. Machine-learning strategies were used to develop a HNSCC cell differentiation score (HCDscore) in order to quantify the unique heterogeneity of individual samples. We also assessed the prognostic value and biological characteristics of HCDscore using the multi-omics data. Results: HNSCCs were stratified into three distinct molecular subtypes based on HDRGs: active stroma (Cluster-A), active metabolism (Cluster-B), and active immune (Cluster-C) types. The three molecular subtypes had different characteristics in terms of biological phenotype, genome and epigenetics, prognosis, immunotherapy and chemotherapy responses. We then demonstrated the correlations between HCDscore and the immune microenvironment, subtypes, carcinogenic biological processes, genetic variation, and prognosis. The low-HCDscore group was characterized by activation of immunity, enhanced response to anti-PD-1/PD-L1 immunotherapy, and better survival compared to the high-HCDscore group. Finally, by integrating the HCDscore with prognostic clinicopathological characteristics, a nomogram with strong predictive performance and high accuracy was constructed. Conclusions: This study revealed that the cell differentiation trajectories in HNSCC played a nonnegligible role in patient prognosis, biological characteristics, and immune responses. Evaluating cancer cell differentiation will help to develop more effective immunotherapy, metabolic therapy, and chemotherapy strategies.
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