Liu XinYu, Liu YuJun, Tian XuTengYue, Xi Yue, Lu MiaoMiao, Zou Xin, Chen WanTao
College of Stomatology, Binzhou Medical University, Yantai, 264003, Shandong, China.
Department of Oral and Maxillofacial-Head and Neck Oncology, School of Medicine, Ninth People's Hospital, Shanghai Jiao Tong University, Shanghai, PR China.
Discov Oncol. 2025 Apr 7;16(1):477. doi: 10.1007/s12672-025-02257-0.
Head and neck squamous cell carcinoma (HNSCC) demonstrates significant heterogeneity, necessitating improved molecular classification for precision treatment.
We integrated single-cell and bulk RNA sequencing data from 59,376 cells across ten datasets using Scissor and scSTAR packages. Molecular subtyping was performed through ssGSEA and WGCNA analysis, with immune infiltration evaluated using CIBERSORT. We developed a machine learning-based risk prediction model using 54 algorithms.
We identified three molecular subtypes with distinct prognostic implications, showing significant survival differences across independent datasets (TCGA-HNSCC, P < 0.0001; GSE65858, P = 0.018). The C3 subtype showed enhanced immunotherapy response potential, while C2 exhibited the highest genomic alteration rate (97.06%) and TP53 mutations (80%). Macrophages emerged as key players in intercellular communication networks. Our risk prediction model demonstrated robust performance across four validation cohorts.
This molecular subtyping framework provides valuable insights for patient stratification and personalized therapeutic strategies in HNSCC, potentially improving clinical outcomes through precise treatment selection.
头颈部鳞状细胞癌（HNSCC）表现出显著的异质性，需要改进分子分类以实现精准治疗。
我们使用Scissor和scSTAR软件包整合了来自十个数据集的59376个细胞的单细胞和批量RNA测序数据。通过单样本基因集富集分析（ssGSEA）和加权基因共表达网络分析（WGCNA）进行分子亚型分类，使用CIBERSORT评估免疫浸润情况。我们使用54种算法开发了一种基于机器学习的风险预测模型。
我们确定了三种具有不同预后意义的分子亚型，在独立数据集（TCGA-HNSCC，P < 0.0001；GSE65858，P = 0.018）中显示出显著的生存差异。C3亚型显示出增强的免疫治疗反应潜力，而C2亚型表现出最高的基因组改变率（97.06%）和TP53突变率（80%）。巨噬细胞成为细胞间通信网络中的关键参与者。我们的风险预测模型在四个验证队列中表现出强大的性能。
这种分子亚型分类框架为HNSCC患者的分层和个性化治疗策略提供了有价值的见解，有可能通过精确的治疗选择改善临床结果。
