Wang Jiale, Li Huan, Shi Mingrui, Ren Chenghao, Wei Wu, Zhao Qi, He Xinxin, Yang Zihui, Wei Jianhua, Yang Xinjie
State Key Laboratory of Oral and Maxillofacial Reconstruction and Regeneration, National Clinical Research Center for Oral Diseases, Shaanxi Clinical Research Center for Oral Diseases, Department of Oral and Maxillofacial Surgery, School of Stomatology, The Former Fourth Military Medical University, Xi'an, China.
Front Immunol. 2025 Aug 12;16:1620931. doi: 10.3389/fimmu.2025.1620931. eCollection 2025.
Tumor associated macrophages (TAMs) in Head and neck squamous cell carcinoma (HNSCC), particularly M2-polarized subtypes, are pivotal drivers of tumorigenesis, angiogenesis, and metastasis, contributing to adverse clinical outcomes. Current prognostic markers lack precision, underscoring the need for novel biomarkers and risk stratification models. Single-cell RNA sequencing (scRNA-seq) was applied to profile the transcriptional landscape of TAMs in HNSCC at single-cell resolution. 1,208 M2 TAMs were integrated from scRNA-seq data with bulk RNA sequencing to identify molecular signatures. Weighted correlation network analysis (WGCNA) and Uniform Manifold Approximation and Projection (UMAP) analysis were applied to dissect TAMs heterogeneity and interactions within the tumor microenvironment. experiments validated the efficacy of the prognostic signature model. In this study, high infiltration of M2 TAMs was strongly associated with advanced clinical stages, lymph node metastasis, and reduced overall survival (P<0.001). TCGA datasets were utilized for cross-platform verification. Multivariate Cox regression and survival analyses were performed to establish prognostic relevance. 11 prognostic signature genes (FCGBP, GIMAP5, WIPF1, RASGEF1B, GIMAP7, IGFLR1, GPR35, NCF1, CLECL1, HEXB, IL10) were identified through integrative analysis, which formed the basis of a robust risk stratification model. The distribution of biomarkers in the high-risk group, as determined by the signature we constructed, can serve as a better indicator for assessing poor prognosis. In clinical samples, prognosis signature has the potential to predict the prognosis effectively in patients with HNSCC.M2 TAMs-driven prognostic signature for HNSCC offers a clinically actionable tool for risk stratification and outcome prediction.
头颈部鳞状细胞癌（HNSCC）中的肿瘤相关巨噬细胞（TAM），尤其是M2极化亚型，是肿瘤发生、血管生成和转移的关键驱动因素，导致不良临床结果。目前的预后标志物缺乏精准性，凸显了对新型生物标志物和风险分层模型的需求。应用单细胞RNA测序（scRNA-seq）以单细胞分辨率描绘HNSCC中TAM的转录图谱。从scRNA-seq数据中整合了1208个M2 TAM，并结合批量RNA测序以识别分子特征。应用加权基因共表达网络分析（WGCNA）和均匀流形近似与投影（UMAP）分析来剖析TAM的异质性以及肿瘤微环境中的相互作用。实验验证了预后特征模型的有效性。在本研究中，M2 TAM的高浸润与晚期临床分期、淋巴结转移及总生存期缩短密切相关（P<0.001）。利用TCGA数据集进行跨平台验证。进行多变量Cox回归和生存分析以确定预后相关性。通过综合分析鉴定出11个预后特征基因（FCGBP、GIMAP5、WIPF1、RASGEF1B、GIMAP7、IGFLR1、GPR35、NCF1、CLECL1、HEXB、IL10），它们构成了一个强大的风险分层模型的基础。我们构建的特征所确定的高危组中生物标志物的分布可作为评估预后不良的更好指标。在临床样本中，预后特征有潜力有效预测HNSCC患者的预后。HNSCC中由M2 TAM驱动的预后特征为风险分层和结果预测提供了一种临床可行的工具。
