Lin Yingmiao, Wu Fangcai, Huang Xuchun, Zhang Zhihan, Liu Cantong, Lin Yiwei, Xu Yiwei, Guo Haipeng, Hong Chaoqun
Department of Clinical Laboratory Medicine, Cancer Hospital of Shantou University Medical College, Shantou, China.
Department of Radiation Oncology, Cancer Hospital of Shantou University Medical College, Shantou, China.
Front Immunol. 2025 Jul 9;16:1538641. doi: 10.3389/fimmu.2025.1538641. eCollection 2025.
Head and neck squamous cell carcinoma (HNSCC) is a highly aggressive and heterogeneous malignant tumor. Mast cells are one of the immune cells widely distributed in the tumor microenvironment (TME), and their immune response with various immune cells is essential in promoting or inhibiting tumor growth and metastasis. However, the role played by mast cells in HNSCC has yet to be fully clarified.
We identified mast cell marker genes using single-cell RNA sequencing (scRNA-seq) from the GSE103322 of the GEO database. The HNSCC data from the TCGA databases was divided into training and validation groups. Cox regression and LASSO regression analyses were used to screen the prognostically relevant mast cell-related genes (MRGs) to construct a prognostic signature and differentiate risk groups. The receiver operating characteristic (ROC) and calibration curves were used to test the model's accuracy. We revealed the immune landscape of HNSCC by immune infiltration, immune checkpoint levels, ESTIMATE, and TIDE analyses. Drug sensitivity analyses were used to understand the sensitivity of different risk groups to drug therapy.
The 14-MRGs prognostic signature classified patients into high- and low-risk groups, and the overall survival (OS) of the low-risk group was significantly higher than that of the high-risk group (p < 0.05). The areas under the ROC curves of the nomogram were 0.740, 0.737 and 0.707 at 1-, 3-, and 5-year, and they also showed better detection efficacy in the validation group than other independent predictors. The low-risk group had richer immune cell infiltration and higher immune scores. The lower TIDE score in the low-risk group demonstrates that patients in this group were less prone to have immune escape and more likely to benefit from immunotherapy. In addition, the low-risk group was more sensitive to a broader range of drugs than the high-risk group.
We combined scRNA-seq data and bulk RNA-seq data to construct a 14-MRGs-based prognostic model capable of well predicting the prognosis of HNSCC patients. This model may also help identify patients who can benefit from immunotherapy.
头颈部鳞状细胞癌（HNSCC）是一种侵袭性很强且异质性的恶性肿瘤。肥大细胞是广泛分布于肿瘤微环境（TME）中的免疫细胞之一，其与各种免疫细胞的免疫反应对于促进或抑制肿瘤生长和转移至关重要。然而，肥大细胞在HNSCC中所起的作用尚未完全阐明。
我们使用来自GEO数据库GSE103322的单细胞RNA测序（scRNA-seq）鉴定肥大细胞标记基因。将来自TCGA数据库的HNSCC数据分为训练组和验证组。采用Cox回归和LASSO回归分析筛选与预后相关的肥大细胞相关基因（MRGs），以构建预后特征并区分风险组。使用受试者工作特征（ROC）曲线和校准曲线来测试模型的准确性。我们通过免疫浸润、免疫检查点水平、ESTIMATE和TIDE分析揭示了HNSCC的免疫格局。药物敏感性分析用于了解不同风险组对药物治疗的敏感性。
基于14个MRGs的预后特征将患者分为高风险组和低风险组，低风险组的总生存期（OS）显著高于高风险组（p<0.05）。列线图在1年、3年和5年时的ROC曲线下面积分别为0.740、0.737和0.707，并且在验证组中其检测效能也优于其他独立预测指标。低风险组具有更丰富的免疫细胞浸润和更高的免疫评分。低风险组较低的TIDE评分表明该组患者较少发生免疫逃逸，更有可能从免疫治疗中获益。此外，低风险组比高风险组对更广泛的药物更敏感。
我们结合scRNA-seq数据和批量RNA-seq数据构建了一个基于14个MRGs的预后模型，该模型能够很好地预测HNSCC患者的预后。该模型也可能有助于识别能从免疫治疗中获益的患者。
