Fang Chao, Zhang Qin, Fang Rui, Li Ying, Bai Jing, Huang Xiaojing, Lu Jingting, Chen Dongsheng, Zhang Yanxiang, Chen Zuhong
The School of Clinical Medicine, Fujian Medical University, Fuzhou 350000, Fujian, China.
Department of Otolaryngology-Head & Neck Surgery, The First Hospital of Putian, Putian 351100, Fujian, China.
Cancer Drug Resist. 2025 Aug 22;8:42. doi: 10.20517/cdr.2025.124. eCollection 2025.
Immune checkpoint inhibitors (ICIs) have transformed cancer therapy; however, their efficacy in head and neck cancer (HNC) remains limited, with only a minority of patients achieving durable responses. Understanding the molecular mechanisms underlying ICI resistance in HNC is therefore crucial. We conducted an integrative analysis of genomic, transcriptomic, and clinical data from 139 ICI-treated HNC patients (MSKCC cohort) and 502 treatment-naïve HNC cases (TCGA cohort). mutation status, tumor mutational burden (TMB), neoantigen load, immune cell infiltration (via CIBERSORT), and immune-related gene expression were evaluated. Gene set enrichment analysis (GSEA) was performed to identify dysregulated pathways. Survival outcomes were assessed using Kaplan-Meier analysis and Cox regression, with statistical significance defined as < 0.05. Patients harboring mutations exhibited significantly poorer outcomes following ICI therapy, with shorter median overall survival [OS: 5.0 11.0 months, hazard ratio (HR) = 3.22, 95%CI: 1.26-8.19, = 0.011] compared to wild-type counterparts. Multivariate analysis confirmed mutation as an independent predictor of poor OS in ICI-treated patients (HR = 4.78, 95%CI: 1.70-13.43, = 0.003). In contrast, mutations showed no prognostic significance in the treatment-naïve TCGA-HNC cohort ( = 0.26), confirming their role as a predictive (not prognostic) biomarker for ICI response. Interestingly, despite exhibiting higher TMB and neoantigen levels, -mutant patients showed inferior survival, underscoring the context-dependent limitations of TMB as a predictive biomarker. Mechanistically, -mutant tumors displayed an immunosuppressive tumor microenvironment characterized by diminished CD8 T cell infiltration, attenuated interferon-γ signaling, and downregulation of immune-related genes (, , , ). GSEA revealed enrichment of pathway activity in -mutant tumors, which suppressed antigen presentation and T cell activation pathways. mutations drive ICI resistance in HNC by promoting an immunosuppressive TME via -mediated transcriptional reprogramming, impairing antigen presentation and T cell function. Incorporating status into biomarker panels may improve patient stratification and guide combinatorial therapies targeting both immune evasion and oncogenic pathways.
免疫检查点抑制剂（ICIs）已经改变了癌症治疗方式；然而，它们在头颈部癌（HNC）中的疗效仍然有限，只有少数患者能实现持久缓解。因此，了解HNC中ICI耐药的分子机制至关重要。我们对139例接受ICI治疗的HNC患者（MSKCC队列）和502例未接受过治疗的HNC病例（TCGA队列）的基因组、转录组和临床数据进行了综合分析。评估了突变状态、肿瘤突变负荷（TMB）、新抗原负荷、免疫细胞浸润（通过CIBERSORT）和免疫相关基因表达。进行基因集富集分析（GSEA）以识别失调的通路。使用Kaplan-Meier分析和Cox回归评估生存结果，统计学显著性定义为P<0.05。携带[具体基因]突变的患者在接受ICI治疗后预后明显较差，与野生型患者相比，中位总生存期较短[OS：5.0对11.0个月，风险比（HR）=3.22，95%CI：1.26-8.19，P=0.011]。多变量分析证实[具体基因]突变是接受ICI治疗患者总生存期较差的独立预测因素（HR=4.78，95%CI：1.70-13.43，P=0.003）。相比之下，[具体基因]突变在未接受过治疗的TCGA-HNC队列中无预后意义（P=0.26），证实了它们作为ICI反应的预测性（而非预后性）生物标志物的作用。有趣的是，尽管[具体基因]突变患者表现出更高的TMB和新抗原水平，但其生存情况较差，这突出了TMB作为预测性生物标志物的背景依赖性局限性。从机制上讲，[具体基因]突变肿瘤表现出免疫抑制性肿瘤微环境，其特征为CD8 T细胞浸润减少、干扰素-γ信号减弱以及免疫相关基因（[具体基因1]、[具体基因2]、[具体基因3]、[具体基因4]）下调。GSEA显示[具体基因]突变肿瘤中[具体通路]通路活性富集，该通路抑制抗原呈递和T细胞激活通路。[具体基因]突变通过[具体基因]介导的转录重编程促进免疫抑制性肿瘤微环境，损害抗原呈递和T细胞功能，从而导致HNC中的ICI耐药。将[具体基因]状态纳入生物标志物面板可能会改善患者分层，并指导针对免疫逃逸和致癌通路的联合治疗。
