Table_3_Identification of the Nerve-Cancer Cross-Talk-Related Prognostic Gene Model in Head and Neck Squamous Cell Carcinoma.xlsx

The incidence of head and neck squamous cell carcinoma (HNSC) is increasing year by year. The nerve is an important component of the tumor microenvironment, which has a wide range of cross-talk with tumor cells and immune cells, especially in highly innervated organs, such as head and neck cancer and pancreatic cancer. However, the role of cancer-nerve cross-talk-related genes (NCCGs) in HNSC is unclear. In our study, we constructed a prognostic model based on genes with prognostic value in NCCGs. We used Pearson’s correlation to analyze the relationship between NCCGs and immune infiltration, microsatellite instability, tumor mutation burden, drug sensitivity, and clinical stage. We used single-cell sequencing data to analyze the expression of genes associated with stage in different cells and explored the possible pathways affected by these genes via gene set enrichment analysis. In the TCGA-HNSC cohort, a total of 23 genes were up- or downregulated compared with normal tissues. GO and KEGG pathway analysis suggested that NCCGs are mainly concentrated in membrane potential regulation, chemical synapse, axon formation, and neuroreceptor-ligand interaction. Ten genes were identified as prognosis genes by Kaplan-Meier plotter and used as candidate genes for LASSO regression. We constructed a seven-gene prognostic model (NTRK1, L1CAM, GRIN3A, CHRNA5, CHRNA6, CHRNB4, CHRND). The model could effectively predict the 1-, 3-, and 5-year survival rates in the TCGA-HNSC cohort, and the effectiveness of the model was verified by external test data. The genes included in the model were significantly correlated with immune infiltration, microsatellite instability, tumor mutation burden, drug sensitivity, and clinical stage. Single-cell sequencing data of HNSC showed that CHRNB4 was mainly expressed in tumor cells, and multiple metabolic pathways were enriched in high CHRNB4 expression tumor cells. In summary, we used comprehensive bioinformatics analysis to construct a prognostic gene model and revealed the potential of NCCGs as therapeutic targets and prognostic biomarkers in HNSC.

头颈部鳞状细胞癌（head and neck squamous cell carcinoma, HNSC）的发病率逐年攀升。神经作为肿瘤微环境的重要组成部分，与肿瘤细胞、免疫细胞存在广泛的交叉对话，在神经高度富集的器官（如头颈部癌、胰腺癌）中尤为显著。然而，癌症-神经交叉对话相关基因（nerve cross-talk-related genes, NCCGs）在头颈部鳞状细胞癌中的作用仍未明确。

本研究基于NCCGs中具有预后价值的基因构建了预后预测模型。我们采用Pearson相关分析，探究了NCCGs与免疫浸润、微卫星不稳定、肿瘤突变负荷、药物敏感性及临床分期之间的关联；利用单细胞测序数据，分析了分期相关基因在不同细胞类群中的表达特征，并通过基因集富集分析（gene set enrichment analysis）探索了这些基因可能参与的调控通路。

在TCGA-HNSC队列中，相较于正常组织，共计23个基因存在表达上调或下调差异。GO与KEGG通路富集分析结果显示，NCCGs主要富集于膜电位调控、化学突触、轴突形成以及神经受体-配体相互作用等通路。通过Kaplan-Meier绘图仪筛选得到10个预后相关基因，将其作为LASSO回归的候选基因，最终构建了包含7个基因的预后模型（NTRK1、L1CAM、GRIN3A、CHRNA5、CHRNA6、CHRNB4、CHRND）。

该模型可有效预测TCGA-HNSC队列患者的1年、3年及5年生存率，且模型的预测效能通过外部测试数据集得到了验证。模型所纳入的基因与免疫浸润、微卫星不稳定、肿瘤突变负荷、药物敏感性及临床分期均存在显著相关性。头颈部鳞状细胞癌的单细胞测序数据显示，CHRNB4主要在肿瘤细胞中表达，且高表达CHRNB4的肿瘤细胞富集于多条代谢通路。

综上，本研究通过综合生物信息学分析构建了预后基因模型，并揭示了NCCGs作为头颈部鳞状细胞癌治疗靶点与预后生物标志物的潜在应用价值。