State Key Laboratory of Oral Diseases, National Center of Stomatology, National Clinical Research Center for Oral Diseases, Frontier Innovation Center for Dental Medicine Plus, West China Hospital of Stomatology, Sichuan University, Chengdu 610041, China.
Int J Mol Sci. 2023 Feb 7;24(4):3317. doi: 10.3390/ijms24043317.
Over 80% of head and neck squamous cell carcinoma (HNSCC) patients failed to respond to immunotherapy, which can likely be attributed to the tumor microenvironment (TME) remolding mediated by chemokines/chemokine receptors (C/CR). This study aimed to establish a C/CR-based risk model for better immunotherapeutic responses and prognosis. After assessing the characteristic patterns of the C/CR cluster from the TCGA-HNSCC cohort, a six-gene C/CR-based risk model was developed to stratify patients by LASSO Cox analysis. The screened genes were multidimensionally validated by RT-qPCR, scRNA-seq, and protein data. A total of 30.4% of patients in the low-risk group had better responses to anti-PD-L1 immunotherapy. A Kaplan-Meier analysis showed that patients in the low-risk group had longer overall survival. A time-dependent receiver operating characteristic curve and Cox analyses indicated that risk score served as an independent predictive indicator. The robustness of the immunotherapy response and prognosis prediction was also validated in independent external datasets. Additionally, the TME landscape revealed that the low-risk group was immune activated. Furthermore, the cell communication analysis on the scRNA-seq dataset revealed that cancer-associated fibroblasts were the main communicators within the C/CR ligand-receptor network of TME. Collectively, The C/CR-based risk model simultaneously predicted immunotherapeutic response and prognosis, potentially optimizing personalized therapeutic strategies of HNSCC.
超过 80%的头颈部鳞状细胞癌 (HNSCC) 患者对免疫疗法没有反应,这可能归因于趋化因子/趋化因子受体 (C/CR) 介导的肿瘤微环境 (TME) 重塑。本研究旨在建立一个基于 C/CR 的风险模型,以更好地预测免疫治疗反应和预后。在评估 TCGA-HNSCC 队列中 C/CR 簇的特征模式后,通过 LASSO Cox 分析,开发了一个基于六个基因的 C/CR 风险模型来对患者进行分层。通过 RT-qPCR、scRNA-seq 和蛋白质数据对筛选出的基因进行了多维验证。在低风险组中,30.4%的患者对抗 PD-L1 免疫疗法有更好的反应。Kaplan-Meier 分析表明,低风险组患者的总生存期更长。时间依赖性接收器操作特征曲线和 Cox 分析表明,风险评分是一个独立的预测指标。在独立的外部数据集也验证了免疫治疗反应和预后预测的稳健性。此外,TME 景观揭示了低风险组的免疫激活状态。此外,对 scRNA-seq 数据集的细胞通讯分析表明,在 TME 的 C/CR 配体-受体网络中,癌症相关成纤维细胞是主要的通讯者。总之,基于 C/CR 的风险模型可同时预测免疫治疗反应和预后,可能优化 HNSCC 的个性化治疗策略。