Department of Radiation Oncology, The Affiliated Hospital of Qingdao University, Qingdao, Shandong, China.
J Biol Regul Homeost Agents. 2021 May-Jun;35(3):975-986. doi: 10.23812/21-14-A.
This study aimed to screen the key immune-related genes (IRGs) in head and neck squamous cell carcinoma (HNSC) and construct the IRGs-related prognostic model to predict the overall survival (OS) of patients with HNSC. The RNA-seq data and clinical data were downloaded from The Cancer Genome Atlas database, and IRGs were obtained from the Immunology Database and Analysis Portal. Differentially expressed genes (DEGs) between HNSC and normal samples were identified, followed by integration with IRGs to screen differentially expressed IRGs. After univariate and multivariate proportional hazard regression analyses, an IRG-based risk model was constructed. Meanwhile, data chip of GSE65858 as the validation set to assess the predicted performance of established model. Next, univariate and multivariate Cox regression analyses were performed to identify the independent prognostic factor of HNSC, and the Nomogram model was developed to predict patient outcome. Furthermore, the correlation between immune cell infiltration and risk score was analyzed. A total of 65 differently expressed IRGs associated with prognosis of HNSC were screened, and finally a 26-gene IRG signature was identified to construct a prognostic prediction model. The AUC of ROC curve was 0.750. Survival analysis showed that patients in the high-risk group had a worse prognosis. Independent prognostic analysis showed that risk score could be considered as an independent predictor for HNSC prognosis. Nomogram assessment showed that the model had high reliability for predicting the survival of patients with HNSC in 1, 2, 3 years. Ultimately, the abundance of B cells and CD4+ T cell infiltration in HNSC showed negative correlations with risk score. Our IRG-based prognostic risk model may be used to estimate the prognosis of HNSC patients.
本研究旨在筛选头颈部鳞状细胞癌（HNSC）中的关键免疫相关基因（IRGs），并构建 IRGs 相关预后模型，以预测 HNSC 患者的总生存期（OS）。从癌症基因组图谱数据库下载 RNA-seq 数据和临床数据，并从免疫数据库和分析门户获取 IRGs。鉴定 HNSC 与正常样本之间的差异表达基因（DEGs），然后与 IRGs 整合以筛选差异表达的 IRGs。经过单因素和多因素比例风险回归分析，构建了基于 IRG 的风险模型。同时，使用 GSE65858 芯片作为验证集，评估建立模型的预测性能。接下来，进行单因素和多因素 Cox 回归分析，以确定 HNSC 的独立预后因素，并开发诺莫图模型以预测患者的结局。此外，分析了免疫细胞浸润与风险评分的相关性。筛选出 65 个与 HNSC 预后相关的差异表达 IRGs，最终确定了一个 26 基因的 IRG 特征来构建预后预测模型。ROC 曲线的 AUC 为 0.750。生存分析表明，风险评分较高的患者预后较差。独立预后分析表明，风险评分可以作为 HNSC 预后的独立预测因子。诺莫图评估表明，该模型对预测 HNSC 患者 1、2、3 年的生存具有较高的可靠性。最终，HNSC 中 B 细胞和 CD4+T 细胞浸润的丰度与风险评分呈负相关。我们的基于 IRG 的预后风险模型可用于估计 HNSC 患者的预后。
