Zhao Jiao, Sui Bai-Yan, Liu Xin, Ruan Min
School of Stomatology, Weifang Medical University. Weifang 261053, Shandong Province, China. E-mail:
Shanghai Kou Qiang Yi Xue. 2024 Aug;33(4):345-353.
To analyze the immune-related core genes differentially expressed in oral squamous cell carcinoma(OSCC) and construct an immune-related prognostic risk model for OSCC patients.
Weighted gene co-expression network analysis of RNA sequencing data from OSCC patients in the Cancer Genome Atlas (TCGA) database was conducted to identify immune-related modules and core genes. Core genes associated with immune prognosis were screened using univariate Cox regression analysis and survival analysis to construct an immune-related prognostic risk model for OSCC. The prognostic risk model's predictive ability was evaluated using Kaplan-Meier analysis, receiver operating characteristic curves, and external datasets from GSE41613. The expression of 8 immune prognostic core genes in tumor samples from OSCC patients was detected by real-time quantitative PCR assay(RT-qPCR), and the correlation between risk score and depth of invasion was assessed by calculating risk scores for OSCC patients. Statistical analysis was performed with SPSS 21.0 software package.
Prognostic risk model for OSCC was successfully constructed based on 8 immune prognostic core genes(CSF2RA, CLEC4C, COL5A3, CTSG, EDNRA, GPC4, GUCY1A2, ANGPT2). The prognostic risk model demonstrated perfect predictive value validated using Kaplan-Meier analysis, receiver operating characteristic curve, and the GSE41613 dataset. The risk scores of OSCC patients calculated based on this model were positively correlated with the depth of invasion, indicating that the model have the ability to predict the potential risk of OSCC.
An OSCC prognostic risk model is constructed based on the signatures of 8 immune prognostic core genes, which may effectively predict the prognosis of OSCC patients, providing an important reference for immune prevention of OSCC.
分析口腔鳞状细胞癌（OSCC）中差异表达的免疫相关核心基因，并构建OSCC患者的免疫相关预后风险模型。
对癌症基因组图谱（TCGA）数据库中OSCC患者的RNA测序数据进行加权基因共表达网络分析，以识别免疫相关模块和核心基因。使用单因素Cox回归分析和生存分析筛选与免疫预后相关的核心基因，构建OSCC的免疫相关预后风险模型。使用Kaplan-Meier分析、受试者工作特征曲线和来自GSE41613的外部数据集评估预后风险模型的预测能力。通过实时定量PCR检测（RT-qPCR）检测OSCC患者肿瘤样本中8个免疫预后核心基因的表达，并通过计算OSCC患者的风险评分评估风险评分与浸润深度之间的相关性。使用SPSS 21.0软件包进行统计分析。
基于8个免疫预后核心基因（CSF2RA、CLEC4C.COL5A3、CTSG、EDNRA、GPC4、GUCY1A2、ANGPT2）成功构建了OSCC的预后风险模型。预后风险模型在使用Kaplan-Meier分析、受试者工作特征曲线和GSE41613数据集验证时显示出完美的预测价值。基于该模型计算的OSCC患者风险评分与浸润深度呈正相关，表明该模型具有预测OSCC潜在风险的能力。
基于8个免疫预后核心基因的特征构建了OSCC预后风险模型，该模型可能有效预测OSCC患者的预后为OSCC的免疫预防提供重要参考。
