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基于G蛋白偶联受体基因的头颈部鳞状细胞癌预后模型的建立与验证
作者:王海宁1  孙婷婷2  陈晓艳2  秦涛2  周宓1 2 
单位:1. 青岛大学 医学部, 山东 青岛 266071;
2. 山东省青岛市市立医院 肿瘤科, 山东 青岛 266071
关键词:头颈部鳞状细胞癌 G蛋白偶联受体基因 预后模型 风险评分 癌症基因组图谱 
分类号:R739.6
出版年·卷·期(页码):2024·52·第四期(537-543)
摘要:

目的:建立G蛋白偶联受体(GPCRs)相关基因的头颈部鳞状细胞癌(HNSCC)预后风险评分模型。方法:从癌症基因组图谱(TCGA)数据库筛选HNSCC差异表达的GPCRs相关基因,并通过Cox和Lasso算法筛选得到8个关键预测基因。使用R软件建立风险评分模型并验证其预测效能。结果:与低风险组相比,高风险组患者的总生存期(OS)更短,死亡率更高,癌组织中的CD8+T细胞浸润水平更差(P<0.001)。风险评分模型1、3、5年OS的AUC分别为0.669、0.723和0.681。在OS、疾病特异性生存期(DSS)和无进展间隔期(PFI)方面,生存患者的风险评分均低于死亡患者(P<0.001)。多因素回归分析显示风险评分和年龄是影响HNSCC患者OS的独立危险因素(P<0.001)。纳入风险评分和年龄建立的列线图模型预测曲线与实际参考线的一致性较好。决策曲线分析(DCA)显示,风险评分模型和列线图模型均有助于提升1年、3年、5年的临床净收益。结论:由8个GPCRs相关基因组成的HNSCC预后模型具有良好的预测能力,为HNSCC的预后预测和临床治疗风险分层提供了一种新的方法。

Objective: To construct a prognostic risk score model for head and neck squamous cell carcinoma(HNSCC) patients based on G protein-coupled receptor(GPCRs) related genes. Methods: The differentially expressed GPCRs related genes of HNSCC were screened from the Cancer Genome Atlas(TCGA) database, and eight predicted genes were selected by Cox and Lasso algorithms. R soft was used to construct a risk score model and verify its predictive efficacy. Results: Compared with the low-risk group, patients in the high-risk group had shorter overall survival(OS), higher mortality, and worse CD8+T cell infiltration in cancer tissues(P<0.001). The AUC of 1-, 3-, and 5-year OS of the risk score model was 0.669, 0.723, and 0.681, respectively. In terms of OS, disease specific survival(DSS), and progression free interval(PFI), the risk scores of survival patients were lower than those of death patients(P<0.001). Multivariate regression analysis showed that risk score and age were independent risk factors for OS in HNSCC patients(P<0.001). The predicted curve of the nomogram model incorporating the risk score and age was in good agreement with the actual reference line. The decision curve analysis(DCA) showed that the risk score model and the nomogram model helped to improve the clinical net benefit in the prediction period of 1 year, 3 years, and 5 years. Conclusion: The HNSCC prognostic model based on the eight GPCRs related genes has good prediction efficiency, which provides a new tool for risk stratification and prognosis prediction of HNSCC clinical treatment.

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