摘要
目的探讨焦亡相关基因(PRGs)在宫颈鳞癌(CSCC)中的作用,构建预后模型,分析其与CSCC免疫浸润的相关性,为患者预后预测及个性化治疗提供依据。方法从癌症基因组图谱(TCGA)数据库中获取253例CSCC患者的RNA测序数据及相应的临床特征。正常宫颈上皮组织样本RNA测序数据从基因型组织表达数据库下载。利用26个在宫颈鳞癌和正常宫颈组织中差异表达的PRGs将所有CSCC分为高危组和低危组。通过单因素、最小绝对收缩和选择算子回归(LASSO)和多因素COX回归分析,建立预后模型。采用决策曲线分析和Kaplan-Meier生存分析评价模型的有效性。通过基因富集分析发现PRGs在CSCC中的潜在分子机制。同时分析PRGs与CSCC免疫细胞浸润的关系。结果在26个PRGs中筛选出3个具有预后价值的基因(GSDMB、IL1B和PRKACA)来构建模型[风险分数=(-0.2157)×GSDMB+(0.2418)×IL1B+(-0.2219)×PRKACA]。该模型将CSCC患者分为高风险组与低风险组,以风险评分中位值为截断值评估CSCC的风险,提示高危评分的CSCC患者总生存时间低于低危评分的CSCC患者(P=0.003)。预后模型1、3、5 a的受试者工作特征曲线的曲线下面积分别为0.782、0.631和0.643,证明该预后模型是预测宫颈鳞癌预后的良好指标。建立列线图表明预测生存与实际观察结果具有较好一致性。另外,高风险评分的患者通常具有较低水平的免疫细胞浸润。结论PRGs可能在CSCC中发挥关键作用,并为CSCC的潜在治疗机制提供新的见解。
Objective To investigate the role of pyroptosis-related genes(PRGs)in cervical squamous cell carcinoma(CSCC),to construct a prognostic model,and to analyze its correlation with immune infiltration of CSCC,so as to provide basis for prognosis prediction and personalized treatment of patients.Methods The RNA sequencing data and the corresponding clinical features from 253 CSCC patients were obtained from The Cancer Genome Atlas(TCGA)database.The RNA sequencing data from the normal human cervical samples were downloaded from the Genotype-Tissue Expression database.According to 26 PRGs identified differentially expressed between CSCC and normal cervical tissues,all the CSCC patients were divided into the high-risk group and the low-risk group.Through univariate,least absolute shrinkage and selection operator(LASSO),and multivariate Cox regression analyses,a three-gene signature was established.The validity of the signature was evaluated by decision curve analysis and Kaplan-Meier survival analysis.The underlying molecular mechanism of the PRGs in CSCC was discovered via gene enrichment analysis.the relationship between PRGs and immune cell infiltration in CSCC patients were respectively analyzed.Results Three genes(GSDMB,IL1B,and PRKACA)among the 26 PRGs were identified to construct a prognostic signature[Risk score=(-0.2157)×GSDMB+(0.2418)×IL1B+(-0.2219)×PRKACA].The model divided CSCC patients into the high-risk group and the low-risk group,and the median risk score was taken as the cut-off value to evaluate the risk of CSCC,suggesting that the overall survival of CSCC patients with high-risk score was lower than that of CSCC patients with low-risk score(P=0.003).The area under curve of receiver operating characteristic curve of the prognostic model was 0.782,0.631 and 0.643,respectively,indicating that the prognostic model was a good predictor of the prognosis of CSCC.The establishment of a nomogram showed that the predicted survival was in good agreement with the actual observation results.In addition,patients
作者
王琦
王媛
饶石磊
WANG Qi;WANG Yuan;RAO Shilei(Department of Oncology,Nanyang Central Hospital,Nanyang 473000,China;Department of Radiotherapy,Nanyang Central Hospital,Nanyang 473000,China)
出处
《肿瘤基础与临床》
2024年第2期165-171,共7页
journal of basic and clinical oncology
关键词
生物信息学
宫颈鳞癌
焦亡
预后模型
免疫微环境
bioinformatics
cervical squamous cell carcinoma
pyroptosis
prognostic model
immune microenvironment
