摘要
目的探究焦亡相关差异表达基因(DEGs)在乳腺癌中预后价值并构建预后风险模型。方法从癌症基因组图谱(TCGA)和肿瘤基因表达数据库(GEO)官网下载乳腺癌的基因测序、临床数据,筛选焦亡相关DEGs。将乳腺癌患者进行聚类分析。在TCGA队列中以最小绝对收缩和选择算子(LASSO)方法建立模型。利用Kaplan-Meier生存曲线、受试者工作特征曲线(ROC)、单因素及多因素Cox回归独立预后因素分析等评价该模型。GEO队列为验证集。通过GO、KEGG、ssGSEA分析风险DEGs的富集情况。结果筛选出焦亡相关DEGs,聚类分析可见C2组总生存期(OS)延长,差异有统计学意义(P=0.020)。该模型K-M生存分析显示,高风险组OS缩短(TCGA队列中P<0.001,GEO队列中P=0.018)。ROC曲线下面积(AUC)表明该模型具有一定预测能力。单因素、多因素Cox回归分析表明,年龄,M、N分期和风险评分为OS的独立预测因子。GO、KEGG富集与ssGSEA分析证实了风险相关DEGs与免疫炎症因子和通路有关。结论研究构建了由9个焦亡相关基因组成的乳腺癌预后风险模型,为乳腺癌患者的风险预后评估提供了参考。
Objective To explore the prognostic value of pyroptosis-related differentially expressed genes(DEGs)in breast cancer and to construct a prognostic risk model.Methods Gene sequencing and clinical data of breast cancer were downloaded from The Cancer Genome Atlas(TCGA)and Gene Expression Ominibus(GEO)to screen for pyroptosis-related DEGs.A cluster analysis was performed on breast cancer patients.The model of TCGA cohort was established by the least absolute shrinkage and selection operator(LASSO)method,which was then evaluated with Kaplan-Meier survival curve,receiver operating characteristic curve(ROC),univariate and multivariate Cox regression independent prognostic factor analysis.The GEO cohort was used as the validation set.Enrichment of DGEs was analyzed with GO,KEGG,and ssGSEA.Results Pyroptosis-related DEGs were screened,cluster analysis showed that the overall survival(OS)of C2 group was prolonged,and the difference was statistically significant(P=0.020).K-M survival analysis showed that OS was shortened in the high-risk group(P<0.001 in the TCGA cohort,P=0.018 in the GEO cohort).The area under the ROC curve(AUC)showed that the model had certain predictive ability.Univariate and multivariate Cox regression showed that age,M and N stage,and risk score were independent predictors of OS.GO,KEGG and ssGSEA analyses confirmed that pyroptosis-related DEGs were related to immune inflammatory factors and pathways.Conclusion This study constructed a prognostic risk model of breast cancer composed of 9 pyroptosis-related genes,which can provide reference for the risk and prognosis assessment of breast cancer patients.
作者
贺士卿
李皖皖
董书晴
牟婧怡
刘宇莹
魏思雨
刘钊
张家新
HE Shiqing;LI Wanwan;DONG Shuqing;MOU Jingyi;LIU Yuying;WEI Siyu;LIU Zhao;ZHANG Jiaxin(Department of Thyroid and Breast Surgery,The Affiliated Hospital of Xuzhou Medical University,Xuzhou 221004,Jingsu,China)
出处
《山东大学学报（医学版）》
CAS
北大核心
2022年第8期34-43,共10页
Journal of Shandong University:Health Sciences
基金
中国乳腺肿瘤青年学者科研项目(CYBER-2021-010)
徐州市重点研发计划(KG21218)
江苏省研究生科研与实践创新计划项目(SJCX22-1266)
关键词
乳腺癌
焦亡
免疫
预后
预测模型
Breast cancer
Pyroptosis
Immunity
Prognosis
Prediction model
作者简介
通信作者:刘钊。E-mail:xylzhao9999@163.com;通信作者:张家新。E-mail:zhangjiaxin1969@163.com
