基于失巢凋亡相关基因的结肠癌预后模型构建及验证  

Construction and validation of a prognostic model for colon cancer based on anoikis-related genes

作　　者：张涛 李子尧 孙莹莹[1] 李博洋 王昭 杨致富 Zhang Tao;Li Ziyao;Sun Yingying;Li Boyang;Wang Zhao;Yang Zhifu(Department of Surgery 1,Xiyuan Hospital,China Academy of Chinese Medical Sciences,Beijing 100091,China)

机构地区：[1]中国中医科学院西苑医院外一科,北京100091

出　　处：《肿瘤研究与临床》2025年第1期55-63,共9页Cancer Research and Clinic

基　　金：北京市自然科学基金面上项目(7242237)。

摘　　要：目的构建基于差异表达的失巢凋亡相关基因的结肠癌预后模型并验证,初步探讨失巢凋亡相关基因与结肠癌肿瘤免疫微环境的关系。方法从癌症基因组图谱(TCGA)数据库下载建库至2024年7月结肠癌患者472个肿瘤组织样本、41个正常组织样本RNA测序数据和临床数据。通过GeneCards数据库筛选出919个与失巢凋亡相关的基因,取其与TCGA数据库中筛选的结肠癌和正常结肠组织的RNA测序基因数据集共有基因,以P<0.05从中筛选出结肠癌和正常结肠组织间差异表达的失巢凋亡相关基因;进一步通过单因素Cox比例风险模型从中筛选出与TCGA数据库有预后数据的446例结肠癌患者预后相关的基因,再用LASSO-Cox比例风险模型从中继续筛选出P<0.05的基因并构建结肠癌预后模型。根据预后模型计算TCGA数据库上述446例结肠癌患者风险评分,按中位风险评分分为低风险(<中位值)组和高风险(≥中位值)组,采用Kaplan-Meier法分析两组总生存;基于R软件的timeROC程序包分析应用风险评分预测TCGA数据库结肠癌患者1、2、3年总生存的效能。依据TCGA数据库结肠癌患者中位风险评分将国际癌症基因组联盟(ICGC)数据库结肠癌患者分为高、低风险组,通过Kaplan-Meier法和受试者工作特征(ROC)曲线外部验证预后模型的预测效果。使用R软件相关程序包,对TCGA数据库中根据预后模型风险评分区分的预后低风险组与高风险组间差异表达基因进行免疫细胞及免疫功能的单样本基因集富集分析(ssGESA),比较各免疫分型(包括炎症反应型、创伤愈合型、干扰素γ为主型、淋巴细胞耗竭型)患者风险评分差异,对肿瘤微环境中的免疫细胞与基质细胞浸润与风险评分的相关性进行分析;基于肿瘤免疫功能与排斥(TIDE)数据库对预后模型风险评分与程序性死亡受体配体1(PD-L1)基因表达量的关系进行分析。结果结合GeneCards数据库失巢凋ObjectiveTo construct and validate a prognostic model of colon cancer based on differentially expressed anoikis-related genes,and to preliminarily investigate the relationship between anoikis-related genes and the tumor immune microenvironment of colon cancer.MethodsA total of 472 cancer tissues samples of patients with colon cancer,RNA sequencing data and clinical data of 41 normal tissues samples were downloaded from the Cancer Genome Atlas(TCGA)database between the establishment time and July in 2024.A total of 919 genes related to anoikis were screened out from GeneCards database,and the common genes were selected from the RNA sequencing gene datasets of colon cancer and normal colon tissues in the TCGA database,among which the differentially expressed anoikis-related genes of colon cancer and normal colon tissues were screened out based on P<0.05.Furthermore,genes related to the prognosis of 446 colon cancer patients with prognostic data in the TCGA database were screened by using univariate Cox proportional risk model;the genes with P<0.05 were further screened out and a colon cancer prognosis model was constructed by using LASSO-Cox proportional risk model.The risk score of the above 446 colon cancer patients in the TCGA database was calculated according to the prognostic model,and the patients were divided into high-risk(≥median value)group and low-risk(<median value)group according to the median risk score,and the overall survival of the 2 groups was analyzed by using the Kaplan-Meier method.The risk score based on R software-based time ROC program package was used to predict 1-year,2-year,3-year overall survival therapeutic efficacy of colon cancer patients in the TCGA database.According to the median risk score of colon cancer patients in the TCGA database,the patients in the International Cancer Genome Consortium(ICGC)database were divided into high-risk group and low-risk group.Kaplan-Meier method and receiver operating characteristic(ROC)curve were used to verify the predictive effect of the progn

关 键 词：结肠肿瘤 Anoikis凋亡 预后 肿瘤微环境 免疫 

分 类 号：R735.35[医药卫生—肿瘤]