文献类型：期刊文献

中文题名：结肠癌免疫相关基因对预后模型构建及预后的相关性分析

英文题名：Construction of prognosis model and correlation analysis between immune-related gene pairs and prognosis in colon cancer

作者：李高勤[1];雍文兴[2];牛帆[1];苏欢[1];宋忠阳[1];王淼[1];杜婷婷[1];金娟[1];张志明[2]

第一作者：李高勤

机构：[1]甘肃中医药大学,甘肃兰州730000;[2]甘肃中医药大学附属医院,甘肃兰州730000

第一机构：甘肃中医药大学

年份：2021

卷号：25

期号：2

起止页码：210

中文期刊名：生物医学工程与临床

外文期刊名：Biomedical Engineering and Clinical Medicine

收录：CSTPCD

基金：甘肃省中西医结合肿瘤临床医学研究中心项目(18JR2FA001)。

语种：中文

中文关键词：结肠癌;总生存期;预后模型;免疫相关基因对(IRGP)

外文关键词：colon cancer;overall survival(OS);prognosis model;immune-related gene pairs(IRGP)

摘要：目的结肠癌作为常见的消化道恶性肿瘤,越来越多的证据表明结肠癌预后与免疫系统之间存在相关性。实验目的是建立一个稳健的免疫相关基因对(IRGP)预后模型来评估结肠癌患者的总生存期(OS)。方法从TCGA、GEO 2个数据库下载结肠癌患者的基因表达谱和临床信息,将两组数据分别规定为Training组和Testing组。按照中位数绝对偏差(MAD)>0.5筛选差异基因,并与Imm Port数据库下载的免疫相关基因取交集筛选免疫表达基因。对每个样品中筛选的免疫相关基因进行两两配对构建IRGP,进行Lasso Cox比例风险回归和10倍交叉验证,计算免疫相关基因对系数(IRGPI)以构建IRGP预后模型。用受试者工作特性(ROC)曲线分析来确定1年总生存率的IRGPI的最佳cut-off值。根据cut-off值将患者分为高免疫风险组与低免疫风险组。运用单变量和多变量Cox比例风险回归分析评估IRGPI对其他临床因素的预测能力。采用在线分析工具Ciber Sort评估了22种免疫细胞在不同风险组中相对比例。采用g Profiler和Bioconductor包fgsea对预后免疫相关基因进行基因本体(GO)分析和基因集富集分析(GSEA)。结果在2499个免疫相关基因中,有56对免疫相关基因与Testing组OS显著相关(P<0.001)。在Testing组中,以IRGP预后模型cut-off值-0.562将患者分为高免疫风险组和低免疫风险组,两组差异有统计学意义(P=0.015)。在单因素Cox分析中,IRGP模型风险值与肿瘤分期等临床特征对预后有影响。在多因素Cox分析中IRGP模型风险值可以作为独立预后因素。对预后免疫相关基因进行GO分析和GSEA发现,高免疫风险组基因涉及对刺激的反应、细胞周期调控、多种RNA加工处理等多种生物学过程。免疫细胞浸润分析显示未活化的CD4+记忆性T细胞、活化的自然杀伤细胞、嗜酸性粒细胞在不同免疫风险组之间差异表达。结论实验成功构建了对结肠癌有预后价值的IRGP预后模型,为结肠癌的治疗与预后评估提供新的见解与思路。
Objective To construct the immune-related gene pairs(IRGP)prognosis model for evaluation of overall survival(OS)in colon cancer patients,under the consideration that as common malignant tumor of digestive tract,more and more evidence showed that colon cancer prognosis has correlation to immune system.Methods The gene expression profiles and clinical information of colon cancer patients were downloaded from TCGA and GEO databases,which were defined as Training group and Testing group,respectively.The differential genes were screened by median absolute deviation(MAD)>0.5,and immune ex-pression genes were selected for intersection with immune-related genes downloaded from Imm Port database.The selected immune-related genes in each sample were paired to construct IRGP,the Lasso Cox proportional hazard regression and 10 fold cross validation were performed to calculate IRGP index(IRGPI)and construct IRGP prognosis model.The receiver operating characteristic(ROC)curve was used to determine the best cut-off value of IRGPI for 1-year OS rate.All of patients were divided into high immune risk group and low immune risk group by cut-off value.The univariate and multivariate Cox proportional hazards regression analysis was used to evaluate the predictive ability of IRGPI for other clinical factors.Ciber Sort,an online analysis tool,was used to evaluate the relative proportion of 22 immune cells in different immune risk groups.The g Profiler and Bioconductor package fgsea were used to perform gene ontology(GO)analysis and gene set enrichment analysis(GSEA)on prognostic immune-related genes.Results Among 2499 immune-realted genes,56 pairs of immune-realted genes were significantly correlated with OS in Testing group(P<0.001).In Testing group,the patients were divided into high immune risk group and low immune risk group by cut-off value of-0.562,and the difference was statistically significant between 2 groups(P=0.015).In univariate Cox analysis,the risk value of IRGP prognosis model and clinical characteristics such as tumor stage had effect on prognosis.In multivariate Cox analysis,IRGP prognosis model risk value could be used as independent prognostic factor.The GO analysis and GSEA results showed that high immune risk group genes were involved in a variety of biological processes,such as response to stimulation,cell cycle regulation and multiple RNA processing.The immunocyte infiltration analysis results showed that the expression of inactive CD4+memory T cells,activated natural killer cells and eosinophils expressed differently among different immune risk groups.Conclusion It is demonstrated that IRGP model with prognostic value for colon cancer is successfully constructed in the experiment,and it provides novel insights and ideas for treatment and prognosis evaluation of colon cancer.