基于免疫相关基因的肝细胞癌预后模型的构建和验证
Construction and validation of a prognostic model of hepatocellular carcinoma based on immune-related genes
陈冬冬 1楼金金 2黄燕燕 1周璐 1李世波 3续力云1
作者信息
- 1. 温州医科大学附属舟山医院细胞分子生物学实验室
- 2. 温州医科大学研究生培养基地(舟山医院)
- 3. 温州医科大学附属舟山医院传染病科,浙江 舟山 316000
- 折叠
摘要
目的 构建一种基于免疫相关基因的肝细胞癌(LIHC)预后模型.方法 在UCSC Xena数据库和癌症基因组图谱(TCGA)数据库中下载肝癌和正常组织样本数据.对 LIHC样本和癌旁/正常样本的基因数据进行差异分析.对差异表达基因(DEGs)进行富集分析.使用TCGA队列中的肝癌样本进行Kaplan-Meier生存分析获得生存与免疫相关的差异表达基因,再采用LASSO Cox和多因素Cox回归分析构建基因风险预后模型.从高通量基因表达(GEO)数据库中获取数据用于外部验证.利用CellMiner数据库研究枢纽基因对常用抗肿癌药物的敏感性.结果 富集分析结果表明,差异表达基因主要与分解代谢相关.通过差异分析和Kaplan-Meier生存分析获得25 个生存与免疫相关的差异表达基因.再基于LASSO Cox和多因素Cox回归分析结果,获得 5 个枢纽基因(FYN、CSF3R、HLA-G、FOS和BIRC5),并构建列线图.训练队列和验证队列的一致性指数(C-index)值分别为 0.739 和0.625.根据枢纽基因与抗肿瘤药物的敏感性结果,选出 12 种抗肿瘤药物用于后续实验.结论 该模型能够有效预测LIHC患者的预后,为LIHC的免疫治疗提供了新的思路.
Abstract
Objective To construct a prognostic model for liver hepatocellular carcinoma(LIHC)based on immune-related genes.Methods LIHC and normal tissue samples were downloaded from the UCSC Xena database and The Cancer Genome Atlas(TCGA)database.Differential analysis was performed on the gene data of LIHC samples and adjacent/normal samples.Enrichment analysis was conducted on differentially expressed genes.Kaplan-Meier survival analysis was performed on liver cancer samples from the TCGA cohort to obtain survival-and immune-related differentially expressed genes.LASSO Cox and multivariate Cox regression analysis were used to identify hub genes and construct a gene risk prognostic model.Data from a high-throughput gene expression(GEO)database was obtained for external validation.The sensitivity of hub genes to common anticancer drugs was investigated using the CellMiner database.Results Enrichment analysis result indicated that differentially expressed genes were mainly associated with metabolic pathways.Through differential analysis and Kaplan-Meier survival analysis,25 survival-and immune-related differentially expressed genes were obtained.Based on the result of LASSO Cox and multivariate Cox regression analysis,five hub genes(FYN,CSF3R,HLA-G,FOS,BIRC5)were identified and a nomogram was constructed.The concordance index(C-index)value for the training cohort and validation cohort were 0.739 and 0.625,respectively.Based on the sensitivity of hub genes to anticancer drugs,12 types of anticancer drugs were selected for subsequent experiments.Conclusion This model can effectively predict the prognosis of LIHC patients and provide a new insights for immune therapy in LIHC.
关键词
肝细胞癌/免疫浸润/列线图/免疫检查点基因/药敏试验/富集分析/Cox回归分析Key words
Liver hepatocellular carcinoma/Immune infiltration/Nomogram/Immune check-point gene/Drug sensitivity test/Enrichment analysis/Cox regression analysis引用本文复制引用
基金项目
国家卫生健康委科研项目()
浙江省医药卫生重大科技计划(WKJ-ZJ-2329)
出版年
2024
NETL
NSTL
万方数据