基于免疫相关基因的肝细胞癌预后模型的构建和验证

陈冬冬; 楼金金; 黄燕燕; 周璐; 李世波; 续力云

doi:10.16098/j.issn.0529-1356.2024.03.009

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解剖学报 ›› 2024, Vol. 55 ›› Issue (3) : 319-328. DOI: 10.16098/j.issn.0529-1356.2024.03.009

肿瘤生物学

基于免疫相关基因的肝细胞癌预后模型的构建和验证

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 +

Construction and validation of a prognostic model of hepatocellular carcinoma based on immune-related genes

CHEN Don-dong1 LOU Jin-jin2 HUANG Yan-yan1 ZHOU Lu1 LI Shi-bo3 XU Li-yun1*

Author information +

文章历史 +

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.

导出引用

陈冬冬楼金金黄燕燕周璐李世波续力云. 基于免疫相关基因的肝细胞癌预后模型的构建和验证[J]. 解剖学报. 2024, 55(3): 319-328 https://doi.org/10.16098/j.issn.0529-1356.2024.03.009

CHEN Don-dong LOU Jin-jin HUANG Yan-yan ZHOU Lu LI Shi-bo XU Li-yun. Construction and validation of a prognostic model of hepatocellular carcinoma based on immune-related genes [J]. Acta Anatomica Sinica. 2024, 55(3): 319-328 https://doi.org/10.16098/j.issn.0529-1356.2024.03.009

中图分类号： R730.1

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