岭南现代临床外科2025，Vol.25Issue(1)：12-18,7.DOI:10.3969/j.issn.1009-976X.2025.01.003
基于GEO数据库的不完全射频消融后肝细胞癌关键基因的生物信息学研究
Bioinformatics of key genes in hepatocellular carcinoma after incomplete radiofrequency ablation using the GEO database
摘要
Abstract
Objective The aim of this study was to identify differentially expressed genes associated with IRFA-treated HCC and to provide potential therapeutic targets by comparing the gene expression pro-files of hepatocellular carcinoma(HCC)patients after incomplete radiofrequency ablation(IRFA)with those of HCC.Methods The GSE212604 dataset was downloaded from the GEO database and divided into IRFA and control groups according to whether they received IRFA treatment or not,and analysed and screened for differentially expressed genes.Potential key biological functions and pathways were iden-tified using functional pathway enrichment analysis(GO,KEGG).We also downloaded the GSE186280 dataset and constructed the co-expressed gene modules of HCC by weighted gene co-expression network analysis(WGCNA)to screen the core genes in the key modules.Results A total of 263 differentially expressed genes were identified,including 179 up-regulated genes and 84 down-regulated genes,and GO and KEGG analyses showed that these genes were mainly enriched in metabolic remodelling,cyto-skeletal regulation,immune regulation and neural-related mechanisms.In addition,WGCNA analysis identified gene modules closely related to HCC after IRFA,and further screened 15 core genes,includ-ing LOC112268313,RNA5-8SN3 and so on.Conclusion In this study,key genes associated with IRFA-treated HCC were identified by bioinformatics analysis,suggesting that immune signalling and pathways such as p53 and PPAR may play an important role in its occurrence and progression.These key genes and pathways are expected to be new targets for the treatment and diagnosis of HCC.关键词
肝细胞癌/不完全射频消融/差异表达基因/加权基因共表达网络分析Key words
hepatocellular carcinoma/incomplete radiofrequency ablation/differentially expressed genes/weighted gene co-expression network analysis分类
临床医学引用本文复制引用
张舟,黄碧,赵慧英..基于GEO数据库的不完全射频消融后肝细胞癌关键基因的生物信息学研究[J].岭南现代临床外科,2025,25(1):12-18,7.基金项目
国家自然科学基金面上项目(82371482) （82371482）
