Gu Wang, Zeng Dongyun, Zhang Chao
Hepatological Surgery Department, The First Affiliated Hospital of Anhui Medical University, 218 Jixi Road, Shushan District, Hefei City, 230032, Anhui Province, China.
Clinicopathological Diagnosis and Research Center, The Affiliated Hospital of Youjiang Medical University for Nationalities, Baise, China.
Discov Oncol. 2024 Jul 31;15(1):321. doi: 10.1007/s12672-024-01203-w.
Hepatocellular carcinoma (HCC) is a common and fatal cancer, and its molecular mechanisms are still not fully understood. This study aimed to explore the potential molecular mechanisms and immune infiltration characteristics of celecoxib combined with sorafenib in the treatment of HCC by analyzing the differentially expressed genes (DEGs) from the GSE45340 dataset in the GEO database and identifying key genes.
The GSE45340 dataset was downloaded from the GEO database, and DEGs were screened using GEO2R, and visualization and statistical analysis were performed. Metascape was used to perform functional annotation and protein-protein interaction network analysis of DEGs. The immune infiltration was analyzed using the TIMER database, and the expression of key genes and their relationship with patient survival were analyzed and verified using the UALCAN database.
A total of 2181 DEGs were screened through GEO2R analysis, and heat maps were drawn for the 50 genes with the highest expression. Metascape was used for enrichment analysis, and the enrichment results of KEGG and GO and the PPI network were obtained, and 44 core genes were screened. Analysis of the TIMER database found that 12 genes were closely related to tumor immune infiltration. UALCAN analysis further verified the differential expression of these genes in HCC and was closely related to the overall survival of patients.
Through comprehensive bioinformatics analysis, this study identified a group of key genes related to the treatment of HCC with celecoxib combined with sorafenib. These genes play an important role in tumor immune infiltration and patient survival, providing important clues for further studying the molecular mechanism of HCC and developing potential therapeutic targets.
肝细胞癌(HCC)是一种常见的致命性癌症,其分子机制仍未完全明确。本研究旨在通过分析GEO数据库中GSE45340数据集的差异表达基因(DEG)并鉴定关键基因,探讨塞来昔布联合索拉非尼治疗HCC的潜在分子机制和免疫浸润特征。
从GEO数据库下载GSE45340数据集,使用GEO2R筛选DEG,并进行可视化和统计分析。使用Metascape对DEG进行功能注释和蛋白质-蛋白质相互作用网络分析。使用TIMER数据库分析免疫浸润情况,并使用UALCAN数据库分析关键基因的表达及其与患者生存的关系并进行验证。
通过GEO2R分析共筛选出2181个DEG,绘制了表达量最高的50个基因的热图。使用Metascape进行富集分析,获得了KEGG和GO的富集结果以及PPI网络,并筛选出44个核心基因。TIMER数据库分析发现12个基因与肿瘤免疫浸润密切相关。UALCAN分析进一步验证了这些基因在HCC中的差异表达,并与患者的总生存密切相关。
通过综合生物信息学分析,本研究鉴定出一组与塞来昔布联合索拉非尼治疗HCC相关的关键基因。这些基因在肿瘤免疫浸润和患者生存中发挥重要作用,为进一步研究HCC的分子机制和开发潜在治疗靶点提供了重要线索。