Abstract
Introduction:
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.
Methods:
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.
Results:
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.
Conclusions:
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.
Keywords:
Bioinformatics; Celecoxib; Differentially expressed genes; GEO database; Hepatocellular carcinoma; Immune infiltration; Key genes.