ArticleIn silico pharmacology2024
Hub gene identification and immune infiltration analysis in hepatocellular carcinoma: Computational approach.
Article in In silico pharmacology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
In the case of hepatocellular carcinoma, there is a need to find novel immune biomarkers to predict cancer prognosis, which will help prolong patient survival. On the basis of these findings, we explored the role of the hub genes in hepatocellular carcinoma via computational analysis for future immunotherapy. To study this phenomenon, we selected three datasets downloaded from the GEO database (GSE25097, GSE76427 and GSE84402). The gene expression analysis platform (GEAP) online tool was used for the data analysis to identify the DEGs. Functional enrichment analysis was performed by GO and KEGG enrichment analysis. The genes associated with these genes were identified via Cytoscape software. Immune cell infiltration and correlation analysis were used to screen the hub genes. The results revealed that the PTTG1, NCAPG, RACGAP1, PBK, ASPM, AURKA, CDCA5, KIF20A, MELK and PRC1 genes were correlated with immune targets, and these hub gene biomarkers will aid in future cancer prognosis and immunotherapy targeting in hepatocellular carcinoma patients. Supplementary Information: The online version contains supplementary material available at 10.1007/s40203-024-00215-2.
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