Identification of Key Genes and Related Drugs of Adrenocortical Carcinoma by Integrated Bioinformatics Analysis

Abstract

Adrenocortical carcinoma (ACC) is a malignant carcinoma with an extremely poor prognosis, and its pathogenesis remains to be understood to date, necessitating further investigation. This study aims to discover biomarkers and potential therapeutic agents for ACC through bioinformatics, enhancing clinical diagnosis and treatment strategies. Differentially expressed genes (DEGs) between ACC and normal adrenal cortex were screened out from the GSE19750 and GSE90713 datasets available in the GEO database. An online Venn diagram tool was utilized to identify the common DEGs between the two datasets. The identified DEGs were subjected to functional assessment, pathway enrichment, and identification of hub genes by performing the protein-protein interaction (PPI), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. The differences in the expressions of hub genes between ACC and normal adrenal cortex were validated at the GEPIA2 website, and the association of these genes with the overall patient survival was also assessed. Finally, on the QuartataWeb website, drugs related to the identified hub genes were determined. A total of 114 DEGs, 10 hub genes, and 69 known drugs that could interact with these genes were identified. The GO and KEGG analyses revealed a close association of the identified DEGs with cellular signal transduction. The 10 hub genes identified were overexpressed in ACC, in addition to being significantly associated with adverse prognosis in ACC. Three genes and the associated known drugs were identified as potential targets for ACC treatment.

Key words

protein-protein interaction network - differentially expressed genes - targeted drug

• References

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