Integrative Bioinformatics Analysis Reveals the Key Molecular Players in Metastatic Adrenocortical Carcinoma

Abstract

AbstractAdrenocortical carcinoma (ACC) is an uncommon, possessive, and highly metastasizable malignancy of the adrenal cortex. Using bioinformatics analysis of microarray datasets, this work is intended to uncover important molecular entities and pathways complicated in ACC metastasis. Three datasets (GSE90713, GSE143383, and GSE19750) were obtained from the Gene Expression Omnibus (GEO) database, comprising a total of 226 ACC samples and healthy controls. A collection of differentially expressed genes (DEGs) and differentially expressed miRNAs (DEmiRs) linked with ACC and ACC metastases was found using differential gene expression analysis. Functional enrichment analysis revealed enriched pathways such as "Staphylococcus aureus infection," "Phagosome," "Cell adhesion molecules," and "Pathways in cancer," indicating potential mechanisms underlying ACC metastasis. Hub genes with potential involvement in ACC metastasis were discovered by protein-protein interaction (PPI) network analysis, includingGAPDH,MYC,VEGFA,CDC20,CCL2,MMP9,ITGAM,DLGAP5,KIF2C, andFCGR3A.CCL2,CDC20,DLGAP5,KIF2C,MMP9, andMYCwere shown to be substantially linked with the prognosis and overall survival of ACC patients by survival analysis. A network was identified between targeted hub genes and DEmiRs. These findings provide insight into the molecular mechanisms of ACC metastasis as well as potential therapeutic targets for further targeted therapies. The identified hub genes and pathways may also have implications for the understanding and treatment of other types of cancer.