Bioinformatics analysis of potential core genes for pilocytic astrocytoma

Abstract

Background Pilocytic astrocytoma (PA) is the most common primary brain tumor of childhood. Due to its complicated pathogenesis, the choice and timing of adjuvant therapy after tumor treatment are controversial. This study explored and identified potential biomarkers for PA. Materials and methods To identify potential core genes in PA that may provide new therapeutic insights, we analyzed three gene chips (GSE50161, GSE66354, GSE86574) screened from the GEO database. Differentially expressed genes (DEG) from the tissues of PA and normal brain were screened using GEO2R. To determine the functional annotation and pathway of DEG, Gene Ontology (GO) and KEGG pathway enrichment analysis were conducted using DAVID database. Protein interactions of DEG were visualized using PPI network on Cytoscape software. Next, 10 Hub nodes were screened from the differentially expressed network using DMNC algorithm on CytoHubba software and subsequently identified as Hub genes. Finally, the relationship between Hub genes and the prognosis of PA patients was described using GEPIA2 survival analysis web tool. Results A total of 37 up-regulated and 144 down-regulated genes were identified through microarray analysis. Amongst the 10 Hub genes selected, SLC12A5 and RAB3C are associated with poor prognosis in a Pilocytic astrocytoma based on the survival analysis. Conclusion Our study suggests that low expression of SLC12A5 and RAB3C are associated with poor prognosis in PA patients, whether they can be used as a new therapeutic target for PA.