Bioinformatics screening of gene expression profile and diagnostic application of meningeal carcinoma.

Abstract

The aim of this study was to research gene expression profiles and diagnostic applications of meningeal carcinoma based on bioinformatics. We used the Gene Expression Omnibus (GEO) database to obtain the GSE43290 dataset based on the expression data of normal meninges and meningiomas consisting of 51 samples divided into two groups (47 samples of meningioma tumors and four samples of normal meninges). We used the GEO2R tool to identify differentially expressed genes (DEGs) by setting the log2 fold change as greater than two and an adjusted p-value lower than 0.05. We used the database for annotation, visualization and integrated discovery (DAVID) to perform gene ontology, biological pathways and functional annotation of the DEGs. A search Tool for the Retrieval of Interacting Gene database (STRING) was used to obtain Protein-Protein Interaction (PPI) and modular networks based on the Markov clustering algorithm. Our study identified 358 significant DEGs, of which 343 were downregulated genes while 15 were upregulated. Five significant hub genes (CXCL8, AGT, CXCR4, CXCL12 and CXCL2) were associated with various biological pathways, molecular functions and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. The DEGs were enriched in biological pathways of chemokine-mediated signaling, positive regulation of leukocyte chemotaxis, second messenger-mediated signaling, induction of positive chemotaxis, CXCR chemokine receptor binding and activities of cytokines. These hub genes and pathways could be targeted in clinical research to discover new treatments for meningeal carcinoma.