Prognostic Markers Identification in Glioma by Gene Expression Profile Analysis.

This study aimed to explore more gene markers associated with glioma or its prognosis. The glioma-related RNAseq data from the Gene Expression Omnibus database and The Cancer Genome Atlas dataset in UCSC Xena database were downloaded. There was a total of 971 tumor samples and 102 normal samples in the 2 datasets. The differentially expressed genes (DEGs) data between tumor and normal samples were analyzed, on which were then performed function and pathway enrichment analyses. Pearson correlation coefficient between DEGs was calculated to construct the coexpression network. Finally, prognostic genes were screened. A total of 634 upregulated and 769 downregulated DEGs were identified between tumor and control groups. These DEGs were significantly involved in 15 upregulated pathways, such as p53 signaling pathway, and 16 downregulated pathways, such as neuroactive ligand-receptor interaction, and cell adhesion molecules. In the coexpression network, pseudouridine synthase 7 (), EFR3 homolog B (), and neuronal cell adhesion molecule () had the top three highest degrees. Additionally, 17 prognostic genes were selected, such as thrombospondin-1 (), caspase-8 (), glutamate ionotropic receptor AMPA type subunit 2 (), , and receptor type I (). Pathways of p53 signaling pathway and neuroactive ligand-receptor interaction may play important roles in glioma progression. , , and may be potential biomarkers of glioma. , , , , and may serve as prognostic markers in glioma.