Using Bioinformatics To Mine The Hub Immune-Related Genes in Low-Grade Gliomas Based On TCGA and CGGA Databases

Abstract

\n Background\n\nLow grade gliomas(LGG) are the most common malignant tumors in the central nervous system. Tumor cells interact with immune cells and stromal molecules to form glioma immune microenvironment, which plays an important role in tumor progression.\nMethods\n\nAccording to the immune median score of ESTIMATE website, the gene expression and clinical data downloaded from TCGA database was analyzed in subgroups (high and low immune score groups). The DEGs were screened with the change threshold of P\u2009<\u20090.05 and | logfc | ≥ 1, and the volcano map and heat map were drawn by the ggplot2 package. Go and KEGG pathway enrichment analysis were performed by Metascape website. The PPI network of DEGs was constructed by STRING website. The hub genes were screened by using cytohubb plug-in of Cytoscape. CGGA and TCGA websites were utilized to analyze the overall survival of hub genes on LGG, and THPA database was used to further verify those protein expression in LGG and normal tissues.\nResults\n\nSubgroup analysis of immune-related score showed that the prognosis of patients was negatively correlated with immune-related score. The ROC curve of 5-year and 3-year survival rate was 0.88 and 0.75 respectively. The immune-related score was substantially correlated with IDH1 mutation status, tumor size and pathological type. The GO term enrichment showed that DEGs were closely related to the activation and regulation of immune related factors, the production and regulation of immune response. KEGG enriched in Staphylococcus aureus infection and phagosome. In addition, CPLX1 and TLR7 were associated with immune cell infiltration in tumor microenvironment.\nConclusions\n\nSubgroups based on immune-related score can guide the prognosis of LGG. And CPLX1 and TLR7 may be the key genes of LGG immunology and potential biological targets for detection, diagnosis and immunology of LGG.