ABSTRACT
Objective:To explore the prognostic biomarkers of glioblastoma (GBM) in the tumor microenvironment (TME) and its function.Methods:A total of 169 GBM samples of 161 GBM patients were collected from the Cancer Genome Atlas (TCGA) database. ESTIMATE algorithm in R4.1.0 software was used to calculate the proportion of immune components and stromal components in TME, which were expressed as immune score and stromal score, respectively. According to the median value of the two scores, 169 GBM samples were divided into the high score group and the low score group, respectively, 84 each in each group (those whose scores were equal to the median were not involved in the grouping). The differentially expressed genes (DEG) [false discovery rate (FDR) < 0.05] between the high score group and the low score group of the two scores were obtained by using limma package, and the co-up-regulated and co-down-regulated DEG of the two scores were obtained by using Venn program. Based on the STRING database, the protein interaction (PPI) network of co-up-regulated and down-regulated DEG of immune score and stromal score was constructed, and the top 30 genes with connectivity were selected. Univariate Cox proportional hazard model analysis of overall survival (OS) of 161 GBM patients in the TCGA database was performed on co-up-regulated and down-regulated DEG between immune score and stromal score by using R4.1.0 software to obtain the DEG affecting OS. The intersection of the DEG obtained from PPI analysis and Cox analysis was taken as the prognostic core genes. According to the median expression value of prognostic core genes in GBM samples from the TCGA database, 161 patients were divided into prognostic core genes high expression group and low expression group (patients whose scores were equal to the median were not involved in the grouping), with 80 cases in each group. Kaplan-Meier survival analysis of OS was performed by using R4.1.0 software. GSEA 4.2.1 software was used to perform gene set enrichment analysis (GSEA) on all genes with transcriptome data of GBM patients in the two groups of the TCGA databases, and the main enriched functions of the two groups of genes were obtained. The CIBERSORT algorithm was used to test the accuracy of the proportion of tumor infiltrating immune cell (TIC) subsets in 169 GBM samples from the TCGA database, and 57 GBM samples were finally obtained. Immune cells with differential expression levels and immune cells related to the expression of prognostic core genes among the samples with different expression levels of prognostic core genes were analyzed; Venn program was used to obtain the intersection of immune cells with differential levels and related immune cells, and differentially expressed TIC related to expressions of prognostic core genes in GBM were obtained.Results:Based on the immune score and stromal score of GBM samples in the TCGA database, a total of 693 co-up-regulated and co-down-regulated DEG of both scores were screened out. After the intersection of 78 DEG related to OS obtained by univariate Cox regression analysis and 30 DEG obtained by PPI network results, CC motif chemokine receptor 2 (CCR2) was identified as the prognostic core gene ( HR = 1.294, 95% CI 1.060-1.579, P = 0.011). GBM patients with CCR2 high expression had worse OS compared with those with CCR2 low expression ( P = 0.009). GSEA analysis showed that genes in the CCR2 high expression group were mainly enriched in immune-related pathways, while genes in the CCR2 low expression group were mainly enriched in metabolism-related pathways. Among 57 screened GBM samples, there were differences in the levels of 3 immune cells between the CCR2 high expression group and the CCR2 low expression group ( P < 0.05). CCR2 expression was correlated with the levels of 9 immune cells (all P < 0.05). Venn program analysis showed that differentially expressed 3 TIC in GBM related to CCR2 gene expression were obtained; among them, M2 macrophages were positively correlated with CCR2 expression, while T follicular helper cell and activated NK cells were negatively correlated with CCR2 expression. Conclusions:CCR2 may be the core gene related to the prognosis in the TME of GBM. As reference, the level of CCR2 can help to predict the status of TME and prognosis in GBM patients, which is expected to provide a new direction for the treatment of GBM.
ABSTRACT
Glioma is the most common primary intracranial tumor. At present, the conventional treatment methods have limited effect and cannot significantly prolong the survival time of patients. Chemokine CCL2 is the most important member of the CC chemokine family, which can regulate glioma angiogenesis, immunosuppression, progression and invasion, and resistance to apoptosis. This article reviews the potential mechanism of CCL2 promoting the malignant progression of glioma, in order to provide new ideas and methods for the targeted therapy of glioma.