Objective To explore the expression and clinical significance of phosphoglucomutase 2 （PGM2） in glioma. Methods Clinical data and mRNA sequencing data of glioma patients were collected from the Chinese Glioma Genome Atlas （CGGA） database and the Cancer Genome Atlas （TCGA） database. After matching the sequencing data with clinical data， the gene expression of PGM2 was extracted， and cases with missing clinical data were excluded. According to the cut-off value obtained from the receiver operating characteristic （ROC） curve， the cases were divided into PGM2 high expression group and PGM2 low expression group. The predictive value of PGM2 expression on the overall survival rate of glioma patients was evaluated using area under the ROC curve （AUC） and Kaplan Meier survival curve. Univariate analysis was used to explore the clinical and pathological factors affecting the expression level of PGM2 in gliomas. Univariate and multivariate Cox regression were used to analyze the relationship between prognosis in glioma patients and clinical and pathological factors related to glioma， as well as PGM2 expression. Gene Ontology （GO） enrichment analysis and KEGG pathway analysis were performed by screening co-expressed genes to explore the involvement of PGM2 in biological processes and related signaling pathways regulation. CIBERSORT algorithm was used to analyze the relationship between PGM2 expression in gliomas and immune cell infiltration. Results A total of 273 cases were left after the deletion of missing values from the CGGA-325 and 560 cases were left after the deletion of missing values from the TCGA. ROC curve analysis of PGM2 expression predicting the overall survival rate of glioma patients showed that the AUC in the CGGA-325 database was 0.705 ［95%CI （0.640， 0.769）］， with a cut-off value of 10.1， and the AUC in the TCGA database was 0.739 ［95%CI （0.699， 0.778）］， with a cut-off value of 8.9. According to the cut off value， the cases were divided into PGM2 high expression group and PGM2 low expression group. Kaplan Meier survival analysis showed that the overall survival rate of patients in PGM2 high expression group decreased compared to those in PGM2 low expression group， and the difference was statistically significant （P ＜ 0.001）. In the CGGA-325 and TCGA databases， there were statistically significant differences in glioma grade， IDH type， and 1p/19q deletion between PGM2 low expression group and PGM2 high expression group （both P ＜ 0.05）. Multivariate Cox regression analysis showed that the common independent prognostic factors in the CGGA-325 and TCGA databases were glioma grade and co-deletion of 1P/19q， and the expression of PGM2 was an independent prognostic factor in the CGGA-325 database， and the difference was statistically significant （all P ＜ 0.05）. GO enrichment analysis and KEGG pathway analysis showed that PGM2 expression was associated with endoplasmic reticulum protein transportation， Toll-like receptor signaling pathway， and I-κB kinase/NF-κB signal pathway. CIBERSORT analysis showed that the initial CD4+ T cells， activated memory CD4+ T cells， regulatory T cells， monocytes， macrophages （M0， M1， M2）， and neutrophils in PGM2 low expression group and PGM2 high expression group were compared in terms of immune infiltration degree， and the differences were statistically significant （all P ＜ 0.05）. Conclusions High expression of PGM2 is associated with a poorer prognosis in glioma and may serve as a prognostic indicator for glioma patients and is expected to become a potential therapeutic target for glioma in the future.