Polo-like kinases (PLKs) are a family of serine-threonine kinases that exert regulatory effects on diverse cellular processes. Dysregulation of PLKs has been implicated in multiple cancers, including glioblastoma (GBM). Notably, PLK2 expression in GBM tumor tissue is lower than that in normal brains. Notably, high PLK2 expression is significantly correlated with poor prognosis. Thus, it can be inferred that PLK2 expression alone may not be sufficient for accurate prognosis evaluation, and there are unknown mechanisms underlying PLK2 regulation. In the present study, it was demonstrated that dual specificity tyrosine-phosphorylation-regulated kinase 1A (DYRK1A) interacts with and phosphorylates PLK2 at Ser358. DYRK1A-mediated phosphorylation of PLK2 increases its protein stability. Moreover, PLK2 kinase activity was markedly induced by DYRK1A, which was exemplified by the upregulation of alpha-synuclein S129 phosphorylation. Furthermore, it was found that phosphorylation of PLK2 by DYRK1A contributes to the proliferation, migration and invasion of GBM cells. DYRK1A further enhances the inhibition of the malignancy of GBM cells already induced by PLK2. The findings of the present study indicate that PLK2 may play a crucial role in GBM pathogenesis partially in a DYRK1A-dependent manner, suggesting that PLK2 Ser358 may serve as a therapeutic target for GBM.

Gliomas, a type of primary brain tumor, have emerged as a threat to global mortality due to their high heterogeneity and mortality. A low-grade glioma (LGG), although less aggressive compared with glioblastoma, still exhibits high recurrence and malignant progression. Ubiquitination is one of the most important posttranslational modifications that contribute to carcinogenesis and cancer recurrence. E3-related genes (E3RGs) play essential roles in the process of ubiquitination. Yet, the biological function and clinical significance of E3RGs in LGGs need further exploration. In this study, differentially expressed genes (DEGs) were screened by three differential expression analyses of LGG samples from The Cancer Genome Atlas (TCGA) database. DEGs with prognostic significance were selected by the univariate Cox regression analysis and log-rank statistical test. The LASSO-COX method was performed to identify an E3-related prognostic signature consisting of seven genes AURKA, PCGF2, MAP3K1, TRIM34, PRKN, TLE3, and TRIM17. The Chinese Glioma Genome Atlas (CGGA) dataset was used as the validation cohort. Kaplan–Meier survival analysis showed that LGG patients in the low-risk group had significantly higher overall survival time than those in the high-risk group in both TCGA and CGGA cohorts. Furthermore, multivariate Cox regression analysis revealed that the E3RG signature could be used as an independent prognostic factor. A nomogram based on the E3RG signature was then established and provided the prediction of the 1-, 3-, and 5-year survival probability of patients with LGGs. Moreover, DEGs were analyzed based on the risk signature, on which function analyses were performed. GO and KEGG analyses uncovered gene enrichment in extracellular matrix–related functions and immune-related biological processes in the high-risk group. GSEA revealed high enrichment in pathways that promote tumorigenesis and progression in the high-risk group. Furthermore, ESTIMATE algorithm analysis showed a significant difference in immune and stroma activity between high- and low-risk groups. Positive correlations between the risk signature and the tumor microenvironment immune cell infiltration and immune checkpoint molecules were also observed, implying that patients with the high-risk score may have better responses to immunotherapy. Overall, our findings might provide potential diagnostic and prognostic markers for LGG patients and offer meaningful insight for individualized treatment.