OBJECTIVES: Despite the close association with patient clinical outcomes, dysregulated kinases in gliomas are not commonly used as clinical indicators. We aimed to identify a kinase-related gene signature for glioma patients that improves clinical risk-stratification. METHODS: Least absolute shrinkage and selection operator (LASSO) Cox regression analysis was conducted to identify kinase-related gene signature. The association between the risk model and patient survival, pathway activation, and immune suppression status was further explored. Additionally, cell proliferation and tumor formation assay were performed to evaluate the oncogenic roles of identified kinase gene. RESULTS: In this study, we identified a 10-gene kinase signature in TCGA dataset that is significantly associated with poor overall survival (OS) in glioma patients. A consistent prediction ability for survival was further demonstrated in the CGGA dataset. In addition, the signature was significantly linked to malignant molecular signatures, such as IDH wild type and non-codeletion of 1p19q. Moreover, the high-risk group exhibited a wide array of oncogenic biological pathways. Interestingly, the result showed that the kinase-related signature is tightly linked with immune suppression signatures, including immune infiltration of MDSCs and Tregs, and expression of immunosuppressive genes. Functionally, the oncogenic roles of WEE1 in gliomas were validated. CONCLUSIONS: The findings present a novel kinase-related gene signature with potential value for survival prediction in gliomas.
Zhang et al. (Wed,) studied this question.