In Silico Analysis of the Correlation of KIF2C with Prognosis and Immune Infiltration in Glioma

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Abstract

Glioblastoma (GBM) is one of the most commonly pivotal malignant caners. Numerous reports have revealed the crucial roles of immune infiltration in the initiation and progression of GBM. In this study, we first identified differentially expressed genes (DEGs) in the progression of GBM using CGGA databases. Totally, 156 upregulated DEGs and 251 downregulated DEGs were revealed. By constructing a protein-protein interaction network, KIF2C was identified as a hub gene in GBM. Further analysis revealed an evidently positive association existing in KIF2C expression and the advanced stages of gliomas. Higher expression of KIF2C was in WHO grade IV samples relative to that in grade III and grade II samples. In addition, our results showed that KIF2C was higher in IDH1 wild-type samples than IDH1 mutant glioma samples, in 1p/19q noncodel samples than 1p/19q code glioma samples, and in recurrent samples than primary glioma samples. Moreover, our results showed that higher expression of KIF2C correlated with shorter survival time in both primary and recurrent gliomas and could act as a potential biomarker for the prognosis of GBM. Further analysis demonstrated that higher expression of KIF2C was related to higher levels of endothelial cell, T cell CD8+ naïve, common lymphoid progenitor, T cell CD4+ Th2, T cell CD4+ Th2, macrophage, macrophage M1, T cell CD4+ memory, and T cell CD4+ effector memory, but was related to lower levels of NK cell, B cell plasma, T cell CD4+ Th1, T cell regulatory (Tregs), neutrophil, and T cell NK. We thought this study could provide potential biomarkers for the prediction of prognosis and immune infiltration of gliomas.

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Tu, B., Xiang, H., Li, M., Zhong, F., Fang, M., & Yan, W. (2022). In Silico Analysis of the Correlation of KIF2C with Prognosis and Immune Infiltration in Glioma. Computational and Mathematical Methods in Medicine, 2022. https://doi.org/10.1155/2022/6320828

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