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pmid:36072978
Identification of a Signature for Predicting Prognosis and Immunotherapy Response in Patients with Glioma.
Wei-Feng Zong · Cui Liu · Yi Zhang · Suo-Jun Zhang · Wen-Sheng Qu · Xiang Luo
Journal of oncology · 2022 doi:10.1155/2022/8615949
Paper
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Experiment
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Data
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Complete file
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In the present study, gene expression profiles of GSE2223 were obtained from the Gene Expression Omnibus (GEO) database. Core modules and hub genes related to glioma were identified using weighted gene coexpression network analysis (WGCNA) and protein-protein interaction (PPI) network analysis of differentially expressed genes (DEGs). After a series of database screening tests, we identified 11 modules during glioma progression, followed by six hub genes (RAB3A, TYROBP, SYP, CAMK2A, VSIG4, and GABRA1) that can predict the prognosis of glioma and were validated in glioma tissues by qRT-PCR. The CIBERSORT algorithm was used to analyze the difference of immune cell infiltration between the glioma and control groups. 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