Identification of a Signature for Predicting Prognosis and Immunotherapy Response in Patients with Glioma

被引：1

作者：

Zong, Wei-Feng ^{[1
]}

Liu, Cui ^{[2
]}

Zhang, Yi ^{[1
]}

Zhang, Suo-Jun ^{[1
]}

Qu, Wen-Sheng ^{[1
]}

Luo, Xiang ^{[1
]}

机构：

[1] Huazhong Univ Sci & Technol, Tongji Hosp, Tongji Med Coll, Dept Neurol, Wuhan 430030, Peoples R China

[2] Capital Med Univ, Beijing Rehabil Hosp, Neurorehabilitat Ctr, Beijing 100144, Peoples R China

来源：

JOURNAL OF ONCOLOGY | 2022年 / 2022卷

基金：

美国国家科学基金会;

关键词：

CENTRAL-NERVOUS-SYSTEM; VSIG4; CLASSIFICATION; EXPRESSION; PROTEIN; CAMK2A; CANCER; SERVER; TUMORS;

D O I：

10.1155/2022/8615949

中图分类号：

R73 [肿瘤学];

学科分类号：

100214 ;

摘要：

Glioma is a deadly tumor that accounts for the vast majority of brain tumors. Thus, it is important to elucidate the molecular pathogenesis and potential diagnostic and prognostic biomarkers of glioma. 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. Finally, Identification VSIG4 for immunotherapy response in patients with glioma demonstrating utility for immunotherapy research.

引用

页数：13

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