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基于微阵列技术的胶质母细胞瘤诊断和治疗的枢纽生物标志物。

Hub biomarkers for the diagnosis and treatment of glioblastoma based on microarray technology.

机构信息

Department of Neurosurgery, The Fourth Hospital of Hebei Medical University, 12 Health Road, Shijiazhuang, Hebei, 050011, People's Republic of China.

Department of Neurosurgery, The Eighth Affiliated Hospital, Sun Yat-Sen University, Shenzhen 518033, People's Republic of China.

出版信息

Technol Cancer Res Treat. 2021 Jan-Dec;20:1533033821990368. doi: 10.1177/1533033821990368.

Abstract

BACKGROUND

Glioblastoma (GBM) is the most common clinical intracranial malignancy worldwide, and the most common supratentorial tumor in adults. GBM mainly causes damage to the brain tissue, which can be fatal. This research explored potential gene targets for the diagnosis and treatment of GBM using bioinformatic technology.

METHODS

Public data from patients with GBM and controls were downloaded from the Gene Expression Omnibus database, and differentially expressed genes (DEGs) were identified by Gene Expression Profiling Interactive Analysis (GEPIA) and Gene Expression Omnibus 2R (GEO2R). Construction of the protein-protein interaction network and the identification of a significant module were performed. Subsequently, hub genes were identified, and their expression was examined and compared by real-time quantitative (RT-q)PCR between patients with GBM and controls.

RESULTS

GSE122498 (GPL570 platform), GSE104291 (GPL570 platform), GSE78703_DMSO (GPL15207 platform), and GSE78703_LXR (GPL15207 platform) datasets were obtained from the GEO. A total of 130 DEGs and 10 hub genes were identified by GEPIA and GEO2R between patients with GBM and controls. Of these, strong connections were identified in correlation analysis between , , , and . RT-qPCR showed that all 4 of these genes were expressed at significantly higher levels in patients with GBM compared with controls.

CONCLUSIONS

The hub genes , , , and are potential biomarkers for the diagnosis and treatment of GBM.

摘要

背景

胶质母细胞瘤(GBM)是全球最常见的临床颅内恶性肿瘤,也是成人最常见的幕上肿瘤。GBM 主要对脑组织造成损害,可导致致命后果。本研究采用生物信息学技术,探讨了用于 GBM 诊断和治疗的潜在基因靶标。

方法

从基因表达综合数据库(GEO)中下载胶质母细胞瘤患者和对照者的公共数据,通过基因表达谱分析交互工具(GEPIA)和 GEO2R 鉴定差异表达基因(DEGs)。构建蛋白质-蛋白质相互作用网络,并识别重要模块。然后,确定关键基因,并通过实时定量(RT-q)PCR 比较 GBM 患者与对照者之间的表达水平。

结果

从 GEO 获得 GSE122498(GPL570 平台)、GSE104291(GPL570 平台)、GSE78703_DMSO(GPL15207 平台)和 GSE78703_LXR(GPL15207 平台)数据集。通过 GEPIA 和 GEO2R 鉴定出 GBM 患者与对照者之间有 130 个 DEGs 和 10 个关键基因。相关性分析显示, 、 、 、 之间存在较强的关联。RT-qPCR 结果显示,这 4 个基因在 GBM 患者中的表达水平均显著高于对照者。

结论

关键基因 、 、 、 可能是 GBM 诊断和治疗的潜在生物标志物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f85/8142016/e154fd203ca5/10.1177_1533033821990368-fig1.jpg

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