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通过生物信息学分析探索胶质母细胞瘤和阿尔茨海默病的负相关关系。

Exploring the inverse association of glioblastoma multiforme and Alzheimer's disease via bioinformatics analysis.

机构信息

Department of Neurosurgery, Renmin Hospital of Wuhan University, Wuhan, 430060, Hubei, China.

Central Laboratory, Renmin Hospital of Wuhan University, 238 Jiefang Street, Wuhan, 430060, Hubei, China.

出版信息

Med Oncol. 2022 Sep 7;39(12):182. doi: 10.1007/s12032-022-01786-w.

DOI:10.1007/s12032-022-01786-w
PMID:36071287
Abstract

Glioblastoma multiforme (GBM) and Alzheimer's disease (AD) are two major diseases in the nervous system with a similar peak age of onset, which has the typical characteristics of high cost, difficult treatment, and poor prognosis. Epidemiological studies and a few molecular biological studies have hinted at an opposite relationship between AD and GBM. However, there are few studies on their reverse relationship, and the regulatory mechanism is still unclear, indicating that further systematic research is urgently needed. Our study firstly employs advanced bioinformatics methods to explore the inverse relationship between them and find various target drugs. We obtained the gene expression dataset from public databases (GEO, TCGA, and GTEx). Then, we identified 122 differentially expressed genes (DEGs) of AD and GBM. Four significant gene modules were identified through protein-protein interaction (PPI) and module construction, and 13 hub genes were found using cytoHubba. We constructed co-expression networks and found various target drugs through these hub genes. Functional enrichment analysis revealed that the AMPK pathway, cell cycle, and cellular senescence play important roles in AD and GBM. Our study may provide a potential direction for studying the opposite molecular mechanism of AD and GBM in the future.

摘要

多形性胶质母细胞瘤(GBM)和阿尔茨海默病(AD)是神经系统中的两种主要疾病,其发病高峰年龄相似,具有成本高、治疗困难、预后差的典型特征。流行病学研究和一些分子生物学研究提示 AD 和 GBM 之间存在相反的关系。然而,关于它们的反向关系的研究较少,其调控机制尚不清楚,表明需要进一步进行系统研究。我们的研究首先采用先进的生物信息学方法来探索它们之间的反向关系,并发现各种潜在的治疗靶点。我们从公共数据库(GEO、TCGA 和 GTEx)中获取 AD 和 GBM 的基因表达数据集。然后,我们鉴定了 122 个 AD 和 GBM 的差异表达基因(DEGs)。通过蛋白质-蛋白质相互作用(PPI)和模块构建,我们确定了四个显著的基因模块,并使用 cytoHubba 找到了 13 个枢纽基因。我们构建了共表达网络,并通过这些枢纽基因找到了各种潜在的治疗靶点。功能富集分析表明,AMPK 通路、细胞周期和细胞衰老在 AD 和 GBM 中发挥重要作用。我们的研究可能为未来研究 AD 和 GBM 相反的分子机制提供一个潜在的方向。

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