mRNA 标志物在多形性胶质母细胞瘤患者生存预测中的应用:系统评价及生物信息学分析。
mRNA markers for survival prediction in glioblastoma multiforme patients: a systematic review with bioinformatic analyses.
机构信息
Neurosurgeon, Neuroscience Research Center, Shahid Beheshti University of Medical Sciences, Arabi Ave, Daneshjoo Blvd, Velenjak, Tehran, 19839- 63113, Iran.
School of Medicine, Capital Medical University, Beijing, China.
出版信息
BMC Cancer. 2024 May 21;24(1):612. doi: 10.1186/s12885-024-12345-z.
BACKGROUND
Glioblastoma multiforme (GBM) is a type of fast-growing brain glioma associated with a very poor prognosis. This study aims to identify key genes whose expression is associated with the overall survival (OS) in patients with GBM.
METHODS
A systematic review was performed using PubMed, Scopus, Cochrane, and Web of Science up to Journey 2024. Two researchers independently extracted the data and assessed the study quality according to the New Castle Ottawa scale (NOS). The genes whose expression was found to be associated with survival were identified and considered in a subsequent bioinformatic study. The products of these genes were also analyzed considering protein-protein interaction (PPI) relationship analysis using STRING. Additionally, the most important genes associated with GBM patients' survival were also identified using the Cytoscape 3.9.0 software. For final validation, GEPIA and CGGA (mRNAseq_325 and mRNAseq_693) databases were used to conduct OS analyses. Gene set enrichment analysis was performed with GO Biological Process 2023.
RESULTS
From an initial search of 4104 articles, 255 studies were included from 24 countries. Studies described 613 unique genes whose mRNAs were significantly associated with OS in GBM patients, of which 107 were described in 2 or more studies. Based on the NOS, 131 studies were of high quality, while 124 were considered as low-quality studies. According to the PPI network, 31 key target genes were identified. Pathway analysis revealed five hub genes (IL6, NOTCH1, TGFB1, EGFR, and KDR). However, in the validation study, only, the FN1 gene was significant in three cohorts.
CONCLUSION
We successfully identified the most important 31 genes whose products may be considered as potential prognosis biomarkers as well as candidate target genes for innovative therapy of GBM tumors.
背景
多形性胶质母细胞瘤(GBM)是一种与预后极差相关的快速生长的脑胶质瘤。本研究旨在鉴定与 GBM 患者总生存期(OS)相关的关键基因。
方法
对截至 2024 年 1 月的 PubMed、Scopus、Cochrane 和 Web of Science 进行了系统评价。两名研究人员独立提取数据,并根据纽卡斯尔渥太华量表(NOS)评估研究质量。确定与生存相关的表达基因,并在随后的生物信息学研究中进行考虑。还使用 STRING 分析了这些基因的产物的蛋白质-蛋白质相互作用(PPI)关系。此外,还使用 Cytoscape 3.9.0 软件识别与 GBM 患者生存相关的最重要基因。为了最终验证,使用 GEPIA 和 CGGA(mRNAseq_325 和 mRNAseq_693)数据库进行 OS 分析。使用基因集富集分析(GO Biological Process 2023)进行分析。
结果
从最初的 4104 篇文章中检索到 255 项研究,这些研究来自 24 个国家,描述了 613 个独特的基因,其 mRNAs 与 GBM 患者的 OS 显著相关,其中 107 个基因在 2 项或更多研究中被描述。根据 NOS,131 项研究为高质量研究,而 124 项研究为低质量研究。根据 PPI 网络,鉴定出 31 个关键靶基因。通路分析显示了 5 个枢纽基因(IL6、NOTCH1、TGFB1、EGFR 和 KDR)。然而,在验证研究中,仅 FN1 基因在三个队列中具有显著性。
结论
我们成功鉴定了最重要的 31 个基因,其产物可能被视为潜在的预后生物标志物,也是 GBM 肿瘤创新治疗的候选靶基因。