Izmir Biomedicine and Genome Center, Izmir, Turkey.
Izmir International Biomedicine and Genome Institute, Dokuz Eylül University, Izmir, Turkey.
PeerJ. 2023 Mar 16;11:e15096. doi: 10.7717/peerj.15096. eCollection 2023.
Low-grade gliomas (LGG) are central nervous system Grade I tumors, and as they progress they are becoming one of the deadliest brain tumors. There is still great need for timely and accurate diagnosis and prognosis of LGG. Herein, we aimed to identify diagnostic and prognostic biomarkers associated with LGG, by employing diverse computational approaches. For this purpose, differential gene expression analysis on high-throughput transcriptomics data of LGG corresponding healthy brain tissue, derived from TCGA and GTEx, respectively, was performed. Weighted gene co-expression network analysis of the detected differentially expressed genes was carried out in order to identify modules of co-expressed genes significantly correlated with LGG clinical traits. The genes comprising these modules were further used to construct gene co-expression and protein-protein interaction networks. Based on the network analyses, we derived a consensus of eighteen hub genes, namely, , and . All detected hub genes were up-regulated in LGG, and were also associated with unfavorable prognosis in LGG patients. The findings of this study could be applicable in the clinical setting for diagnosing and monitoring LGG.
低级别胶质瘤（LGG）是中枢神经系统 I 级肿瘤，随着其发展，它已成为最致命的脑肿瘤之一。因此，仍非常需要及时、准确地诊断和预测 LGG。为此，我们采用多种计算方法，旨在鉴定与 LGG 相关的诊断和预后生物标志物。为此，分别对来自 TCGA 和 GTEx 的 LGG 相应正常脑组织的高通量转录组学数据进行差异基因表达分析。为了鉴定与 LGG 临床特征显著相关的共表达基因模块，对检测到的差异表达基因进行加权基因共表达网络分析。包含这些模块的基因进一步用于构建基因共表达和蛋白质-蛋白质相互作用网络。基于网络分析，我们得出了十八个关键基因的共识，即 、 和 。所有检测到的关键基因在 LGG 中均上调，并且与 LGG 患者的不良预后相关。本研究的结果可适用于临床诊断和监测 LGG。
