Department of Clinical Laboratory Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou, China.
Department of Neurosurgery, Suining Central Hospital, Suining, China.
J Cell Biochem. 2020 Jun;121(5-6):3099-3111. doi: 10.1002/jcb.29577. Epub 2019 Dec 30.
Glioma is one of the most common types of human brain tumor, with high mortality in high-grade gliomas (HGG). Low-grade gliomas (LGG) can progress into HGG, leading to poor prognosis. However, it is unclear what factors affect the progression of LGG to HGG. This study aims to explore the function of the crosstalk genes on the progression and prognosis of LGG using bioinformatics analysis. Integrated transcriptome analysis was used to screen differentially expressed genes (DEGs). Then, gene ontology (GO) function enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed to investigate the association between DEGs and gene functions and pathways by ClusterProfiler package and ClueGO plug-in. Protein-protein interaction (PPI) network analysis was applied to explore the connection between genes and biological processes. Subsequently, the gene clusters were analyzed using the Centiscape and molecular complex detection (MCODE) plug-in in Cytoscape software, where the crosstalk genes were identified for further study. Ultimately, the UALCAN website and Gene Expression Profiling Interactive Analysis (GEPIA) website were performed to visualize the expression levels and survival curves of genes, respectively. There were 74 DEGs identified in glioma, including 55 upregulated genes and 19 downregulated genes, which mainly were enriched in extracellular matrix (ECM)-receptor interaction, focal adhesion, PI3K-Akt signaling pathway, and so on. Then, six crosstalk genes were selected, including COL1A1, COL1A2, COL3A1, COL4A1, COL4A2, and COL5A2 genes. Overall survival (OS) analysis of crosstalk genes was conducted on the GEPIA website. High expression levels of crosstalk genes were closely related to the low survival rate of patients with LGG. The overexpressed crosstalk genes, such as COL1A1, COL1A2, COL3A1, COL4A1, COL4A2, and COL5A2 may participate in the progression and poor prognosis of LGG through the ECM-receptor interaction pathway.
神经胶质瘤是最常见的人类脑肿瘤类型之一，高级别神经胶质瘤（HGG）死亡率较高。低级别神经胶质瘤（LGG）可进展为 HGG，导致预后不良。然而，目前尚不清楚哪些因素会影响 LGG 向 HGG 的进展。本研究旨在通过生物信息学分析探讨 LGG 进展和预后相关的串扰基因的功能。采用整合转录组分析筛选差异表达基因（DEGs）。然后，通过 ClusterProfiler 包和 ClueGO 插件对 DEGs 与基因功能和通路的关联进行基因本体（GO）功能富集和京都基因与基因组百科全书（KEGG）通路分析。应用蛋白质-蛋白质相互作用（PPI）网络分析探讨基因与生物学过程之间的联系。随后，在 Cytoscape 软件中使用 Centiscape 和分子复合物检测（MCODE）插件对基因簇进行分析，以识别进一步研究的串扰基因。最后，通过 UALCAN 网站和基因表达谱交互式分析（GEPIA）网站分别可视化基因的表达水平和生存曲线。在神经胶质瘤中鉴定出 74 个 DEGs，包括 55 个上调基因和 19 个下调基因，这些基因主要富集在细胞外基质（ECM）-受体相互作用、粘着斑、PI3K-Akt 信号通路等通路中。然后，选择了 6 个串扰基因，包括 COL1A1、COL1A2、COL3A1、COL4A1、COL4A2 和 COL5A2 基因。在 GEPIA 网站上对串扰基因的总生存（OS）进行分析。发现串扰基因的高表达水平与 LGG 患者的低生存率密切相关。COL1A1、COL1A2、COL3A1、COL4A1、COL4A2 和 COL5A2 等过表达的串扰基因可能通过 ECM-受体相互作用通路参与 LGG 的进展和不良预后。
