Abstract：
Glioblastoma (GBM) is the most common primary intracranial malignancy with a very low survival rate. Exploring key molecular markers for GBM can help with early diagnosis, prognostic prediction, and recurrence monitoring. This study aims to explore novel biomarkers for GBM via bioinformatics analysis and experimental verification. Dataset GSE103229 was obtained from the GEO database to search differentially expressed lncRNA (DELs), mRNAs (DEMs), and miRNAs (DEMis). Hub genes were selected to establish competing endogenous RNA (ceRNA) networks. The GEPIA database was employed for the survival analysis and expression detection of hub genes. Hub gene expression in GBM tissue samples and cell lines was validated using RT-qPCR. Western blotting was employed for protein expression evaluation. SYT1 overexpression vector was transfected in GBM cells. CCK-8 assay and flow cytometry were performed to detect the malignant phenotypes of GBM cells. There were 901 upregulated and 1086 downregulated DEMs identified, which were prominently enriched in various malignancy-related functions and pathways. Twenty-two hub genes were selected from PPI networks. Survival analysis and experimental validation revealed that four hub genes were tightly associated with GBM prognosis and progression, including SYT1, GRIN2A, KCNA1, and SYNPR. The four genes were significantly downregulated in GBM tissues and cell lines. Overexpressing SYT1 alleviated the proliferation and promoted the apoptosis of GBM cells in vitro. We identify four genes that may be potential molecular markers of GBM, which may provide new ideas for improving early diagnosis and prediction of the disease.
摘要：
胶质母细胞瘤（GBM）是最常见的原发性颅内恶性肿瘤，生存率很低。探索GBM的关键分子标记可以帮助早期诊断，预后预测，和复发监测。本研究旨在通过生物信息学分析和实验验证，探索GBM的新型生物标志物。从GEO数据库获取数据集GSE103229，用于搜索差异表达的lncRNA（DELs），mRNA(DEM)，和miRNA(DEMis)。选择Hub基因以建立竞争内源性RNA(ceRNA)网络。GEPIA数据库用于hub基因的存活分析和表达检测。使用RT-qPCR验证GBM组织样品和细胞系中的Hub基因表达。蛋白质印迹用于蛋白质表达评估。在GBM细胞中转染SYT1过表达载体。CCK-8法和流式细胞术检测GBM细胞的恶性表型。确定了901个上调的DEM和1086个下调的DEM，它们在各种恶性肿瘤相关的功能和途径中显著富集。从PPI网络中选择22个hub基因。生存分析和实验验证显示四个hub基因与GBM预后和进展密切相关。包括SYT1、GRIN2A、KCNA1和SYNPR。这四个基因在GBM组织和细胞系中显著下调。SYT1过表达减轻了体外GBM细胞的增殖，促进了细胞凋亡。我们确定了四个可能是GBM潜在分子标记的基因，为提高疾病的早期诊断和预测提供新的思路。
