PDF(Pubmed)
Abstract：
The underlying mechanisms of gastric cancer (GC) remain unknown. Therefore, in this study, we employed a comprehensive approach, combining computational and experimental methods, to identify potential key genes and unveil the underlying pathogenesis and prognosis of GC.
Gene expression profiles from GEO databases (GSE118916, GSE79973, and GSE29272) were analyzed to identify DEGs between GC and normal tissues. A PPI network was constructed using STRING and Cytoscape, followed by hub gene identification with CytoHubba. Investigations included expression and promoter methylation analysis, survival modeling, mutational and miRNA analysis, gene enrichment, drug prediction, and in vitro assays for cellular behaviors.
A total of 83 DEGs were identified in the three datasets, comprising 41 up-regulated genes and 42 down-regulated genes. Utilizing the degree and MCC methods, we identified four hub genes that were hypomethylated and up-regulated: COL1A1, COL1A2, COL3A1, and FN1. Subsequent validation of their expression and promoter methylation on clinical GC samples through targeted bisulfite sequencing and RT-qPCR analysis further confirmed the hypomethylation and overexpression of these genes in local GC patients. Furthermore, it was observed that these hub genes regulate tumor proliferation and metastasis in in vivo and exhibited mutations in GC patients.
We found four potential diagnostic and prognostic biomarkers, including COL1A1, COL1A2, COL3A1, and FN1 that may be involved in the occurrence and progression of GC.
Gene expression profiles from GEO databases (GSE118916, GSE79973, and GSE29272) were analyzed to identify DEGs between GC and normal tissues. A PPI network was constructed using STRING and Cytoscape, followed by hub gene identification with CytoHubba. Investigations included expression and promoter methylation analysis, survival modeling, mutational and miRNA analysis, gene enrichment, drug prediction, and in vitro assays for cellular behaviors.
A total of 83 DEGs were identified in the three datasets, comprising 41 up-regulated genes and 42 down-regulated genes. Utilizing the degree and MCC methods, we identified four hub genes that were hypomethylated and up-regulated: COL1A1, COL1A2, COL3A1, and FN1. Subsequent validation of their expression and promoter methylation on clinical GC samples through targeted bisulfite sequencing and RT-qPCR analysis further confirmed the hypomethylation and overexpression of these genes in local GC patients. Furthermore, it was observed that these hub genes regulate tumor proliferation and metastasis in in vivo and exhibited mutations in GC patients.
We found four potential diagnostic and prognostic biomarkers, including COL1A1, COL1A2, COL3A1, and FN1 that may be involved in the occurrence and progression of GC.
摘要：
背景：胃癌（GC）的潜在机制仍然未知。因此,在这项研究中，我们采用了全面的方法，结合计算和实验方法，确定潜在的关键基因，揭示GC的潜在发病机制和预后。
方法:分析来自GEO数据库(GSE118916、GSE79973和GSE29272)的基因表达谱以鉴定GC和正常组织之间的DEGs。使用STRING和Cytoscape构建了PPI网络，然后用CytoHubba进行hub基因鉴定。研究包括表达和启动子甲基化分析，生存建模,突变和miRNA分析，基因富集，药物预测，和细胞行为的体外测定。
结果：在三个数据集中总共确定了83个DEG，包括41个上调基因和42个下调基因。利用学位和MCC方法，我们确定了4个低甲基化和上调的hub基因:COL1A1,COL1A2,COL3A1和FN1.随后通过靶向亚硫酸氢盐测序和RT-qPCR分析验证其在临床GC样品上的表达和启动子甲基化进一步证实了这些基因在局部GC患者中的低甲基化和过表达。此外，观察到这些hub基因在体内调节肿瘤增殖和转移，并在GC患者中表现出突变。
结论：我们发现了四种潜在的诊断和预后生物标志物，包括COL1A1、COL1A2、COL3A1和FN1，可能参与GC的发生和进展。
方法:分析来自GEO数据库(GSE118916、GSE79973和GSE29272)的基因表达谱以鉴定GC和正常组织之间的DEGs。使用STRING和Cytoscape构建了PPI网络，然后用CytoHubba进行hub基因鉴定。研究包括表达和启动子甲基化分析，生存建模,突变和miRNA分析，基因富集，药物预测，和细胞行为的体外测定。
结果：在三个数据集中总共确定了83个DEG，包括41个上调基因和42个下调基因。利用学位和MCC方法，我们确定了4个低甲基化和上调的hub基因:COL1A1,COL1A2,COL3A1和FN1.随后通过靶向亚硫酸氢盐测序和RT-qPCR分析验证其在临床GC样品上的表达和启动子甲基化进一步证实了这些基因在局部GC患者中的低甲基化和过表达。此外，观察到这些hub基因在体内调节肿瘤增殖和转移，并在GC患者中表现出突变。
结论：我们发现了四种潜在的诊断和预后生物标志物，包括COL1A1、COL1A2、COL3A1和FN1，可能参与GC的发生和进展。
