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Identification of key pathways and genes from gastric precancerous lesions to gastric cancer by integrated bioinformatics analysis

机译:通过综合生物信息学分析鉴定胃癌癌前病变对胃癌的关键途径和基因

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Highlights This study explored possible changes in gene expression during the transition from precancerous lesions to gastric cancer. Until now, the underlining mechanisms of precancerous lesions to cancer transition remain unclear. Bioinformatics analysis may find out genes that are differentially expressed in this process, and provide ideas for studying the transformation of precancerous lesions into cancer. Abstract Objective: This work aimed to illuminate the potential key genes and pathways in GC tumorigenesis based on bioinformatics analysis. Methods: The differentially expressed genes (DEGs) between GPL tissue samples and GC tissue samples were investigated using the GSE55696 and GSE87666 microarray data from the Gene Expression Omnibus (GEO) database. DEGs were identified by an empirical Bayes method based on the Limma R package. Then, KEGG and GO enrichment analyses of DEGs were performed followed by protein-protein interaction (PPI) network construction. Finally, the overall survival (OS) analysis of key genes was performed by the Kaplan-Meier plotter online tool. Results: A total of 250 DEGs were obtained, of which 216 were up-regulated and 34 were down-regulated. KEGG pathways analysis showed that the up-regulated DEGs were enriched in cytokine-cytokine receptor interaction, chemokine signaling pathway, metabolic pathways, PI3K-Akt signaling pathway, NF-kappa B signaling pathway, and other signaling pathways about cancer, while no down-regulated pathways were enriched. A PPI network of DEGs was constructed with 117 nodes and 660 edges, and 20 genes were selected as hub genes owing to high degrees in the network. According to the Kaplan-Meier analysis, 6 out of 20 hub genes including CCR7, FPR1, C3, CXCR5, GNB4, and PPBP with high mRNA expression were associated with poor OS for GC patients. Conclusion: The results of this study provide possible factors for the occurrence of GC, and the identification of the genes and pathways associated with the progression from GPL to GC provides valuable data for investigating the pathogenesis in future studies.
机译:亮点本研究探讨了从癌前病变过渡到胃癌的基因表达可能的变化。到目前为止,癌前病变对癌症过渡的强调机制仍不清楚。生物信息学分析可能发现在该过程中差异表达的基因,并提供研究癌前病变转化为癌症的想法。摘要目的:基于生物信息学分析,这项工作旨在阐明GC肿瘤瘤中的潜在关键基因和途径。方法:使用GSE55696和GSE87666微阵列数据从基因表达OMNIBUS(GEO)数据库中研究了GPL组织样品和GC组织样品之间的差异表达基因(DEGS)。基于利缘R包的经验贝叶斯方法鉴定了DEG。然后,进行Kegg和GO富集的DEGs,然后进行蛋白质 - 蛋白质相互作用(PPI)网络施工。最后,通过Kaplan-Meier绘图仪在线工具进行了关键基因的总体存活(OS)分析。结果:获得了总共250℃,其中216次上调,34例下调。 Kegg途径分析表明,上调的含量富含细胞因子 - 细胞因子受体相互作用,趋化因子信号通路,代谢途径,PI3K-AKT信号通路,NF-Kappa信令途径以及关于癌症的其他信号通路,而没有下降 - 受调节的途径富集。用117个节点和660边缘构建PPI网络,并且由于网络中的高度选择了20个基因作为集线基因。根据KAPLAN-MEIER分析,20个集线基因中的6种,包括CCR7,FPR1,C3,CXCR5,GNB4和具有高mRNA表达的PPBP的6种与GC患者的差的OS相关。结论:本研究的结果为GC发生的可能因素提供了可能的因素,并且与GPL至GC的进展相关的基因和途径提供了有价值的数据,用于研究未来的研究中的发病机制。

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