背景:肺部的纯磨玻璃结节(pGGNs)中是否存在侵入性成分仍然是预测的巨大挑战。我们的研究目的是基于生物信息学分析方法研究和鉴定纯磨玻璃结节(pGGN)的潜在生物标志物基因。
方法:为了研究差异表达基因(DEGs),首先使用从基因表达综合(GEO)数据库获得的数据。接下来,加权基因共表达网络分析(WGCNA)研究DEGs的共表达网络。选择黑键模块作为与pGGN相关的键模块。进行了基因本体论(GO)和京都基因和基因组百科全书(KEGG)途径分析。然后使用STRING创建蛋白质-蛋白质相互作用(PPI)网络,并通过Cytoscape软件对选择的模块基因进行分析。此外,与对照组相比,使用聚合酶链反应(PCR)评估pGGN患者肿瘤组织中这些hub基因的价值。
结果:从GSE193725中筛选出4475个DEG,然后在黑键模块中识别出225个DEG,被发现丰富了各种功能和途径,如细胞外泌体,囊泡,核糖体等等。在这些DEG中,选择了6个具有高应激程度的重叠hub基因。这些hub基因包括RPL4、RPL8、RPLP0、RPS16、RPS2和CCT3。最后,与对照组相比,pGGN患者肿瘤组织中CCT3和RPL8mRNA的相对表达水平均受到调节。
结论:总结一下,确定的DEG,通路,模块,重叠的hub基因可以揭示pGGN的潜在分子机制。
BACKGROUND: Whether there are invasive components in pure ground glass nodules(pGGNs) in the lungs is still a huge challenge to forecast. The objective of our study is to investigate and identify the potential biomarker genes for pure ground glass nodule(pGGN) based on the method of bioinformatics analysis.
METHODS: To investigate differentially expressed genes (DEGs), firstly the data obtained from the gene expression omnibus (GEO) database was used.Next Weighted gene co-expression network analysis (WGCNA) investigate the co-expression network of DEGs. The black key module was chosen as the key one in correlation with pGGN. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways analyses were done. Then STRING was uesd to create a protein-protein interaction (PPI) network, and the chosen module genes were analyzed by Cytoscape software.In addition the polymerase chain reaction (PCR) was used to evaluate the value of these hub genes in pGGN patients\' tumor tissues compared to controls.
RESULTS: A total of 4475 DEGs were screened out from GSE193725, then 225 DEGs were identified in black key module, which were found to be enriched for various functions and pathways, such as extracellular exosome, vesicle,
ribosome and so on. Among these DEGs, 6 overlapped hub genes with high degrees of stress method were selected. These hub genes include RPL4, RPL8, RPLP0, RPS16, RPS2 and CCT3.At last relative expression levels of CCT3 and RPL8 mRNA were both regulated in pGGN patients\' tumor tissues compared to controls.
CONCLUSIONS: To summarize, the determined DEGs, pathways, modules, and overlapped hub genes can throw light on the potential molecular mechanisms of pGGN.