The identification of hub genes associated with pure ground glass nodules using weighted gene co-expression network analysis

使用加权基因共表达网络分析识别与纯毛玻璃结节相关的中心基因

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作者:Yuan Cheng, Zuoqing Song

Background

Whether there are invasive components in pure ground glass nodules(pGGNs) in the lungs is still a huge challenge to forecast. The

Conclusions

To summarize, the determined DEGs, pathways, modules, and overlapped hub genes can throw light on the potential molecular mechanisms of pGGN.

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.

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