Bioinformatics analysis of differentially expressed genes and identifycation of AGER as a key gene in lung cancer

Inhalt:
Lung cancer (LC) is one of the most fatal diseases. Over a quarter of cancer-related death was caused by LC. It would cause some up- or down-regulated genes accompany with the lung cancer that could provide some clues for treatment and prevention. In the present research, the gene data of 227 samples were downloaded from gene expression omnibus (GEO) datasets GSE10072 and GSE19804. By using R software and package, the common differential expression genes (DEGs) were screened out from the two profiles. Then, we did the gene ontology (GO) analysis and protein protein interaction (PPI) network analysis according to the DEGs. The selected key gene was studied by online tools. There were 11 genes up-regulated and 34 genes down-regulated simultaneously in the samples. The 45 common DEGs were enriched in 36 different GO terms, 26 biological process, 11 cellular component and 9 molecular function. Protein expression of AGER in LC specimens was lower than the normal lung tissues, and the survival curves also proved this feature. By using bioinformatics analysis, LC would cause some DEGs enriched in different GO terms. Among then, AGER expressed higher in lung than other organisms and significantly associated with LC.