Differential Gene Selection From TCGA Of Lung Adenocarcinoma And The Validation Of EFNA3 Expression

[Objectives]1.We used the Deseq package of R language to pick out the differential genes from the LUAD datasets in TCGA,then GO,KEGG and other bioinformatic analysis are executed to find the target gene.2.The target gene should be validated in experiments.[Methods]1.To get the differential genes from TCGA LUAD datasets by DEseq package of R language,2.To check the function and pathway in which the differential gene involved by GO and KEGG analysis,3.To predict the connection between the target gene and miRNA,lncRNA and other genes,4.Survival analysis of the target gene,5.To validate the expression of target gene by IHC and Real-time PCR.[Results]l.We got 3465 obviously upregulated genes from TCGA analysis,and EFNA3 was chosen as the target gene,2.GO and KEGG analysis showed that EFNA3 was involved in cell-cell signaling,cell axon guidance,Ras signaling pathway,Rap 1 signaling pathway and PI3K-Akt signaling pathway,3.The prediction showed that the interaction influence coefficient contained miR210、miR1275 and etc.4.The survival analysis showed that the expression level of EFNA3 was negative correlation with overall survival of lung adenocarcinoma patients,5.Real-time PCR of lung adenocarcinoma cell showed no statistical difference while EFNA3 protein obviously upregulated in the tissue IHC of lung adenocarcinoma.[Conclusion]1.EFNA3 is the target gene selected from TCGA,2.the expression level of EFNA3 was negative correlation with overall survival of lung adenocarcinoma patients,3.EFNA3 protein obviously upregulated in the tissue IHC of lung adenocarcinoma,and the translation of mRNA may be regulated by upstream IncRNA.