Identification Of DSCAM-AS1 As A Potential Biomarker For Lung Adenocarcinoma Based On Bioinformatics Approaches

Background:Lung cancer is one of the most common malignant tumors,and the major types of lung cancer include lung squamous cell carcinoma and lung adenocarcinoma.In recent years,the incidence of lung adenocarcinoma has increased year by year.Screening for biomarkers related to lung adenocarcinoma is of great significance for the early diagnosis and prognosis of lung adenocarcinoma.The study aims to identify potential therapeutic target long-noncoding RNA in lung cancer and to explore the underlying pathogenesis of lung cancer in the molecular level,with the bioinformatics approaches.Method:We downloaded the gene chip dataset of lung adenocarcinoma samples from The Cancer Genome Atlas(TCGA)dataset.The R was utilized to find out differential expression RNAs(DERs)and make the hierarchical analysis of all the DERs.Then we took advantage of the free tool,Cytoscape,to make the Gene Ontology analysis and KEGG pathway enrichment analysis.And Cytoscape were used to make construction of protein-protein interaction(PPI)network.Results:A total of 1476 lncRNAs were differentially expressed in lung adenocarcinoma,of which 1230 were down-regulated and 246 were up-regulated,of which the most significant one was DSCAM-AS1.The 41 possible target genes corresponding to DSCAM-AS1 were identified by co-expression network integration analysis.Gene ontology enrichment analysis found that DSCAM-AS1 is involved in the pathogenesis of lung adenocarcinoma through cell signaling,cell metabolism,and energy-related pathways.Survival prognosis was analyzed by Kaplan Meier Plotter.It was finally determined that DSCAM-AS1 may be a potential therapeutic target for lung adenocarcinoma.Conclusion:1.The data from TCGA and result from qPCR showed that lncRNA DSCAM-AS1 was distinctly up-regulated in tumor tissues.2.lncRNA DSCAM-AS1 may play key roles in cancer initiation and progress and influence patients' survival by binding target genes.3.3.This bioinformatics method can effectively screen the target gene and provide a basis for further experimental verification.