Identification of potential key molecular biomarkers in lung adenocarcinoma by bioinformatics analysis

BACKGROUND: Lung cancer is one of the most common malignant tumors in the world, of which the rate of incidence has continuously increased over recent years. Lung adenocarcinoma (LUAD) is the most frequent pathological type of lung cancer. METHODS: In order to discover the key markers for the occurrence and development of LUAD, we collected messenger RNA (mRNA) expression datasets in the Gene Expression Omnibus (GEO), namely, GSE2514, GSE7670, and GSE40275. The differentially expressed genes (DEGs) were screened using the online interface between GEO and R (GEO2R). Then, DEGs were functionally annotated in the Database for Annotation, Visualization, and Integrated Discovery (DAVID). Next, a protein-protein interaction (PPI) network was drawn by using the Search Tool for the Retrieval of Interacting Genes (STRING) web tool and Cytoscape software. Finally, Kaplan-Meier plotter was utilized to analyze the overall survival (OS) of the hub genes. The correlation between fibroblast growth factor 2 (FGF2) and immune infiltration was studied by TIMER web services. RESULTS: In this study, we obtained a total of 284 DEGs through the intersection of 3 datasets, and found that DEGs were highly related to biological processes such as “cell adhesion”, “cell differentiation”, and “cell proliferation”. After that, the hub genes were obtained by analyzing the PPI network. Finally, we found that the abnormal expression of hub genes is obviously related to poor prognosis in LUAD patients. The expression level of FGF2 was positively correlated with the immune infiltration in LUAD. CONCLUSIONS: In general, the DEGs and hub genes can provide new research targets for the development of LUAD, as well as potential diagnosis and treatment strategies for disease treatment. In particular, FGF2 expression was found to be involved in the immune microenvironment of LUAD.