Screening of hub genes associated with prognosis in non-small cell lung cancer by integrated bioinformatics analysis

Abstract

Background: Lung cancer is an intractable disease and the second leading cause of cancer-related deaths and morbidity in the world. This study conducted a bioinformatics analysis to identify critical genes associated with poor prognosis in non-small cell lung cancer (NSCLC).Methods: We downloaded three datasets (GSE33532, GSE27262, and GSE18842) from the gene expression omnibus (GEO), and used the GEO2R online tools to identify the differentially expressed genes (DEGs). We then used the Search Tool for Retrieval of Interacting Genes (STRING) database to establish a protein-protein interaction (PPI) network and used the Cytoscape software to perform a module analysis of the PPI network. A Kaplan-Meier plotter was used to perform the overall survival (OS) analysis, and the Gene Expression Profiling Interactive Analysis (GEPIA) database was used for expression level analysis of hub genes. Further, the UALCAN database was used to validate the relationship between the gene expression level of each hub gene and clinical characteristics.Results: We identified 254 DEGs, which were composed of 66 up-regulated genes and 188 downregulated genes. Out of these, five DEGs were identified as hub genes (CDC20, BUB1, CCNB2, CCNB1, UBE2C) by constructing a PPI network. The use of a Kaplan-Meier plotter to generate patient survival curves suggested a strong relationship between the five hub genes with worse OS. Validation of the above results using the GEPIA database showed that all the hub genes were highly expressed in NSCLC tissues.Using the UALACN data mining platform, we found that the five hub genes are correlated with tumor stage and the status of node metastasis in NSCLC patients. Conclusions:We identified five hub DEGs that might provide perspectives in the explorations of pathogenesis and treatments for NSCLC.

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Tumor mutation burden determined by a 645-cancer gene panel and compared with microsatellite instability and mismatch repair genes in colorectal cancer

“…To established a prognostic system for cancer patients, cancer-related genes have been used to develop cancer panels in lung cancer (28), malignant lymphoma (29), melanoma (30), gastric cancer (31), and other cancers (32).…”

Key genes involved with prognosis were identified in lung adenocarcinoma by integrated bioinformatics analysis

“…At the same time, based on some current biological information analysis, in some studies of non-small cell lung cancer, CDC 20 and CCNB2 are related to the survival rate of patients to a certain extent. Meanwhile, in cell experiments, the expression level of CCNB2 is also high in lung cancer [ [27] , [28] , [29] ]. In addition, as a heterogeneous disease.…”