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

SUBMITTER: Zeng Y 

PROVIDER: S-EPMC8798611 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature