Core genes in lung adenocarcinoma identified by integrated bioinformatic analysis

Int J Environ Health Res. 2023 Mar;33(3):243-257. doi: 10.1080/09603123.2021.2016660. Epub 2021 Dec 27.

Abstract

This study aims to identify potential core genes of lung adenocarcinoma (LUAD). Three datasets (GSE32863, GSE43458, and GSE116959) were retrieved from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between LUAD and normal tissues were filtrated by GEO2R tool. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed via Metascape database. The protein-protein interaction (PPI) network was constructed and core genes were identified using STRING and Cytoscape. Core genes expressions and their relevant clinical characteristics were performed via Oncomine and UALCAN databases respectively. The correlation between core genes and immune infiltrates was investigated by TIMER database. Kaplan-Meier plotter was performed for survival analysis. The signal pathway network of core genes was mapped by KEGG Mapper analysis tool. In this study, ten core genes were significantly related to overall survival (OS) of LUAD patients, which can provide clues for prognosis of LUAD.

Keywords: Lung adenocarcinoma; bioinformatics analysis; core genes; immune infiltrates; survival analysis.

MeSH terms

  • Adenocarcinoma of Lung* / genetics
  • Computational Biology
  • Gene Expression Profiling
  • Humans
  • Lung Neoplasms* / genetics
  • Protein Interaction Maps / genetics