Dai B, Ren LQ, Han XY, Liu DJ. Bioinformatics analysis reveals 6 key biomarkers associated with non-small-cell lung cancer.
J Int Med Res 2019;
48:300060519887637. [PMID:
31775549 PMCID:
PMC7783251 DOI:
10.1177/0300060519887637]
[Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023] Open
Abstract
Objective
Non-small-cell lung cancer (NSCLC) accounts for >85% of lung cancers, and
its incidence is increasing. We explored expression differences between
NSCLC and normal cells and predicted potential target sites for detection
and diagnosis of NSCLC.
Methods
Three microarray datasets from the Gene Expression Omnibus database were
analyzed using GEO2R. Gene Ontology and Kyoto Encyclopedia of Genes and
Genomes enrichment analysis were conducted. Then, the String database,
Cytoscape, and MCODE plug-in were used to construct a protein–protein
interaction (PPI) network and screen hub genes. Overall and disease-free
survival of hub genes were analyzed using Kaplan-Meier curves, and the
relationship between expression patterns of target genes and tumor grades
were analyzed and validated. Gene set enrichment analysis and receiver
operating characteristic curves were used to verify enrichment pathways and
diagnostic performance of hub genes.
Results
In total, 293 differentially expressed genes were identified and mainly
enriched in cell cycle, ECM–receptor interaction, and malaria. In the PPI
network, 36 hub genes were identified, of which 6 were found to play
significant roles in carcinogenesis of NSCLC: CDC20,
ECT2, KIF20A, MKI67,
TPX2, and TYMS.
Conclusion
The identified target genes can be used as biomarkers for the detection and
diagnosis of NSCLC.
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