Frontiers in Oncology (Apr 2021)

Identifying and Validating Potential Biomarkers of Early Stage Lung Adenocarcinoma Diagnosis and Prognosis

  • Yingji Chen,
  • Longyu Jin,
  • Zhibin Jiang,
  • Suo Liu,
  • Wei Feng

DOI
https://doi.org/10.3389/fonc.2021.644426
Journal volume & issue
Vol. 11

Abstract

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BackgroundLung adenocarcinoma (LUAD) is the most common pathological type of lung cancer. At present, most patients with LUAD are diagnosed at an advanced stage, and the prognosis of advanced LUAD is poor. Hence, we aimed to identify novel biomarkers for the diagnosis and treatment of early stage LUAD and to explore their predictive value.MethodsThe microarray datasets GSE63459, GSE27262, and GSE33532 were searched, and the differentially expressed genes (DEGs) were obtained using GEO2R. The DEGs were subjected to gene ontology (GO) and pathway enrichment analyses using METASCAPE. A protein–protein interaction (PPI) network was plotted with STRING and visualized by Cytoscape. Module analysis of the PPI network was performed using MCODE. Overall survival (OS) analysis and analysis of the mRNA expression levels of genes identified by MCODE were performed with UALCAN. Western blot analysis of hub genes in LUAD patients, MTS assays, and clonogenic assays were performed to test the effects of the hub genes on cell proliferation in vitro.ResultsA total of 341 DEGs were obtained, which were mainly enriched in terms related to blood vessel development, growth factor binding, and extracellular matrix organization. A PPI network consisting of 300 nodes and 1140 edges was constructed, and a significant module including 15 genes was identified. Elevated expression of ASPM, CCNB2, CDCA5, PRC1, KIAA0101, and UBE2T was associated with poor OS in LUAD patients. In the protein level, the hub gene was overexpressed in LUAD patients. In vitro experiments showed that knockdown of the hub genes in the LUAD cell lines could promote cell proliferation.ConclusionsDEGs are potential biomarkers for early stage lung adenocarcinoma and could have utility for the diagnosis and predicting treatment efficacy.

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