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ICAM1 Regulates the Development of Gastric Cancer and May Be a Potential Biomarker for the Early Diagnosis and Prognosis of Gastric Cancer

Authors Chen S, Pan S, Wu H, Zhou J, Huang Y, Wang S, Liu A

Received 5 November 2019

Accepted for publication 31 January 2020

Published 2 March 2020 Volume 2020:12 Pages 1523—1534

DOI https://doi.org/10.2147/CMAR.S237443

Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 3

Editor who approved publication: Dr Ahmet Emre Eskazan


Songda Chen,1 Shan Pan,1 Huijie Wu,1 Jingyuan Zhou,1 Yueli Huang,1 Shuai Wang,2 Aiqun Liu1

1Department of Endoscopy, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, People’s Republic of China; 2Department of Colorectal Anal Surgery, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, People’s Republic of China

Correspondence: Aiqun Liu
Department of Endoscopy, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, People’s Republic of China
Email liuaiqun_2004@163.com

Background: Gastric cancer (GC) is among the most common forms of cancer affecting the digestive system. This study sought to identify hub genes regulating early GC (EGC) in order to explore their potential for early diagnosis and prognosis of patients.
Methods: We utilized a publically available dataset from the Gene Expression Omnibus database (GSE55696). Differences between EGC and LGIN with respect to gene expression were compared using the limma software. Identified differentially expressed genes (DEGs) were subjected to gene ontology (GO) and pathway enrichment analyses with the DAVID application, and the STRING website and Cytoscape software were used to construct a protein-protein interaction (PPI) network incorporating these DEGs. This network was in turn used to identify hub genes among selected DEGs, which were analyzed with the Kaplan-Meier Plotter database. In addition, Western blotting, qRT-PCR, immunohistochemistry, and UALCAN were all employed to validate the relationship between the expression of these genes and GC patient prognosis.
Results: A total of 482 DEGs were identified, with GO analyses indicating an increase in the expression of genes linked with the development of cancer. Pathway analyses also indicated that these genes play a role in certain cancer-related pathways. The PPI network highlighted four potential hub genes, of which only ICAM1 was linked to a poor GC patient prognosis. This link between ICAM1 and GC patient outcomes was confirmed via UALCAN, Western blotting, immunohistochemistry, and qRT-PCR.
Conclusion: ICAM1 may therefore modulate tumor progression in GC, thus potentially representing a valuable prognostic and diagnostic biomarker of EGC.

Keywords: bioinformatics analysis, gastric cancer, early diagnosis, ICAM1, biomarker

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