Integrated Bioinformatics Analysis for Identifying the Significant Genes as Poor Prognostic Markers in Gastric Adenocarcinoma

Gastric adenocarcinoma (GAC) is the most common histological type of gastric cancer and imposes a considerable health burden globally. The purpose of this study was to identify significant genes and key pathways participated in the initiation and progression of GAC. Four datasets (GSE13911, GSE19826...

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Bibliographic Details
Published in:Journal of oncology 2022-06, Vol.2022, p.1-12
Main Authors: Li, Yamei, Luo, Yan, Tian, Qiang, Lai, Yu, Xu, Lei, Yun, Hailong, Liang, Yang, Liao, Dandan, Gu, Rui, Liu, Liye, Yuan, Mu, Li, Yijiao, Li, Yufan, Lu, Mingze, Yong, Xin, Zhang, Hua
Format: Article
Language:English
Subjects:
Adenocarcinoma
Antigens
Bioinformatics
Biomarkers
Cancer
Computational biology
Datasets
Gastric cancer
Gene expression
Genes
Genetic aspects
Genomes
Immunohistochemistry
Kinases
Medical prognosis
Oncology, Experimental
Protein-protein interactions
Proteins
Software
Stomach cancer
Survival analysis
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Summary:Gastric adenocarcinoma (GAC) is the most common histological type of gastric cancer and imposes a considerable health burden globally. The purpose of this study was to identify significant genes and key pathways participated in the initiation and progression of GAC. Four datasets (GSE13911, GSE19826, GSE54129, and GSE79973) including 171 GAC and 77 normal tissues from Gene Expression Omnibus (GEO) database were collected and analyzed. Through integrated bioinformatics analysis, we obtained 69 commonly differentially expressed genes (DEGs) among the four datasets, including 20 upregulated and 49 downregulated genes. The prime module in protein-protein interaction network of DEGs, including ADAMTS2, COL10A1, COL1A1, COL1A2, COL8A1, BGN, and SPP1, was enriched in protein digestion and absorption, ECM-receptor interaction, focal adhesion, PI3K-Akt signaling pathway, and amoebiasis. Furthermore, expression and survival analysis found that all seven hub genes were highly expressed in GAC tissues and 6 of them (except for SPP1) were able to predict poor prognosis of GAC. Finally, we verified the 6 high-expressed hub genes in GAC tissues via immunohistochemistry, Western blot, and RNA quantification analysis. Altogether, we identified six significantly upregulated DEGs as poor prognostic markers in GAC based on integrated bioinformatical methods, which could be potential molecular markers and therapeutic targets for GAC patients.
ISSN:1687-8450
1687-8450
DOI:10.1155/2022/9080460