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Identification of Core Genes and Key Pathways in Gastric Cancer using Bioinformatics Analysis

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Abstract

Objective: To identify the key genes and pathways involved in the occurrence and development of gastric cancer (GC). Methods: Differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs) were obtained using GEO2R. Function and pathway enrichment analysis of DEGs were performed using DAVID database.Protein-protein interaction (PPI) network analysis of DEGs was established by STRING database and visualized by Cytoscape software. Module analysis and hub genes selection of the PPI network was performed using Molecular Complex Detection (MCODE) and cytoHubba plug-in of Cytoscape software, respectively. Overall survival analysis of hub genes was performed by the Kaplan-Meier plotter online tool. Results: Totally, 98 DEGs were picked out, of which, 31 up-regulated genes were mainly involved in extracellular matrix (ECM)-receptor interaction, PI3K-Akt signaling pathway and focal adhesion, while 67 down-regulated DEGs were enriched in gastric acid secretion, collecting duct acid secretion and glycolysis/gluconeogenesis. Top 3 modules and top 10 hub genes with high centrality degree were selected from PPI network. Among these hub genes, high expression of secreted phosphoprotein 1 (SPP1), fibronectin1 (FN1) and collagen type I alpha 1 chain (COL1A1) were significantly associated worse overall survival for gastric cancer patients. Conclusions: The present study identified several key genes and pathways which may play an important role in the initiation and development of gastric cancer and could provide us potential targets for gastric cancer diagnosis and prognostic prediction.

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Funding

This work was supported by National Natural Science Foundation of China (no. 30672058); Scientific Research project of Southwest Medical University (no. 2020ZRQNB038).

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Contributions

ZL and MS made substantial contributions to the conception of the present study. ZL and MS performed the primary bioinformatics analysis and were the major contributor in writing the manuscript. YZ and GT made substantial contributions to data analysis, including the biological significance of hub genes and figure editing. All authors revised and approved the final manuscript.

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Correspondence to M. Song.

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The authors declare that they have no conflict of interest.

This article does not contain any studies involving animals or human participants performed by any of the authors.

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Li, Z., Zhou, Y., Tian, G. et al. Identification of Core Genes and Key Pathways in Gastric Cancer using Bioinformatics Analysis. Russ J Genet 57, 963–971 (2021). https://doi.org/10.1134/S1022795421080081

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