A panel of collagen genes are associated with prognosis of patients with gastric cancer and regulated by microRNA-29c-3p: an integrated bioinformatics analysis and experimental validation
Authors Zhang QN, Zhu HL, Xia MT, Liao J, Huang XT, Xiao JW, Yuan C
Received 15 December 2018
Accepted for publication 5 May 2019
Published 24 May 2019 Volume 2019:11 Pages 4757—4772
Checked for plagiarism Yes
Review by Single-blind
Peer reviewers approved by Dr Colin Mak
Peer reviewer comments 3
Editor who approved publication: Dr Beicheng Sun
Qiang-Nu Zhang,1,* Hui-Li Zhu,1,* Meng-Ting Xia,2,* Juan Liao,1 Xiao-Tao Huang,2 Jiang-Wei Xiao,3 Cong Yuan2
1Department of Gastroenterology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu 610041, People’s Republic of China; 2Department of Gastroenterology, the Affiliated Hospital of North Sichuan Medical College, Nanchong 637000, Sichuan, People’s Republic of China; 3Department of Gastrointestinal Surgery, the Affiliated Hospital of North Sichuan Medical College, Nanchong 637000, People’s Republic of China
*These authors contributed equally to this work
Background: The systematic expression characteristics and functions of collagen genes in gastric cancer (GC) have not been reported. Through public data integration, combined with bioinformatics analysis, we identified a panel of collagen genes overexpressed in GC. The functions of these genes were analyzed and validated in a GC-related cohort. microRNAs that may potentially target such genes were investigated in vitro.
Methods: Four GC-related datasets retrieved from the Gene Expression Omnibus (GEO) were used to extract differentially expressed genes (DEGs) in GC. Functional annotation was performed to identify the potential roles of the identified DEGs. The association of candidate genes involved in the prognosis of GC patients (n=876) was determined using data provided by the Kaplan–Meier-plotter database, The Cancer Genome Atlas Stomach Adenocarcinoma (TCGA-STAD) repository, and a GC-related dataset (GSE15459). The expression characteristics of candidate genes and their associations with clinical parameters were validated in our in-house cohort (n=58). MicroRNAs able to target the identified candidate genes were predicted and confirmed using qRT-PCR, Western blotting, and dual-luciferase reporter assays in vitro.
Results: After the integration of four GEO datasets, 76 DEGs were identified. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis indicated that these DEGs were significantly enriched in ECM-related functions and pathways. A group of collagen genes was significantly upregulated in the GC tissues and constituted a protein–protein interaction network as important nodes. Some of these collagen genes were closely associated with poor prognosis in GC patients. Overexpression of COL1A1 and COL4A1 was confirmed in our in-house cohort, and this was related to prognosis and certain clinicopathological parameters. We found that microRNA-29c-3p could directly target COL1A1 and COL4A1 in BGC-823 cells.
Conclusions: Collagen genes identified in this study were associated with patient prognosis in GC and may represent diagnostic markers or potential therapeutic targets. Aberrant expression of such candidate genes may be induced by microRNA-29c-3p.
Keywords: gastric cancer, collagen, prognosis, microRNA-29c-3p, COL1A1, COL4A1
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