Clinical and Translational Research
Copyright ©The Author(s) 2023. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Clin Cases. Jul 16, 2023; 11(20): 4763-4787
Published online Jul 16, 2023. doi: 10.12998/wjcc.v11.i20.4763
Identification of survival-associated biomarkers based on three datasets by bioinformatics analysis in gastric cancer
Long-Kuan Yin, Hua-Yan Yuan, Jian-Jun Liu, Xiu-Lian Xu, Wei Wang, Xiang-Yu Bai, Pan Wang
Long-Kuan Yin, Hua-Yan Yuan, Jian-Jun Liu, Xiu-Lian Xu, Wei Wang, Xiang-Yu Bai, Pan Wang, Department of Gastrointestinal Surgery, Affiliated Hospital of North Sichuan Medical College, Nanchong 637000, Sichuan Province, China
Long-Kuan Yin, Xiang-Yu Bai, Pan Wang, Sichuan Key Laboratory of Medical Imaging, North Sichuan Medical College, Nanchong 637000, Sichuan Province, China
Author contributions: Yin LK and Yuan HY contributed equally to this work. Yin LK, Yuan HY, Liu JJ and Wang P contributed to data collection and manuscript drafting; Yin LK, Xu XL, Wang W, Bai XY and Wang P prepared for the figures and tables; and all authors have approved the final manuscript.
Institutional review board statement: All of the data of this paper are from the public database of TCGA, GEO and GEPIA, and there is no ethical statement needed to be declared for this manuscript.
Clinical trial registration statement: All of the data of this paper are from the public database of TCGA, GEO and GEPIA, and no clinical trial registration needed for this manuscript.
Informed consent statement: All of the data of this paper are from the public database of TCGA, GEO and GEPIA, and no informed consent form documents are needed to be signed by any patients.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Data sharing statement: The data supporting the results of this study are available from GEO database (GSE19826, GSE79973 and GSE29998).
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Pan Wang, MD, Doctor, Professor, Department of Gastrointestinal Surgery, Affiliated Hospital of North Sichuan Medical College, No. 1 Maoyuan South Road, Shunqing District, Nanchong 637000, Sichuan Province, China. ncwangpan@126.com
Received: January 4, 2023
Peer-review started: January 4, 2023
First decision: April 3, 2023
Revised: April 11, 2023
Accepted: June 6, 2023
Article in press: June 6, 2023
Published online: July 16, 2023
Processing time: 174 Days and 6.9 Hours
Abstract
BACKGROUND

Gastric cancer (GC) is one of the most common malignant tumors with poor prognosis in terms of advanced stage. However, the survival-associated biomarkers for GC remains unclear.

AIM

To investigate the potential biomarkers of the prognosis of patients with GC, so as to provide new methods and strategies for the treatment of GC.

METHODS

RNA sequencing data from The Cancer Genome Atlas (TCGA) database of STAD tumors, and microarray data from Gene Expression Omnibus (GEO) database (GSE19826, GSE79973 and GSE29998) were obtained. The differentially expressed genes (DEGs) between GC patients and health people were picked out using R software (x64 4.1.3). The intersections were underwent between the above obtained co-expression of differential genes (co-DEGs) and the DEGs of GC from Gene Expression Profiling Interactive Analysis database, and Gene Ontology (GO) analysis, Kyoto Encyclopedia of Gene and Genome (KEGG) pathway analysis, Gene Set Enrichment Analysis (GSEA), Protein-protein Interaction (PPI) analysis and Kaplan-Meier Plotter survival analysis were performed on these DEGs. Using Immunohistochemistry (IHC) database of Human Protein Atlas (HPA), we verified the candidate Hub genes.

RESULTS

With DEGs analysis, there were 334 co-DEGs, including 133 up-regulated genes and 201 down-regulated genes. GO enrichment analysis showed that the co-DEGs were involved in biological process, cell composition and molecular function pathways. KEGG enrichment analysis suggested the co-DEGs pathways were mainly enriched in ECM-receptor interaction, protein digestion and absorption pathways, etc. GSEA pathway analysis showed that co-DEGs mainly concentrated in cell cycle progression, mitotic cell cycle and cell cycle pathways, etc. PPI analysis showed 84 nodes and 654 edges for the co-DEGs. The survival analysis illustrated 11 Hub genes with notable significance for prognosis of patients were screened. Furtherly, using IHC database of HPA, we confirmed the above candidate Hub genes, and 10 Hub genes that associated with prognosis of GC were identified, namely BGN, CEP55, COL1A2, COL4A1, FZD2, MAOA, PDGFRB, SPARC, TIMP1 and VCAN.

CONCLUSION

The 10 Hub genes may be the potential biomarkers for predicting the prognosis of GC, which can provide new strategies and methods for the diagnosis and treatment of GC.

Keywords: Gastric cancer, Survival-associated biomarkers, Bioinformatics analysis, Hub genes

Core Tip: Gastric cancer (GC) is one of the most common leading cause of death worldwide. The cases with advanced GC usually have poor prognosis. To date, the prognostic biomarkers of GC remain unclear. In this article, we investigated the co-expression of differential genes (co-DEGs) between GC tissues and normal tissues based on the data from Gene Expression Omnibus, Gene Expression Profiling Interactive Analysis and The Cancer Genome Atlas. By using bioinformatics analysis, the signal pathways of co-DEGs involvement in GC were identified, and 10 Hub biomarkers for the survival of GC were screened.