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Identification and Validation of SNP-Containing Genes With Prognostic Value in Gastric Cancer via Integrated Bioinformatics Analysis

BACKGROUND: Gastric cancer is one of the most common malignancies worldwide. Although the diagnosis and treatment of this disease have substantially improved in recent years, the five-year survival rate of gastric cancer is still low due to local recurrence and distant metastasis. An in-depth study...

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Autores principales: Li, Hui, Guo, Jing, Cheng, Guang, Wei, Yucheng, Liu, Shihai, Qi, Yaoyue, Wang, Gongjun, Xiao, Ruoxi, Qi, Weiwei, Qiu, Wensheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8112818/
https://www.ncbi.nlm.nih.gov/pubmed/33987081
http://dx.doi.org/10.3389/fonc.2021.564296
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author Li, Hui
Guo, Jing
Cheng, Guang
Wei, Yucheng
Liu, Shihai
Qi, Yaoyue
Wang, Gongjun
Xiao, Ruoxi
Qi, Weiwei
Qiu, Wensheng
author_facet Li, Hui
Guo, Jing
Cheng, Guang
Wei, Yucheng
Liu, Shihai
Qi, Yaoyue
Wang, Gongjun
Xiao, Ruoxi
Qi, Weiwei
Qiu, Wensheng
author_sort Li, Hui
collection PubMed
description BACKGROUND: Gastric cancer is one of the most common malignancies worldwide. Although the diagnosis and treatment of this disease have substantially improved in recent years, the five-year survival rate of gastric cancer is still low due to local recurrence and distant metastasis. An in-depth study of the molecular pathogenesis of gastric cancer and related prognostic markers will help improve the quality of life and prognosis of patients with this disease. The purpose of this study was to identify and verify key SNPs in genes with prognostic value for gastric cancer. METHODS: SNP-related data from gastric cancer patients were obtained from The Cancer Genome Atlas (TCGA) database, and the functions and pathways of the mutated genes were analyzed using DAVID software. A protein-protein interaction (PPI) network was constructed using the STRING database and visualized by Cytoscape software, and molecular complex detection (MCODE) was used to screen the PPI network to extract important mutated genes. Ten hub genes were identified using cytoHubba, and the expression levels and the prognostic value of the central genes were determined by UALCAN and Kaplan-Meier Plotter. Finally, quantitative PCR and Western blotting were used to verify the expression of the hub genes in gastric cancer cells. RESULTS: From the database, 945 genes with mutations in more than 25 samples were identified. The PPI network had 360 nodes and 1616 edges. Finally, cytoHubba identified six key genes (TP53, HRAS, BRCA1, PIK3CA, AKT1, and SMARCA4), and their expression levels were closely related to the survival rate of gastric cancer patients. CONCLUSION: Our results indicate that TP53, HRAS, BRCA1, PIK3CA, AKT1, and SMARCA4 may be key genes for the development and prognosis of gastric cancer. Our research provides an important bioinformatics foundation and related theoretical foundation for further exploring the molecular pathogenesis of gastric cancer and evaluating the prognosis of patients.
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spelling pubmed-81128182021-05-12 Identification and Validation of SNP-Containing Genes With Prognostic Value in Gastric Cancer via Integrated Bioinformatics Analysis Li, Hui Guo, Jing Cheng, Guang Wei, Yucheng Liu, Shihai Qi, Yaoyue Wang, Gongjun Xiao, Ruoxi Qi, Weiwei Qiu, Wensheng Front Oncol Oncology BACKGROUND: Gastric cancer is one of the most common malignancies worldwide. Although the diagnosis and treatment of this disease have substantially improved in recent years, the five-year survival rate of gastric cancer is still low due to local recurrence and distant metastasis. An in-depth study of the molecular pathogenesis of gastric cancer and related prognostic markers will help improve the quality of life and prognosis of patients with this disease. The purpose of this study was to identify and verify key SNPs in genes with prognostic value for gastric cancer. METHODS: SNP-related data from gastric cancer patients were obtained from The Cancer Genome Atlas (TCGA) database, and the functions and pathways of the mutated genes were analyzed using DAVID software. A protein-protein interaction (PPI) network was constructed using the STRING database and visualized by Cytoscape software, and molecular complex detection (MCODE) was used to screen the PPI network to extract important mutated genes. Ten hub genes were identified using cytoHubba, and the expression levels and the prognostic value of the central genes were determined by UALCAN and Kaplan-Meier Plotter. Finally, quantitative PCR and Western blotting were used to verify the expression of the hub genes in gastric cancer cells. RESULTS: From the database, 945 genes with mutations in more than 25 samples were identified. The PPI network had 360 nodes and 1616 edges. Finally, cytoHubba identified six key genes (TP53, HRAS, BRCA1, PIK3CA, AKT1, and SMARCA4), and their expression levels were closely related to the survival rate of gastric cancer patients. CONCLUSION: Our results indicate that TP53, HRAS, BRCA1, PIK3CA, AKT1, and SMARCA4 may be key genes for the development and prognosis of gastric cancer. Our research provides an important bioinformatics foundation and related theoretical foundation for further exploring the molecular pathogenesis of gastric cancer and evaluating the prognosis of patients. Frontiers Media S.A. 2021-04-27 /pmc/articles/PMC8112818/ /pubmed/33987081 http://dx.doi.org/10.3389/fonc.2021.564296 Text en Copyright © 2021 Li, Guo, Cheng, Wei, Liu, Qi, Wang, Xiao, Qi and Qiu https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Oncology
Li, Hui
Guo, Jing
Cheng, Guang
Wei, Yucheng
Liu, Shihai
Qi, Yaoyue
Wang, Gongjun
Xiao, Ruoxi
Qi, Weiwei
Qiu, Wensheng
Identification and Validation of SNP-Containing Genes With Prognostic Value in Gastric Cancer via Integrated Bioinformatics Analysis
title Identification and Validation of SNP-Containing Genes With Prognostic Value in Gastric Cancer via Integrated Bioinformatics Analysis
title_full Identification and Validation of SNP-Containing Genes With Prognostic Value in Gastric Cancer via Integrated Bioinformatics Analysis
title_fullStr Identification and Validation of SNP-Containing Genes With Prognostic Value in Gastric Cancer via Integrated Bioinformatics Analysis
title_full_unstemmed Identification and Validation of SNP-Containing Genes With Prognostic Value in Gastric Cancer via Integrated Bioinformatics Analysis
title_short Identification and Validation of SNP-Containing Genes With Prognostic Value in Gastric Cancer via Integrated Bioinformatics Analysis
title_sort identification and validation of snp-containing genes with prognostic value in gastric cancer via integrated bioinformatics analysis
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8112818/
https://www.ncbi.nlm.nih.gov/pubmed/33987081
http://dx.doi.org/10.3389/fonc.2021.564296
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