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Identification of functional genes regulating gastric cancer progression using integrated bioinformatics analysis

BACKGROUND: Gastric cancer (GC) is one of the most common cancers and has a poor prognosis. Treatment of GC has remained unchanged over the past few years. AIM: To investigate the potential therapeutic targets and related regulatory biomarkers of GC. METHODS: We obtained the public GC transcriptome...

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Autores principales: Yu, Kun, Zhang, Dong, Yao, Qiang, Pan, Xing, Wang, Gang, Qian, Hai-Yang, Xiao, Yao, Chen, Qiong, Mei, Ke
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Baishideng Publishing Group Inc 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10424021/
https://www.ncbi.nlm.nih.gov/pubmed/37583848
http://dx.doi.org/10.12998/wjcc.v11.i21.5023
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author Yu, Kun
Zhang, Dong
Yao, Qiang
Pan, Xing
Wang, Gang
Qian, Hai-Yang
Xiao, Yao
Chen, Qiong
Mei, Ke
author_facet Yu, Kun
Zhang, Dong
Yao, Qiang
Pan, Xing
Wang, Gang
Qian, Hai-Yang
Xiao, Yao
Chen, Qiong
Mei, Ke
author_sort Yu, Kun
collection PubMed
description BACKGROUND: Gastric cancer (GC) is one of the most common cancers and has a poor prognosis. Treatment of GC has remained unchanged over the past few years. AIM: To investigate the potential therapeutic targets and related regulatory biomarkers of GC. METHODS: We obtained the public GC transcriptome sequencing dataset from the Gene Expression Omnibus database. The datasets contained 348 GC tissues and 141 healthy tissues. In total, 251 differentially expressed genes (DEGs) were identified, including 187 down-regulated genes and 64 up-regulated genes. The DEGs’ enriched functions and pathways include Progesterone-mediated oocyte maturation, cell cycle, and oocyte meiosis, Hepatitis B, and the Hippo signaling pathway. Survival analysis showed that BUB1, MAD2L1, CCNA2, CCNB1, and BIRC5 may be associated with regulation of the cell cycle phase mitotic spindle checkpoint pathway. We selected 26 regulated genes with the aid of the protein-protein interaction network analyzed by Molecular Complex Detection. RESULTS: We focused on three critical genes, which were highly expressed in GC, but negatively related to patient survival. Furthermore, we found that knockdown of BIRC5, TRIP13 or UBE2C significantly inhibited cell proliferation and induced cell apoptosis. In addition, knockdown of BIRC5, TRIP13 or UBE2C increased cellular sensitivity to cisplatin. CONCLUSION: Our study identified significantly upregulated genes in GC with a poor prognosis using integrated bioinformatics methods.
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spelling pubmed-104240212023-08-15 Identification of functional genes regulating gastric cancer progression using integrated bioinformatics analysis Yu, Kun Zhang, Dong Yao, Qiang Pan, Xing Wang, Gang Qian, Hai-Yang Xiao, Yao Chen, Qiong Mei, Ke World J Clin Cases Retrospective Study BACKGROUND: Gastric cancer (GC) is one of the most common cancers and has a poor prognosis. Treatment of GC has remained unchanged over the past few years. AIM: To investigate the potential therapeutic targets and related regulatory biomarkers of GC. METHODS: We obtained the public GC transcriptome sequencing dataset from the Gene Expression Omnibus database. The datasets contained 348 GC tissues and 141 healthy tissues. In total, 251 differentially expressed genes (DEGs) were identified, including 187 down-regulated genes and 64 up-regulated genes. The DEGs’ enriched functions and pathways include Progesterone-mediated oocyte maturation, cell cycle, and oocyte meiosis, Hepatitis B, and the Hippo signaling pathway. Survival analysis showed that BUB1, MAD2L1, CCNA2, CCNB1, and BIRC5 may be associated with regulation of the cell cycle phase mitotic spindle checkpoint pathway. We selected 26 regulated genes with the aid of the protein-protein interaction network analyzed by Molecular Complex Detection. RESULTS: We focused on three critical genes, which were highly expressed in GC, but negatively related to patient survival. Furthermore, we found that knockdown of BIRC5, TRIP13 or UBE2C significantly inhibited cell proliferation and induced cell apoptosis. In addition, knockdown of BIRC5, TRIP13 or UBE2C increased cellular sensitivity to cisplatin. CONCLUSION: Our study identified significantly upregulated genes in GC with a poor prognosis using integrated bioinformatics methods. Baishideng Publishing Group Inc 2023-07-26 2023-07-26 /pmc/articles/PMC10424021/ /pubmed/37583848 http://dx.doi.org/10.12998/wjcc.v11.i21.5023 Text en ©The Author(s) 2023. Published by Baishideng Publishing Group Inc. All rights reserved. https://creativecommons.org/licenses/by-nc/4.0/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/
spellingShingle Retrospective Study
Yu, Kun
Zhang, Dong
Yao, Qiang
Pan, Xing
Wang, Gang
Qian, Hai-Yang
Xiao, Yao
Chen, Qiong
Mei, Ke
Identification of functional genes regulating gastric cancer progression using integrated bioinformatics analysis
title Identification of functional genes regulating gastric cancer progression using integrated bioinformatics analysis
title_full Identification of functional genes regulating gastric cancer progression using integrated bioinformatics analysis
title_fullStr Identification of functional genes regulating gastric cancer progression using integrated bioinformatics analysis
title_full_unstemmed Identification of functional genes regulating gastric cancer progression using integrated bioinformatics analysis
title_short Identification of functional genes regulating gastric cancer progression using integrated bioinformatics analysis
title_sort identification of functional genes regulating gastric cancer progression using integrated bioinformatics analysis
topic Retrospective Study
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10424021/
https://www.ncbi.nlm.nih.gov/pubmed/37583848
http://dx.doi.org/10.12998/wjcc.v11.i21.5023
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