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Prognostic marker identification based on weighted gene co-expression network analysis and associated in vitro confirmation in gastric cancer

The aim of this study was to explore the potential molecular mechanisms of Gastric cancer (GC) and identify new prognostic markers for GC. RNA sequencing data were downloaded from the Gene Expression Omnibus database, and 418 differentially expressed genes (DEGs) were screened. Weighted correlation...

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Autores principales: Guo, Haonan, Yang, Jun, Liu, Shanshan, Qin, Tao, Zhao, Qianwen, Hou, Xianliang, Ren, Lei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Taylor & Francis 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8806585/
https://www.ncbi.nlm.nih.gov/pubmed/34338150
http://dx.doi.org/10.1080/21655979.2021.1957645
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author Guo, Haonan
Yang, Jun
Liu, Shanshan
Qin, Tao
Zhao, Qianwen
Hou, Xianliang
Ren, Lei
author_facet Guo, Haonan
Yang, Jun
Liu, Shanshan
Qin, Tao
Zhao, Qianwen
Hou, Xianliang
Ren, Lei
author_sort Guo, Haonan
collection PubMed
description The aim of this study was to explore the potential molecular mechanisms of Gastric cancer (GC) and identify new prognostic markers for GC. RNA sequencing data were downloaded from the Gene Expression Omnibus database, and 418 differentially expressed genes (DEGs) were screened. Weighted correlation network analysis (WGCNA) was performed to identify six hub modules related to the clinical features of GC. Cytoscape software was used to identify five hub genes in the co-expression network, including CST1, CEMIP, COL8A1, PMEPA1, and MSLN. The TCGA database was used to verify hub gene expression in GC. The overall survival in the high CEMIP expression group was significantly lower than that of patients in the low CEMIP expression group. CEMIP expression was also found to be negatively correlated with B cell and CD4 + T cell infiltration. Further, associated in vitro experiments confirmed that CEMIP downregulation suppressed the proliferation and migration of GC cells and impaired the chemoresistance of GC cells to 5-fluorouracil. Our study effectively identified and validated prognostic biomarkers for GC, laying a new foundation for the therapeutic target, occurrence, and development of gastric cancer.
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spelling pubmed-88065852022-02-02 Prognostic marker identification based on weighted gene co-expression network analysis and associated in vitro confirmation in gastric cancer Guo, Haonan Yang, Jun Liu, Shanshan Qin, Tao Zhao, Qianwen Hou, Xianliang Ren, Lei Bioengineered Research Paper The aim of this study was to explore the potential molecular mechanisms of Gastric cancer (GC) and identify new prognostic markers for GC. RNA sequencing data were downloaded from the Gene Expression Omnibus database, and 418 differentially expressed genes (DEGs) were screened. Weighted correlation network analysis (WGCNA) was performed to identify six hub modules related to the clinical features of GC. Cytoscape software was used to identify five hub genes in the co-expression network, including CST1, CEMIP, COL8A1, PMEPA1, and MSLN. The TCGA database was used to verify hub gene expression in GC. The overall survival in the high CEMIP expression group was significantly lower than that of patients in the low CEMIP expression group. CEMIP expression was also found to be negatively correlated with B cell and CD4 + T cell infiltration. Further, associated in vitro experiments confirmed that CEMIP downregulation suppressed the proliferation and migration of GC cells and impaired the chemoresistance of GC cells to 5-fluorouracil. Our study effectively identified and validated prognostic biomarkers for GC, laying a new foundation for the therapeutic target, occurrence, and development of gastric cancer. Taylor & Francis 2021-08-02 /pmc/articles/PMC8806585/ /pubmed/34338150 http://dx.doi.org/10.1080/21655979.2021.1957645 Text en © 2021 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Paper
Guo, Haonan
Yang, Jun
Liu, Shanshan
Qin, Tao
Zhao, Qianwen
Hou, Xianliang
Ren, Lei
Prognostic marker identification based on weighted gene co-expression network analysis and associated in vitro confirmation in gastric cancer
title Prognostic marker identification based on weighted gene co-expression network analysis and associated in vitro confirmation in gastric cancer
title_full Prognostic marker identification based on weighted gene co-expression network analysis and associated in vitro confirmation in gastric cancer
title_fullStr Prognostic marker identification based on weighted gene co-expression network analysis and associated in vitro confirmation in gastric cancer
title_full_unstemmed Prognostic marker identification based on weighted gene co-expression network analysis and associated in vitro confirmation in gastric cancer
title_short Prognostic marker identification based on weighted gene co-expression network analysis and associated in vitro confirmation in gastric cancer
title_sort prognostic marker identification based on weighted gene co-expression network analysis and associated in vitro confirmation in gastric cancer
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8806585/
https://www.ncbi.nlm.nih.gov/pubmed/34338150
http://dx.doi.org/10.1080/21655979.2021.1957645
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