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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...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Taylor & Francis
2021
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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. |
format | Online Article Text |
id | pubmed-8806585 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Taylor & Francis |
record_format | MEDLINE/PubMed |
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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