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Candidate genes in gastric cancer identified by constructing a weighted gene co-expression network
BACKGROUND: Gastric cancer (GC) is one of the most common cancers with high mortality globally. However, the molecular mechanisms of GC are unclear, and the prognosis of GC is poor. Therefore, it is important to explore the underlying mechanisms and screen for novel prognostic markers and treatment...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5937478/ https://www.ncbi.nlm.nih.gov/pubmed/29740513 http://dx.doi.org/10.7717/peerj.4692 |
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author | Chen, Jian Wang, Xiuwen Hu, Bing He, Yifu Qian, Xiaojun Wang, Wei |
author_facet | Chen, Jian Wang, Xiuwen Hu, Bing He, Yifu Qian, Xiaojun Wang, Wei |
author_sort | Chen, Jian |
collection | PubMed |
description | BACKGROUND: Gastric cancer (GC) is one of the most common cancers with high mortality globally. However, the molecular mechanisms of GC are unclear, and the prognosis of GC is poor. Therefore, it is important to explore the underlying mechanisms and screen for novel prognostic markers and treatment targets. METHODS: The genetic and clinical data of GC patients in The Cancer Genome Atlas (TCGA) was analyzed by weighted gene co-expression network analysis (WGCNA). Modules with clinical significance and preservation were distinguished, and gene ontology and pathway enrichment analysis were performed. Hub genes of these modules were validated in the TCGA dataset and another independent dataset from the Gene Expression Omnibus (GEO) database by t-test. Furthermore, the significance of these genes was confirmed via survival analysis. RESULTS: We found a preserved module consisting of 506 genes was associated with clinical traits including pathologic T stage and histologic grade. PDGFRB, COL8A1, EFEMP2, FBN1, EMILIN1, FSTL1 and KIRREL were identified as candidate genes in the module. Their expression levels were correlated with pathologic T stage and histologic grade, also affected overall survival of GC patients. CONCLUSION: These candidate genes may be involved in proliferation and differentiation of GC cells. They may serve as novel prognostic markers and treatment targets. Moreover, most of them were first reported in GC and deserved further research. |
format | Online Article Text |
id | pubmed-5937478 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-59374782018-05-08 Candidate genes in gastric cancer identified by constructing a weighted gene co-expression network Chen, Jian Wang, Xiuwen Hu, Bing He, Yifu Qian, Xiaojun Wang, Wei PeerJ Bioinformatics BACKGROUND: Gastric cancer (GC) is one of the most common cancers with high mortality globally. However, the molecular mechanisms of GC are unclear, and the prognosis of GC is poor. Therefore, it is important to explore the underlying mechanisms and screen for novel prognostic markers and treatment targets. METHODS: The genetic and clinical data of GC patients in The Cancer Genome Atlas (TCGA) was analyzed by weighted gene co-expression network analysis (WGCNA). Modules with clinical significance and preservation were distinguished, and gene ontology and pathway enrichment analysis were performed. Hub genes of these modules were validated in the TCGA dataset and another independent dataset from the Gene Expression Omnibus (GEO) database by t-test. Furthermore, the significance of these genes was confirmed via survival analysis. RESULTS: We found a preserved module consisting of 506 genes was associated with clinical traits including pathologic T stage and histologic grade. PDGFRB, COL8A1, EFEMP2, FBN1, EMILIN1, FSTL1 and KIRREL were identified as candidate genes in the module. Their expression levels were correlated with pathologic T stage and histologic grade, also affected overall survival of GC patients. CONCLUSION: These candidate genes may be involved in proliferation and differentiation of GC cells. They may serve as novel prognostic markers and treatment targets. Moreover, most of them were first reported in GC and deserved further research. PeerJ Inc. 2018-05-04 /pmc/articles/PMC5937478/ /pubmed/29740513 http://dx.doi.org/10.7717/peerj.4692 Text en ©2018 Chen et al. http://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/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited. |
spellingShingle | Bioinformatics Chen, Jian Wang, Xiuwen Hu, Bing He, Yifu Qian, Xiaojun Wang, Wei Candidate genes in gastric cancer identified by constructing a weighted gene co-expression network |
title | Candidate genes in gastric cancer identified by constructing a weighted gene co-expression network |
title_full | Candidate genes in gastric cancer identified by constructing a weighted gene co-expression network |
title_fullStr | Candidate genes in gastric cancer identified by constructing a weighted gene co-expression network |
title_full_unstemmed | Candidate genes in gastric cancer identified by constructing a weighted gene co-expression network |
title_short | Candidate genes in gastric cancer identified by constructing a weighted gene co-expression network |
title_sort | candidate genes in gastric cancer identified by constructing a weighted gene co-expression network |
topic | Bioinformatics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5937478/ https://www.ncbi.nlm.nih.gov/pubmed/29740513 http://dx.doi.org/10.7717/peerj.4692 |
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