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Convergent evidence from systematic analysis of GWAS revealed genetic basis of esophageal cancer
Recent genome-wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) associated with risk of esophageal cancer (EC). However, investigation of genetic basis from the perspective of systematic biology and integrative genomics remains scarce. In this study, we explored...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Impact Journals LLC
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5190123/ https://www.ncbi.nlm.nih.gov/pubmed/27331408 http://dx.doi.org/10.18632/oncotarget.10133 |
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author | Gao, Xue-xin Gao, Lei Wang, Jiu-qiang Qu, Su-su Qu, Yue Sun, Hong-lei Liu, Si-dang Shang, Ying-li |
author_facet | Gao, Xue-xin Gao, Lei Wang, Jiu-qiang Qu, Su-su Qu, Yue Sun, Hong-lei Liu, Si-dang Shang, Ying-li |
author_sort | Gao, Xue-xin |
collection | PubMed |
description | Recent genome-wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) associated with risk of esophageal cancer (EC). However, investigation of genetic basis from the perspective of systematic biology and integrative genomics remains scarce. In this study, we explored genetic basis of EC based on GWAS data and implemented a series of bioinformatics methods including functional annotation, expression quantitative trait loci (eQTL) analysis, pathway enrichment analysis and pathway grouped network analysis. Two hundred and thirteen risk SNPs were identified, in which 44 SNPs were found to have significantly differential gene expression in esophageal tissues by eQTL analysis. By pathway enrichment analysis, 170 risk genes mapped by risk SNPs were enriched into 38 significant GO terms and 17 significant KEGG pathways, which were significantly grouped into 9 sub-networks by pathway grouped network analysis. The 9 groups of interconnected pathways were mainly involved with muscle cell proliferation, cellular response to interleukin-6, cell adhesion molecules, and ethanol oxidation, which might participate in the development of EC. Our findings provide genetic evidence and new insight for exploring the molecular mechanisms of EC. |
format | Online Article Text |
id | pubmed-5190123 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Impact Journals LLC |
record_format | MEDLINE/PubMed |
spelling | pubmed-51901232017-01-05 Convergent evidence from systematic analysis of GWAS revealed genetic basis of esophageal cancer Gao, Xue-xin Gao, Lei Wang, Jiu-qiang Qu, Su-su Qu, Yue Sun, Hong-lei Liu, Si-dang Shang, Ying-li Oncotarget Research Paper Recent genome-wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) associated with risk of esophageal cancer (EC). However, investigation of genetic basis from the perspective of systematic biology and integrative genomics remains scarce. In this study, we explored genetic basis of EC based on GWAS data and implemented a series of bioinformatics methods including functional annotation, expression quantitative trait loci (eQTL) analysis, pathway enrichment analysis and pathway grouped network analysis. Two hundred and thirteen risk SNPs were identified, in which 44 SNPs were found to have significantly differential gene expression in esophageal tissues by eQTL analysis. By pathway enrichment analysis, 170 risk genes mapped by risk SNPs were enriched into 38 significant GO terms and 17 significant KEGG pathways, which were significantly grouped into 9 sub-networks by pathway grouped network analysis. The 9 groups of interconnected pathways were mainly involved with muscle cell proliferation, cellular response to interleukin-6, cell adhesion molecules, and ethanol oxidation, which might participate in the development of EC. Our findings provide genetic evidence and new insight for exploring the molecular mechanisms of EC. Impact Journals LLC 2016-06-17 /pmc/articles/PMC5190123/ /pubmed/27331408 http://dx.doi.org/10.18632/oncotarget.10133 Text en Copyright: © 2016 Gao et al. http://creativecommons.org/licenses/by/2.5/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Paper Gao, Xue-xin Gao, Lei Wang, Jiu-qiang Qu, Su-su Qu, Yue Sun, Hong-lei Liu, Si-dang Shang, Ying-li Convergent evidence from systematic analysis of GWAS revealed genetic basis of esophageal cancer |
title | Convergent evidence from systematic analysis of GWAS revealed genetic basis of esophageal cancer |
title_full | Convergent evidence from systematic analysis of GWAS revealed genetic basis of esophageal cancer |
title_fullStr | Convergent evidence from systematic analysis of GWAS revealed genetic basis of esophageal cancer |
title_full_unstemmed | Convergent evidence from systematic analysis of GWAS revealed genetic basis of esophageal cancer |
title_short | Convergent evidence from systematic analysis of GWAS revealed genetic basis of esophageal cancer |
title_sort | convergent evidence from systematic analysis of gwas revealed genetic basis of esophageal cancer |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5190123/ https://www.ncbi.nlm.nih.gov/pubmed/27331408 http://dx.doi.org/10.18632/oncotarget.10133 |
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