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Identification of Potential Key Genes Associated With the Pathogenesis and Prognosis of Gastric Cancer Based on Integrated Bioinformatics Analysis
Background and Objective: Despite striking advances in multimodality management, gastric cancer (GC) remains the third cause of cancer mortality globally and identifying novel diagnostic and prognostic biomarkers is urgently demanded. The study aimed to identify potential key genes associated with t...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6056647/ https://www.ncbi.nlm.nih.gov/pubmed/30065754 http://dx.doi.org/10.3389/fgene.2018.00265 |
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author | Liu, Xinkui Wu, Jiarui Zhang, Dan Bing, Zhitong Tian, Jinhui Ni, Mengwei Zhang, Xiaomeng Meng, Ziqi Liu, Shuyu |
author_facet | Liu, Xinkui Wu, Jiarui Zhang, Dan Bing, Zhitong Tian, Jinhui Ni, Mengwei Zhang, Xiaomeng Meng, Ziqi Liu, Shuyu |
author_sort | Liu, Xinkui |
collection | PubMed |
description | Background and Objective: Despite striking advances in multimodality management, gastric cancer (GC) remains the third cause of cancer mortality globally and identifying novel diagnostic and prognostic biomarkers is urgently demanded. The study aimed to identify potential key genes associated with the pathogenesis and prognosis of GC. Methods: Differentially expressed genes between GC and normal gastric tissue samples were screened by an integrated analysis of multiple gene expression profile datasets. Key genes related to the pathogenesis and prognosis of GC were identified by employing protein–protein interaction network and Cox proportional hazards model analyses. Results: We identified nine hub genes (TOP2A, COL1A1, COL1A2, NDC80, COL3A1, CDKN3, CEP55, TPX2, and TIMP1) which might be tightly correlated with the pathogenesis of GC. A prognostic gene signature consisted of CST2, AADAC, SERPINE1, COL8A1, SMPD3, ASPN, ITGBL1, MAP7D2, and PLEKHS1 was constructed with a good performance in predicting overall survivals. Conclusion: The findings of this study would provide some directive significance for further investigating the diagnostic and prognostic biomarkers to facilitate the molecular targeting therapy of GC. |
format | Online Article Text |
id | pubmed-6056647 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-60566472018-07-31 Identification of Potential Key Genes Associated With the Pathogenesis and Prognosis of Gastric Cancer Based on Integrated Bioinformatics Analysis Liu, Xinkui Wu, Jiarui Zhang, Dan Bing, Zhitong Tian, Jinhui Ni, Mengwei Zhang, Xiaomeng Meng, Ziqi Liu, Shuyu Front Genet Genetics Background and Objective: Despite striking advances in multimodality management, gastric cancer (GC) remains the third cause of cancer mortality globally and identifying novel diagnostic and prognostic biomarkers is urgently demanded. The study aimed to identify potential key genes associated with the pathogenesis and prognosis of GC. Methods: Differentially expressed genes between GC and normal gastric tissue samples were screened by an integrated analysis of multiple gene expression profile datasets. Key genes related to the pathogenesis and prognosis of GC were identified by employing protein–protein interaction network and Cox proportional hazards model analyses. Results: We identified nine hub genes (TOP2A, COL1A1, COL1A2, NDC80, COL3A1, CDKN3, CEP55, TPX2, and TIMP1) which might be tightly correlated with the pathogenesis of GC. A prognostic gene signature consisted of CST2, AADAC, SERPINE1, COL8A1, SMPD3, ASPN, ITGBL1, MAP7D2, and PLEKHS1 was constructed with a good performance in predicting overall survivals. Conclusion: The findings of this study would provide some directive significance for further investigating the diagnostic and prognostic biomarkers to facilitate the molecular targeting therapy of GC. Frontiers Media S.A. 2018-07-17 /pmc/articles/PMC6056647/ /pubmed/30065754 http://dx.doi.org/10.3389/fgene.2018.00265 Text en Copyright © 2018 Liu, Wu, Zhang, Bing, Tian, Ni, Zhang, Meng and Liu. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Genetics Liu, Xinkui Wu, Jiarui Zhang, Dan Bing, Zhitong Tian, Jinhui Ni, Mengwei Zhang, Xiaomeng Meng, Ziqi Liu, Shuyu Identification of Potential Key Genes Associated With the Pathogenesis and Prognosis of Gastric Cancer Based on Integrated Bioinformatics Analysis |
title | Identification of Potential Key Genes Associated With the Pathogenesis and Prognosis of Gastric Cancer Based on Integrated Bioinformatics Analysis |
title_full | Identification of Potential Key Genes Associated With the Pathogenesis and Prognosis of Gastric Cancer Based on Integrated Bioinformatics Analysis |
title_fullStr | Identification of Potential Key Genes Associated With the Pathogenesis and Prognosis of Gastric Cancer Based on Integrated Bioinformatics Analysis |
title_full_unstemmed | Identification of Potential Key Genes Associated With the Pathogenesis and Prognosis of Gastric Cancer Based on Integrated Bioinformatics Analysis |
title_short | Identification of Potential Key Genes Associated With the Pathogenesis and Prognosis of Gastric Cancer Based on Integrated Bioinformatics Analysis |
title_sort | identification of potential key genes associated with the pathogenesis and prognosis of gastric cancer based on integrated bioinformatics analysis |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6056647/ https://www.ncbi.nlm.nih.gov/pubmed/30065754 http://dx.doi.org/10.3389/fgene.2018.00265 |
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