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Investigating Potential Molecular Mechanisms of Carcinogenesis and Genes as Biomarkers for Prognosis of Gastric Cancer Based on Integrated Bioinformatics Analysis

Gastric cancer, as the fifth most common malignancy worldwide, is a deadly disease afflicting nearly a million people. Researchers have devoted much to study the mechanisms of carcinogenesis and progression, but the exact information of tumor initiation and progression is remained largely unknown. H...

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Autores principales: Zhu, Yi, Sun, Xiangwei, Lin, Ji, Zhang, Teming, Liu, Xin, Shen, Xian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Netherlands 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6614141/
https://www.ncbi.nlm.nih.gov/pubmed/30430424
http://dx.doi.org/10.1007/s12253-018-0523-4
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author Zhu, Yi
Sun, Xiangwei
Lin, Ji
Zhang, Teming
Liu, Xin
Shen, Xian
author_facet Zhu, Yi
Sun, Xiangwei
Lin, Ji
Zhang, Teming
Liu, Xin
Shen, Xian
author_sort Zhu, Yi
collection PubMed
description Gastric cancer, as the fifth most common malignancy worldwide, is a deadly disease afflicting nearly a million people. Researchers have devoted much to study the mechanisms of carcinogenesis and progression, but the exact information of tumor initiation and progression is remained largely unknown. Here, we hypothesized several differentially expressed genes and possible pathways by employing integrated bioinformatics analysis. We fully analyzed four gastric cancer-related microarray datasets to screen differentially expressed mRNAs (DEMs), miRNAs (DEMis) and lncRNAs (DELs). The functional enrichment analysis was deeply construed, PPI network and ceRNA regulatory network were constructed to investigate potential mechanisms of tumorigenesis and progression. Furthermore, survival analysis was performed to identify critical lncRNAs that may significantly affect pathogenesis of gastric cancer. QRT-PCR was applied to verify our result. We identified two hub subnetworks that may explain the progression, metastasis and poor prognosis of gastric cancer. Meanwhile, several potential significant lncRNAs were identified. In summary, we ascertained several significantly changed KEGG pathways in the tumor initiation and progression. We also hypothesized several lncRNAs that contribute to poor prognosis of gastric cancer via integrated bioinformatics, which deserve further investigation.
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spelling pubmed-66141412019-07-28 Investigating Potential Molecular Mechanisms of Carcinogenesis and Genes as Biomarkers for Prognosis of Gastric Cancer Based on Integrated Bioinformatics Analysis Zhu, Yi Sun, Xiangwei Lin, Ji Zhang, Teming Liu, Xin Shen, Xian Pathol Oncol Res Original Article Gastric cancer, as the fifth most common malignancy worldwide, is a deadly disease afflicting nearly a million people. Researchers have devoted much to study the mechanisms of carcinogenesis and progression, but the exact information of tumor initiation and progression is remained largely unknown. Here, we hypothesized several differentially expressed genes and possible pathways by employing integrated bioinformatics analysis. We fully analyzed four gastric cancer-related microarray datasets to screen differentially expressed mRNAs (DEMs), miRNAs (DEMis) and lncRNAs (DELs). The functional enrichment analysis was deeply construed, PPI network and ceRNA regulatory network were constructed to investigate potential mechanisms of tumorigenesis and progression. Furthermore, survival analysis was performed to identify critical lncRNAs that may significantly affect pathogenesis of gastric cancer. QRT-PCR was applied to verify our result. We identified two hub subnetworks that may explain the progression, metastasis and poor prognosis of gastric cancer. Meanwhile, several potential significant lncRNAs were identified. In summary, we ascertained several significantly changed KEGG pathways in the tumor initiation and progression. We also hypothesized several lncRNAs that contribute to poor prognosis of gastric cancer via integrated bioinformatics, which deserve further investigation. Springer Netherlands 2018-11-14 2019 /pmc/articles/PMC6614141/ /pubmed/30430424 http://dx.doi.org/10.1007/s12253-018-0523-4 Text en © The Author(s) 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Original Article
Zhu, Yi
Sun, Xiangwei
Lin, Ji
Zhang, Teming
Liu, Xin
Shen, Xian
Investigating Potential Molecular Mechanisms of Carcinogenesis and Genes as Biomarkers for Prognosis of Gastric Cancer Based on Integrated Bioinformatics Analysis
title Investigating Potential Molecular Mechanisms of Carcinogenesis and Genes as Biomarkers for Prognosis of Gastric Cancer Based on Integrated Bioinformatics Analysis
title_full Investigating Potential Molecular Mechanisms of Carcinogenesis and Genes as Biomarkers for Prognosis of Gastric Cancer Based on Integrated Bioinformatics Analysis
title_fullStr Investigating Potential Molecular Mechanisms of Carcinogenesis and Genes as Biomarkers for Prognosis of Gastric Cancer Based on Integrated Bioinformatics Analysis
title_full_unstemmed Investigating Potential Molecular Mechanisms of Carcinogenesis and Genes as Biomarkers for Prognosis of Gastric Cancer Based on Integrated Bioinformatics Analysis
title_short Investigating Potential Molecular Mechanisms of Carcinogenesis and Genes as Biomarkers for Prognosis of Gastric Cancer Based on Integrated Bioinformatics Analysis
title_sort investigating potential molecular mechanisms of carcinogenesis and genes as biomarkers for prognosis of gastric cancer based on integrated bioinformatics analysis
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6614141/
https://www.ncbi.nlm.nih.gov/pubmed/30430424
http://dx.doi.org/10.1007/s12253-018-0523-4
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