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Identification of hub genes and therapeutic drugs in esophageal squamous cell carcinoma based on integrated bioinformatics strategy

BACKGROUND: Esophageal squamous cell carcinoma (ESCC) is one of leading malignant cancers of gastrointestinal tract worldwide. Until now, the involved mechanisms during the development of ESCC are largely unknown. This study aims to explore the driven-genes and biological pathways in ESCC. METHODS:...

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Autores principales: Yang, Wanli, Zhao, Xinhui, Han, Yu, Duan, Lili, Lu, Xin, Wang, Xiaoqian, Zhang, Yujie, Zhou, Wei, Liu, Jinqiang, Zhang, Hongwei, Zhao, Qingchuan, Hong, Liu, Fan, Daiming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6530124/
https://www.ncbi.nlm.nih.gov/pubmed/31139019
http://dx.doi.org/10.1186/s12935-019-0854-6
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author Yang, Wanli
Zhao, Xinhui
Han, Yu
Duan, Lili
Lu, Xin
Wang, Xiaoqian
Zhang, Yujie
Zhou, Wei
Liu, Jinqiang
Zhang, Hongwei
Zhao, Qingchuan
Hong, Liu
Fan, Daiming
author_facet Yang, Wanli
Zhao, Xinhui
Han, Yu
Duan, Lili
Lu, Xin
Wang, Xiaoqian
Zhang, Yujie
Zhou, Wei
Liu, Jinqiang
Zhang, Hongwei
Zhao, Qingchuan
Hong, Liu
Fan, Daiming
author_sort Yang, Wanli
collection PubMed
description BACKGROUND: Esophageal squamous cell carcinoma (ESCC) is one of leading malignant cancers of gastrointestinal tract worldwide. Until now, the involved mechanisms during the development of ESCC are largely unknown. This study aims to explore the driven-genes and biological pathways in ESCC. METHODS: mRNA expression datasets of GSE29001, GSE20347, GSE100942, and GSE38129, containing 63 pairs of ESCC and non-tumor tissues data, were integrated and deeply analyzed. The bioinformatics approaches include identification of differentially expressed genes (DEGs) and hub genes, gene ontology (GO) terms analysis and biological pathway enrichment analysis, construction and analysis of protein–protein interaction (PPI) network, and miRNA–gene network construction. Subsequently, GEPIA2 database and qPCR assay were utilized to validate the expression of hub genes. DGIdb database was performed to search the candidate drugs for ESCC. RESULTS: Finally, 120 upregulated and 26 downregulated DEGs were identified. The functional enrichment of DEGs in ESCC were mainly correlated with cell cycle, DNA replication, deleted in colorectal cancer (DCC) mediated attractive signaling pathway, and Netrin-1 signaling pathway. The PPI network was constructed using STRING software with 146 nodes and 2392 edges. The most significant three modules in PPI were filtered and analyzed. Totally ten genes were selected and considered as the hub genes and nuclear division cycle 80 (NDC80) was closely related to the survival of ESCC patients. DGIdb database predicted 33 small molecules as the possible drugs for treating ESCC. CONCLUSIONS: In summary, the data may provide new insights into ESCC pathogenesis and treatments. The candidate drugs may improve the efficiency of personalized therapy in future. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12935-019-0854-6) contains supplementary material, which is available to authorized users.
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spelling pubmed-65301242019-05-28 Identification of hub genes and therapeutic drugs in esophageal squamous cell carcinoma based on integrated bioinformatics strategy Yang, Wanli Zhao, Xinhui Han, Yu Duan, Lili Lu, Xin Wang, Xiaoqian Zhang, Yujie Zhou, Wei Liu, Jinqiang Zhang, Hongwei Zhao, Qingchuan Hong, Liu Fan, Daiming Cancer Cell Int Primary Research BACKGROUND: Esophageal squamous cell carcinoma (ESCC) is one of leading malignant cancers of gastrointestinal tract worldwide. Until now, the involved mechanisms during the development of ESCC are largely unknown. This study aims to explore the driven-genes and biological pathways in ESCC. METHODS: mRNA expression datasets of GSE29001, GSE20347, GSE100942, and GSE38129, containing 63 pairs of ESCC and non-tumor tissues data, were integrated and deeply analyzed. The bioinformatics approaches include identification of differentially expressed genes (DEGs) and hub genes, gene ontology (GO) terms analysis and biological pathway enrichment analysis, construction and analysis of protein–protein interaction (PPI) network, and miRNA–gene network construction. Subsequently, GEPIA2 database and qPCR assay were utilized to validate the expression of hub genes. DGIdb database was performed to search the candidate drugs for ESCC. RESULTS: Finally, 120 upregulated and 26 downregulated DEGs were identified. The functional enrichment of DEGs in ESCC were mainly correlated with cell cycle, DNA replication, deleted in colorectal cancer (DCC) mediated attractive signaling pathway, and Netrin-1 signaling pathway. The PPI network was constructed using STRING software with 146 nodes and 2392 edges. The most significant three modules in PPI were filtered and analyzed. Totally ten genes were selected and considered as the hub genes and nuclear division cycle 80 (NDC80) was closely related to the survival of ESCC patients. DGIdb database predicted 33 small molecules as the possible drugs for treating ESCC. CONCLUSIONS: In summary, the data may provide new insights into ESCC pathogenesis and treatments. The candidate drugs may improve the efficiency of personalized therapy in future. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12935-019-0854-6) contains supplementary material, which is available to authorized users. BioMed Central 2019-05-22 /pmc/articles/PMC6530124/ /pubmed/31139019 http://dx.doi.org/10.1186/s12935-019-0854-6 Text en © The Author(s) 2019 Open AccessThis 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. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Primary Research
Yang, Wanli
Zhao, Xinhui
Han, Yu
Duan, Lili
Lu, Xin
Wang, Xiaoqian
Zhang, Yujie
Zhou, Wei
Liu, Jinqiang
Zhang, Hongwei
Zhao, Qingchuan
Hong, Liu
Fan, Daiming
Identification of hub genes and therapeutic drugs in esophageal squamous cell carcinoma based on integrated bioinformatics strategy
title Identification of hub genes and therapeutic drugs in esophageal squamous cell carcinoma based on integrated bioinformatics strategy
title_full Identification of hub genes and therapeutic drugs in esophageal squamous cell carcinoma based on integrated bioinformatics strategy
title_fullStr Identification of hub genes and therapeutic drugs in esophageal squamous cell carcinoma based on integrated bioinformatics strategy
title_full_unstemmed Identification of hub genes and therapeutic drugs in esophageal squamous cell carcinoma based on integrated bioinformatics strategy
title_short Identification of hub genes and therapeutic drugs in esophageal squamous cell carcinoma based on integrated bioinformatics strategy
title_sort identification of hub genes and therapeutic drugs in esophageal squamous cell carcinoma based on integrated bioinformatics strategy
topic Primary Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6530124/
https://www.ncbi.nlm.nih.gov/pubmed/31139019
http://dx.doi.org/10.1186/s12935-019-0854-6
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