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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:...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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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. |
format | Online Article Text |
id | pubmed-6530124 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
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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