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Time series expression pattern of key genes reveals the molecular process of esophageal cancer

Background: Esophageal cancer is one of the most poorly diagnosed and fatal cancers in the world. Although a series of studies on esophageal cancer have been reported, the molecular pathogenesis of the disease is still elusive. Aim: To investigate the molecular process of esophageal cancer comprehen...

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Autores principales: Wang, Jiafu, Xie, Xiang, Sun, Yurong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Portland Press Ltd. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7048673/
https://www.ncbi.nlm.nih.gov/pubmed/32068233
http://dx.doi.org/10.1042/BSR20191985
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author Wang, Jiafu
Xie, Xiang
Sun, Yurong
author_facet Wang, Jiafu
Xie, Xiang
Sun, Yurong
author_sort Wang, Jiafu
collection PubMed
description Background: Esophageal cancer is one of the most poorly diagnosed and fatal cancers in the world. Although a series of studies on esophageal cancer have been reported, the molecular pathogenesis of the disease is still elusive. Aim: To investigate the molecular process of esophageal cancer comprehensively and deeply. Methods: Differential expression analysis was performed to identify differentially expressed genes (DEGs) in different stages of esophageal cancer. Then exacting gene interaction modules and hub genes were identified in module interaction network. Further, though survival analysis, methylation analysis, pivot analysis, and enrichment analysis, some important molecules and related function or pathway were identified to elucidate potential mechanism in esophageal cancer. Results: A total of 7457 DEGs and 14 gene interaction modules were identified. These module genes were significantly involved in the positive regulation of protein transport, gastric acid secretion, insulin-like growth factor receptor binding and other biological processes (BPs), as well as p53 signaling pathway, ERBB signaling pathway and epidermal growth factor receptor (EGFR) signaling pathway. Then, transcription factors (TFs) (including HIF1A) and ncRNAs (including CRNDE and hsa-mir-330-3p) significantly regulate dysfunction modules were identified. Further, survival analysis showed that GNGT2 was closely related to survival of esophageal cancer. And DEGs with strong methylation regulation ability were identified, including SST and SH3GL2. Conclusion: These works not only help us to reveal the potential regulatory factors in the development of disease, but also deepen our understanding of its deterioration mechanism.
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spelling pubmed-70486732020-03-10 Time series expression pattern of key genes reveals the molecular process of esophageal cancer Wang, Jiafu Xie, Xiang Sun, Yurong Biosci Rep Cancer Background: Esophageal cancer is one of the most poorly diagnosed and fatal cancers in the world. Although a series of studies on esophageal cancer have been reported, the molecular pathogenesis of the disease is still elusive. Aim: To investigate the molecular process of esophageal cancer comprehensively and deeply. Methods: Differential expression analysis was performed to identify differentially expressed genes (DEGs) in different stages of esophageal cancer. Then exacting gene interaction modules and hub genes were identified in module interaction network. Further, though survival analysis, methylation analysis, pivot analysis, and enrichment analysis, some important molecules and related function or pathway were identified to elucidate potential mechanism in esophageal cancer. Results: A total of 7457 DEGs and 14 gene interaction modules were identified. These module genes were significantly involved in the positive regulation of protein transport, gastric acid secretion, insulin-like growth factor receptor binding and other biological processes (BPs), as well as p53 signaling pathway, ERBB signaling pathway and epidermal growth factor receptor (EGFR) signaling pathway. Then, transcription factors (TFs) (including HIF1A) and ncRNAs (including CRNDE and hsa-mir-330-3p) significantly regulate dysfunction modules were identified. Further, survival analysis showed that GNGT2 was closely related to survival of esophageal cancer. And DEGs with strong methylation regulation ability were identified, including SST and SH3GL2. Conclusion: These works not only help us to reveal the potential regulatory factors in the development of disease, but also deepen our understanding of its deterioration mechanism. Portland Press Ltd. 2020-02-28 /pmc/articles/PMC7048673/ /pubmed/32068233 http://dx.doi.org/10.1042/BSR20191985 Text en © 2020 The Author(s). https://creativecommons.org/licenses/by/4.0/ This is an open access article published by Portland Press Limited on behalf of the Biochemical Society and distributed under the Creative Commons Attribution License 4.0 (CC BY).
spellingShingle Cancer
Wang, Jiafu
Xie, Xiang
Sun, Yurong
Time series expression pattern of key genes reveals the molecular process of esophageal cancer
title Time series expression pattern of key genes reveals the molecular process of esophageal cancer
title_full Time series expression pattern of key genes reveals the molecular process of esophageal cancer
title_fullStr Time series expression pattern of key genes reveals the molecular process of esophageal cancer
title_full_unstemmed Time series expression pattern of key genes reveals the molecular process of esophageal cancer
title_short Time series expression pattern of key genes reveals the molecular process of esophageal cancer
title_sort time series expression pattern of key genes reveals the molecular process of esophageal cancer
topic Cancer
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7048673/
https://www.ncbi.nlm.nih.gov/pubmed/32068233
http://dx.doi.org/10.1042/BSR20191985
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