Cargando…

Identification of key genes for esophageal squamous cell carcinoma via integrated bioinformatics analysis and experimental confirmation

BACKGROUND: Esophageal squamous cell carcinoma (ESCC) as the main subtype of esophageal cancer (EC) is a leading cause of cancer-related death worldwide. Despite advances in early diagnosis and clinical management, the long-term survival of ESCC patients remains disappointing, due to a lack of full...

Descripción completa

Detalles Bibliográficos
Autores principales: Hu, Jia, Li, Rongzhen, Miao, Huikai, Wen, Zhesheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7330802/
https://www.ncbi.nlm.nih.gov/pubmed/32642240
http://dx.doi.org/10.21037/jtd.2020.01.33
_version_ 1783553199985131520
author Hu, Jia
Li, Rongzhen
Miao, Huikai
Wen, Zhesheng
author_facet Hu, Jia
Li, Rongzhen
Miao, Huikai
Wen, Zhesheng
author_sort Hu, Jia
collection PubMed
description BACKGROUND: Esophageal squamous cell carcinoma (ESCC) as the main subtype of esophageal cancer (EC) is a leading cause of cancer-related death worldwide. Despite advances in early diagnosis and clinical management, the long-term survival of ESCC patients remains disappointing, due to a lack of full understanding of the molecular mechanisms. METHODS: In order to identify the differentially expressed genes (DEGs) in ESCC, the microarray datasets GSE20347 and GSE26886 from Gene Expression Omnibus (GEO) database were analyzed. The enrichment analyses of gene ontology (GO) terms, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Set Enrichment Analysis (GSEA) were performed for the DEGs. The protein-protein interaction (PPI) network of these DEGs was constructed using the Cytoscape software based on the STRING database to select as hub genes for weighted co-expression network analysis (WGCNA) with ESCC samples from TCGA database. RESULTS: A total of 746 DEGs were commonly shared in the two datasets including 286 upregulated genes and 460 downregulated genes in ESCC. The DEGs were enriched in biological processes such as extracellular matrix organization, proliferation and keratinocyte differentiation, and were enriched in biological pathways such as ECM-receptor interaction and cell cycle. GSEA analysis also indicated the enrichment of upregulated DEGs in cell cycle. The 40 DEGs were selected as hub genes. The MEblack module was found to be enriched in the cell cycle, Spliceosome, DNA replication and Oocyte meiosis. Among the hub genes correlated with MEblack module, GSEA analysis indicated that DEGs of TCGA samples with DLGAP5 upregulation was enriched in cell cycle. Moreover, the highly endogenous expression of DLGAP5 was confirmed in ESCC cells. DLGAP5 knockdown significantly inhibited the proliferation of ESCC cells. CONCLUSIONS: DEGs and hub genes such as DLGAP5 from independent datasets in the current study will provide clues to elucidate the molecular mechanisms involved in development and progression of ESCC.
format Online
Article
Text
id pubmed-7330802
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher AME Publishing Company
record_format MEDLINE/PubMed
spelling pubmed-73308022020-07-07 Identification of key genes for esophageal squamous cell carcinoma via integrated bioinformatics analysis and experimental confirmation Hu, Jia Li, Rongzhen Miao, Huikai Wen, Zhesheng J Thorac Dis Original Article BACKGROUND: Esophageal squamous cell carcinoma (ESCC) as the main subtype of esophageal cancer (EC) is a leading cause of cancer-related death worldwide. Despite advances in early diagnosis and clinical management, the long-term survival of ESCC patients remains disappointing, due to a lack of full understanding of the molecular mechanisms. METHODS: In order to identify the differentially expressed genes (DEGs) in ESCC, the microarray datasets GSE20347 and GSE26886 from Gene Expression Omnibus (GEO) database were analyzed. The enrichment analyses of gene ontology (GO) terms, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Set Enrichment Analysis (GSEA) were performed for the DEGs. The protein-protein interaction (PPI) network of these DEGs was constructed using the Cytoscape software based on the STRING database to select as hub genes for weighted co-expression network analysis (WGCNA) with ESCC samples from TCGA database. RESULTS: A total of 746 DEGs were commonly shared in the two datasets including 286 upregulated genes and 460 downregulated genes in ESCC. The DEGs were enriched in biological processes such as extracellular matrix organization, proliferation and keratinocyte differentiation, and were enriched in biological pathways such as ECM-receptor interaction and cell cycle. GSEA analysis also indicated the enrichment of upregulated DEGs in cell cycle. The 40 DEGs were selected as hub genes. The MEblack module was found to be enriched in the cell cycle, Spliceosome, DNA replication and Oocyte meiosis. Among the hub genes correlated with MEblack module, GSEA analysis indicated that DEGs of TCGA samples with DLGAP5 upregulation was enriched in cell cycle. Moreover, the highly endogenous expression of DLGAP5 was confirmed in ESCC cells. DLGAP5 knockdown significantly inhibited the proliferation of ESCC cells. CONCLUSIONS: DEGs and hub genes such as DLGAP5 from independent datasets in the current study will provide clues to elucidate the molecular mechanisms involved in development and progression of ESCC. AME Publishing Company 2020-06 /pmc/articles/PMC7330802/ /pubmed/32642240 http://dx.doi.org/10.21037/jtd.2020.01.33 Text en 2020 Journal of Thoracic Disease. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Original Article
Hu, Jia
Li, Rongzhen
Miao, Huikai
Wen, Zhesheng
Identification of key genes for esophageal squamous cell carcinoma via integrated bioinformatics analysis and experimental confirmation
title Identification of key genes for esophageal squamous cell carcinoma via integrated bioinformatics analysis and experimental confirmation
title_full Identification of key genes for esophageal squamous cell carcinoma via integrated bioinformatics analysis and experimental confirmation
title_fullStr Identification of key genes for esophageal squamous cell carcinoma via integrated bioinformatics analysis and experimental confirmation
title_full_unstemmed Identification of key genes for esophageal squamous cell carcinoma via integrated bioinformatics analysis and experimental confirmation
title_short Identification of key genes for esophageal squamous cell carcinoma via integrated bioinformatics analysis and experimental confirmation
title_sort identification of key genes for esophageal squamous cell carcinoma via integrated bioinformatics analysis and experimental confirmation
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7330802/
https://www.ncbi.nlm.nih.gov/pubmed/32642240
http://dx.doi.org/10.21037/jtd.2020.01.33
work_keys_str_mv AT hujia identificationofkeygenesforesophagealsquamouscellcarcinomaviaintegratedbioinformaticsanalysisandexperimentalconfirmation
AT lirongzhen identificationofkeygenesforesophagealsquamouscellcarcinomaviaintegratedbioinformaticsanalysisandexperimentalconfirmation
AT miaohuikai identificationofkeygenesforesophagealsquamouscellcarcinomaviaintegratedbioinformaticsanalysisandexperimentalconfirmation
AT wenzhesheng identificationofkeygenesforesophagealsquamouscellcarcinomaviaintegratedbioinformaticsanalysisandexperimentalconfirmation