Cargando…
Systematic identification of key functional modules and genes in esophageal cancer
BACKGROUND: Esophageal cancer is associated with high incidence and mortality worldwide. Differential expression genes (DEGs) and weighted gene co-expression network analysis (WGCNA) are important methods to screen the core genes as bioinformatics methods. METHODS: The DEGs and WGCNA were combined t...
Autores principales: | , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7905886/ https://www.ncbi.nlm.nih.gov/pubmed/33632229 http://dx.doi.org/10.1186/s12935-021-01826-x |
_version_ | 1783655191649714176 |
---|---|
author | Wu, Rui Zhuang, Hao Mei, Yu-Kun Sun, Jin-Yu Dong, Tao Zhao, Li-Li Fan, Zhi-Ning Liu, Li |
author_facet | Wu, Rui Zhuang, Hao Mei, Yu-Kun Sun, Jin-Yu Dong, Tao Zhao, Li-Li Fan, Zhi-Ning Liu, Li |
author_sort | Wu, Rui |
collection | PubMed |
description | BACKGROUND: Esophageal cancer is associated with high incidence and mortality worldwide. Differential expression genes (DEGs) and weighted gene co-expression network analysis (WGCNA) are important methods to screen the core genes as bioinformatics methods. METHODS: The DEGs and WGCNA were combined to screen the hub genes, and pathway enrichment analyses were performed on the hub module in the WGCNA. The CCNB1 was identified as the hub gene based on the intersection between DEGs and the greenyellow module in WGCNA. Expression levels and prognostic values of CCNB1 were verified in UALCAN, GEPIA2, HCMDB, Kaplan–Meier plotter, and TIMER databases. RESULTS: We identified 1,044 DEGs from dataset GSE20347, 1,904 from GSE29001, and 2,722 from GSE111044, and 32 modules were revealed by WGCNA. The greenyellow module was identified as the hub module in the WGCNA. CCNB1 gene was identified as the hub gene, which was upregulated in tumour tissues. Moreover, esophageal cancer patients with higher expression of CCNB1 showed a worse prognosis. However, CCNB1 ‘might not play an important role in immune cell infiltration. CONCLUSIONS: Based on DEGs and key modules related to esophageal cancer, CCNB1 was identified as the hub gene, which offered novel insights into the development and treatment of esophageal cancer. |
format | Online Article Text |
id | pubmed-7905886 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-79058862021-02-26 Systematic identification of key functional modules and genes in esophageal cancer Wu, Rui Zhuang, Hao Mei, Yu-Kun Sun, Jin-Yu Dong, Tao Zhao, Li-Li Fan, Zhi-Ning Liu, Li Cancer Cell Int Primary Research BACKGROUND: Esophageal cancer is associated with high incidence and mortality worldwide. Differential expression genes (DEGs) and weighted gene co-expression network analysis (WGCNA) are important methods to screen the core genes as bioinformatics methods. METHODS: The DEGs and WGCNA were combined to screen the hub genes, and pathway enrichment analyses were performed on the hub module in the WGCNA. The CCNB1 was identified as the hub gene based on the intersection between DEGs and the greenyellow module in WGCNA. Expression levels and prognostic values of CCNB1 were verified in UALCAN, GEPIA2, HCMDB, Kaplan–Meier plotter, and TIMER databases. RESULTS: We identified 1,044 DEGs from dataset GSE20347, 1,904 from GSE29001, and 2,722 from GSE111044, and 32 modules were revealed by WGCNA. The greenyellow module was identified as the hub module in the WGCNA. CCNB1 gene was identified as the hub gene, which was upregulated in tumour tissues. Moreover, esophageal cancer patients with higher expression of CCNB1 showed a worse prognosis. However, CCNB1 ‘might not play an important role in immune cell infiltration. CONCLUSIONS: Based on DEGs and key modules related to esophageal cancer, CCNB1 was identified as the hub gene, which offered novel insights into the development and treatment of esophageal cancer. BioMed Central 2021-02-25 /pmc/articles/PMC7905886/ /pubmed/33632229 http://dx.doi.org/10.1186/s12935-021-01826-x Text en © The Author(s) 2021 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. 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 in a credit line to the data. |
spellingShingle | Primary Research Wu, Rui Zhuang, Hao Mei, Yu-Kun Sun, Jin-Yu Dong, Tao Zhao, Li-Li Fan, Zhi-Ning Liu, Li Systematic identification of key functional modules and genes in esophageal cancer |
title | Systematic identification of key functional modules and genes in esophageal cancer |
title_full | Systematic identification of key functional modules and genes in esophageal cancer |
title_fullStr | Systematic identification of key functional modules and genes in esophageal cancer |
title_full_unstemmed | Systematic identification of key functional modules and genes in esophageal cancer |
title_short | Systematic identification of key functional modules and genes in esophageal cancer |
title_sort | systematic identification of key functional modules and genes in esophageal cancer |
topic | Primary Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7905886/ https://www.ncbi.nlm.nih.gov/pubmed/33632229 http://dx.doi.org/10.1186/s12935-021-01826-x |
work_keys_str_mv | AT wurui systematicidentificationofkeyfunctionalmodulesandgenesinesophagealcancer AT zhuanghao systematicidentificationofkeyfunctionalmodulesandgenesinesophagealcancer AT meiyukun systematicidentificationofkeyfunctionalmodulesandgenesinesophagealcancer AT sunjinyu systematicidentificationofkeyfunctionalmodulesandgenesinesophagealcancer AT dongtao systematicidentificationofkeyfunctionalmodulesandgenesinesophagealcancer AT zhaolili systematicidentificationofkeyfunctionalmodulesandgenesinesophagealcancer AT fanzhining systematicidentificationofkeyfunctionalmodulesandgenesinesophagealcancer AT liuli systematicidentificationofkeyfunctionalmodulesandgenesinesophagealcancer |