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Overexpression of CCNE1 confers a poorer prognosis in triple-negative breast cancer identified by bioinformatic analysis
BACKGROUND: Triple-negative breast cancer (TNBC) is a major subtype of breast cancer. Due to the lack of effective therapeutic targets, the prognosis is poor. In order to find an effective target, despite many efforts, the molecular mechanisms of TNBC are still not well understood which remain to be...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7989008/ https://www.ncbi.nlm.nih.gov/pubmed/33757543 http://dx.doi.org/10.1186/s12957-021-02200-x |
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author | Yuan, Qianqian Zheng, Lewei Liao, Yiqin Wu, Gaosong |
author_facet | Yuan, Qianqian Zheng, Lewei Liao, Yiqin Wu, Gaosong |
author_sort | Yuan, Qianqian |
collection | PubMed |
description | BACKGROUND: Triple-negative breast cancer (TNBC) is a major subtype of breast cancer. Due to the lack of effective therapeutic targets, the prognosis is poor. In order to find an effective target, despite many efforts, the molecular mechanisms of TNBC are still not well understood which remain to be a profound clinical challenge. METHODS: To identify the candidate genes in the carcinogenesis and progression of TNBC, microarray datasets GSE36693 and GSE65216 were downloaded from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified, and functional and pathway enrichment analyses were performed using the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases via DAVID. We constructed the protein-protein interaction network (PPI) and performed the module analysis using STRING and Cytoscape. Then, we reanalyzed the selected DEG genes, and the survival analysis was performed using cBioportal. RESULTS: A total of 140 DEGs were identified, consisting of 69 upregulated genes and 71 downregulated genes. Three hub genes were upregulated among the selected genes from PPI, and biological process analysis uncovered the fact that these genes were mainly enriched in p53 pathway and the pathways in cancer. Survival analysis showed that only CCNE1 may be involved in the carcinogenesis, invasion, or recurrence of TNBC. The expression levels of CCNE1 were significantly higher in TNBC cells than non-TNBC cells that were detected by qRT-PCR (P < 0.05). CONCLUSION: CCNE1 could confer a poorer prognosis in TNBC identified by bioinformatic analysis and plays key roles in the progression of TNBC which may contribute potential targets for the diagnosis, treatment, and prognosis assessment of TNBC. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12957-021-02200-x. |
format | Online Article Text |
id | pubmed-7989008 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-79890082021-03-25 Overexpression of CCNE1 confers a poorer prognosis in triple-negative breast cancer identified by bioinformatic analysis Yuan, Qianqian Zheng, Lewei Liao, Yiqin Wu, Gaosong World J Surg Oncol Research BACKGROUND: Triple-negative breast cancer (TNBC) is a major subtype of breast cancer. Due to the lack of effective therapeutic targets, the prognosis is poor. In order to find an effective target, despite many efforts, the molecular mechanisms of TNBC are still not well understood which remain to be a profound clinical challenge. METHODS: To identify the candidate genes in the carcinogenesis and progression of TNBC, microarray datasets GSE36693 and GSE65216 were downloaded from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified, and functional and pathway enrichment analyses were performed using the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases via DAVID. We constructed the protein-protein interaction network (PPI) and performed the module analysis using STRING and Cytoscape. Then, we reanalyzed the selected DEG genes, and the survival analysis was performed using cBioportal. RESULTS: A total of 140 DEGs were identified, consisting of 69 upregulated genes and 71 downregulated genes. Three hub genes were upregulated among the selected genes from PPI, and biological process analysis uncovered the fact that these genes were mainly enriched in p53 pathway and the pathways in cancer. Survival analysis showed that only CCNE1 may be involved in the carcinogenesis, invasion, or recurrence of TNBC. The expression levels of CCNE1 were significantly higher in TNBC cells than non-TNBC cells that were detected by qRT-PCR (P < 0.05). CONCLUSION: CCNE1 could confer a poorer prognosis in TNBC identified by bioinformatic analysis and plays key roles in the progression of TNBC which may contribute potential targets for the diagnosis, treatment, and prognosis assessment of TNBC. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12957-021-02200-x. BioMed Central 2021-03-23 /pmc/articles/PMC7989008/ /pubmed/33757543 http://dx.doi.org/10.1186/s12957-021-02200-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 | Research Yuan, Qianqian Zheng, Lewei Liao, Yiqin Wu, Gaosong Overexpression of CCNE1 confers a poorer prognosis in triple-negative breast cancer identified by bioinformatic analysis |
title | Overexpression of CCNE1 confers a poorer prognosis in triple-negative breast cancer identified by bioinformatic analysis |
title_full | Overexpression of CCNE1 confers a poorer prognosis in triple-negative breast cancer identified by bioinformatic analysis |
title_fullStr | Overexpression of CCNE1 confers a poorer prognosis in triple-negative breast cancer identified by bioinformatic analysis |
title_full_unstemmed | Overexpression of CCNE1 confers a poorer prognosis in triple-negative breast cancer identified by bioinformatic analysis |
title_short | Overexpression of CCNE1 confers a poorer prognosis in triple-negative breast cancer identified by bioinformatic analysis |
title_sort | overexpression of ccne1 confers a poorer prognosis in triple-negative breast cancer identified by bioinformatic analysis |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7989008/ https://www.ncbi.nlm.nih.gov/pubmed/33757543 http://dx.doi.org/10.1186/s12957-021-02200-x |
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