Overexpression of CCNE1 confers a poorer prognosis in triple-negative breast cancer identified by bioinformatic analysis

Abstract 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 rema...

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Main Authors: Qianqian Yuan, Lewei Zheng, Yiqin Liao, Gaosong Wu
Format: Article
Language:English
Published: BMC 2021-03-01
Series:World Journal of Surgical Oncology
Subjects:
GEO
Online Access:https://doi.org/10.1186/s12957-021-02200-x
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spelling doaj-695b784fecf64ec791ed4233209612132021-03-28T11:21:18ZengBMCWorld Journal of Surgical Oncology1477-78192021-03-0119111010.1186/s12957-021-02200-xOverexpression of CCNE1 confers a poorer prognosis in triple-negative breast cancer identified by bioinformatic analysisQianqian Yuan0Lewei Zheng1Yiqin Liao2Gaosong Wu3Department of Thyroid and Breast Surgery, Zhongnan Hospital of Wuhan UniversityDepartment of Thyroid and Breast Surgery, Zhongnan Hospital of Wuhan UniversityDepartment of Thyroid and Breast Surgery, Zhongnan Hospital of Wuhan UniversityDepartment of Thyroid and Breast Surgery, Zhongnan Hospital of Wuhan UniversityAbstract 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.https://doi.org/10.1186/s12957-021-02200-xTriple-negative breast cancerGEOCCNE1Prognosis
collection DOAJ
language English
format Article
sources DOAJ
author Qianqian Yuan
Lewei Zheng
Yiqin Liao
Gaosong Wu
spellingShingle Qianqian Yuan
Lewei Zheng
Yiqin Liao
Gaosong Wu
Overexpression of CCNE1 confers a poorer prognosis in triple-negative breast cancer identified by bioinformatic analysis
World Journal of Surgical Oncology
Triple-negative breast cancer
GEO
CCNE1
Prognosis
author_facet Qianqian Yuan
Lewei Zheng
Yiqin Liao
Gaosong Wu
author_sort Qianqian Yuan
title 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_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_sort overexpression of ccne1 confers a poorer prognosis in triple-negative breast cancer identified by bioinformatic analysis
publisher BMC
series World Journal of Surgical Oncology
issn 1477-7819
publishDate 2021-03-01
description Abstract 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.
topic Triple-negative breast cancer
GEO
CCNE1
Prognosis
url https://doi.org/10.1186/s12957-021-02200-x
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AT yiqinliao overexpressionofccne1confersapoorerprognosisintriplenegativebreastcanceridentifiedbybioinformaticanalysis
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