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Identification of key genes as potential biomarkers for triple-negative breast cancer using integrating genomics analysis
Triple-negative breast cancer (TNBC) accounts for the worst prognosis of all types of breast cancers due to a high risk of recurrence and a lack of targeted therapeutic options. Extensive effort is required to identify novel targets for TNBC. In the present study, a robust rank aggregation (RRA) ana...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
D.A. Spandidos
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6947886/ https://www.ncbi.nlm.nih.gov/pubmed/31974598 http://dx.doi.org/10.3892/mmr.2019.10867 |
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author | Zhong, Guansheng Lou, Weiyang Shen, Qinyan Yu, Kun Zheng, Yajuan |
author_facet | Zhong, Guansheng Lou, Weiyang Shen, Qinyan Yu, Kun Zheng, Yajuan |
author_sort | Zhong, Guansheng |
collection | PubMed |
description | Triple-negative breast cancer (TNBC) accounts for the worst prognosis of all types of breast cancers due to a high risk of recurrence and a lack of targeted therapeutic options. Extensive effort is required to identify novel targets for TNBC. In the present study, a robust rank aggregation (RRA) analysis based on genome-wide gene expression datasets involving TNBC patients from the Gene Expression Omnibus (GEO) database was performed to identify key genes associated with TNBC. A total of 194 highly ranked differentially expressed genes (DEGs) were identified in TNBC vs. non-TNBC. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analysis was utilized to explore the biological functions of the identified genes. These DEGs were mainly involved in the biological processes termed positive regulation of transcription from RNA polymerase II promoter, negative regulation of apoptotic process, response to drug, response to estradiol and negative regulation of cell growth. Genes were mainly involved in the KEGG pathway termed estrogen signaling pathway. The aberrant expression of several randomly selected DEGs were further validated in cell lines, clinical tissues and The Cancer Genome Atlas (TCGA) cohort. Furthermore, all the top-ranked DEGs underwent survival analysis using TCGA database, of which overexpression of 4 genes (FABP7, ART3, CT83, and TTYH1) were positively correlated to the life expectancy (P<0.05) of TNBC patients. In addition, a model consisting of two genes (FABP7 and CT83) was identified to be significantly associated with the overall survival (OS) of TNBC patients by means of Cox regression, Kaplan-Meier, and receiver operating characteristic (ROC) analyses. In conclusion, the present study identified a number of key genes as potential biomarkers involved in TNBC, which provide novel insights into the tumorigenesis of TNBC at the gene level and may serve as independent prognostic factors for TNBC prognosis. |
format | Online Article Text |
id | pubmed-6947886 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | D.A. Spandidos |
record_format | MEDLINE/PubMed |
spelling | pubmed-69478862020-01-13 Identification of key genes as potential biomarkers for triple-negative breast cancer using integrating genomics analysis Zhong, Guansheng Lou, Weiyang Shen, Qinyan Yu, Kun Zheng, Yajuan Mol Med Rep Articles Triple-negative breast cancer (TNBC) accounts for the worst prognosis of all types of breast cancers due to a high risk of recurrence and a lack of targeted therapeutic options. Extensive effort is required to identify novel targets for TNBC. In the present study, a robust rank aggregation (RRA) analysis based on genome-wide gene expression datasets involving TNBC patients from the Gene Expression Omnibus (GEO) database was performed to identify key genes associated with TNBC. A total of 194 highly ranked differentially expressed genes (DEGs) were identified in TNBC vs. non-TNBC. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analysis was utilized to explore the biological functions of the identified genes. These DEGs were mainly involved in the biological processes termed positive regulation of transcription from RNA polymerase II promoter, negative regulation of apoptotic process, response to drug, response to estradiol and negative regulation of cell growth. Genes were mainly involved in the KEGG pathway termed estrogen signaling pathway. The aberrant expression of several randomly selected DEGs were further validated in cell lines, clinical tissues and The Cancer Genome Atlas (TCGA) cohort. Furthermore, all the top-ranked DEGs underwent survival analysis using TCGA database, of which overexpression of 4 genes (FABP7, ART3, CT83, and TTYH1) were positively correlated to the life expectancy (P<0.05) of TNBC patients. In addition, a model consisting of two genes (FABP7 and CT83) was identified to be significantly associated with the overall survival (OS) of TNBC patients by means of Cox regression, Kaplan-Meier, and receiver operating characteristic (ROC) analyses. In conclusion, the present study identified a number of key genes as potential biomarkers involved in TNBC, which provide novel insights into the tumorigenesis of TNBC at the gene level and may serve as independent prognostic factors for TNBC prognosis. D.A. Spandidos 2020-02 2019-12-06 /pmc/articles/PMC6947886/ /pubmed/31974598 http://dx.doi.org/10.3892/mmr.2019.10867 Text en Copyright: © Zhong et al. This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. |
spellingShingle | Articles Zhong, Guansheng Lou, Weiyang Shen, Qinyan Yu, Kun Zheng, Yajuan Identification of key genes as potential biomarkers for triple-negative breast cancer using integrating genomics analysis |
title | Identification of key genes as potential biomarkers for triple-negative breast cancer using integrating genomics analysis |
title_full | Identification of key genes as potential biomarkers for triple-negative breast cancer using integrating genomics analysis |
title_fullStr | Identification of key genes as potential biomarkers for triple-negative breast cancer using integrating genomics analysis |
title_full_unstemmed | Identification of key genes as potential biomarkers for triple-negative breast cancer using integrating genomics analysis |
title_short | Identification of key genes as potential biomarkers for triple-negative breast cancer using integrating genomics analysis |
title_sort | identification of key genes as potential biomarkers for triple-negative breast cancer using integrating genomics analysis |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6947886/ https://www.ncbi.nlm.nih.gov/pubmed/31974598 http://dx.doi.org/10.3892/mmr.2019.10867 |
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