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Integrated analysis of differentially expressed genes and pathways in triple-negative breast cancer

Triple-negative breast cancer (TNBC) is a heterogeneous disease characterized by an aggressive phenotype and reduced survival. The aim of the present study was to investigate the molecular mechanisms involved in the carcinogenesis of TNBC and to identify novel target molecules for therapy. The diffe...

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Autores principales: Peng, Cancan, Ma, Wenli, Xia, Wei, Zheng, Wenling
Formato: Online Artículo Texto
Lenguaje:English
Publicado: D.A. Spandidos 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5367345/
https://www.ncbi.nlm.nih.gov/pubmed/28075450
http://dx.doi.org/10.3892/mmr.2017.6101
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author Peng, Cancan
Ma, Wenli
Xia, Wei
Zheng, Wenling
author_facet Peng, Cancan
Ma, Wenli
Xia, Wei
Zheng, Wenling
author_sort Peng, Cancan
collection PubMed
description Triple-negative breast cancer (TNBC) is a heterogeneous disease characterized by an aggressive phenotype and reduced survival. The aim of the present study was to investigate the molecular mechanisms involved in the carcinogenesis of TNBC and to identify novel target molecules for therapy. The differentially expressed genes (DEGs) in TNBC and normal adjacent tissue were assessed by analyzing the GSE41970 microarray data using Qlucore Omics Explorer, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes. Pathway enrichment analyses for DEGs were performed using the Database for Annotation, Visualization and Integrated Discovery online resource. A protein-protein interaction (PPI) network was constructed using Search Tool for the Retrieval of Interacting Genes, and subnetworks were analyzed by ClusterONE. The PPI network and subnetworks were visualized using Cytoscape software. A total of 121 DEGs were obtained, of which 101 were upregulated and 20 were downregulated. The upregulated DEGs were significantly enriched in 14 pathways and 83 GO biological processes, while the downregulated DEGs were significantly enriched in 18 GO biological processes. The PPI network with 118 nodes and 1,264 edges was constructed and three subnetworks were extracted from the entire network. The significant hub DEGs with high degrees were identified, including TP53, glyceraldehyde-3-phosphate dehydrogenase, cyclin D1, HRAS and proliferating cell nuclear antigen, which were predominantly enriched in the cell cycle pathway and pathways in cancer. A number of critical genes and pathways were revealed to be associated with TNBC. The present study may provide an improved understanding of the pathogenesis of TNBC and contribute to the development of therapeutic targets for TNBC.
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spelling pubmed-53673452017-04-13 Integrated analysis of differentially expressed genes and pathways in triple-negative breast cancer Peng, Cancan Ma, Wenli Xia, Wei Zheng, Wenling Mol Med Rep Articles Triple-negative breast cancer (TNBC) is a heterogeneous disease characterized by an aggressive phenotype and reduced survival. The aim of the present study was to investigate the molecular mechanisms involved in the carcinogenesis of TNBC and to identify novel target molecules for therapy. The differentially expressed genes (DEGs) in TNBC and normal adjacent tissue were assessed by analyzing the GSE41970 microarray data using Qlucore Omics Explorer, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes. Pathway enrichment analyses for DEGs were performed using the Database for Annotation, Visualization and Integrated Discovery online resource. A protein-protein interaction (PPI) network was constructed using Search Tool for the Retrieval of Interacting Genes, and subnetworks were analyzed by ClusterONE. The PPI network and subnetworks were visualized using Cytoscape software. A total of 121 DEGs were obtained, of which 101 were upregulated and 20 were downregulated. The upregulated DEGs were significantly enriched in 14 pathways and 83 GO biological processes, while the downregulated DEGs were significantly enriched in 18 GO biological processes. The PPI network with 118 nodes and 1,264 edges was constructed and three subnetworks were extracted from the entire network. The significant hub DEGs with high degrees were identified, including TP53, glyceraldehyde-3-phosphate dehydrogenase, cyclin D1, HRAS and proliferating cell nuclear antigen, which were predominantly enriched in the cell cycle pathway and pathways in cancer. A number of critical genes and pathways were revealed to be associated with TNBC. The present study may provide an improved understanding of the pathogenesis of TNBC and contribute to the development of therapeutic targets for TNBC. D.A. Spandidos 2017-03 2017-01-04 /pmc/articles/PMC5367345/ /pubmed/28075450 http://dx.doi.org/10.3892/mmr.2017.6101 Text en Copyright: © Peng 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
Peng, Cancan
Ma, Wenli
Xia, Wei
Zheng, Wenling
Integrated analysis of differentially expressed genes and pathways in triple-negative breast cancer
title Integrated analysis of differentially expressed genes and pathways in triple-negative breast cancer
title_full Integrated analysis of differentially expressed genes and pathways in triple-negative breast cancer
title_fullStr Integrated analysis of differentially expressed genes and pathways in triple-negative breast cancer
title_full_unstemmed Integrated analysis of differentially expressed genes and pathways in triple-negative breast cancer
title_short Integrated analysis of differentially expressed genes and pathways in triple-negative breast cancer
title_sort integrated analysis of differentially expressed genes and pathways in triple-negative breast cancer
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5367345/
https://www.ncbi.nlm.nih.gov/pubmed/28075450
http://dx.doi.org/10.3892/mmr.2017.6101
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