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KEGG-expressed genes and pathways in triple negative breast cancer: Protocol for a systematic review and data mining
BACKGROUND: The incidence of triple negative breast cancer (TNBC) is at a relatively high level, and our study aimed to identify differentially expressed genes (DEGs) in TNBC and explore the key pathways and genes of TNBC. METHODS: The gene expression profiling (GSE86945, GSE86946 and GSE102088) dat...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Wolters Kluwer Health
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7440132/ https://www.ncbi.nlm.nih.gov/pubmed/32358373 http://dx.doi.org/10.1097/MD.0000000000019986 |
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author | Chen, Jiarui Liu, Chong Cen, Jiemei Liang, Tuo Xue, Jiang Zeng, Haopeng Zhang, Zide Xu, Guoyong Yu, Chaojie Lu, Zhaojun Wang, Zequn Jiang, Jie Zhan, Xinli Zeng, Jian |
author_facet | Chen, Jiarui Liu, Chong Cen, Jiemei Liang, Tuo Xue, Jiang Zeng, Haopeng Zhang, Zide Xu, Guoyong Yu, Chaojie Lu, Zhaojun Wang, Zequn Jiang, Jie Zhan, Xinli Zeng, Jian |
author_sort | Chen, Jiarui |
collection | PubMed |
description | BACKGROUND: The incidence of triple negative breast cancer (TNBC) is at a relatively high level, and our study aimed to identify differentially expressed genes (DEGs) in TNBC and explore the key pathways and genes of TNBC. METHODS: The gene expression profiling (GSE86945, GSE86946 and GSE102088) data were obtained from Gene Expression Omnibus Datasets, DEGs were identified by using R software, Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of DEGs were performed by the Database for Annotation, Visualization and Integrated Discovery (DAVID) tools, and the protein-protein interaction (PPI) network of the DEGs was constructed by the STRING database and visualized by Cytoscape software. Finally, the survival value of hub DEGs in breast cancer patients were performed by the Kaplan–Meier plotter online tool. RESULTS: A total of 2998 DEGs were identified between TNBC and health breast tissue, including 411 up-regulated DEGs and 2587 down-regulated DEGs. GO analysis results showed that down-regulated DEGs were enriched in gene expression (BP), extracellular exosome (CC), and nucleic acid binding, and up-regulated were enriched in chromatin assembly (BP), nucleosome (CC), and DNA binding (MF). KEGG pathway results showed that DEGs were mainly enriched in Pathways in cancer and Systemic lupus erythematosus and so on. Top 10 hub genes were picked out from PPI network by connective degree, and 7 of top 10 hub genes were significantly related with adverse overall survival in breast cancer patients (P < .05). Further analysis found that only EGFR had a significant association with the prognosis of triple-negative breast cancer (P < .05). CONCLUSIONS: Our study showed that DEGs were enriched in pathways in cancer, top 10 DEGs belong to up-regulated DEGs, and 7 gene connected with poor prognosis in breast cancer, including HSP90AA1, SRC, HSPA8, ESR1, ACTB, PPP2CA, and RPL4. These can provide some guidance for our research on the diagnosis and prognosis of TNBC, and further research is needed to evaluate their value in the targeted therapy of TNBC. |
format | Online Article Text |
id | pubmed-7440132 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Wolters Kluwer Health |
record_format | MEDLINE/PubMed |
spelling | pubmed-74401322020-09-04 KEGG-expressed genes and pathways in triple negative breast cancer: Protocol for a systematic review and data mining Chen, Jiarui Liu, Chong Cen, Jiemei Liang, Tuo Xue, Jiang Zeng, Haopeng Zhang, Zide Xu, Guoyong Yu, Chaojie Lu, Zhaojun Wang, Zequn Jiang, Jie Zhan, Xinli Zeng, Jian Medicine (Baltimore) 4100 BACKGROUND: The incidence of triple negative breast cancer (TNBC) is at a relatively high level, and our study aimed to identify differentially expressed genes (DEGs) in TNBC and explore the key pathways and genes of TNBC. METHODS: The gene expression profiling (GSE86945, GSE86946 and GSE102088) data were obtained from Gene Expression Omnibus Datasets, DEGs were identified by using R software, Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of DEGs were performed by the Database for Annotation, Visualization and Integrated Discovery (DAVID) tools, and the protein-protein interaction (PPI) network of the DEGs was constructed by the STRING database and visualized by Cytoscape software. Finally, the survival value of hub DEGs in breast cancer patients were performed by the Kaplan–Meier plotter online tool. RESULTS: A total of 2998 DEGs were identified between TNBC and health breast tissue, including 411 up-regulated DEGs and 2587 down-regulated DEGs. GO analysis results showed that down-regulated DEGs were enriched in gene expression (BP), extracellular exosome (CC), and nucleic acid binding, and up-regulated were enriched in chromatin assembly (BP), nucleosome (CC), and DNA binding (MF). KEGG pathway results showed that DEGs were mainly enriched in Pathways in cancer and Systemic lupus erythematosus and so on. Top 10 hub genes were picked out from PPI network by connective degree, and 7 of top 10 hub genes were significantly related with adverse overall survival in breast cancer patients (P < .05). Further analysis found that only EGFR had a significant association with the prognosis of triple-negative breast cancer (P < .05). CONCLUSIONS: Our study showed that DEGs were enriched in pathways in cancer, top 10 DEGs belong to up-regulated DEGs, and 7 gene connected with poor prognosis in breast cancer, including HSP90AA1, SRC, HSPA8, ESR1, ACTB, PPP2CA, and RPL4. These can provide some guidance for our research on the diagnosis and prognosis of TNBC, and further research is needed to evaluate their value in the targeted therapy of TNBC. Wolters Kluwer Health 2020-05-01 /pmc/articles/PMC7440132/ /pubmed/32358373 http://dx.doi.org/10.1097/MD.0000000000019986 Text en Copyright © 2020 the Author(s). Published by Wolters Kluwer Health, Inc. http://creativecommons.org/licenses/by-nc/4.0 This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial License 4.0 (CCBY-NC), where it is permissible to download, share, remix, transform, and buildup the work provided it is properly cited. The work cannot be used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc/4.0 |
spellingShingle | 4100 Chen, Jiarui Liu, Chong Cen, Jiemei Liang, Tuo Xue, Jiang Zeng, Haopeng Zhang, Zide Xu, Guoyong Yu, Chaojie Lu, Zhaojun Wang, Zequn Jiang, Jie Zhan, Xinli Zeng, Jian KEGG-expressed genes and pathways in triple negative breast cancer: Protocol for a systematic review and data mining |
title | KEGG-expressed genes and pathways in triple negative breast cancer: Protocol for a systematic review and data mining |
title_full | KEGG-expressed genes and pathways in triple negative breast cancer: Protocol for a systematic review and data mining |
title_fullStr | KEGG-expressed genes and pathways in triple negative breast cancer: Protocol for a systematic review and data mining |
title_full_unstemmed | KEGG-expressed genes and pathways in triple negative breast cancer: Protocol for a systematic review and data mining |
title_short | KEGG-expressed genes and pathways in triple negative breast cancer: Protocol for a systematic review and data mining |
title_sort | kegg-expressed genes and pathways in triple negative breast cancer: protocol for a systematic review and data mining |
topic | 4100 |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7440132/ https://www.ncbi.nlm.nih.gov/pubmed/32358373 http://dx.doi.org/10.1097/MD.0000000000019986 |
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