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Bioinformatics analysis of key genes in triple negative breast cancer and validation of oncogene PLK1

BACKGROUND: Breast cancer is the most common malignancy in women. Triple-negative breast cancer (TNBC) refers to a special subtype that is deficient in the expression of estrogen (ER), progesterone (PR), and human epidermal growth factor receptor 2 (HER-2). In this study, a variety of bioinformatics...

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Autores principales: Ren, Yi, Deng, Rong, Zhang, Qian, Li, Jing, Han, Baosan, Ye, Ping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7812170/
https://www.ncbi.nlm.nih.gov/pubmed/33490149
http://dx.doi.org/10.21037/atm-20-6873
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author Ren, Yi
Deng, Rong
Zhang, Qian
Li, Jing
Han, Baosan
Ye, Ping
author_facet Ren, Yi
Deng, Rong
Zhang, Qian
Li, Jing
Han, Baosan
Ye, Ping
author_sort Ren, Yi
collection PubMed
description BACKGROUND: Breast cancer is the most common malignancy in women. Triple-negative breast cancer (TNBC) refers to a special subtype that is deficient in the expression of estrogen (ER), progesterone (PR), and human epidermal growth factor receptor 2 (HER-2). In this study, a variety of bioinformatics analysis tools were used to screen Hub genes related to the occurrence and development of triple negative breast cancer, and their biological functions were analyzed. METHODS: Gene Expression Omnibus (GEO) breast cancer microarray data GSE62931 was selected as the research object. The differentially expressed genes (DEGs) were screened and the protein-protein interaction (PPI) network of DEGs was constructed using bioinformatics tools. The Hub genes were also screened. The Gene Ontology (GO) knowledgebase and the Kyoto Encyclopedia of Genes and Genomes (KEGG) were used for biological enrichment analysis. The Gene Expression Profiling Interactive Analysis (GEPIA) online tool was used to verify the expression of the screened genes and patient survival. The effects of polo-like kinase 1 (PLK1) on the proliferation, invasion, migration, and dryness of breast cancer cells were verified using cell counting kit 8 (CCK-8), transwell migration assays, scratch tests, and clone formation tests. An animal model of subcutaneous xenotransplantation of breast cancer was established to evaluate the effect of PLK1 on the proliferation of breast cancer. RESULTS: A total of 824 DEGs were screened by GSE62931 microarray data; 405 of which were up-regulated and 419 of which were down-regulated. Functional enrichment analysis showed that these DEGs were mainly enriched in cancer-related pathways and were primarily involved in biological processes (BP) such as cell and mitotic division. From the Hub gene screening, PLK1 was further identified as the Hub gene associated with TNBC. Cell and animal experiments indicated that PLK1 promotes the proliferation, invasion, migration, and clone formation of breast cancer cells. CONCLUSIONS: Gene chip combined with bioinformatics methods can effectively analyze the DEGs related to the occurrence and development of breast cancer, and the screening of PLK1 can provide theoretical guidance for further research on the molecular mechanism of breast cancer and the screening of molecular markers.
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spelling pubmed-78121702021-01-22 Bioinformatics analysis of key genes in triple negative breast cancer and validation of oncogene PLK1 Ren, Yi Deng, Rong Zhang, Qian Li, Jing Han, Baosan Ye, Ping Ann Transl Med Original Article BACKGROUND: Breast cancer is the most common malignancy in women. Triple-negative breast cancer (TNBC) refers to a special subtype that is deficient in the expression of estrogen (ER), progesterone (PR), and human epidermal growth factor receptor 2 (HER-2). In this study, a variety of bioinformatics analysis tools were used to screen Hub genes related to the occurrence and development of triple negative breast cancer, and their biological functions were analyzed. METHODS: Gene Expression Omnibus (GEO) breast cancer microarray data GSE62931 was selected as the research object. The differentially expressed genes (DEGs) were screened and the protein-protein interaction (PPI) network of DEGs was constructed using bioinformatics tools. The Hub genes were also screened. The Gene Ontology (GO) knowledgebase and the Kyoto Encyclopedia of Genes and Genomes (KEGG) were used for biological enrichment analysis. The Gene Expression Profiling Interactive Analysis (GEPIA) online tool was used to verify the expression of the screened genes and patient survival. The effects of polo-like kinase 1 (PLK1) on the proliferation, invasion, migration, and dryness of breast cancer cells were verified using cell counting kit 8 (CCK-8), transwell migration assays, scratch tests, and clone formation tests. An animal model of subcutaneous xenotransplantation of breast cancer was established to evaluate the effect of PLK1 on the proliferation of breast cancer. RESULTS: A total of 824 DEGs were screened by GSE62931 microarray data; 405 of which were up-regulated and 419 of which were down-regulated. Functional enrichment analysis showed that these DEGs were mainly enriched in cancer-related pathways and were primarily involved in biological processes (BP) such as cell and mitotic division. From the Hub gene screening, PLK1 was further identified as the Hub gene associated with TNBC. Cell and animal experiments indicated that PLK1 promotes the proliferation, invasion, migration, and clone formation of breast cancer cells. CONCLUSIONS: Gene chip combined with bioinformatics methods can effectively analyze the DEGs related to the occurrence and development of breast cancer, and the screening of PLK1 can provide theoretical guidance for further research on the molecular mechanism of breast cancer and the screening of molecular markers. AME Publishing Company 2020-12 /pmc/articles/PMC7812170/ /pubmed/33490149 http://dx.doi.org/10.21037/atm-20-6873 Text en 2020 Annals of Translational Medicine. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Original Article
Ren, Yi
Deng, Rong
Zhang, Qian
Li, Jing
Han, Baosan
Ye, Ping
Bioinformatics analysis of key genes in triple negative breast cancer and validation of oncogene PLK1
title Bioinformatics analysis of key genes in triple negative breast cancer and validation of oncogene PLK1
title_full Bioinformatics analysis of key genes in triple negative breast cancer and validation of oncogene PLK1
title_fullStr Bioinformatics analysis of key genes in triple negative breast cancer and validation of oncogene PLK1
title_full_unstemmed Bioinformatics analysis of key genes in triple negative breast cancer and validation of oncogene PLK1
title_short Bioinformatics analysis of key genes in triple negative breast cancer and validation of oncogene PLK1
title_sort bioinformatics analysis of key genes in triple negative breast cancer and validation of oncogene plk1
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7812170/
https://www.ncbi.nlm.nih.gov/pubmed/33490149
http://dx.doi.org/10.21037/atm-20-6873
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