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Identification of Key Genes Associated with Brain Metastasis from Breast Cancer: A Bioinformatics Analysis

BACKGROUND: As the second most frequent factor of brain metastasis worldwide, breast cancer and its pathogenesis have been researched intensively. Nevertheless, the molecular mechanisms of brain metastasis from breast cancer (BMBC) remain uncertain. The purpose of this study was to explore the key g...

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Autores principales: Zeng, Cheng, Lin, Mingxi, Jin, Yizi, Zhang, Jian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: International Scientific Literature, Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8939238/
https://www.ncbi.nlm.nih.gov/pubmed/35296631
http://dx.doi.org/10.12659/MSM.935071
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author Zeng, Cheng
Lin, Mingxi
Jin, Yizi
Zhang, Jian
author_facet Zeng, Cheng
Lin, Mingxi
Jin, Yizi
Zhang, Jian
author_sort Zeng, Cheng
collection PubMed
description BACKGROUND: As the second most frequent factor of brain metastasis worldwide, breast cancer and its pathogenesis have been researched intensively. Nevertheless, the molecular mechanisms of brain metastasis from breast cancer (BMBC) remain uncertain. The purpose of this study was to explore the key genes concerning the prognosis of BMBC and identify their predictive value. MATERIAL/METHODS: Obtained from the Gene Expression Omnibus (GEO) database, microarray datasets GSE125989, GSE52604, and GSE159956 were used to identify the differentially expressed genes (DEGs) and perform function enrichment analysis. RESULTS: Of a total of 240 DEGs, 113 genes were upregulated and 127 genes were downregulated. The protein–protein interaction (PPI) was performed through STRING, and 29 hub genes were screened through Cytoscape. After being examined through the cBioportal online platform and the Oncomine database, 8 key genes were finally obtained, including COL14A1, COL3A1, COL6A3, THY1, MMP14, GAP43, PTPRN, and SNAP25. In the validation dataset GSE46928, COL14A1 was shown to have predictive significance of brain metastasis in breast cancer. CONCLUSIONS: The key genes explored in this article could assist in identifying the molecular mechanism of BMBC. Also, COL14A1, COL3A1, COL6A3, THY1, MMP14, GAP43, PTPRN, and SNAP25 might be candidate targets for diagnosis and treatment of BMBC, and COL3A1 might have predictive value.
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spelling pubmed-89392382022-04-14 Identification of Key Genes Associated with Brain Metastasis from Breast Cancer: A Bioinformatics Analysis Zeng, Cheng Lin, Mingxi Jin, Yizi Zhang, Jian Med Sci Monit Database Analysis BACKGROUND: As the second most frequent factor of brain metastasis worldwide, breast cancer and its pathogenesis have been researched intensively. Nevertheless, the molecular mechanisms of brain metastasis from breast cancer (BMBC) remain uncertain. The purpose of this study was to explore the key genes concerning the prognosis of BMBC and identify their predictive value. MATERIAL/METHODS: Obtained from the Gene Expression Omnibus (GEO) database, microarray datasets GSE125989, GSE52604, and GSE159956 were used to identify the differentially expressed genes (DEGs) and perform function enrichment analysis. RESULTS: Of a total of 240 DEGs, 113 genes were upregulated and 127 genes were downregulated. The protein–protein interaction (PPI) was performed through STRING, and 29 hub genes were screened through Cytoscape. After being examined through the cBioportal online platform and the Oncomine database, 8 key genes were finally obtained, including COL14A1, COL3A1, COL6A3, THY1, MMP14, GAP43, PTPRN, and SNAP25. In the validation dataset GSE46928, COL14A1 was shown to have predictive significance of brain metastasis in breast cancer. CONCLUSIONS: The key genes explored in this article could assist in identifying the molecular mechanism of BMBC. Also, COL14A1, COL3A1, COL6A3, THY1, MMP14, GAP43, PTPRN, and SNAP25 might be candidate targets for diagnosis and treatment of BMBC, and COL3A1 might have predictive value. International Scientific Literature, Inc. 2022-03-17 /pmc/articles/PMC8939238/ /pubmed/35296631 http://dx.doi.org/10.12659/MSM.935071 Text en © Med Sci Monit, 2022 https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under Creative Common Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) )
spellingShingle Database Analysis
Zeng, Cheng
Lin, Mingxi
Jin, Yizi
Zhang, Jian
Identification of Key Genes Associated with Brain Metastasis from Breast Cancer: A Bioinformatics Analysis
title Identification of Key Genes Associated with Brain Metastasis from Breast Cancer: A Bioinformatics Analysis
title_full Identification of Key Genes Associated with Brain Metastasis from Breast Cancer: A Bioinformatics Analysis
title_fullStr Identification of Key Genes Associated with Brain Metastasis from Breast Cancer: A Bioinformatics Analysis
title_full_unstemmed Identification of Key Genes Associated with Brain Metastasis from Breast Cancer: A Bioinformatics Analysis
title_short Identification of Key Genes Associated with Brain Metastasis from Breast Cancer: A Bioinformatics Analysis
title_sort identification of key genes associated with brain metastasis from breast cancer: a bioinformatics analysis
topic Database Analysis
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8939238/
https://www.ncbi.nlm.nih.gov/pubmed/35296631
http://dx.doi.org/10.12659/MSM.935071
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