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Identification of hub genes for early detection of bone metastasis in breast cancer
BACKGROUND: Globally, among all women, the most frequently detected and diagnosed and the most lethal type of cancer is breast cancer (BC). In particular, bone is one of the most frequent distant metastases 24in breast cancer patients and bone metastasis arises in approximately 80% of advanced patie...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9556899/ https://www.ncbi.nlm.nih.gov/pubmed/36246872 http://dx.doi.org/10.3389/fendo.2022.1018639 |
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author | Zhao, Zitong Yang, Haoran Ji, Guangling Su, Shanshan Fan, Yuqi Wang, Minghao Gu, Shengli |
author_facet | Zhao, Zitong Yang, Haoran Ji, Guangling Su, Shanshan Fan, Yuqi Wang, Minghao Gu, Shengli |
author_sort | Zhao, Zitong |
collection | PubMed |
description | BACKGROUND: Globally, among all women, the most frequently detected and diagnosed and the most lethal type of cancer is breast cancer (BC). In particular, bone is one of the most frequent distant metastases 24in breast cancer patients and bone metastasis arises in approximately 80% of advanced patients. Thus, we need to identify and validate early detection markers that can differentiate metastasis from non-metastasis breast cancers. METHODS: GSE55715, GSE103357, and GSE146661 gene expression profiling data were downloaded from the GEO database. There was 14 breast cancer with bone metastasis samples and 8 breast cancer tissue samples. GEO2R was used to screen for differentially expressed genes (DEGs). The volcano plots, Venn diagrams, and annular heatmap were generated by using the ggplot2 package. By using the cluster Profiler R package, KEGG and GO enrichment analyses of DEGs were conducted. Through PPI network construction using the STRING database, key hub genes were identified by cytoHubba. Finally, K-M survival and ROC curves were generated to validate hub gene expression. RESULTS: By GO enrichment analysis, 143 DEGs were enriched in the following GO terms: extracellular structure organization, extracellular matrix organization, leukocyte migration class II protein complex, collagen tridermic protein complex, extracellular matrix structural constituent, growth factor binding, and platelet-derived growth factor binding. In the KEGG pathway enrichment analysis, DEGs were enriched in Staphylococcus aureus infection, Complement and coagulation cascades, and Asthma. By PPI network analysis, we selected the top 10 genes, including SLCO2B1, STAB1, SERPING1, HLA-DOA, AIF1, GIMAP4, C1orf162, HLA-DMB, ADAP2, and HAVCR2. By using TCGA and THPA databases, we validated 2 genes, SERPING1 and GIMAP4, that were related to the early detection of bone metastasis in BC. CONCLUSIONS: 2 abnormally expressed hub genes could play a pivotal role in the breast cancer with bone metastasis by affecting bone homeostasis imbalance in the bone microenvironment. |
format | Online Article Text |
id | pubmed-9556899 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-95568992022-10-14 Identification of hub genes for early detection of bone metastasis in breast cancer Zhao, Zitong Yang, Haoran Ji, Guangling Su, Shanshan Fan, Yuqi Wang, Minghao Gu, Shengli Front Endocrinol (Lausanne) Endocrinology BACKGROUND: Globally, among all women, the most frequently detected and diagnosed and the most lethal type of cancer is breast cancer (BC). In particular, bone is one of the most frequent distant metastases 24in breast cancer patients and bone metastasis arises in approximately 80% of advanced patients. Thus, we need to identify and validate early detection markers that can differentiate metastasis from non-metastasis breast cancers. METHODS: GSE55715, GSE103357, and GSE146661 gene expression profiling data were downloaded from the GEO database. There was 14 breast cancer with bone metastasis samples and 8 breast cancer tissue samples. GEO2R was used to screen for differentially expressed genes (DEGs). The volcano plots, Venn diagrams, and annular heatmap were generated by using the ggplot2 package. By using the cluster Profiler R package, KEGG and GO enrichment analyses of DEGs were conducted. Through PPI network construction using the STRING database, key hub genes were identified by cytoHubba. Finally, K-M survival and ROC curves were generated to validate hub gene expression. RESULTS: By GO enrichment analysis, 143 DEGs were enriched in the following GO terms: extracellular structure organization, extracellular matrix organization, leukocyte migration class II protein complex, collagen tridermic protein complex, extracellular matrix structural constituent, growth factor binding, and platelet-derived growth factor binding. In the KEGG pathway enrichment analysis, DEGs were enriched in Staphylococcus aureus infection, Complement and coagulation cascades, and Asthma. By PPI network analysis, we selected the top 10 genes, including SLCO2B1, STAB1, SERPING1, HLA-DOA, AIF1, GIMAP4, C1orf162, HLA-DMB, ADAP2, and HAVCR2. By using TCGA and THPA databases, we validated 2 genes, SERPING1 and GIMAP4, that were related to the early detection of bone metastasis in BC. CONCLUSIONS: 2 abnormally expressed hub genes could play a pivotal role in the breast cancer with bone metastasis by affecting bone homeostasis imbalance in the bone microenvironment. Frontiers Media S.A. 2022-09-29 /pmc/articles/PMC9556899/ /pubmed/36246872 http://dx.doi.org/10.3389/fendo.2022.1018639 Text en Copyright © 2022 Zhao, Yang, Ji, Su, Fan, Wang and Gu https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Endocrinology Zhao, Zitong Yang, Haoran Ji, Guangling Su, Shanshan Fan, Yuqi Wang, Minghao Gu, Shengli Identification of hub genes for early detection of bone metastasis in breast cancer |
title | Identification of hub genes for early detection of bone metastasis in breast cancer |
title_full | Identification of hub genes for early detection of bone metastasis in breast cancer |
title_fullStr | Identification of hub genes for early detection of bone metastasis in breast cancer |
title_full_unstemmed | Identification of hub genes for early detection of bone metastasis in breast cancer |
title_short | Identification of hub genes for early detection of bone metastasis in breast cancer |
title_sort | identification of hub genes for early detection of bone metastasis in breast cancer |
topic | Endocrinology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9556899/ https://www.ncbi.nlm.nih.gov/pubmed/36246872 http://dx.doi.org/10.3389/fendo.2022.1018639 |
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