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Single-cell RNA sequencing reveals gene expression signatures of breast cancer-associated endothelial cells
Tumor endothelial cells (TEC) play an indispensible role in tumor growth and metastasis although much of the detailed mechanism still remains elusive. In this study we characterized and compared the global gene expression profiles of TECs and control ECs isolated from human breast cancerous tissues...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Impact Journals LLC
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5834272/ https://www.ncbi.nlm.nih.gov/pubmed/29541388 http://dx.doi.org/10.18632/oncotarget.23760 |
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author | Sun, Zhengda Wang, Chih-Yang Lawson, Devon A. Kwek, Serena Velozo, Hugo Gonzalez Owyong, Mark Lai, Ming-Derg Fong, Lawrence Wilson, Mark Su, Hua Werb, Zena Cooke, Daniel L. |
author_facet | Sun, Zhengda Wang, Chih-Yang Lawson, Devon A. Kwek, Serena Velozo, Hugo Gonzalez Owyong, Mark Lai, Ming-Derg Fong, Lawrence Wilson, Mark Su, Hua Werb, Zena Cooke, Daniel L. |
author_sort | Sun, Zhengda |
collection | PubMed |
description | Tumor endothelial cells (TEC) play an indispensible role in tumor growth and metastasis although much of the detailed mechanism still remains elusive. In this study we characterized and compared the global gene expression profiles of TECs and control ECs isolated from human breast cancerous tissues and reduction mammoplasty tissues respectively by single cell RNA sequencing (scRNA-seq). Based on the qualified scRNA-seq libraries that we made, we found that 1302 genes were differentially expressed between these two EC phenotypes. Both principal component analysis (PCA) and heat map-based hierarchical clustering separated the cancerous versus control ECs as two distinctive clusters, and MetaCore disease biomarker analysis indicated that these differentially expressed genes are highly correlated with breast neoplasm diseases. Gene Set Enrichment Analysis software (GSEA) enriched these genes to extracellular matrix (ECM) signal pathways and highlighted 127 ECM-associated genes. External validation verified some of these ECM-associated genes are not only generally overexpressed in various cancer tissues but also specifically overexpressed in colorectal cancer ECs and lymphoma ECs. In conclusion, our data demonstrated that ECM-associated genes play pivotal roles in breast cancer EC biology and some of them could serve as potential TEC biomarkers for various cancers. |
format | Online Article Text |
id | pubmed-5834272 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Impact Journals LLC |
record_format | MEDLINE/PubMed |
spelling | pubmed-58342722018-03-14 Single-cell RNA sequencing reveals gene expression signatures of breast cancer-associated endothelial cells Sun, Zhengda Wang, Chih-Yang Lawson, Devon A. Kwek, Serena Velozo, Hugo Gonzalez Owyong, Mark Lai, Ming-Derg Fong, Lawrence Wilson, Mark Su, Hua Werb, Zena Cooke, Daniel L. Oncotarget Research Paper Tumor endothelial cells (TEC) play an indispensible role in tumor growth and metastasis although much of the detailed mechanism still remains elusive. In this study we characterized and compared the global gene expression profiles of TECs and control ECs isolated from human breast cancerous tissues and reduction mammoplasty tissues respectively by single cell RNA sequencing (scRNA-seq). Based on the qualified scRNA-seq libraries that we made, we found that 1302 genes were differentially expressed between these two EC phenotypes. Both principal component analysis (PCA) and heat map-based hierarchical clustering separated the cancerous versus control ECs as two distinctive clusters, and MetaCore disease biomarker analysis indicated that these differentially expressed genes are highly correlated with breast neoplasm diseases. Gene Set Enrichment Analysis software (GSEA) enriched these genes to extracellular matrix (ECM) signal pathways and highlighted 127 ECM-associated genes. External validation verified some of these ECM-associated genes are not only generally overexpressed in various cancer tissues but also specifically overexpressed in colorectal cancer ECs and lymphoma ECs. In conclusion, our data demonstrated that ECM-associated genes play pivotal roles in breast cancer EC biology and some of them could serve as potential TEC biomarkers for various cancers. Impact Journals LLC 2017-12-29 /pmc/articles/PMC5834272/ /pubmed/29541388 http://dx.doi.org/10.18632/oncotarget.23760 Text en Copyright: © 2018 Sun et al. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/) 3.0 (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Paper Sun, Zhengda Wang, Chih-Yang Lawson, Devon A. Kwek, Serena Velozo, Hugo Gonzalez Owyong, Mark Lai, Ming-Derg Fong, Lawrence Wilson, Mark Su, Hua Werb, Zena Cooke, Daniel L. Single-cell RNA sequencing reveals gene expression signatures of breast cancer-associated endothelial cells |
title | Single-cell RNA sequencing reveals gene expression signatures of breast cancer-associated endothelial cells |
title_full | Single-cell RNA sequencing reveals gene expression signatures of breast cancer-associated endothelial cells |
title_fullStr | Single-cell RNA sequencing reveals gene expression signatures of breast cancer-associated endothelial cells |
title_full_unstemmed | Single-cell RNA sequencing reveals gene expression signatures of breast cancer-associated endothelial cells |
title_short | Single-cell RNA sequencing reveals gene expression signatures of breast cancer-associated endothelial cells |
title_sort | single-cell rna sequencing reveals gene expression signatures of breast cancer-associated endothelial cells |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5834272/ https://www.ncbi.nlm.nih.gov/pubmed/29541388 http://dx.doi.org/10.18632/oncotarget.23760 |
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