Single-cell RNA sequencing reveals gene expression signatures of breast cancer-associated endothelial cells

Zhengda Sun, Chih Yang Wang, Devon A. Lawson, Serena Kwek, Hugo Gonzalez Velozo, Mark Owyong, Ming Derg Lai, Lawrence Fong, Mark Wilson, Hua Su, Zena Werb, Daniel L. Cooke

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)

Abstract

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 ECMassociated 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.

Original languageEnglish
Pages (from-to)10945-10961
Number of pages17
JournalOncotarget
Volume9
Issue number13
DOIs
Publication statusPublished - 2018

All Science Journal Classification (ASJC) codes

  • Oncology

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