Back

Transcriptomic Profiles from Normal and Tumor Tissue Samples Reveal Distinct Venule Populations and Novel Tumor Endothelial Cell Markers in Breast Cancer

Phoenix, K. N.; Singh, V.; Murphy, P.; Claffey, K. P.

2026-02-22 cancer biology
10.1101/2025.06.23.661087 bioRxiv
Show abstract

BackgroundThe breast tumor microenvironment (TME) is a complex milieu composed of many factors contributing to breast cancer (BC) heterogeneity and therapeutic resistance. Aberrant tumor vasculature in the TME limits nutrient and drug delivery, inhibits anti-tumor immunity, and contributes to a lack of cancer therapy efficacy. Utilizing publicly available scRNA-seq datasets, this study characterizes differences between normal breast and breast tumor endothelial cells (EC), provides insights into tumor endothelial cell subtypes, endothelial anergy, and identifies novel, tumor-specific vascular therapeutic targets. MethodsGene expression data from normal and breast tumor tissue samples were integrated, and the EC subset was extracted via canonical gene marker expression. The EC subset was clustered and evaluated for cell subtypes and differentially expressed genes (DEG). Normal EC (NEC) and tumor EC (TEC) markers were further assessed for correlation to bulk gene expression and patient survival outcomes in cBioPortal and Kaplan-Meier Plotter. Cell type gene expression specificity was evaluated in the 3CA single-cell RNA-seq datasets across multiple cancers. ResultsThis analysis revealed differences in NEC and TEC subtype populations. Breast NEC contained similar proportions of venule and capillary populations, while breast TEC demonstrated a majority of the venule subtype. Further, TEC venules were phenotypically distinct from the NEC venules. Consistent with endothelial anergy, suppression of the key adhesion protein SELE was noted, as well as several pro-inflammatory cytokines including IL6, CCL2, and CXCL8, likely downstream of aberrant NF-kB signaling. Differential gene expression analysis identified several TEC specific up-regulated genes compared to NEC, including CLEC14a, IGFBP4, EMCN, and ADM5. CLEC14a, EMCN, and ADM5 were further validated in the single-cell Curated Cancer Cell Atlas (3CA) to be highly specific to the endothelial cell clusters across multiple tumor types, while IGFBP4 was diversely expressed in endothelial, fibroblast, and some malignant cell types. ADM5, a novel tumor vascular marker, was enhanced in TEC venules and less so in arteriole or capillaries. High expression of ADM5 was associated with poor breast cancer patient survival in the basal PAM50 cancer subtype compared to normal and luminal subtypes. Further, across multiple cancer types, high ADM5 expression was associated with reduced patient survival in anti-PD1- and anti-CTLA4-treated patients but not in anti-PDL-treated patients. ConclusionsIntegration of single-cell RNA-seq data identified an anergic-like response in breast TEC and multiple, highly specific markers to TEC not found in normal breast tissue. CLEC14a and EMCN were validated as TEC markers, extending their annotation in breast TEC, and ADM5 identified as a novel TEC marker in breast and other cancers. Moreover, as ADM5 is associated with reduced patient overall survival, this data suggests that a better understanding of ADM5 and other TEC-specific response pathways may provide novel approaches to reactivate anergic TECs and lead to effective therapeutic interventions for cancer patients. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=96 SRC="FIGDIR/small/661087v2_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@a81bf2org.highwire.dtl.DTLVardef@c2b983org.highwire.dtl.DTLVardef@216ab9org.highwire.dtl.DTLVardef@1e5bebb_HPS_FORMAT_FIGEXP M_FIG Graphical Abstract C_FIG

Matching journals

The top 2 journals account for 50% of the predicted probability mass.

1
Breast Cancer Research
32 papers in training set
Top 0.1%
44.5%
2
Cancers
200 papers in training set
Top 0.5%
9.0%
50% of probability mass above
3
npj Breast Cancer
18 papers in training set
Top 0.1%
3.3%
4
BMC Cancer
52 papers in training set
Top 0.8%
2.8%
5
Frontiers in Oncology
95 papers in training set
Top 2%
2.6%
6
Cell Reports Medicine
140 papers in training set
Top 2%
2.6%
7
OncoImmunology
22 papers in training set
Top 0.2%
1.8%
8
The Journal of Pathology
22 papers in training set
Top 0.2%
1.6%
9
Cancer Medicine
24 papers in training set
Top 0.9%
1.4%
10
Genome Medicine
154 papers in training set
Top 5%
1.4%
11
PLOS ONE
4510 papers in training set
Top 58%
1.4%
12
International Journal of Cancer
42 papers in training set
Top 0.7%
1.4%
13
Cancer Research Communications
46 papers in training set
Top 0.6%
1.3%
14
Frontiers in Immunology
586 papers in training set
Top 6%
1.0%
15
PLOS Computational Biology
1633 papers in training set
Top 21%
1.0%
16
Scientific Reports
3102 papers in training set
Top 72%
0.8%
17
Cancer Research
116 papers in training set
Top 3%
0.8%
18
Communications Biology
886 papers in training set
Top 21%
0.8%
19
Translational Oncology
18 papers in training set
Top 0.4%
0.8%
20
Journal of Translational Medicine
46 papers in training set
Top 2%
0.8%
21
Annals of Oncology
13 papers in training set
Top 0.9%
0.8%
22
Cell Communication and Signaling
35 papers in training set
Top 1%
0.7%
23
Molecular Cancer Research
42 papers in training set
Top 0.9%
0.7%
24
Cellular and Molecular Bioengineering
21 papers in training set
Top 0.4%
0.7%
25
Cancer Epidemiology, Biomarkers & Prevention
17 papers in training set
Top 0.7%
0.5%
26
British Journal of Cancer
42 papers in training set
Top 2%
0.5%