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. 2025 Jun 5;27(1):101.
doi: 10.1186/s13058-025-02022-9.

Dissecting the tumor microenvironment in primary breast angiosarcoma: insights from single-cell RNA sequencing

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Dissecting the tumor microenvironment in primary breast angiosarcoma: insights from single-cell RNA sequencing

Peikai Ding et al. Breast Cancer Res. .

Abstract

Background: Angiosarcoma, a rare and highly aggressive malignancy originating from vascular endothelial cells, is characterized by its rapid progression, high invasiveness, and poor prognosis. Due to the limited understanding of its tumor microenvironment (TME) and the absence of effective treatments, further research is essential to elucidate its pathogenic mechanisms and improve therapeutic strategies.

Objective: This study aims to characterize the cellular heterogeneity and unique TME of primary breast angiosarcoma using single-cell RNA sequencing (scRNA-seq), to identify potential therapeutic targets and improve clinical outcomes.

Methods: Tumor samples were obtained from a patient with bilateral primary breast angiosarcoma and two patients with invasive breast cancer. Single-cell RNA sequencing (scRNA-seq) was conducted to capture the transcriptomic profiles of individual cells within the tumor samples. Following stringent quality control, a total of 31,771 cells were analyzed using comprehensive bioinformatics approaches. Cell populations were identified and classified into distinct cell types, and differential gene expression analysis was performed to explore key signaling pathways. Functional enrichment analysis was used to identify pathways related to tumor progression and immune evasion. Additionally, cell-cell communication networks were mapped to understand interactions within the TME, with a focus on pathways that may serve as therapeutic targets.

Results: The scRNA-seq analysis revealed significant differences in the distribution of perivascular cells, fibroblasts, T cells, endothelial cells, and myeloid cells in breast angiosarcoma compared to invasive breast cancer. Key pathways enriched in angiosarcoma samples included growth factor binding, platelet-derived growth factor binding, and ribosome biogenesis, with abnormal expression of several ribosomal proteins. Notably, genes such as FAT4, KDR, FN1, and KIT were highly expressed in angiosarcoma endothelial cells, correlating with poor prognosis. Cell communication analysis highlighted the CXCL12-CXCR4 axis as a crucial mediator of the TME in angiosarcoma.

Conclusion: This study provides critical insights into the TME of primary breast angiosarcoma, highlighting potential molecular targets and pathways for therapeutic intervention. These findings may inform the development of more effective treatment strategies for this rare and challenging tumor type.

Keywords: Breast angiosarcoma; Breast cancer; ScRNA-seq; Tumor microenvironment.

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Conflict of interest statement

Declarations. Ethics approval and consent to participate: The study involving human participants was reviewed and approved by the Ethics Committee of National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences (NCC2024G-263). All samples were collected with the universal consent form from the enrolled patients. Consent for publication: Written informed consent was obtained from all patients for the publication of any potentially identifiable images or data presented in this article. Competing interests: The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Imaging and pathological analysis of a breast angiosarcoma patient. MRI reveals two masses in the central and lower outer quadrants of the right breast (A). CT scan shows a large mass in the left breast and multiple masses in the right breast (B). H&E staining at 40× magnification shows primary angiosarcoma of the breast, with tumor tissue exhibiting diverse morphologies. Interconnecting slit-like structures are visible, with well-formed anastomosing blood vessels at the periphery. The central region displays a higher tumor cell density and dilated lumina (C). H&E staining at 200× magnification reveals dense areas where tumor cells grow in sheets. The cells exhibit spindle-shaped and epithelioid morphologies, with visible mitotic figures. Blood lakes are present within variably shaped and dilated blood vessels (D). Immunohistochemical staining for CD31, CD34, Factor VIII, and FLI-1 shows variable expression across these markers (E-H)
Fig. 2
Fig. 2
Single-cell RNA-seq analysis of tumor microenvironment differences between breast angiosarcoma and breast cancer. A flowchart outlining the study’s methodology (A). UMAP visualization of major cell clusters identified using the Seurat package (version 4.0.4) in R (version 4.0.5) (B). UMAP visualization of cell clusters at a resolution of 0.6 (C). Dot plot showing the top three markers for each cluster, as identified by the “FindAllMarkers” function in the Seurat package (D). Distribution of different cell types across each sample (E). Heatmap and UMAP display the distribution of each cluster in each sample, with clusters predominantly derived from the PR_BA sample highlighted in red boxes (F-G)
Fig. 3
Fig. 3
Differential gene expression and functional enrichment analysis. Differential gene expression between breast angiosarcoma and breast cancer (A). GO analysis reveals pathways enriched with upregulated genes (B). Survival analysis of ribosomal protein subunits (small and large) in angiosarcoma, utilizing the TCGA-SARC dataset on the Gepia2 platform (http://gepia2.cancer-pku.cn/#survival) (C). GO analysis identifies pathways enriched with downregulated genes (D)
Fig. 4
Fig. 4
Analysis of endothelial cell subclusters in three samples. UMAP visualization of major endothelial cell clusters and their distribution across each sample (A). Dot plot showing the top three markers for each endothelial cell cluster, as identified by the “FindAllMarkers” function in the Seurat package (B). Heatmap illustrating the distribution of endothelial cell clusters across samples, with clusters primarily derived from the PR_BA sample highlighted in red boxes (C). KDR expression levels in endothelial cell subclusters across tumor tissues (D). Notable gene expression in endothelial cell subpopulations of the PR_BA sample (E). Survival analysis of gene signatures identified in panel E, using the TCGA-SARC dataset on the Gepia2 platform (F). Reactome enrichment analysis indicates significant enrichment of multiple signaling pathways in Clusters 1 and 5 (G)
Fig. 5
Fig. 5
Analysis of immune cell subclusters in three samples. UMAP visualization of major T cell clusters across the three samples (A). Dot plot showing the top three markers for each T cell cluster, as identified by the “FindAllMarkers” function in the Seurat package (B). Distribution of T cell clusters across the three samples (C). Expression of immune checkpoint markers across two groups of malignant tumors (Group 1 = breast angiosarcoma, Group 2 = breast cancer) (D). UMAP visualization of major myeloid cell clusters across the three samples (E). Dot plot showing the top three markers for each myeloid cell cluster, as identified by the “FindAllMarkers” function in the Seurat package (F). Distribution of myeloid cell clusters across the three samples (G)
Fig. 6
Fig. 6
Cell communication analysis in breast angiosarcoma. Heatmap depicting the number of potential ligand-receptor pairs between cell groups, as predicted by CellPhoneDB (A). Dot plot showing the top three markers for each cluster, as identified by the “FindAllMarkers” function in the Seurat package (B). Bubble plot illustrating ligand-receptor pairs of chemokines between endothelial cells and other cell groups (C). Bubble plot displaying the top 30 ligand-receptor pairs of growth factors in the PR_BA sample (D). Survival analysis of gene signatures (FLT1, KDR, NRP1, FLT4, FGFR1, PDGFRB, PDGFA, PDGFB, PDGFD, IGF1R, MET) in PR_BA, using the TCGA-SARC dataset on the Gepia2 platform (http://gepia2.cancer-pku.cn/#survival) (E)

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References

    1. Pandey M, Sutton GR, Giri S, Martin MG. grade and prognosis in localized primary angiosarcoma. Clin Breast Cancer. 2015;15:266–9. - PubMed
    1. Chan JY, Lim JQ, Yeong J, Ravi V, Guan P, Boot A, et al. Multiomic analysis and immunoprofiling reveal distinct subtypes of human angiosarcoma. J Clin Invest. 2020;130:5833–46. - PMC - PubMed
    1. Teng L, Yan S, Du J, Yang R, Xu P, Tao W. Clinicopathological analysis and prognostic treatment study of angiosarcoma of the breast: a SEER population-based analysis. World J Surg Oncol. 2023;21:144. - PMC - PubMed
    1. Lin WM, Juan YH, Lin YC, Ueng SH, Lo YF, Cheung YC. Awareness of primary spontaneous hemorrhagic angiosarcoma of the breast associated with Kasabach-Merritt syndrome in a pregnant woman by enhanced magnetic resonance imaging: a CARE-compliant case report. Medicine (Baltimore). 2016;95:e5276. - PMC - PubMed
    1. Chau B, Loggers ET, Cranmer LD, Mogal H, Sharib JM, Kim EY, et al. Secondary breast angiosarcoma after a primary diagnosis of breast cancer: a retrospective analysis of the Surveillance, Epidemiology, and End Results (SEER) database. Am J Clin Oncol. 2023;46:567–71. - PMC - PubMed

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