Journal of Shanghai Jiao Tong University (Medical Science) >

2026 , Vol. 46 >Issue 1: 34 - 42

DOI: https://doi.org/10.3969/j.issn.1674-8115.2026.01.004

Basic research

Mass cytometry reveals prognostic immune microenvironment features in breast cancer

  • Zhang Yue ,
  • Chen Qingjian
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  • Department of Oncology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200080, China
First author contact:Zhang Yue was responsible for experimental design, experimental operations, and manuscript writing and revision. Chen Qingjian was responsible for project design, bioinformatics analysis, and manuscript revision. Both authors have read the last version of paper and consented to submission.
Chen Qingjian, E-mail: chenqingjian2010@163.com.

Received date: 2025-04-01

  Accepted date: 2025-08-16

  Online published: 2026-01-30

Supported by

National Natural Science Foundation of China(82002470)

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Abstract

Objective ·To analyze the expression of multiple antigens in tumor tissues from breast cancer patients using cytometry by time-of-flight (CyTOF), with the aim of investigating their associations with the tumor microenvironment and patient prognosis. Methods ·A panel of optimally combined metal-labeled antibodies (or probes) was designed by employing Maxpar® Panel Designer v2.0.1 software in conjunction with relevant antigenic proteins and histiocytic markers. Antibodies targeting panel proteins were conjugated with lanthanide (Ln) metal isotopes using the Maxpar X8 Antibody Labeling Kit. Breast cancer tissue microarrays were then stained using imaging mass cytometry staining (IMC). Protein expression profiles and spatial distributions were acquired using the Hyperion Imaging System. Raw data were processed using R, including data normalization, noise reduction/removal, signal compensation, transformation, and dimensionality reduction. Cellular subpopulations were annotated via clustering algorithms, while spatial neighborhood analysis was performed to map the spatial organization of diverse cell types within the breast cancer microenvironment and assess their clinical relevance. Results ·Successful metal-antibody conjugation resulted in high-quality staining suitable for IMC analysis. Analysis of breast cancer tissue microarrays using 26 markers identified nine distinct cell populations (410 000 cells) within the tumor microenvironment. Paired comparisons of tumor and adjacent tissues revealed that the microenvironment predominantly consisted of B cells, CD4+ T cells, CD8+ T cells, epithelial cells, endothelial cells, macrophages, myoepithelial cells, neutrophils, and fibroblasts. Quantitative analysis showed statistically significant differences in the abundance of macrophages and CD4+ T cells between malignant and adjacent tissues (P<0.05). Spatial analysis identified 15 distinct cellular neighborhoods, and the colocalization of CD8+ T cells and macrophages with tumor cells was significantly associated with improved patient survival (P=0.011, P<0.001). Conclusion ·CyTOF is a powerful tool for high-throughput detection of multiple antigens in tissue samples, enabling detailed analysis of tumor-immune interactions in the breast cancer microenvironment. The presence and spatial organization of CD8+ T cells and macrophages within the breast cancer microenvironment are positively associated with favorable patient outcomes.

Key words： breast cancer; cytometry by time-of-flight (CyTOF); tumor microenvironment

Cite this article

Zhang Yue , Chen Qingjian . Mass cytometry reveals prognostic immune microenvironment features in breast cancer[J]. Journal of Shanghai Jiao Tong University (Medical Science), 2026 , 46(1) : 34 -42 . DOI: 10.3969/j.issn.1674-8115.2026.01.004

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