ArticleBMC cancer2026
Single-cell and spatial transcriptome analysis of breast cancer tumor-associated fibroblast heterogeneity and its mediated remodeling of the tumor microenvironment.
Article in BMC cancer, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Breast cancer (BC) progression is driven by a complex tumor microenvironment (TME), where heterogeneous cancer-associated fibroblasts (CAFs) play pivotal roles in metastasis and therapy resistance. To decipher CAF diversity and spatial interactions, this study integrated single-cell RNA sequencing data from 24 BC samples with spatial transcriptomics. Intercellular networks were mapped using CellChat, spatial single-cell maps were reconstructed with Seurat, CAF developmental origins were traced through Monocle2-based trajectory analysis, and key spatial interactions were validated via immunohistochemistry. Results revealed eight major cell types, with fibroblast abundance showing positive correlation with malignant epithelial cells (ECs) prevalence. Subclustering identified six distinct CAFs subtypes: inflammatory CAFs, pericytes, matrix CAFs, antigen-presenting CAFs, smooth muscle cells, and proliferative CAFs. Spatial mapping demonstrated that these CAF subtypes form mutually exclusive niches within tumor regions, with matrix CAFs exhibiting pronounced co-localization and enhanced interactions with malignant ECs. Pseudotime trajectory analysis suggested pericytes may serve as developmental precursors differentiating into four CAF subtypes. Intercellular communication analysis uncovered significantly elevated crosstalk between malignant ECs and matrix CAFs, primarily mediated through the MDK-NCL and MIF-(CD74 + CD44) ligand-receptor axes. Importantly, a prognostic signature based on NCL, SDC2, CXCR4, and CD44 expression effectively stratified patient survival outcomes. Immunohistochemistry confirmed significant upregulation of these markers in BC patients. This study systematically profiles CAF heterogeneity in BC, revealing intricate TME signaling networks. The identified CAFs clusters and their functional engagement with tumor cells offer promising therapeutic targets.
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