Integrating single-cell and spatial transcriptomics to dissect mast-cell heterogeneity and arginine-metabolism-associated markers in BRCA
Year: 2026
Type: article
Abstract: BACKGROUND: Mast cells (MCs) are immunometabolic sentinels, yet their heterogeneity and functional specialization in breast cancer (BRCA) remain unclear. We hypothesized that arginine metabolism defines transcriptionally and functionally distinct MC subpopulations that shape the BRCA microenvironment. METHODS: We integrated single-cell RNA-seq (GSE161529; 272,592 cells, 38 clusters), spatial transcriptomics (GSE243022) and bulk RNA-seq (TCGA, GSE42568). After harmony batch-correction and Seurat-Louvian clustering, MCs were split by median arginine score (AUCell/UCell/AddModuleScore/singscore) into high- (HAS) and low-activity (LAS) subsets. Monocle2 pseudotime, CellChat, hdWGCNA (power = 15), LASSO-Cox and MiloR were used to trace differentiation, communication, prognostic value and triple-negative breast cancer (TNBC) enrichment. Functional validation of the model-prioritized gene OAT was subsequently conducted in clinical tissues and breast cancer cell lines through loss-of-function assays. RESULTS: MC hotspots in tumor cores (AUC = 0.89 vs normal). Experimentally, OAT expression was elevated in TNBC tissues and cell lines. Knockdown of OAT impaired proliferation, induced apoptosis, suppressed migration/invasion, and modulated apoptosis- and EMT-related protein expression, functionally supporting its role in BRCA progression. CONCLUSION: Arginine metabolism stratifies MCs into pro-tumorigenic HAS and quiescent LAS subsets; ASL-high MCs constitute a metabolically wired, highly communicating population that fuels TNBC progression and furnishes an exploitable prognostic signature. OAT, a key HAS-associated gene, promotes breast cancer aggressiveness through proliferation, survival, and invasion.
Source: Neoplasia
Language: English
Topic: Mast cells and histamine
Subfield: Immunology
Field: Immunology and Microbiology
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $3,530
Funder: Hebei University
Award: G1775594497
OpenAlex ID: W7128360922
