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Background <p>Breast cancer is one of the most prevalent malignant tumors among women, with its metastasis serving as a leading cause of mortality in affected patients. Recent studies have increasingly highlighted the significant role of tumor in nervation in the development and progression of breast cancer; however, the specific underlying mechanisms remain poorly understood.</p> Methods <p>This study investigated the relationship between tumor immune microenvironment (TIME) cell subpopulations, mediated by neuro-immune mechanisms in metastatic sites of breast cancer, and both disease severity and treatment response. We employed an analysis of single-cell transcriptomics (scRNA-seq) in conjunction with bulk RNA-seq data. The single-cell dataset GSE158399 was obtained from the GEO database, while bulk RNA-seq data from breast cancer patients were retrieved from UCSC Xena. The analysis utilized tools such as Seurat, CellChat, and Monocle, along with a GABA-related gene set.</p> Results <p>Our results identified 9 major cell types in the metastatic sites of breast cancer, including T cells, B cells, myofibroblasts, epithelial cells, macrophages, endothelial cells, proliferating cells, mature dendritic cells, and mast cells. Notably, the B cell subpopulation B_C2, the CD4<sup>+</sup> T cell subpopulation CD4<sup>+</sup>Tcm, the M2 macrophage subpopulation, and the myofibroblast subpopulation Myo_C2 were associated with the GABA gene set and appeared to play crucial roles in cell differentiation and intercellular communication. The analysis of cell communication revealed that the GABA-mediated TIME model enhanced intercellular signaling, with receptor-ligand pairs such as PTN/MDK-NCL, CXCL12-CXCR4, and APP-CD74 exhibiting significant functional patterns within the samples. Additionally, the bulk RNA-seq data analysis identified the target gene COL1A2, whose expression was significantly correlated with tumor grading and metastatic status, indicating that Stage III patients had higher expression levels than those in Stage I and II, and that the N2 and N3 metastatic groups exhibited higher expression than the N0 group.</p> Conclusion <p>This study suggests that GABA may reshape the TIME through the modulation of the neuro-immune axis, offering new insights for prognostic assessments and the development of therapeutic targets in breast cancer metastasis.</p>

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Single-cell landscape of intratumoral heterogeneity and GABA-mediated remodeling of the immune microenvironment in breast cancer metastases

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年3月31日

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  • Lina Tang

摘要

Background

Breast cancer is one of the most prevalent malignant tumors among women, with its metastasis serving as a leading cause of mortality in affected patients. Recent studies have increasingly highlighted the significant role of tumor in nervation in the development and progression of breast cancer; however, the specific underlying mechanisms remain poorly understood.

Methods

This study investigated the relationship between tumor immune microenvironment (TIME) cell subpopulations, mediated by neuro-immune mechanisms in metastatic sites of breast cancer, and both disease severity and treatment response. We employed an analysis of single-cell transcriptomics (scRNA-seq) in conjunction with bulk RNA-seq data. The single-cell dataset GSE158399 was obtained from the GEO database, while bulk RNA-seq data from breast cancer patients were retrieved from UCSC Xena. The analysis utilized tools such as Seurat, CellChat, and Monocle, along with a GABA-related gene set.

Results

Our results identified 9 major cell types in the metastatic sites of breast cancer, including T cells, B cells, myofibroblasts, epithelial cells, macrophages, endothelial cells, proliferating cells, mature dendritic cells, and mast cells. Notably, the B cell subpopulation B_C2, the CD4+ T cell subpopulation CD4+Tcm, the M2 macrophage subpopulation, and the myofibroblast subpopulation Myo_C2 were associated with the GABA gene set and appeared to play crucial roles in cell differentiation and intercellular communication. The analysis of cell communication revealed that the GABA-mediated TIME model enhanced intercellular signaling, with receptor-ligand pairs such as PTN/MDK-NCL, CXCL12-CXCR4, and APP-CD74 exhibiting significant functional patterns within the samples. Additionally, the bulk RNA-seq data analysis identified the target gene COL1A2, whose expression was significantly correlated with tumor grading and metastatic status, indicating that Stage III patients had higher expression levels than those in Stage I and II, and that the N2 and N3 metastatic groups exhibited higher expression than the N0 group.

Conclusion

This study suggests that GABA may reshape the TIME through the modulation of the neuro-immune axis, offering new insights for prognostic assessments and the development of therapeutic targets in breast cancer metastasis.