Spatial gene expression analysis reveals drivers of extremely early lymph node metastasis in breast cancer

Lymph node metastasis correlates with breast cancer prognosis; however, the cellular mechanisms underlying the earliest metastatic events remain unclear. In spatial transcriptomic analysis of a patient with breast cancer at single-cell resolution, we identified 30 tumor cells representing the initial metastatic seeding in a lymph node. These cells originated from multiple epithelial-mesenchymal (EM) transition status and included six distinct subpopulations with biological significance. Only cells exhibiting a metabolic shift toward fatty acid metabolism successfully established lymph node colonies, implicating this shift in metastatic fitness. The tumor microenvironment surrounding these cells showed immunosuppressive and tumor-promoting features, supporting metastasis establishment. Cross-referencing these expression profiles with public datasets revealed that poor prognosis correlated not with fully mesenchymal or metastatic populations, but with hybrid EM cells exhibiting epithelial and mesenchymal traits. These findings highlight the metabolic and phenotypic plasticity of metastatic cells and serve as translational bridges between the spatial evolution of tumor cells in the extremely early stages of lymph node metastasis and clinical prognosis in breast cancer.