bioRxivCancer BiologyPreprint
A Developmental Lectin-Glycan Program Enables Early Breast Cancer Dissemination and Metastatic Onset
Ramiro M. PerrottaiD, Magalí Bertón, Luis E. Valencia SalazariD, Yamil Damian MahmoudiD, Juan Manuel Pérez Sáez, Tomás Dalotto‐MorenoiD, Beatriz del Valle‐PéreziD, Neus Martínez‐BoschiD, Rosa María Morales, Sabrina G. Gatto, Pilar NavarroiD, Raquel BatlleiD, Julio A. Aguirre‐GhisoiD, Gabriel A. RabinovichiD, Mariana Salatino
Abstract
Early dissemination of breast cancer cells can precede clinically detectable tumor progression, yet the programs enabling this process, remain poorly understood. Here, we identify a developmental glycocheckpoint governed by the galectin-1 (GAL1)-glycan axis that is hijacked during early breast cancer dissemination. In the mammary gland, regulated GAL1 expression and glycan accessibility directed epithelial lineage specification and progesterone-induced branching morphogenesis. This program was aberrantly reactivated in early breast cancer lesions to promote epithelial plasticity, stem-like traits and metastatic competence. Mechanistically, GAL1 was enriched in mammary stem cell compartments and sustained progesterone receptor expression and activity. Genetic ablation or therapeutic inhibition of GAL1 across breast cancer models restrained early lesion progression, reduced circulating tumor cell frequency, and limited lung metastasis. Consistent with these findings, high GAL1 expression combined with low expression of the GAL1-restricting sialyltransferase ST6GAL1 was associated with poor clinical outcomes in patients. Thus, breast cancer co-opts a developmental GAL1-glycan program to disseminate early, revealing an unexpected link between mammary morphogenesis and metastatic progression and identifying GAL1 as a therapeutic vulnerability in early-stage disease.
- organism: human
- assay: bulk RNA-seq
- research focus: cancer & tumor microenvironment
- research focus: cell type annotation
- research focus: differential expression
- approach: experimental assay
- approach: statistical model
- Citations
- 0
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