Adhesion strength of tumor cells predicts metastatic disease in vivo.

ABSTRACT: Although only a fraction of tumor cells contribute to metastatic disease, no prognostic biomarkers currently exist to identify these cells. We show that a physical marker-adhesion strength-predicts metastatic potential in a mouse breast cancer model and that it may stratify human disease. Cells disseminating from murine mammary tumors are weakly adherent, and, when pre-sorted by adhesion, primary tumors created from strongly adherent cells exhibit fewer lung metastases than weakly adherent cells do. We demonstrate that admixed cancer lines can be separated by label-free adhesive signatures. When applied to murine metastatic tumors, adhesion retrospectively predicts metastatic disease with 100% specificity, 85% sensitivity, and area under the curve (AUC) of 0.94. Cells from human reduction

SUBMITTER: Kane MA 

PROVIDER: S-EPMC12014391 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature