Abstract 4926: Modeling the metaplastic triple negative breast cancer matrix

Abstract Metaplastic breast cancer accounts for 1% of all breast cancers and is marked by an aggressive phenotype with poor patient survival. Individuals diagnosed with metaplastic breast cancer have higher rates of recurrence, metastasis, and limited therapeutics options. Further the five-year survival rate of metaplastic breast cancer is 55%. Metaplastic breast cancer is characterized by unique histological features and recent evidence suggests that metaplastic breast tumors have extensive extracellular matrix (ECM) remodeling, including altered protein expression and increased ECM stiffness. Due to the scarcity of this tumor type, accurate modeling of the metaplastic ECM would provide enhanced in vitro testing and ultimately guide the discovery of novel targeted treatments for this rare disease. Here we demonstrate changes in the metaplastic TNBC tumor microenvironment and preliminary modeling of the metaplastic matrix in vitro. Specifically, SEM imaging revealed enhanced pore size and stiffness in the metaplastic tumor compared to matched distal breast adipose tissue. Further, metaplastic TNBC had significant enrichment for ECM proteins, notably glycoproteins (MFAP2, POSTN, FN1), compared to distal adipose. The enhanced expression of the glycoprotein MFAP2 in primary metaplastic and non-metaplastic TNBC breast cancer cell lines demonstrated enrichment of genes associated with the biological process: epithelial-to-mesenchymal transition. In depth analysis of genes elevated with MFAP2 expression in metaplastic TNBC demonstrated elevated expression of genes associated with a cancer stem like phenotype and ECM remodeling. Overall, our results establish an extracellular signature and onco-architecture for the metaplastic triple-negative tumor type. Citation Format: Elizabeth Martin, Katherine Hebert, Mackenzie Hawes, Thomas Cheng, Delia Carlino, Matthew E. Burow, Bridgette M. Collins-Burow, Jorge Belgodere. Modeling the metaplastic triple negative breast cancer matrix abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 4926.