3016 - Molecular Determinants of Breast Cancer Metastatic Organotropism
Presenter(s)
E. Yang1, J. McFadden1, A. Kim2, B. Garomsa2, J. Meng2, D. G. Miller3, A. K. Simhal2, and T. L. Chaunzwa3; 1Yale School of Medicine, New Haven, CT, 2Memorial Sloan Kettering Cancer Center, New York, NY, 3Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY
Purpose/Objective(s): The molecular determinants of organotropism in metastatic breast cancer are incompletely understood. This study investigates the relationship between molecular features such as microsatellite instability (MSI), tumor mutational burden (TMB) and metastatic site tropism in breast cancer.
Materials/Methods: We conducted a retrospective analysis of metastatic breast cancer patients in the MSK-CHORD database. Metastatic involvement across 49 distinct sites was identified. A one-way ANOVA was performed to identify molecular features that were significantly associated with metastatic site tropism.
Results: A total of 1,178 metastatic breast cancer patients across 13 histological subtypes were included in the analysis. The median age was 58, 98.81% of patients were female, 65.03% of patients had hormone receptor-positive breast cancer, while 21.39% had HER2+ disease. MSI score (F = 2.80, p < 0.001) and TMB (F = 1.91, p < 0.001) differed significantly by metastatic site. Spinal epidural metastases had the highest MSI score on average (4.56), while metastases to the adnexa had the lowest average MSI score (0.05). Metastases to the mediastinum were associated with the highest average TMB (10.38 mutations/Mb), while axillary lymph node metastases had the lowest TMB.
Conclusion: MSI and TMB varied significantly across metastatic sites, suggesting that these molecular characteristics influence tumor tropism. Future work includes developing a machine learning model to leverage these features for predicting metastatic sites from primary breast tumors. If validated, this model could enable early prediction of metastatic spread based on the molecular profile of primary breast tumors, with potential implications for prognosis and future therapeutic strategy.