Molecular Classification for Phyllodes Tumors Improves Diagnosis and Guides Treatment Decisions
Description
This project aims to improve the understanding and management of phyllodes tumors of the breast, which are aggressive and recurrent fibroepithelial neoplasms distinct from breast cancer. Currently, surgical intervention is the primary treatment due to the lack of effective medical therapies, and histopathological diagnosis fails to accurately predict tumor behavior and clinical outcomes. To address this, we established a large cohort of phyllodes tumors and utilized multi-omics data to identify molecular subtypes, aiming to develop precise classifications for prognosis and targeted treatment strategies. Additionally, we created a gene signature classifier and IHC-based markers to define subtypes and predict outcomes. This research seeks to pave the way for precision medicine in phyllodes tumor management, enabling personalized therapeutic approaches for patients.
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Institutions
- Sun Yat-Sen University Second University Hospital