This $167,230 federal Project Grant award from the National Cancer Institute (CFDA 93.398 - Cancer Research Manpower) aims to develop innovative diagnostic approaches to accurately stratify HER2-low breast cancer patients for targeted therapy selection. The key products and services to be delivered include:
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Quantifying spatial heterogeneity and HER2 expression patterns using a high-sensitivity HER2 (HS-HER2) assay to predict response to the antibody-drug conjugate trastuzumab deruxtecan (T-DXD) in HER2-low breast cancer patients. This research will investigate large retrospective and prospective breast cancer cohorts, as well as ongoing T-DXD clinical trial cohorts.
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Exploring if an H&E-based "virtual HER2 stain" can predict low HER2 expression status by training computer vision models on aligned H&E and HS-HER2 data to discover morphologic features associated with HER2-low breast cancer and T-DXD response.
The goal is to develop reliable companion diagnostics to accurately identify HER2-low breast cancer patients eligible for emerging targeted therapies like T-DXD. The award runs from September 1, 2024 to March 31, 2027 and is being led by Yale University as the prime grantee.
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