When Disorder Becomes Data: Pathology and Cell Biology Chair's Breast Cancer Research Makes National News
Dr. Kevin Gardner's research on breast cancer diagnostics has reached a national audience, building on a discovery that started here.
Pathologists have always assessed tumors by how organized or chaotic their tissue looks under the microscope. Dr. Gardner, chair of Pathology and Cell Biology, is senior author on a study in Cancer Journal that turns a visual judgment into a precise number. Using a method called persistent homology, part of a field called topology, Dr. Gardner’s team found a way to measure that disorder mathematically and score how tumor and immune cells are arranged within breast cancer tissue. The resulting scores predicted patient survival and treatment response more accurately than many traditional biomarkers, and showed less variation across racial and ethnic groups. As Dr. Gardner put it in HICCC's coverage of the study earlier this month:
Pathologists have been looking at disorganized structures for years. What topology allows us to do is move from something subjective to something quantitative.
The research didn't stay in academic circles for long. On July 22, Newsweek picked it up, reporting on what these methods could mean for the future of breast cancer diagnosis and framing them as a step toward diagnostics that are faster, more accurate, and more accessible. Dr. Gardner described the bigger picture behind his work, telling the outlet that it focuses on combining advances in digital pathology, AI, and machine learning to better understand the disease.
By combining detailed images of tumor tissue with information about a patient's genes, proteins, and other clinical characteristics, we're working towards creating a more complete picture of each individual's cancer. Our long-term goal is to make these advances more widely available so more patients can benefit from precision cancer care.
Two publications, one story worth telling: Dr. Gardner’s research is helping to shape what breast cancer diagnosis will look like next. Congratulations to Dr. Gardner and the full research team on this well-earned recognition.