James Hicks, PhD

Applying blood biopsy technology to understand cancer progression and find predictive markers that indicate how cancer will react to treatment.

Impact

Liquid biopsy, a blood test that detects cancer cells and other tumor-associated factors, is a promising, less-invasive alternative to tumor biopsy. In addition to more readily providing information about a patient’s cancer, its minimally invasive nature means several samples can be taken over time. This would allow clinicians to have real-time data on a tumor’s response to therapy, informing treatment decisions and potentially revolutionize the way cancer is managed. Liquid biopsies are not currently available for widespread clinical applications, but Drs. Hicks and Kuhn and their teams are pushing this new technology to expand the scope of what information can be derived from patient blood and exploring its potential in early detection as well as predicting cancer progression and recurrence.

Progress Thus Far

The team have developed new ways to study breast cancer by combining advanced imaging of single cells in the blood with powerful computational tools and clinical research. Using artificial intelligence, they can now detect many types of tumor-related cells in a simple blood test, including cancer-associated fibroblasts, which are known to be key players in promoting cancer, and even tiny particles released by tumors. They also discovered that some tumor cells disguise themselves by carrying markers usually found on immune cells, which may help them hide from the body’s defenses. To analyze these complex cell populations, they have created two new machine learning methods that can sort through millions of cell images and provide a detailed picture of what’s happening in a patient’s blood. These methods, combined with protein-based tests for confirmation, will now be applied to their large digital databank from breast cancer trials.

What’s next

Over the next year, they’ll apply their advanced single-cell analysis tools to blood samples from hundreds of women across ongoing breast cancer trials—including studies focused on Black women, who disproportionately experience poorer breast cancer outcomes. By combining cell profiling with clinical data, they aim to develop an AI-powered system that can classify breast cancer types and stages from a blood test. Their goal is a widely accessible blood test that helps doctors diagnose and personalize treatment for every patient.