Pancreatic cancer remains one of the deadliest cancers, and most patients do not benefit from current immunotherapies. One major reason is that pancreatic tumors create a dense, scar-like environment that physically blocks immune cells from entering the tumor and suppresses their activity. 

Dr. Huang develops computational models that connect molecular biology with tissue-level immune behavior. Her earlier work combined genetics, systems immunology, and mathematical modeling to understand how immune cells make decisions and respond to disease. 

This project will study how the tumor environment changes in pancreatic cancer patients receiving a combination of chemotherapy, immunotherapy, and a drug designed to help immune cells enter tumors. Using advanced imaging and molecular profiling, Dr. Huang will analyze tumor samples collected before and during treatment to map where immune cells are located and how they interact with cancer cells. 

She will then use artificial intelligence to identify tissue patterns that predict whether a patient is likely to respond to therapy. Finally, Dr. Huang will create personalized “virtual tumor” simulations that can safely test different treatment combinations and dosing strategies. If successful, this work could help doctors better predict which patients will benefit from immunotherapy, reduce exposure to ineffective treatments, and accelerate development of more personalized therapies for pancreatic cancer.

Mentor

Venu Pillarisetty, MD

Projects and Grants

Interpretable virtual tumor to simulate TIME remodeling in PDAC during chemo-immunotherapy