The first few minutes of this conversation is for a lay audience, as Elham Azizi, PhD, and Charly Good, PhD, explained how they’re investigating what causes cancer to grow and spread and how to improve immunotherapy. Then the discussion moved toward a scientific audience, as Drs. Azizi and Good shared recent findings and asked probing questions about future directions and opportunities in cancer research. Elham Azizi, PhD, is a former American Cancer Society postdoctoral fellow who is now an Assistant Professor of Biomedical Engineering at Columbia University. She joined the podcast to share findings from her recent publication, “Mapping the evolution of T cell states during response and resistance to adoptive cellular therapy” (https://www.cell.com/cell-reports/fulltext/S2211-1247(21)01471-6#secsectitle0020). Charly Good, PhD, is an American Cancer Society postdoctoral fellow in the lab of Shelley Berger, PhD, at the University of Pennsylvania. She recently published research in Cell on “An NK-like CAR T cell transition in CAR T cell dysfunction” (https://www.cell.com/cell/fulltext/S0092-8674(21)01331-3). FOR A GENERAL AUDIENCE 1:25 – Dr. Azizi explains how her lab uses machine learning techniques and other cutting-edge technologies to understand what’s happening in the tumor microenvironment 2:47 – Dr. Good describes the focus of her research—using the patient’s own immune system to attack cancer FOR A SCIENTIFIC AUDIENCE 4:19 – Dr. Good describes takeaways from her recent publication on “An NK-like CAR T cell transition in CAR T cell dysfunction” (https://www.cell.com/cell/fulltext/S0092-8674(21)01331-3) 7:25 – Dr. Azizi reacts to the paper… 8:51 – …and asks why some patients didn’t see an increase in NK receptor expression 12:22 – Dr. Azizi shares findings from her paper, “Mapping the evolution of T cell states during response and resistance to adoptive cellular therapy” (https://www.cell.com/cell-reports/fulltext/S2211-1247(21)01471-6#secsectitle0020) 17:40 – Dr. Good asks: “Was it at all surprising to you when you first realized that the exhausted population was specific to the responders pre-infusion?” 22:10 – What’s next in machine learning? 26:03 – On the impact of ACS funding on their research 30:26– Why it’s an exciting time for cancer research