Speaker
Description
Non-Hodgkin lymphoma (NHL) is a heterogeneous group of hematological malignancies arising from lymphoid cells. In relapsed or refractory cases, chimeric antigen receptor (CAR) T-cell therapy offers a potentially curative treatment by engineering patient-derived T-cells to target tumor-associated antigens. Despite promising outcomes, treatment response remains variable across patients.
Lactate dehydrogenase (LDH) is a serum marker that reflects tumor burden, cell turnover, and tissue damage. It is routinely measured prior to lymphodepletion and during CAR T-cell therapy and may provide insight into the immunological context at treatment onset.
We developed a mechanistic ordinary differential equation (ODE) model that studies the relationship between CAR T-cell kinetics, tumor burden, and treatment response. By integrating individual patients’ longitudinal CAR T-cell and LDH measurements of NHL patients within a Bayesian inference framework, we aim to infer latent tumor burden trajectories, linking tumor-immune interactions to treatment outcome.
