Functional signatures of post-infusion CAR T cells for early indication of patient response

7. Project Summary/Abstract
Chimeric antigen receptor (CAR) T cells are potent immunotherapies with demonstrated efficacy, especially for
patients with poor prognoses such as those with relapsed/refractory large B cell lymphoma (r/rLBCL). While a
majority of patients with r/rLBCL who receive CAR T cell therapy achieve a response, most patients will
eventually experience disease progression. Early identification of the patients who are not likely to experience
durable response is vital so that the appropriate treatment plan can be prioritized. Identifying resistance to CAR-
T therapy requires a multifaceted approach that accounts for the complexity of immune response and intrinsically
dynamic and heterogeneous nature of CAR-T cells. What is needed is a robust early predictive assessment of
response to therapy using scalable, cost-efficient technology that requires relatively few effector cells and has a
rapid turnaround time. With inadequate results from sequencing, bulk live-cell imaging, and flow cytometry-based
assays, a high-throughput dynamic single-cell technology is needed to directly link individual cell functions with
patient response. Assessing inter- and intra-patient heterogeneity of effector cells can be made practical using
single-cell analysis, but these cells must be studied over time. Time-lapse Imaging Microscopy In Nanowell Grids
(TIMING™) is an artificial intelligence-powered live cell analysis platform that directly integrates immune cell
function and behavior over time at single-cell resolution and in high-throughput. The Stanford University Division
of Blood and Marrow Transplantation & Cellular Therapy (Stanford BMT-CT) Biobank has banked samples with
associated clinical data for patients treated with CAR T cell therapy. In this project, we will profile post-infusion
CAR-T cells from r/rLBCL patients to develop a widely applicable functional signature associated with response.

Grant Number: 1R43CA298411-01A1
NIH Institute/Center: NIH
Principal Investigator: Rebecca Berdeaux