Project Scientist
Department of Hematology-Oncology
Cedars-Sinai Medical Center

Project title: Single Cell Spatial Analysis of DLBCL to Develop Biomarkers and Optimize CAR T Therapy

Mentors:
Akil Merchant, MD - Cedars-Sinai Medical Center
Helen Goodridge, PhD - Cedars-Sinai Medical Center
Edwin Posadas, MD - Cedars-Sinai Medical Center
Clive Svendsen, PhD - Cedars-Sinai Medical Center
Simon Gayther, PhD - Cedars-Sinai Medical Center
Yvonne Chen, PhD - UCLA
Joshua Sasine, MD, PhD - Cedars-Sinai Medical Center

Multidisciplinary Expertise:
Nanobiotechnology, Single-Cell Analysis, Microfluidics, Bioinformatics, Materials Science and Engineering

Project Description:
Diffuse Large B-Cell Lymphoma (DLBCL) is the most common non-Hodgkin lymphoma, with high cellular heterogeneity and a significant immune component. DLBCL standard therapy has a failure rate of ~35%, and CAR T-cells are engineered immune cells that have emerged as viable treatments for ~50% of patients that fail standard therapies. New strategies are needed to predict clinical outcomes and improve the efficacy of CAR T therapy. Immune cells in the tumor microenvironment of DLBCL are highly heterogeneous, they have antitumor or pro-tumor properties that affect the clinical outcomes of patients, and they can be conflated with the tumor itself, which expresses immune markers. CAR T cells add yet another moving piece to this intricate puzzle. To resolve this complexity, new technology has emerged to perform spatial analysis of DLBCL at single cell resolution and reveal tumor and immune phenotypes that can act as biomarkers of clinical response. Using Imaging Mass Cytometry (IMC) to analyze 40+ proteins at 1 μm resolution, we can identify tumor-immune spatial relationships in DLBCL, such as local areas of checkpoint expression or infiltrating immune cells. This project’s goal is to use IMC to identify new spatial and protein predictors of clinical outcome, to study CAR T therapy response and its evolution over time, and to test the effects of two CAR T co-treatments on treatment efficacy.