A Functional Screening Strategy for Engineering Chimeric Antigen Receptors with Reduced On-Target, Off-Tumor Activation

Authors:
Raphaël B Di Roberto, Rocío Castellanos-Rueda, Samara Frey, David Egli, Rodrigo Vazquez-Lombardi, Edo Kapetanovic, Jakub Kucharczyk, Sai T Reddy
In:
Source:
Publication Date: (2020)
Issue: :
Research Area:
Immunotherapy / Hematology
Cells used in publication:
B3Z
Species: mouse
Tissue Origin:
Platform:
4D-Nucleofector® X-Unit
Experiment

 Briefly, 500,000 B3Z cells were collected and resuspended in SF buffer. The RNP/DNA mixture was added to the cells in a 1:10 ratio for a total volume of 100 µL. Electroporations were performed in Nucleocuvettes with the program CA-138. Cells were then diluted in 600 µL warm medium. Assays or sorting were performed at least 4 days later.

Abstract

In recent years, chimeric antigen receptor (CAR) T cell cancer immunotherapies have advanced substantially in the clinic. However, challenges related to safety persist; one major concern occurs when CARs trigger a response to antigen present on healthy cells (on-target, off-tumor response). A strategy to ameliorate this relies on the complex relationship between receptor affinity and signaling, such that one can engineer a CAR that is only activated by tumor cells expressing high antigen levels. Here, we developed a CAR T cell display platform with stable genomic expression and rapid functional screening based on interleukin-2 signaling. Starting with a CAR with high affinity toward its target antigen, we combined CRISPR-Cas9 genome editing and deep mutational scanning to generate a library of antigen-binding domain variants. This library was subjected to multiple rounds of selection based on either antigen binding or cell signaling. Deep sequencing of the resulting libraries and a comparative analysis revealed the enrichment and depletion of specific variants from which we selected CARs that were selectively activated by tumor cells based on antigen expression levels. Our platform demonstrates how directed evolution based on functional screening and deep sequencing-guided selection can be combined to enhance the selectivity and safety of CARs.