Project 1. Smart Tumor Recognition. While CAR T cells have been successful in treating B cell cancers, they have not shown significant success in treating solid cancers. One of the major problems in targeting engineered immune cells to solid cancers is the lack of absolutely tumor specific surface antigen targets that can be used to discriminate the cancers from normal tissues. CAR T cell crossreaction with normal epithelial organs can be lethal. Thus, it is imperative to develop new schemes that allow immune cells to more precisely recognize tumors based on combinatorial sets of molecular features. At the same time, we recognize that when tumors are targeted too stringently, they can escape treatment via intrinsic tumor heterogeneity or mutation. Our goal is to develop immune cell recognition circuits that can detect cancers based on multi- antigen patterns, and which can balance both stringency and flexibility in recognition. We have recently developed a novel prototype T cell circuit that is capable of recognizing precise antigen pairs: a synNotch receptor that recognizes a priming antigen induces expression of a CAR that recognizes a killing antigen. Here we propose to build on this prototype circuit to develop new specific schemes for targeting solid cancers.
Our specific aims are: 1) Computationally screen cancer and normal tissue gene expression datasets to identify combinatorial surface antigen signatures that would be optimal for tumor recognition without normal tissue cross-reaction. 2) Engineer a complete set of synNotch-CAR circuits that can recognize all possible types of 2-3 antigen combinatorial patterns including AND, NOT, and OR relationships (new Boolean gate circuits). 3) Engineer versions of these combinatorial recognition circuits that can incorporate flexibility to overcome tumor heterogeneity or mutational escape 4) Engineer new classes of immune cell antigen sensors that induce new cellular behaviors, new sensing dynamics, and can be used to build more types of recognition circuits. 5) Develop high-throughput, semi-automated pipeline for circuit assembly, and apply to design of immune cells to attack specific cancers This toolkit of new recognition receptors, new pattern recognition circuits, and bioinformatically filtered actionable targets should significantly increase our capability to intelligently and safely target solid tumors using therapeutic immune cells.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Specialized Center--Cooperative Agreements (U54)
Project #
1U54CA244438-01
Application #
9869711
Study Section
Special Emphasis Panel (ZCA1)
Project Start
Project End
Budget Start
2019-09-01
Budget End
2020-08-31
Support Year
1
Fiscal Year
2019
Total Cost
Indirect Cost
Name
University of California San Francisco
Department
Type
DUNS #
094878337
City
San Francisco
State
CA
Country
United States
Zip Code
94118