# Protein Recognition in Signal Transduction

> **NIH NIH R01** · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · 2022 · $338,302

## Abstract

Project Summary/Abstract
T cells engineered to recognize and kill cancer cells via chimeric antigen receptors (CARs) have emerged as a
promising and potentially transformative therapeutic platform. CAR T cells have proven to be an extremely
effective therapy for certain B cell cancers. Nonetheless, many issues still remain in order to apply engineered
T cells to a broader range of cancers. First, current CAR T cells, are not able to discriminate between high and
low antigen expressing cells. Therefore, targeting antigens that are overexpressed in solid tumor cells (e.g.
Her2 or EGFR) can result in lethal off-target killing of bystander tissues expressing lower levels of the antigen.
Here we propose to attack this problem by using common biochemical mechanisms for cooperative recognition
(i.e. sigmoidal thresholds) to engineer new synthetic T cell receptors or circuits that can sense antigen density.
Second, we would ideally like to develop T cell receptor variants that, when activated, drive the cell to a more
persistent and effective state (e.g. Th1 or central memory state). To identify next-generation CARs that drive
particular T cell responses, we have developed a new strategy for constructing and screening a combinatorial
barcoded library of CARs that contain synthetic intracellular co-stimulatory signaling domains. We will screen
this library for CAR variants that improve T cell activation, proliferation, and differentiation. We will also use the
composite information from analyzing the library to identify critical signaling motifs most responsible for
directing T cell response trajectories towards specific paths. Our specific aims are:
Aim 1. Engineer synthetic T cell receptors and circuits that can discriminate cancer and bystander
cells based on differences in antigen density (using Her2 antigen as a primary testcase)
A. Engineer and test a series of cooperative low affinity but high valency CARs for Her2
B. Engineer and test cooperative two-step multi-receptor circuits for sharp threshold detection of Her2
C. Extend these density sensing strategies to sense EGFR density
Cells will be tested against cell lines expressing different antigen densities; They will be evaluated in vivo using
cell lines and PDX mouse models; crossreactivity will be tested using human tissue xenografts.
Aim 2. Build and screen combinatorial CAR libraries to identify synthetic T cell receptors with
optimized activation, proliferation and cell fate differentiation
A. Develop a novel method for assembling barcoded library of synthetic T cell receptors containing
 combinations of linear immune signaling motifs (i.e. “synthetic co-stimulatory domains”)
B. Screen receptor libraries for receptors with specific optimized or novel response behaviors
We will evaluate the therapeutic function of new receptor candidates that emerge from these libraries;
Composite analysis will be used to better understand the dominant signaling motifs that direct particular types
responses. ...

## Key facts

- **NIH application ID:** 10460232
- **Project number:** 5R01CA220257-21
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
- **Principal Investigator:** WENDELL A LIM
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $338,302
- **Award type:** 5
- **Project period:** 2018-09-01 → 2025-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10460232

## Citation

> US National Institutes of Health, RePORTER application 10460232, Protein Recognition in Signal Transduction (5R01CA220257-21). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10460232. Licensed CC0.

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