# Engineering synthetic feedback control in T cell signaling for anti-tumor immunity

> **NIH NIH R01** · UNIVERSITY OF WASHINGTON · 2024 · $642,044

## Abstract

Project Summary
Engineered T cells are emerging as promising therapeutic agents against a wide variety of cancers. However,
despite remarkable success against blood cancers, these cells remain largely ineffective against solid cancers,
due to their inability to sustain antitumor activity in response to chronic tumor stimulation, a process termed
exhaustion. While antigen stimulation is essential for driving the acquisition of effector functions in T cells,
strong and continued stimulation can cause cells to lose effector capabilities and enter an exhausted,
dysfunctional state. Limiting the intensity or duration of signaling could enable T cells to sustain effector
functions without concomitant exhaustion; indeed recent studies have shown that inhibiting signaling to rest
cells from chronic stimulation can enhance T cell persistence and tumor control. However, as some
stimulation is needed for effector function, it will be critical to have therapeutic strategies that can reduce
signaling activity to appropriate intensities or durations for optimal function. In this proposal, we seek to
design, build and test a synthetic feedback controller of T cell signaling, to maintain optimal signaling
for prolonging anti-tumor effector functions and mitigating exhaustion. Feedback loops are widely used
in engineering to maintain systems at defined set points, and could constitute an effective strategy for
tempering excessive signaling in T cells due to chronic stimulation in the tumor microenvironment. To enable
feedback circuit design, we will first define the relationships between input signals, pathway output, and
downstream gene regulatory and functional responses. These input/output relationships are critical for
feedback circuit design, as they reveal how much signaling activity is elicited by different inputs and how much
is optimal for sustaining desired function, thereby defining the optimal system set points and feedback
strengths. We will measure these input/output relationships in T cells (Aims 1-2), utilizing a dual-pathway
reporter system we have developed that enables concurrent live-cell measurements of the activity of two key
signaling nodes, Erk and NFAT, in primary mouse T cells. Next, informed by these quantified input/ouput
relationships, we will identify genetic components for the actuation in this feedback controller, then proceed to
build prototype circuits and test their ability to boost antitumor T cell functions within in a mouse tumor model
(Aim 3). If successful, our work will define a new strategy to counter exhaustion for engineered T cell
therapies and establish a new paradigm for engineering self-regulating cell therapies that can maintain optimal
function through environmental sensing and internal adaptation.

## Key facts

- **NIH application ID:** 10978167
- **Project number:** 1R01CA282512-01A1
- **Recipient organization:** UNIVERSITY OF WASHINGTON
- **Principal Investigator:** Hao Yuan Kueh
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $642,044
- **Award type:** 1
- **Project period:** 2024-07-17 → 2029-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10978167

## Citation

> US National Institutes of Health, RePORTER application 10978167, Engineering synthetic feedback control in T cell signaling for anti-tumor immunity (1R01CA282512-01A1). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10978167. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*