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

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.