Degron-based bioPROTACs for controlling signaling in CAR T cells.

Chimeric antigen receptor (CAR) T cells have made a tremendous impact in the clinic, but potent signaling through the CAR can be detrimental to treatment safety and efficacy. The use of protein degradation to control CAR signaling can address these issues in pre-clinical models. Existing strategies for regulating CAR stability rely on small molecules to induce systemic degradation. In contrast to small molecule regulation, genetic circuits offer a more precise method to control CAR signaling in an autonomous, cell-by-cell fashion. Here, we describe a programmable protein degradation tool that adopts the framework of bioPROTACs, heterobifunctional proteins that are composed of a target recognition domain fused to a domain that recruits the endogenous ubiquitin proteasome system. We develop novel bioPROTACs that utilize a compact four residue degron and demonstrate degradation of cytosolic and membrane protein targets using either a nanobody or synthetic leucine zipper as a protein binder. Our bioPROTACs exhibit potent degradation of CARs and can inhibit CAR signaling in primary human T cells. We demonstrate the utility of our bioPROTACs by constructing a genetic circuit to degrade the tyrosine kinase ZAP70 in response to recognition of a specific membrane-bound antigen. This circuit is able to disrupt CAR T cell signaling only in the presence of a specific cell population. These results suggest that bioPROTACs are a powerful tool for expanding the cell engineering toolbox for CAR T cells.

An immune-based tool platform for in vivo cell clearance.

Immunological targeting of pathological cells has been successful in oncology and is expanding to other pathobiological contexts. Here, we present a flexible platform that allows labeling cells of interest with the surface-expressed model antigen ovalbumin (OVA), which can be eliminated via either antigen-specific T cells or newly developed OVA antibodies. We demonstrate that hepatocytes can be effectively targeted by either modality. In contrast, pro-fibrotic fibroblasts associated with pulmonary fibrosis are only eliminated by T cells in initial experiments, which reduced collagen deposition in a fibrosis model. This new experimental platform will facilitate development of immune-based approaches to clear potential pathological cell types in vivo.

Instructional materials that control cellular activity through synthetic Notch receptors.

The field of regenerative engineering relies primarily on the dual technical platforms of cell selection/conditioning and biomaterial fabrication to support directed cell differentiation. As the field has matured, an appreciation for the influence of biomaterials on cell behaviors has resulted in engineered matrices that meet biomechanical and biochemical demands of target pathologies. Yet, despite advances in methods to produce designer matrices, regenerative engineers remain unable to reliably orchestrate behaviors of therapeutic cells in situ. Here, we present a platform named MATRIX whereby cellular responses to biomaterials can be custom defined by combining engineered materials with cells expressing cognate synthetic biology control modules. Such privileged channels of material-to-cell communication can activate synthetic Notch receptors and govern activities as diverse as transcriptome engineering, inflammation attenuation, and pluripotent stem cell differentiation, all in response to materials decorated with otherwise bioinert ligands. Further, we show that engineered cellular behaviors are confined to programmed biomaterial surfaces, highlighting the potential to use this platform to spatially organize cellular responses to bulk, soluble factors. This integrated approach of co-engineering cells and biomaterials for orthogonal interactions opens new avenues for reproducible control of cell-based therapies and tissue replacements.

Harnessing synthetic biology to engineer organoids and tissues.

The development of an organism depends on intrinsic genetic programs of progenitor cells and their spatiotemporally complex extrinsic environment. Ex vivo generation of organoids from progenitor cells provides a platform for recapitulating and exploring development. Current approaches rely largely on soluble morphogens or engineered biomaterials to manipulate the physical environment, but the emerging field of synthetic biology provides a powerful toolbox to genetically manipulate cell communication, adhesion, and even cell fate. Applying these modular tools to organoids should lead to a deeper understanding of developmental principles, improved organoid models, and an enhanced capability to design tissues for regenerative purposes.

Programming multicellular assembly with synthetic cell adhesion molecules.

Cell adhesion molecules are ubiquitous in multicellular organisms, specifying precise cell-cell interactions in processes as diverse as tissue development, immune cell trafficking and the wiring of the nervous system1-4. Here we show that a wide array of synthetic cell adhesion molecules can be generated by combining orthogonal extracellular interactions with intracellular domains from native adhesion molecules, such as cadherins and integrins. The resulting molecules yield customized cell-cell interactions with adhesion properties that are similar to native interactions. The identity of the intracellular domain of the synthetic cell adhesion molecules specifies interface morphology and mechanics, whereas diverse homotypic or heterotypic extracellular interaction domains independently specify the connectivity between cells. This toolkit of orthogonal adhesion molecules enables the rationally programmed assembly of multicellular architectures, as well as systematic remodelling of native tissues. The modularity of synthetic cell adhesion molecules provides fundamental insights into how distinct classes of cell-cell interfaces may have evolved. Overall, these tools offer powerful abilities for cell and tissue engineering and for systematically studying multicellular organization.

Decoding CAR T cell phenotype using combinatorial signaling motif libraries and machine learning.

Chimeric antigen receptor (CAR) costimulatory domains derived from native immune receptors steer the phenotypic output of therapeutic T cells. We constructed a library of CARs containing ~2300 synthetic costimulatory domains, built from combinations of 13 signaling motifs. These CARs promoted diverse human T cell fates, which were sensitive to motif combinations and configurations. Neural networks trained to decode the combinatorial grammar of CAR signaling motifs allowed extraction of key design rules. For example, non-native combinations of motifs that bind tumor necrosis factor receptor-associated factors (TRAFs) and phospholipase C gamma 1 (PLCγ1) enhanced cytotoxicity and stemness associated with effective tumor killing. Thus, libraries built from minimal building blocks of signaling, combined with machine learning, can efficiently guide engineering of receptors with desired phenotypes.

Synthetic cytokine circuits that drive T cells into immune-excluded tumors.

Chimeric antigen receptor (CAR) T cells are ineffective against solid tumors with immunosuppressive microenvironments. To overcome suppression, we engineered circuits in which tumor-specific synNotch receptors locally induce production of the cytokine IL-2. These circuits potently enhance CAR T cell infiltration and clearance of immune-excluded tumors, without systemic toxicity. The most effective IL-2 induction circuit acts in an autocrine and T cell receptor (TCR)- or CAR-independent manner, bypassing suppression mechanisms including consumption of IL-2 or inhibition of TCR signaling. These engineered cells establish a foothold in the target tumors, with synthetic Notch-induced IL-2 production enabling initiation of CAR-mediated T cell expansion and cell killing. Thus, it is possible to reconstitute synthetic T cell circuits that activate the outputs ultimately required for an antitumor response, but in a manner that evades key points of tumor suppression.

The emerging era of cell engineering: Harnessing the modularity of cells to program complex biological function.

A new era of biological engineering is emerging in which living cells are used as building blocks to address therapeutic challenges. These efforts are distinct from traditional molecular engineering-their focus is not on optimizing individual genes and proteins as therapeutics, but rather on using molecular components as modules to reprogram how cells make decisions and communicate to achieve higher-order physiological functions in vivo. This cell-centric approach is enabled by a growing tool kit of components that can synthetically control core cell-level functional outputs, such as where in the body a cell should go, what other cells it should interact with, and what messages it should transmit or receive. The power of cell engineering has been clinically validated by the development of immune cells designed to kill cancer. This same tool kit for rewiring cell connectivity is beginning to be used to engineer cell therapies for a host of other diseases and to program the self-organization of tissues and organs. By forcing the conceptual distillation of complex biological functions into a finite set of instructions that operate at the cell level, these efforts also shed light on the fundamental hierarchical logic that links molecular components to higher-order physiological function.

Rethinking cancer targeting strategies in the era of smart cell therapeutics.

In the past several decades, the development of cancer therapeutics has largely focused on precision targeting of single cancer-associated molecules. Despite great advances, such targeted therapies still show incomplete precision and the eventual development of resistance due to target heterogeneity or mutation. However, the recent development of cell-based therapies such as chimeric antigen receptor (CAR) T cells presents a revolutionary opportunity to reframe strategies for targeting cancers. Immune cells equipped with synthetic circuits are essentially living computers that can be programmed to recognize tumours based on multiple signals, including both tumour cell-intrinsic and microenvironmental. Moreover, cells can be programmed to launch broad but highly localized therapeutic responses that can limit the potential for escape while still maintaining high precision. Although these emerging smart cell engineering capabilities have yet to be fully implemented in the clinic, we argue here that they will become much more powerful when combined with machine learning analysis of genomic data, which can guide the design of therapeutic recognition programs that are the most discriminatory and actionable. The merging of cancer analytics and synthetic biology could lead to nuanced paradigms of tumour recognition, more akin to facial recognition, that have the ability to more effectively address the complex challenges of treating cancer.

SynNotch-CAR T cells overcome challenges of specificity, heterogeneity, and persistence in treating glioblastoma.

Treatment of solid cancers with chimeric antigen receptor (CAR) T cells is plagued by the lack of ideal target antigens that are both absolutely tumor specific and homogeneously expressed. We show that multi-antigen prime-and-kill recognition circuits provide flexibility and precision to overcome these challenges in the context of glioblastoma. A synNotch receptor that recognizes a specific priming antigen, such as the heterogeneous but tumor-specific glioblastoma neoantigen epidermal growth factor receptor splice variant III (EGFRvIII) or the central nervous system (CNS) tissue-specific antigen myelin oligodendrocyte glycoprotein (MOG), can be used to locally induce expression of a CAR. This enables thorough but controlled tumor cell killing by targeting antigens that are homogeneous but not absolutely tumor specific. Moreover, synNotch-regulated CAR expression averts tonic signaling and exhaustion, maintaining a higher fraction of the T cells in a naïve/stem cell memory state. In immunodeficient mice bearing intracerebral patient-derived xenografts (PDXs) with heterogeneous expression of EGFRvIII, a single intravenous infusion of EGFRvIII synNotch-CAR T cells demonstrated higher antitumor efficacy and T cell durability than conventional constitutively expressed CAR T cells, without off-tumor killing. T cells transduced with a synNotch-CAR circuit primed by the CNS-specific antigen MOG also exhibited precise and potent control of intracerebral PDX without evidence of priming outside of the brain. In summary, by using circuits that integrate recognition of multiple imperfect but complementary antigens, we improve the specificity, completeness, and persistence of T cells directed against glioblastoma, providing a general recognition strategy applicable to other solid tumors.

T cell circuits that sense antigen density with an ultrasensitive threshold.

Overexpressed tumor-associated antigens [for example, epidermal growth factor receptor (EGFR) and human epidermal growth factor receptor 2 (HER2)] are attractive targets for therapeutic T cells, but toxic "off-tumor" cross-reaction with normal tissues that express low levels of target antigen can occur with chimeric antigen receptor (CAR)-T cells. Inspired by natural ultrasensitive response circuits, we engineered a two-step positive-feedback circuit that allows human cytotoxic T cells to discriminate targets on the basis of a sigmoidal antigen-density threshold. In this circuit, a low-affinity synthetic Notch receptor for HER2 controls the expression of a high-affinity CAR for HER2. Increasing HER2 density thus has cooperative effects on T cells-it increases both CAR expression and activation-leading to a sigmoidal response. T cells with this circuit show sharp discrimination between target cells expressing normal amounts of HER2 and cancer cells expressing 100 times as much HER2, both in vitro and in vivo.

T cells selectively filter oscillatory signals on the minutes timescale.

T cells experience complex temporal patterns of stimulus via receptor-ligand-binding interactions with surrounding cells. From these temporal patterns, T cells are able to pick out antigenic signals while establishing self-tolerance. Although features such as duration of antigen binding have been examined, our understanding of how T cells interpret signals with different frequencies or temporal stimulation patterns is relatively unexplored. We engineered T cells to respond to light as a stimulus by building an optogenetically controlled chimeric antigen receptor (optoCAR). We discovered that T cells respond to minute-scale oscillations of activation signal by stimulating optoCAR T cells with tunable pulse trains of light. Systematically scanning signal oscillation period from 1 to 150 min revealed that expression of CD69, a T cell activation marker, reached a local minimum at a period of ∼25 min (corresponding to 5 to 15 min pulse widths). A combination of inhibitors and genetic knockouts suggest that this frequency filtering mechanism lies downstream of the Erk signaling branch of the T cell response network and may involve a negative feedback loop that diminishes Erk activity. The timescale of CD69 filtering corresponds with the duration of T cell encounters with self-peptide-presenting APCs observed via intravital imaging in mice, indicating a potential functional role for temporal filtering in vivo. This study illustrates that the T cell signaling machinery is tuned to temporally filter and interpret time-variant input signals in discriminatory ways.

DNA scaffolds enable efficient and tunable functionalization of biomaterials for immune cell modulation.

Biomaterials can improve the safety and presentation of therapeutic agents for effective immunotherapy, and a high level of control over surface functionalization is essential for immune cell modulation. Here, we developed biocompatible immune cell-engaging particles (ICEp) that use synthetic short DNA as scaffolds for efficient and tunable protein loading. To improve the safety of chimeric antigen receptor (CAR) T cell therapies, micrometre-sized ICEp were injected intratumorally to present a priming signal for systemically administered AND-gate CAR-T cells. Locally retained ICEp presenting a high density of priming antigens activated CAR T cells, driving local tumour clearance while sparing uninjected tumours in immunodeficient mice. The ratiometric control of costimulatory ligands (anti-CD3 and anti-CD28 antibodies) and the surface presentation of a cytokine (IL-2) on ICEp were shown to substantially impact human primary T cell activation phenotypes. This modular and versatile biomaterial functionalization platform can provide new opportunities for immunotherapies.

Precise T cell recognition programs designed by transcriptionally linking multiple receptors.

Living cells often identify their correct partner or target cells by integrating information from multiple receptors, achieving levels of recognition that are difficult to obtain with individual molecular interactions. In this study, we engineered a diverse library of multireceptor cell-cell recognition circuits by using synthetic Notch receptors to transcriptionally interconnect multiple molecular recognition events. These synthetic circuits allow engineered T cells to integrate extra- and intracellular antigen recognition, are robust to heterogeneity, and achieve precise recognition by integrating up to three different antigens with positive or negative logic. A three-antigen AND gate composed of three sequentially linked receptors shows selectivity in vivo, clearing three-antigen tumors while ignoring related two-antigen tumors. Daisy-chaining multiple molecular recognition events together in synthetic circuits provides a powerful way to engineer cellular-level recognition.

Engineering synthetic morphogen systems that can program multicellular patterning.

In metazoan tissues, cells decide their fates by sensing positional information provided by specialized morphogen proteins. To explore what features are sufficient for positional encoding, we asked whether arbitrary molecules (e.g., green fluorescent protein or mCherry) could be converted into synthetic morphogens. Synthetic morphogens expressed from a localized source formed a gradient when trapped by surface-anchoring proteins, and they could be sensed by synthetic receptors. Despite their simplicity, these morphogen systems yielded patterns reminiscent of those observed in vivo. Gradients could be reshaped by altering anchor density or by providing a source of competing inhibitor. Gradient interpretation could be altered by adding feedback loops or morphogen cascades to receiver cell response circuits. Orthogonal cell-cell communication systems provide insight into morphogen evolution and a platform for engineering tissues.

Discriminatory Power of Combinatorial Antigen Recognition in Cancer T Cell Therapies.

Precise discrimination of tumor from normal tissues remains a major roadblock for therapeutic efficacy of chimeric antigen receptor (CAR) T cells. Here, we perform a comprehensive in silico screen to identify multi-antigen signatures that improve tumor discrimination by CAR T cells engineered to integrate multiple antigen inputs via Boolean logic, e.g., AND and NOT. We screen >2.5 million dual antigens and ∼60 million triple antigens across 33 tumor types and 34 normal tissues. We find that dual antigens significantly outperform the best single clinically investigated CAR targets and confirm key predictions experimentally. Further, we identify antigen triplets that are predicted to show close to ideal tumor-versus-normal tissue discrimination for several tumor types. This work demonstrates the potential of 2- to 3-antigen Boolean logic gates for improving tumor discrimination by CAR T cell therapies. Our predictions are available on an interactive web server resource (antigen.princeton.edu).

The Design Principles of Biochemical Timers: Circuits that Discriminate between Transient and Sustained Stimulation.

Many cellular responses for which timing is critical display temporal filtering-the ability to suppress response until stimulated for longer than a given minimal time. To identify biochemical circuits capable of kinetic filtering, we comprehensively searched the space of three-node enzymatic networks. We define a metric of "temporal ultrasensitivity," the steepness of activation as a function of stimulus duration. We identified five classes of core network motifs capable of temporal filtering, each with distinct functional properties such as rejecting high-frequency noise, committing to response (bistability), and distinguishing between long stimuli. Combinations of the two most robust motifs, double inhibition (DI) and positive feedback with AND logic (PFAND), underlie several natural timer circuits involved in processes such as cell cycle transitions, T cell activation, and departure from the pluripotent state. The biochemical network motifs described in this study form a basis for understanding common ways cells make dynamic decisions.