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

Advancing CAR T-cell Therapies with Artificial Intelligence: Opportunities and Challenges

Artificial intelligence could enhance chimeric antigen receptor T-cell therapy outcomes through optimization of all steps, from target identification, vector design, and manufacturing to personalized data-driven clinical decisions. In this report, we highlight steps toward unlocking this potential, including the need for standardized, comprehensive data repositories as a way for addressing barriers to artificial intelligence learning, such as data heterogeneity and patient privacy.

Engineering TCR-controlled fuzzy logic into CAR T cells enhances therapeutic specificity

Chimeric antigen receptor (CAR) T cell immunotherapy represents a breakthrough in the treatment of hematological malignancies, but poor specificity has limited its applicability to solid tumors. By contrast, natural T cells harboring T cell receptors (TCRs) can discriminate between neoantigen-expressing cancer cells and self-antigen-expressing healthy tissues but have limited potency against tumors. We used a high-throughput platform to systematically evaluate the impact of co-expressing a TCR and CAR on the same CAR T cell. While strong TCR-antigen interactions enhanced CAR activation, weak TCR-antigen interactions actively antagonized their activation. Mathematical modeling captured this TCR-CAR crosstalk in CAR T cells, allowing us to engineer dual TCR/CAR T cells targeting neoantigens (HHATL8F/p53R175H) and human epithelial growth factor receptor 2 (HER2) ligands, respectively. These T cells exhibited superior anti-cancer activity and minimal toxicity against healthy tissue compared with conventional CAR T cells in a humanized solid tumor mouse model. Harnessing pre-existing inhibitory crosstalk between receptors, therefore, paves the way for the design of more precise cancer immunotherapies.

ML-enhanced peroxisome capacity enables compartmentalization of multienzyme pathway

Repurposing an organelle for specialized metabolism provides an avenue for fermentable, unicellular organisms such as Saccharomyces cerevisiae to mimic compartmentalization of metabolic pathways within different plant tissues. Peroxisomes are attractive organelles for repurposing as they are not required for yeast viability when grown on glucose and can efficiently compartmentalize heterologous enzymes to enable physical separation of cytosolic native metabolism and peroxisomal engineered metabolism. However, when not required, peroxisomes are repressed, leading to low functional capacities for heterologous proteins. Here we engineer peroxisomes with enhanced functional capacities, with the goal of compartmentalizing up to eight metabolic enzymes to enhance titers. We implement a machine learning pipeline that allows the identification of factors to overexpress, culminating in a 137% increase in peroxisome functional capacity compared to a wild-type strain. Improved pathway compartmentalization enables an 80% increase in the biosynthesis titers of the monoterpene geraniol, up to 9.5 g L-1.

Nickase fidelity drives EvolvR-mediated diversification in mammalian cells

In vivo genetic diversifiers have previously enabled efficient searches of genetic variant fitness landscapes for continuous directed evolution. However, existing genomic diversification modalities for mammalian genomic loci exclusively rely on deaminases to generate transition mutations within target loci, forfeiting access to most missense mutations. Here, we engineer CRISPR-guided error-prone DNA polymerases (EvolvR) to diversify all four nucleotides within genomic loci in mammalian cells. We demonstrate that EvolvR generates both transition and transversion mutations throughout a mutation window of at least 40 bp and implement EvolvR to evolve previously unreported drug-resistant MAP2K1 variants via substitutions not achievable with deaminases. Moreover, we discover that the nickase's mismatch tolerance limits EvolvR's mutation window and substitution biases in a gRNA-specific fashion. To compensate for gRNA-to-gRNA variability in mutagenesis, we maximize the number of gRNA target sequences by incorporating a PAM-flexible nickase into EvolvR. Finally, we find a strong correlation between predicted free energy changes underlying R-loop formation and EvolvR's performance using a given gRNA. The EvolvR system diversifies all four nucleotides to enable the evolution of mammalian cells, while nuclease and gRNA-specific properties underlying nickase fidelity can be engineered to further enhance EvolvR's mutation rates.

Chimeric antigen receptor therapies: Development, design, and implementation

Chimeric antigen receptor (CAR) T and natural killer (NK) cell therapies represent a promising strategy for the treatment of cancers and other chronic diseases. Engineered CAR constructs endow immune cells with the ability to target desired antigens with high specificity, allowing for directed responses to antigen-expressing cells. CAR T and NK cells have shown marked success in the treatment of hematologic malignancies, although there remains a large population of patients with disease that fails to respond to CAR therapies, and their efficacy in solid tumors is still limited. In this review, we provide a broad overview of the development, design, and implementation of CAR therapies from bench to bedside. We discuss the building blocks of CAR constructs and how these can be manipulated to optimize CAR functionality, review the possible sources of T and NK cells for CAR therapies, and examine the limitations of both CAR T and CAR NK cells. Finally, we discuss recent breakthroughs in the CAR field and consider how these advances may affect the success of CAR therapies in the years to come.

Immunomodulatory Effects of Curcumin on CAR T-Cell Therapy

Chimeric Antigen Receptor (CAR) T-cell therapy has revolutionized the treatment of hematological malignancies, demonstrating high efficacy in targeting and eliminating cancer cells. However, its clinical application can be associated with the risk of acute adverse effects, including cytokine release syndrome (CRS), a severe inflammatory response caused by excessive cytokine production. While anti-cytokine therapies are available to manage CRS, additional strategies are needed to optimize CAR T-cell efficacy with reduced toxicities. Curcumin, a bioactive polyphenol known for its anti-inflammatory and antioxidant properties, represents a promising adjunct for CAR T-cell therapy. In this study, we investigated the effects of curcumin on anti-CD19 CAR T-cells in vitro. Our results show that curcumin enhances the cytotoxic activity of CAR T-cells against Nalm-6, a B-cell acute lymphoblastic leukemia model, while reducing the production of pro-inflammatory cytokines, including IL-2 and IFN-γ. To explore its underlying mechanisms, network pharmacology and molecular docking analyses were performed, which revealed that curcumin interacts with key signaling pathways involved in T-cell activation and cytokine regulation. These findings support the potential of curcumin as a therapeutic adjunct to improve CAR T-cell efficacy while mitigating inflammatory toxicity.

Library-based single-cell analysis of CAR signaling reveals drivers of in vivo persistence

The anti-tumor function of engineered T cells expressing chimeric antigen receptors (CARs) is dependent on signals transduced through intracellular signaling domains (ICDs). Different ICDs are known to drive distinct phenotypes, but systematic investigations into how ICD architectures direct T cell function-particularly at the molecular level-are lacking. Here, we use single-cell sequencing to map diverse signaling inputs to transcriptional outputs, focusing on a defined library of clinically relevant ICD architectures. Informed by these observations, we functionally characterize transcriptionally distinct ICD variants across various contexts to build comprehensive maps from ICD composition to phenotypic output. We identify a unique tonic signaling signature associated with a subset of ICD architectures that drives durable in vivo persistence and efficacy in liquid, but not solid, tumors. Our findings work toward decoding CAR signaling design principles, with implications for the rational design of next-generation ICD architectures optimized for in vivo function.

Expanding the CAR toolbox with high throughput screening strategies for CAR domain exploration: a comprehensive review

Chimeric antigen receptor (CAR)-T-cell therapy has been highly successful in the treatment of B-cell hematological malignancies. CARs are modular synthetic molecules that can redirect immune cells towards target cells with antibody-like specificity. Despite their modularity, CARs used in the clinic are currently composed of a limited set of domains, mostly derived from IgG, CD8α, 4-1BB, CD28 and CD3ζ. The current low throughput CAR screening workflows are labor-intensive and time-consuming, and lie at the basis of the limited toolbox of CAR building blocks available. High throughput screening methods facilitate simultaneous investigation of hundreds of thousands of CAR domain combinations, allowing discovery of novel domains and increasing our understanding of how they behave in the context of a CAR. Here we review the growing body of reports that employ these high throughput screening and computational methods to advance CAR design. We summarize and highlight the important differences between the different studies and discuss their limitations and future considerations for further improvements. In conclusion, while still in its infancy, high throughput screening of CARs has the capacity to vastly expand the CAR domain toolbox and improve our understanding of CAR design. This knowledge could be foundational for translating CAR therapy beyond hematological malignancies and push the frontiers in personalized medicine.

Revolutionising Cancer Immunotherapy: Advancements and Prospects in Non-Viral CAR-NK Cell Engineering

The recent advancements in cancer immunotherapy have spotlighted the potential of natural killer (NK) cells, particularly chimeric antigen receptor (CAR)-transduced NK cells. These cells, pivotal in innate immunity, offer a rapid and potent response against cancer cells and pathogens without the need for prior sensitization or recognition of peptide antigens. Although NK cell genetic modification is evolving, the viral transduction method continues to be inefficient and fraught with risks, often resulting in cytotoxic outcomes and the possibility of insertional mutagenesis. Consequently, there has been a surge in the development of non-viral transfection technologies to overcome these challenges in NK cell engineering. Non-viral approaches for CAR-NK cell generation are becoming increasingly essential. Cutting-edge techniques such as trogocytosis, electroporation, lipid nanoparticle (LNP) delivery, clustered regularly interspaced short palindromic repeats-associated protein 9 (CRISPR-Cas9) gene editing and transposons not only enhance the efficiency and safety of CAR-NK cell engineering but also open new avenues for novel therapeutic possibilities. Additionally, the infusion of technologies already successful in CAR T-cell therapy into the CAR-NK paradigm holds immense potential for further advancements. In this review, we present an overview of the potential of NK cells in cancer immunotherapies, as well as non-viral transfection technologies for engineering NK cells.

Advances in CAR optimization strategies based on CD28

Chimeric antigen receptor (CAR)-T cell therapy, which utilizes genetic engineering techniques to modify T-cells to achieve specific targeting of cancer cells, has made significant breakthroughs in cancer treatment in recent years. All marketed CAR-T products are second-generation CAR-T cells containing co-stimulatory structural domains, and co-stimulatory molecules are critical for CAR-T cell activation and function. Although CD28-based co-stimulatory molecules have demonstrated potent cytotoxicity in the clinical application of CAR-T cells, they still suffer from high post-treatment relapse rates, poor efficacy durability, and accompanying severe adverse reactions. In recent years, researchers have achieved specific results in enhancing the anti-tumor function of CD28 by mutating its signaling motifs, combining the co-stimulatory structural domains, and modifying other CAR components besides co-stimulation. This paper reviewed the characteristics and roles of CD28 in CAR-T cell-mediated anti-tumor signaling and activation. We explored potential strategies to enhance CAR-T cell efficacy and reduce side effects by optimizing CD28 motifs and CAR structures, aiming to provide a theoretical basis for further clinical CAR-T cell therapy development.

Dissecting the role of CAR signaling architectures on T cell activation and persistence using pooled screens and single-cell sequencing

Chimeric antigen receptor (CAR) T cells offer a promising cancer treatment, yet challenges such as limited T cell persistence hinder efficacy. Given its critical role in modulating T cell responses, it is crucial to understand how the CAR signaling architecture influences T cell function. Here, we designed a combinatorial CAR signaling domain library and performed repeated antigen stimulation assays, pooled screens, and single-cell sequencing to systematically investigate the impact of modifying CAR signaling domains on T cell activation and persistence. Our data reveal the predominant influence of membrane-proximal domains in driving T cell phenotype. Notably, CD40 costimulation was crucial for fostering robust and lasting T cell responses. Furthermore, we correlated in vitro generated CAR T cell phenotypes with clinical outcomes in patients treated with CAR T therapy, establishing the foundation for a clinically informed screening approach. This work deepens our understanding of CAR T cell biology and may guide future CAR engineering efforts.

Pooled screening for CAR function identifies novel IL-13Rα2-targeted CARs for treatment of glioblastoma

BACKGROUND

Chimeric antigen receptor (CAR) therapies have demonstrated potent efficacy in treating B-cell malignancies, but have yet to meaningfully translate to solid tumors. Nonetheless, they are of particular interest for the treatment of glioblastoma, which is an aggressive form of brain cancer with few effective therapeutic options, due to their ability to cross the highly selective blood-brain barrier.

METHODS

Here, we use our pooled screening platform, CARPOOL, to expedite the discovery of CARs with antitumor functions necessary for solid tumor efficacy. We performed selections in primary human T cells expressing a library of 1.3×106 third generation CARs targeting IL-13Rα2, a cancer testis antigen commonly expressed in glioblastoma. Selections were performed for cytotoxicity, proliferation, memory formation, and persistence on repeated antigen challenge.

RESULTS

Each enriched CAR robustly produced the phenotype for which it was selected, and one enriched CAR triggered potent cytotoxicity and long-term proliferation on in vitro tumor rechallenge. It also showed significantly improved persistence and comparable tumor control in a microphysiological human in vitro model and a xenograft model of human glioblastoma, but also demonstrated increased off-target recognition of IL-13Rα1.

CONCLUSION

Taken together, this work demonstrates the utility of extending CARPOOL to diseases beyond hematological malignancies and represents the largest exploration of signaling combinations in human primary cells to date.

An Analysis of Monitoring Solutions for CAR T Cell Production

The chimeric antigen receptor T cell (CAR T) therapy has shown remarkable results in treating certain cancers. It involves genetically modifying a patient's T cells to recognize and attack cancer cells. Despite its potential, CAR T cell therapy is complex and costly and requires the integration of multiple technologies and specialized equipment. Further research is needed to achieve the maximum potential of CAR T cell therapies and to develop effective and efficient methods for their production. This paper presents an overview of current measurement methods used in the key steps of the production of CAR T cells. The study aims to assess the state of the art in monitoring solutions and identify their potential for online monitoring. The results of this paper contribute to the understanding of measurement methods in CAR T cell manufacturing and identify areas where on-line monitoring can be improved. Thus, this research facilitates progress toward the development of effective monitoring of CAR T cell therapies.

Applications of artificial intelligence in regenerative dentistry: promoting stem cell therapy and the scaffold development

Tissue repair represents a critical concern within the domain of dentistry. On a daily basis, countless individuals seek dental clinic services due to inadequate dental care. Many of the treatments that patients receive have unfavorable side effects. The employment of innovative methodologies, including gene therapy, tissue engineering, and stem cell (SCs) applications for regenerative purposes, has garnered significant interest over the past years. In recent times, artificial intelligence, particularly neural networks, has emerged as a topic of considerable attention among many medical professionals. Artificial intelligence possesses the capability to analyze data patterns through learning algorithms. Research opportunities in the rapidly expanding field of health sciences have been made possible by the use of artificial intelligence (AI) technologies. Though its uses are not restricted to these situations, artificial intelligence (AI) has the potential to improve and accelerate many aspects of regenerative medicine research and development, especially when working with complicated patterns. This review article is to investigate how artificial intelligence might be used to enhance regenerative processes in dentistry by using scaffolds and stem cells, in light of the continuous advances in artificial intelligence in the fields of medicine and tissue regeneration. It highlights the difficulties that still exist in this developing sector and explores the possible uses of AI with a particular emphasis on dentistry practices.

Engineering next-generation chimeric antigen receptor-T cells: recent breakthroughs and remaining challenges in design and screening of novel chimeric antigen receptor variants

Chimeric antigen receptor (CAR) T cells are a powerful treatment against hematologic cancers. The functional phenotype of a CAR-T cell is influenced by the domains that comprise the synthetic receptor. Typically, the potency of therapeutic CAR-T cell candidates is assessed by preclinical functional assays and mouse models (i.e. human tumor xenografts). However, to date, only a few sets of domains (e.g. CD8, CD28, 41BB) have been extensively tested in preclinical assays and human clinical studies. To characterize the efficiency of a CAR, different assays have been utilized to analyze T cell phenotypes, such as expansion, cytotoxicity, secretome, and persistence. However, each of these previous studies evaluated the importance of an assay differently, resulting in a wide range of functionally diverse CARs. In this review, we highlight recent (high-throughput) methods to analyze CAR domains and demonstrate their impact on inducing T cell phenotypes and activity. We also describe advances in computational methods and their potential for identifying CAR variants with enhanced properties. Finally, we reflect on the need for a standardized scoring system to support the clinical development of next-generation CARs.

IL-2-inducible T cell kinase deficiency sustains chimeric antigen receptor T cell therapy against tumor cells

Despite the revolutionary achievements of chimeric antigen receptor (CAR) T cell therapy in treating cancers, especially leukemia, several key challenges still limit its therapeutic efficacy. Of particular relevance is the relapse of cancer in large part as a result of exhaustion and short persistence of CAR-T cells in vivo. IL-2-inducible T cell kinase (ITK) is a critical modulator of the strength of T cell receptor signaling, while its role in CAR signaling is unknown. By electroporation of CRISPR-associated protein 9 (Cas9) ribonucleoprotein (RNP) complex into CAR-T cells, we successfully deleted ITK in CD19-CAR-T cells with high efficiency. Bulk and single-cell RNA sequencing analyses revealed downregulation of exhaustion and upregulation of memory gene signatures in ITK-deficient CD19-CAR-T cells. Our results further demonstrated a significant reduction of T cell exhaustion and enhancement of T cell memory, with significant improvement of CAR-T cell expansion and persistence both in vitro and in vivo. Moreover, ITK-deficient CD19-CAR-T cells showed better control of tumor relapse. Our work provides a promising strategy of targeting ITK to develop sustainable CAR-T cell products for clinical use.

Optimizing CAR-T cell therapy for solid tumors: current challenges and potential strategies

Chimeric antigen receptor (CAR)-T cell therapy demonstrates substantial efficacy in various hematological malignancies. However, its application in solid tumors is still limited. Clinical studies report suboptimal outcomes such as reduced cytotoxicity of CAR-T cells and tumor evasion, underscoring the need to address the challenges of sliding cytotoxicity in CAR-T cells. Despite improvements from fourth and next-generation CAR-T cells, new challenges include systemic toxicity from continuously secreted proteins, low productivity, and elevated costs. Recent research targets genetic modifications to boost killing potential, metabolic interventions to hinder tumor progression, and diverse combination strategies to enhance CAR-T cell therapy. Efforts to reduce the duration and cost of CAR-T cell therapy include developing allogenic and in-vivo approaches, promising significant future advancements. Concurrently, innovative technologies and platforms enhance the potential of CAR-T cell therapy to overcome limitations in treating solid tumors. This review explores strategies to optimize CAR-T cell therapies for solid tumors, focusing on enhancing cytotoxicity and overcoming application restrictions. We summarize recent advances in T cell subset selection, CAR-T structural modifications, infiltration enhancement, genetic and metabolic interventions, production optimization, and the integration of novel technologies, presenting therapeutic approaches that could improve CAR-T cell therapy's efficacy and applicability in solid tumors.

Unlocking the Gates: Therapeutic Agents for Noninvasive Drug Delivery Across the Blood-Brain Barrier

The blood-brain barrier (BBB) is a highly selective network of various cell types that acts as a filter between the blood and the brain parenchyma. Because of this, the BBB remains a major obstacle for drug delivery to the central nervous system (CNS). In recent years, there has been a focus on developing various modifiable platforms, such as monoclonal antibodies (mAbs), nanobodies (Nbs), peptides, and nanoparticles, as both therapeutic agents and carriers for targeted drug delivery to treat brain cancers and diseases. Methods for bypassing the BBB can be invasive or noninvasive. Invasive techniques, such as transient disruption of the BBB using low pulse electrical fields and intracerebroventricular infusion, lack specificity and have numerous safety concerns. In this review, we will focus on noninvasive transport mechanisms that offer high levels of biocompatibility, personalization, specificity and are regarded as generally safer than their invasive counterparts. Modifiable platforms can be designed to noninvasively traverse the BBB through one or more of the following pathways: passive diffusion through a physio-pathologically disrupted BBB, adsorptive-mediated transcytosis, receptor-mediated transcytosis, shuttle-mediated transcytosis, and somatic gene transfer. Through understanding the noninvasive pathways, new applications, including Chimeric Antigen Receptors T-cell (CAR-T) therapy, and approaches for drug delivery across the BBB are emerging.

Tumor-reactive T cell clonotype dynamics underlying clinical response to TIL therapy in melanoma

Adoptive cell therapy (ACT) using in vitro expanded tumor-infiltrating lymphocytes (TILs) has inconsistent clinical responses. To better understand determinants of therapeutic success, we tracked TIL clonotypes from baseline tumors to ACT products and post-ACT blood and tumor samples in melanoma patients using single-cell RNA and T cell receptor (TCR) sequencing. Patients with clinical responses had baseline tumors enriched in tumor-reactive TILs, and these were more effectively mobilized upon in vitro expansion, yielding products enriched in tumor-specific CD8+ cells that preferentially infiltrated tumors post-ACT. Conversely, lack of clinical responses was associated with tumors devoid of tumor-reactive resident clonotypes and with cell products mostly composed of blood-borne clonotypes that persisted in blood but not in tumors post-ACT. Upon expansion, tumor-specific TILs lost tumor-associated transcriptional signatures, including exhaustion, and responders exhibited an intermediate exhausted effector state after TIL engraftment in the tumor, suggesting functional reinvigoration. Our findings provide insight into the nature and dynamics of tumor-specific clonotypes associated with clinical response to TIL-ACT, with implications for treatment optimization.

Current landscape of mRNA technologies and delivery systems for new modality therapeutics

Realizing the immense clinical potential of mRNA-based drugs will require continued development of methods to safely deliver the bioactive agents with high efficiency and without triggering side effects. In this regard, lipid nanoparticles have been successfully utilized to improve mRNA delivery and protect the cargo from extracellular degradation. Encapsulation in lipid nanoparticles was an essential factor in the successful clinical application of mRNA vaccines, which conclusively demonstrated the technology's potential to yield approved medicines. In this review, we begin by describing current advances in mRNA modifications, design of novel lipids and development of lipid nanoparticle components for mRNA-based drugs. Then, we summarize key points pertaining to preclinical and clinical development of mRNA therapeutics. Finally, we cover topics related to targeted delivery systems, including endosomal escape and targeting of immune cells, tumors and organs for use with mRNA vaccines and new treatment modalities for human diseases.

ReCARving the future: bridging CAR T-cell therapy gaps with synthetic biology, engineering, and economic insights

Chimeric antigen receptor (CAR) T-cell therapy has revolutionized the treatment of hematologic malignancies, offering remarkable remission rates in otherwise refractory conditions. However, its expansion into broader oncological applications faces significant hurdles, including limited efficacy in solid tumors, safety concerns related to toxicity, and logistical challenges in manufacturing and scalability. This review critically examines the latest advancements aimed at overcoming these obstacles, highlighting innovations in CAR T-cell engineering, novel antigen targeting strategies, and improvements in delivery and persistence within the tumor microenvironment. We also discuss the development of allogeneic CAR T cells as off-the-shelf therapies, strategies to mitigate adverse effects, and the integration of CAR T cells with other therapeutic modalities. This comprehensive analysis underscores the synergistic potential of these strategies to enhance the safety, efficacy, and accessibility of CAR T-cell therapies, providing a forward-looking perspective on their evolutionary trajectory in cancer treatment.

AI in cellular engineering and reprogramming

During the last decade, artificial intelligence (AI) has increasingly been applied in biophysics and related fields, including cellular engineering and reprogramming, offering novel approaches to understand, manipulate, and control cellular function. The potential of AI lies in its ability to analyze complex datasets and generate predictive models. AI algorithms can process large amounts of data from single-cell genomics and multiomic technologies, allowing researchers to gain mechanistic insights into the control of cell identity and function. By integrating and interpreting these complex datasets, AI can help identify key molecular events and regulatory pathways involved in cellular reprogramming. This knowledge can inform the design of precision engineering strategies, such as the development of new transcription factor and signaling molecule cocktails, to manipulate cell identity and drive authentic cell fate across lineage boundaries. Furthermore, when used in combination with computational methods, AI can accelerate and improve the analysis and understanding of the intricate relationships between genes, proteins, and cellular processes. In this review article, we explore the current state of AI applications in biophysics with a specific focus on cellular engineering and reprogramming. Then, we showcase a couple of recent applications where we combined machine learning with experimental and computational techniques. Finally, we briefly discuss the challenges and prospects of AI in cellular engineering and reprogramming, emphasizing the potential of these technologies to revolutionize our ability to engineer cells for a variety of applications, from disease modeling and drug discovery to regenerative medicine and biomanufacturing.

In vivo manufacture and manipulation of CAR-T cells for better druggability

The current CAR-T cell therapy products have been hampered in their druggability due to the personalized preparation required, unclear pharmacokinetic characteristics, and unpredictable adverse reactions. Enabling standardized manufacturing and having clear efficacy and pharmacokinetic characteristics are prerequisites for ensuring the effective practicality of CAR-T cell therapy drugs. This review provides a broad overview of the different approaches for controlling behaviors of CAR-T cells in vivo. The utilization of genetically modified vectors enables in vivo production of CAR-T cells, thereby abbreviating or skipping the lengthy in vitro expansion process. By equipping CAR-T cells with intricately designed control elements, using molecule switches or small-molecule inhibitors, the control of CAR-T cell activity can be achieved. Moreover, the on-off control of CAR-T cell activity would yield potential gains in phenotypic remodeling. These methods provide beneficial references for the future development of safe, controllable, convenient, and suitable for standardized production of CAR-T cell therapy products.

Beyond CAR-T: The rise of CAR-NK cell therapy in asthma immunotherapy

Asthma poses a major public health burden. While existing asthma drugs manage symptoms for many, some patients remain resistant. The lack of a cure, especially for severe asthma, compels exploration of novel therapies. Cancer immunotherapy successes with CAR-T cells suggest its potential for asthma treatment. Researchers are exploring various approaches for allergic diseases including membrane-bound IgE, IL-5, PD-L2, and CTLA-4 for asthma, and Dectin-1 for fungal asthma. NK cells offer several advantages over T cells for CAR-based immunotherapy. They offer key benefits: (1) HLA compatibility, meaning they can be used in a wider range of patients without the need for matching tissue types. (2) Minimal side effects (CRS and GVHD) due to their limited persistence and cytokine profile. (3) Scalability for "off-the-shelf" production from various sources. Several strategies have been introduced that highlight the superiority and challenges of CAR-NK cell therapy for asthma treatment including IL-10, IFN-γ, ADCC, perforin-granzyme, FASL, KIR, NCRs (NKP46), DAP, DNAM-1, TGF-β, TNF-α, CCL, NKG2A, TF, and EGFR. Furthermore, we advocate for incorporating AI for CAR design optimization and CRISPR-Cas9 gene editing technology for precise gene manipulation to generate highly effective CAR constructs. This review will delve into the evolution and production of CAR designs, explore pre-clinical and clinical studies of CAR-based therapies in asthma, analyze strategies to optimize CAR-NK cell function, conduct a comparative analysis of CAR-T and CAR-NK cell therapy with their respective challenges, and finally present established novel CAR designs with promising potential for asthma treatment.

Improving chimeric antigen receptor T-cell therapies by using artificial intelligence and internet of things technologies: A narrative review

Cancer poses a formidable challenge in the field of medical science, prompting the exploration of innovative and efficient treatment strategies. One revolutionary breakthrough in cancer therapy is Chimeric Antigen Receptor (CAR) T-cell therapy, an avant-garde method involving the customization of a patient's immune cells to combat cancer. Particularly successful in addressing blood cancers, CAR T-cell therapy introduces an unprecedented level of effectiveness, offering the prospect of sustained disease management. As ongoing research advances to overcome current challenges, CAR T-cell therapy stands poised to become an essential tool in the fight against cancer. Ongoing enhancements aim to improve its effectiveness and reduce time and cost, with the integration of Artificial Intelligence (AI) and Internet of Things (IoT) technologies. The synergy of AI and IoT could enable more precise tailoring of CAR T-cell therapy to individual patients, streamlining the therapeutic process. This holds the potential to elevate treatment efficacy, mitigate adverse effects, and expedite the overall progress of CAR T-cell therapies.

Altered cancer metabolism and implications for next-generation CAR T-cell therapies

This review critically examines the evolving landscape of chimeric antigen receptor (CAR) T-cell therapy in treating solid tumors, with a particular focus on the metabolic challenges within the tumor microenvironment. CAR T-cell therapy has demonstrated remarkable success in hematologic malignancies, yet its efficacy in solid tumors remains limited. A significant barrier is the hostile milieu of the tumor microenvironment, which impairs CAR T-cell survival and function. This review delves into the metabolic adaptations of cancer cells and their impact on immune cells, highlighting the competition for nutrients and the accumulation of immunosuppressive metabolites. It also explores emerging strategies to enhance CAR T-cell metabolic fitness and persistence, including genetic engineering and metabolic reprogramming. An integrated approach, combining metabolic interventions with CAR T-cell therapy, has the potential to overcome these constraints and improve therapeutic outcomes in solid tumors.

Engineered immune cells as therapeutics for autoimmune diseases

Current treatment options for autoimmune disease (AID) are essentially immunosuppressive, inhibiting the inflammatory cascade, without curing the disease. Therapeutic monoclonal antibodies (mAbs) that target B cells showed efficacy, emphasizing the importance of B lymphocytes in autoimmune pathogenesis. Treatments that eliminate more potently B cells would open a new therapeutic era for AID. Immune cells can now be bioengineered to express constructs that enable them to specifically eradicate pathogenic B lymphocytes. Engineered immune cells (EICs) have shown therapeutic promise in both experimental models and in clinical trials in AID. Next-generation platforms are under development to optimize their specificity and improve safety. The profound and durable B cell depletion achieved reinforces the view that this biotherapeutic option holds promise for treating AID.

Deciphering the tumor immune microenvironment from a multidimensional omics perspective: insight into next-generation CAR-T cell immunotherapy and beyond

Tumor immune microenvironment (TIME) consists of intra-tumor immunological components and plays a significant role in tumor initiation, progression, metastasis, and response to therapy. Chimeric antigen receptor (CAR)-T cell immunotherapy has revolutionized the cancer treatment paradigm. Although CAR-T cell immunotherapy has emerged as a successful treatment for hematologic malignancies, it remains a conundrum for solid tumors. The heterogeneity of TIME is responsible for poor outcomes in CAR-T cell immunotherapy against solid tumors. The advancement of highly sophisticated technology enhances our exploration in TIME from a multi-omics perspective. In the era of machine learning, multi-omics studies could reveal the characteristics of TIME and its immune resistance mechanism. Therefore, the clinical efficacy of CAR-T cell immunotherapy in solid tumors could be further improved with strategies that target unfavorable conditions in TIME. Herein, this review seeks to investigate the factors influencing TIME formation and propose strategies for improving the effectiveness of CAR-T cell immunotherapy through a multi-omics perspective, with the ultimate goal of developing personalized therapeutic approaches.

A high-throughput synthetic biology approach for studying combinatorial chromatin-based transcriptional regulation

The construction of synthetic gene circuits requires the rational combination of multiple regulatory components, but predicting their behavior can be challenging due to poorly understood component interactions and unexpected emergent behaviors. In eukaryotes, chromatin regulators (CRs) are essential regulatory components that orchestrate gene expression. Here, we develop a screening platform to investigate the impact of CR pairs on transcriptional activity in yeast. We construct a combinatorial library consisting of over 1,900 CR pairs and use a high-throughput workflow to characterize the impact of CR co-recruitment on gene expression. We recapitulate known interactions and discover several instances of CR pairs with emergent behaviors. We also demonstrate that supervised machine learning models trained with low-dimensional amino acid embeddings accurately predict the impact of CR co-recruitment on transcriptional activity. This work introduces a scalable platform and machine learning approach that can be used to study how networks of regulatory components impact gene expression.

Data-driven learning of structure augments quantitative prediction of biological responses

Multi-factor screenings are commonly used in diverse applications in medicine and bioengineering, including optimizing combination drug treatments and microbiome engineering. Despite the advances in high-throughput technologies, large-scale experiments typically remain prohibitively expensive. Here we introduce a machine learning platform, structure-augmented regression (SAR), that exploits the intrinsic structure of each biological system to learn a high-accuracy model with minimal data requirement. Under different environmental perturbations, each biological system exhibits a unique, structured phenotypic response. This structure can be learned based on limited data and once learned, can constrain subsequent quantitative predictions. We demonstrate that SAR requires significantly fewer data comparing to other existing machine-learning methods to achieve a high prediction accuracy, first on simulated data, then on experimental data of various systems and input dimensions. We then show how a learned structure can guide effective design of new experiments. Our approach has implications for predictive control of biological systems and an integration of machine learning prediction and experimental design.

CAR-NKT Cells in Asthma: Use of NKT as a Promising Cell for CAR Therapy

NKT cells, unique lymphocytes bridging innate and adaptive immunity, offer significant potential for managing inflammatory disorders like asthma. Activating iNKT induces increasing IFN-γ, TGF-β, IL-2, and IL-10 potentially suppressing allergic asthma. However, their immunomodulatory effects, including granzyme-perforin-mediated cytotoxicity, and expression of TIM-3 and TRAIL warrant careful consideration and targeted approaches. Although CAR-T cell therapy has achieved remarkable success in treating certain cancers, its limitations necessitate exploring alternative approaches. In this context, CAR-NKT cells emerge as a promising approach for overcoming these challenges, potentially achieving safer and more effective immunotherapies. Strategies involve targeting distinct IgE-receptors and their interactions with CAR-NKT cells, potentially disrupting allergen-mast cell/basophil interactions and preventing inflammatory cytokine release. Additionally, targeting immune checkpoints like PDL-2, inducible ICOS, FASL, CTLA-4, and CD137 or dectin-1 for fungal asthma could further modulate immune responses. Furthermore, artificial intelligence and machine learning hold immense promise for revolutionizing NKT cell-based asthma therapy. AI can optimize CAR-NKT cell functionalities, design personalized treatment strategies, and unlock a future of precise and effective care. This review discusses various approaches to enhancing CAR-NKT cell efficacy and longevity, along with the challenges and opportunities they present in the treatment of allergic asthma.

Pooled screening for CAR function identifies novel IL13Rα2-targeted CARs for treatment of glioblastoma

Chimeric antigen receptor therapies have demonstrated potent efficacy in treating B cell malignancies, but have yet to meaningfully translate to solid tumors. Here, we utilize our pooled screening platform, CARPOOL, to expedite the discovery of CARs with anti-tumor functions necessary for solid tumor efficacy. We performed selections in primary human T cells expressing a library of 1.3×10 6 3 rd generation CARs targeting IL13Rα2, a cancer testis antigen commonly expressed in glioblastoma. Selections were performed for cytotoxicity, proliferation, memory formation, and persistence upon repeated antigen challenge. Each enriched CAR robustly produced the phenotype for which it was selected, and one enriched CAR triggered potent cytotoxicity and long-term proliferation upon in vitro tumor rechallenge. It also showed significantly improved persistence and comparable antigen-specific tumor control in a microphysiological human in vitro model and a xenograft model of human glioblastoma. Taken together, this work demonstrates the utility of extending CARPOOL to diseases beyond hematological malignancies and represents the largest exploration of signaling combinations in human primary cells to date.

Library-based single-cell analysis of CAR signaling reveals drivers of in vivo persistence

The anti-tumor function of engineered T cells expressing chimeric antigen receptors (CARs) is dependent on signals transduced through intracellular signaling domains (ICDs). Different ICDs are known to drive distinct phenotypes, but systematic investigations into how ICD architectures direct T cell function-particularly at the molecular level-are lacking. Here, we use single-cell sequencing to map diverse signaling inputs to transcriptional outputs, focusing on a defined library of clinically relevant ICD architectures. Informed by these observations, we functionally characterize transcriptionally distinct ICD variants across various contexts to build comprehensive maps from ICD composition to phenotypic output. We identify a unique tonic signaling signature associated with a subset of ICD architectures that drives durable in vivo persistence and efficacy in liquid, but not solid, tumors. Our findings work toward decoding CAR signaling design principles, with implications for the rational design of next-generation ICD architectures optimized for in vivo function.

CAR T treatment beyond cancer: Hope for immunomodulatory therapy of non-cancerous diseases

Engineering a patient's own T cells to accurately identify and eliminate cancer cells has effectively cured individuals afflicted with previously incurable hematologic cancers. These findings have stimulated research into employing chimeric antigen receptor (CAR) T therapy across various areas within the field of oncology. However, evidence from both clinical and preclinical investigations emphasize the broader potential of CAR T therapy, extending beyond oncology to address autoimmune disorders, persistent infections, cardiac fibrosis, age-related ailments and other conditions. Concurrently, the advent of novel technologies and platforms presents additional avenues for utilizing CAR T therapy in non-cancerous contexts. This review provides an overview of the rationale behind CAR T therapy, delineates ongoing challenges in its application to cancer treatment, summarizes recent findings in non-cancerous diseases, and engages in discourse regarding emerging technologies that bear relevance. The review delves into prospective applications of this therapeutic approach across a diverse range of scenarios. Lastly, the review underscores concerns related to precision and safety, while also outlining the envisioned trajectory for extending CAR T therapy beyond cancer treatment.

Making drugs from T cells: The quantitative pharmacology of engineered T cell therapeutics

Engineered T cells have emerged as highly effective treatments for hematological cancers. Hundreds of clinical programs are underway in efforts to expand the efficacy, safety, and applications of this immuno-therapeutic modality. A primary challenge in developing these "living drugs" is the complexity of their pharmacology, as the drug product proliferates, differentiates, traffics between tissues, and evolves through interactions with patient immune systems. Using publicly available clinical data from Chimeric Antigen Receptor (CAR) T cells, we demonstrate how mathematical models can be used to quantify the relationships between product characteristics, patient physiology, pharmacokinetics and clinical outcomes. As scientists work to develop next-generation cell therapy products, mathematical models will be integral for contextualizing data and facilitating the translation of product designs to clinical strategy.

Informing immunotherapy with multi-omics driven machine learning

Progress in sequencing technologies and clinical experiments has revolutionized immunotherapy on solid and hematologic malignancies. However, the benefits of immunotherapy are limited to specific patient subsets, posing challenges for broader application. To improve its effectiveness, identifying biomarkers that can predict patient response is crucial. Machine learning (ML) play a pivotal role in harnessing multi-omic cancer datasets and unlocking new insights into immunotherapy. This review provides an overview of cutting-edge ML models applied in omics data for immunotherapy analysis, including immunotherapy response prediction and immunotherapy-relevant tumor microenvironment identification. We elucidate how ML leverages diverse data types to identify significant biomarkers, enhance our understanding of immunotherapy mechanisms, and optimize decision-making process. Additionally, we discuss current limitations and challenges of ML in this rapidly evolving field. Finally, we outline future directions aimed at overcoming these barriers and improving the efficiency of ML in immunotherapy research.

Are we ready for personalized CAR-T therapy?

The future of chimeric antigen receptor T (CAR-T) therapy remains unclear. New studies are constantly being published confirming the efficacy and favorable safety profile of its innovative enhancements. Currently approved CAR-T drugs are manufactured exclusively for a specific patient from the recipient's own cells. This does not close the door to further modifications with subsequent personalization and better adaptation to the individual needs. Bringing such a drug to market would involve raising the already high costs, so it is necessary to lower the existing ones. On the other hand, so-called universal CAR-T are also getting closer to the patient's bed, but its implementation may struggle with multiple challenges, including development of graft-versus-host disease (GvHD) and alloimmunity. However, that off-the-shelf therapy could prove useful as a quick solution for patients in very poor condition or excluded from current therapy due to manufacturing limitations. The introduction of currently tested solutions may undoubtedly change the current paradigm of treatment.

De novo protein design-From new structures to programmable functions

Methods from artificial intelligence (AI) trained on large datasets of sequences and structures can now "write" proteins with new shapes and molecular functions de novo, without starting from proteins found in nature. In this Perspective, I will discuss the state of the field of de novo protein design at the juncture of physics-based modeling approaches and AI. New protein folds and higher-order assemblies can be designed with considerable experimental success rates, and difficult problems requiring tunable control over protein conformations and precise shape complementarity for molecular recognition are coming into reach. Emerging approaches incorporate engineering principles-tunability, controllability, and modularity-into the design process from the beginning. Exciting frontiers lie in deconstructing cellular functions with de novo proteins and, conversely, constructing synthetic cellular signaling from the ground up. As methods improve, many more challenges are unsolved.

"Digital twins elucidate critical role of Tscm in clinical persistence of TCR-engineered cell therapy"

Despite recent progress in adoptive T cell therapy for cancer, understanding and predicting the kinetics of infused T cells remains a challenge. Multiple factors can impact the distribution, expansion, and decay or persistence of infused T cells in patients. We have developed a novel quantitative systems pharmacology (QSP) model of TCR-transgenic T cell therapy in patients with solid tumors to describe the kinetics of endogenous T cells and multiple memory subsets of engineered T cells after infusion. These T cells undergo lymphodepletion, proliferation, trafficking, differentiation, and apoptosis in blood, lymph nodes, tumor site, and other peripheral tissues. Using the model, we generated patient-matched digital twins that recapitulate the circulating T cell kinetics reported from a clinical trial of TCR-engineered T cells targeting E7 in patients with metastatic HPV-associated epithelial cancers. Analyses of key parameters influencing cell kinetics and differences among digital twins identify stem cell-like memory T cells (Tscm) cells as an important determinant of both expansion and persistence and suggest that Tscm-related differences contribute significantly to the observed variability in cellular kinetics among patients. We simulated in silico clinical trials using digital twins and predict that Tscm enrichment in the infused product improves persistence of the engineered T cells and could enable administration of a lower dose. Finally, we verified the broader relevance of the QSP model, the digital twins, and findings on the importance of Tscm enrichment by predicting kinetics for two patients with pancreatic cancer treated with KRAS G12D targeting T cell therapy. This work offers insight into the key role of Tscm biology on T cell kinetics and provides a quantitative framework to evaluate cellular kinetics for future efforts in the development and clinical application of TCR-engineered T cell therapies.

Programmable synthetic receptors: the next-generation of cell and gene therapies

Cell and gene therapies hold tremendous promise for treating a range of difficult-to-treat diseases. However, concerns over the safety and efficacy require to be further addressed in order to realize their full potential. Synthetic receptors, a synthetic biology tool that can precisely control the function of therapeutic cells and genetic modules, have been rapidly developed and applied as a powerful solution. Delicately designed and engineered, they can be applied to finetune the therapeutic activities, i.e., to regulate production of dosed, bioactive payloads by sensing and processing user-defined signals or biomarkers. This review provides an overview of diverse synthetic receptor systems being used to reprogram therapeutic cells and their wide applications in biomedical research. With a special focus on four synthetic receptor systems at the forefront, including chimeric antigen receptors (CARs) and synthetic Notch (synNotch) receptors, we address the generalized strategies to design, construct and improve synthetic receptors. Meanwhile, we also highlight the expanding landscape of therapeutic applications of the synthetic receptor systems as well as current challenges in their clinical translation.

Broadening the horizon: potential applications of CAR-T cells beyond current indications

Engineering immune cells to treat hematological malignancies has been a major focus of research since the first resounding successes of CAR-T-cell therapies in B-ALL. Several diseases can now be treated in highly therapy-refractory or relapsed conditions. Currently, a number of CD19- or BCMA-specific CAR-T-cell therapies are approved for acute lymphoblastic leukemia (ALL), diffuse large B-cell lymphoma (DLBCL), mantle cell lymphoma (MCL), multiple myeloma (MM), and follicular lymphoma (FL). The implementation of these therapies has significantly improved patient outcome and survival even in cases with previously very poor prognosis. In this comprehensive review, we present the current state of research, recent innovations, and the applications of CAR-T-cell therapy in a selected group of hematologic malignancies. We focus on B- and T-cell malignancies, including the entities of cutaneous and peripheral T-cell lymphoma (T-ALL, PTCL, CTCL), acute myeloid leukemia (AML), chronic myeloid leukemia (CML), chronic lymphocytic leukemia (CLL), classical Hodgkin-Lymphoma (HL), Burkitt-Lymphoma (BL), hairy cell leukemia (HCL), and Waldenström's macroglobulinemia (WM). While these diseases are highly heterogenous, we highlight several similarly used approaches (combination with established therapeutics, target depletion on healthy cells), targets used in multiple diseases (CD30, CD38, TRBC1/2), and unique features that require individualized approaches. Furthermore, we focus on current limitations of CAR-T-cell therapy in individual diseases and entities such as immunocompromising tumor microenvironment (TME), risk of on-target-off-tumor effects, and differences in the occurrence of adverse events. Finally, we present an outlook into novel innovations in CAR-T-cell engineering like the use of artificial intelligence and the future role of CAR-T cells in therapy regimens in everyday clinical practice.

A synthetic biology approach to engineering circuits in immune cells

A synthetic circuit in a biological system involves the designed assembly of genetic elements, biomolecules, or cells to create a defined function. These circuits are central in synthetic biology, enabling the reprogramming of cellular behavior and the engineering of cells with customized responses. In cancer therapeutics, engineering T cells with circuits have the potential to overcome the challenges of current approaches, for example, by allowing specific recognition and killing of cancer cells. Recent advances also facilitate engineering integrated circuits for the controlled release of therapeutic molecules at specified locations, for example, in a solid tumor. In this review, we discuss recent strategies and applications of synthetic receptor circuits aimed at enhancing immune cell functions for cancer immunotherapy. We begin by introducing the concept of circuits in networks at the molecular and cellular scales and provide an analysis of the development and implementation of several synthetic circuits in T cells that have the goal to overcome current challenges in cancer immunotherapy. These include specific targeting of cancer cells, increased T-cell proliferation, and persistence in the tumor microenvironment. By harnessing the power of synthetic biology, and the characteristics of certain circuit architectures, it is now possible to engineer a new generation of immune cells that recognize cancer cells, while minimizing off-target toxicities. We specifically discuss T-cell circuits for antigen density sensing. These circuits allow targeting of solid tumors that share antigens with normal tissues. Additionally, we explore designs for synthetic circuits that could control T-cell differentiation or T-cell fate as well as the concept of synthetic multicellular circuits that leverage cellular communication and division of labor to achieve improved therapeutic efficacy. As our understanding of cell biology expands and novel tools for genome, protein, and cell engineering are developed, we anticipate further innovative approaches to emerge in the design and engineering of circuits in immune cells.

Toward the clinical development of synthetic immunity to cancer

Synthetic biology (synbio) tools, such as chimeric antigen receptors (CARs), have been designed to target, activate, and improve immune cell responses to tumors. These therapies have demonstrated an ability to cure patients with blood cancers. However, there are significant challenges to designing, testing, and efficiently translating these complex cell therapies for patients who do not respond or have immune refractory solid tumors. The rapid progress of synbio tools for cell therapy, particularly for cancer immunotherapy, is encouraging but our development process should be tailored to increase translational success. Particularly, next-generation cell therapies should be rooted in basic immunology, tested in more predictive preclinical models, engineered for potency with the right balance of safety, educated by clinical findings, and multi-faceted to combat a range of suppressive mechanisms. Here, we lay out five principles for engineering future cell therapies to increase the probability of clinical impact, and in the context of these principles, we provide an overview of the current state of synbio cell therapy design for cancer. Although these principles are anchored in engineering immune cells for cancer therapy, we posit that they can help guide translational synbio research for broad impact in other disease indications with high unmet need.

Arming CAR-T cells with cytokines and more: Innovations in the fourth-generation CAR-T development

Chimeric antigen receptor T cells (CAR-T) therapy has shown great potential in tumor treatment. However, many factors impair the efficacy of CAR-T therapy, such as antigenic heterogeneity and loss, limited potency and persistence, poor infiltration capacity, and a suppressive tumor microenvironment. To overcome these obstacles, recent studies have reported a new generation of CAR-T cells expressing cytokines called armored CAR-T, TRUCK-T, or the fourth-generation CAR-T. Here we summarize the strategies of arming CAR-T cells with natural or synthetic cytokine signals to enhance their anti-tumor capacity. Moreover, we summarize the advances in CAR-T cells expressing non-cytokine proteins, such as membrane receptors, antibodies, enzymes, co-stimulatory molecules, and transcriptional factors. Furthermore, we discuss several prospective strategies for armored CAR-T therapy development. Altogether, these ideas may provide new insights for the innovations of the next-generation CAR-T therapy.

Coengineering specificity, safety, and function into T cells for cancer immunotherapy

Adoptive T-cell transfer (ACT) therapies, including of tumor infiltrating lymphocytes (TILs) and T cells gene-modified to express either a T cell receptor (TCR) or a chimeric antigen receptor (CAR), have demonstrated clinical efficacy for a proportion of patients and cancer-types. The field of ACT has been driven forward by the clinical success of CD19-CAR therapy against various advanced B-cell malignancies, including curative responses for some leukemia patients. However, relapse remains problematic, in particular for lymphoma. Moreover, for a variety of reasons, relative limited efficacy has been demonstrated for ACT of non-hematological solid tumors. Indeed, in addition to pre-infusion challenges including lymphocyte collection and manufacturing, ACT failure can be attributed to several biological processes post-transfer including, (i) inefficient tumor trafficking, infiltration, expansion and retention, (ii) chronic antigen exposure coupled with insufficient costimulation resulting in T-cell exhaustion, (iii) a range of barriers in the tumor microenvironment (TME) mediated by both tumor cells and suppressive immune infiltrate, (iv) tumor antigen heterogeneity and loss, or down-regulation of antigen presentation machinery, (v) gain of tumor intrinsic mechanisms of resistance such as to apoptosis, and (vi) various forms of toxicity and other adverse events in patients. Affinity-optimized TCRs can improve T-cell function and innovative CAR designs as well as gene-modification strategies can be used to coengineer specificity, safety, and function into T cells. Coengineering strategies can be designed not only to directly support the transferred T cells, but also to block suppressive barriers in the TME and harness endogenous innate and adaptive immunity. Here, we review a selection of the remarkable T-cell coengineering strategies, including of tools, receptors, and gene-cargo, that have been developed in recent years to augment tumor control by ACT, more and more of which are advancing to the clinic.

Harnessing the power of artificial intelligence to advance cell therapy

Cell therapies are powerful technologies in which human cells are reprogrammed for therapeutic applications such as killing cancer cells or replacing defective cells. The technologies underlying cell therapies are increasing in effectiveness and complexity, making rational engineering of cell therapies more difficult. Creating the next generation of cell therapies will require improved experimental approaches and predictive models. Artificial intelligence (AI) and machine learning (ML) methods have revolutionized several fields in biology including genome annotation, protein structure prediction, and enzyme design. In this review, we discuss the potential of combining experimental library screens and AI to build predictive models for the development of modular cell therapy technologies. Advances in DNA synthesis and high-throughput screening techniques enable the construction and screening of libraries of modular cell therapy constructs. AI and ML models trained on this screening data can accelerate the development of cell therapies by generating predictive models, design rules, and improved designs.

Refining chimeric antigen receptors via barcoded protein domain combination pooled screening

Chimeric antigen receptor (CAR)-T cells represent a promising frontier in cancer immunotherapy. However, the current process for developing new CAR constructs is time consuming and inefficient. To address this challenge and expedite the evaluation and comparison of full-length CAR designs, we have devised a novel cloning strategy. This strategy involves the sequential assembly of individual CAR domains using blunt ligation, with each domain being assigned a unique DNA barcode. Applying this method, we successfully generated 360 CAR constructs that specifically target clinically validated tumor antigens CD19 and GD2. By quantifying changes in barcode frequencies through next-generation sequencing, we characterize CARs that best mediate proliferation and expansion of transduced T cells. The screening revealed a crucial role for the hinge domain in CAR functionality, with CD8a and IgG4 hinges having opposite effects in the surface expression, cytokine production, and antitumor activity in CD19- versus GD2-based CARs. Importantly, we discovered two novel CD19-CAR architectures containing the IgG4 hinge domain that mediate superior in vivo antitumor activity compared with the construct used in Kymriah, a U.S. Food and Drug Administration (FDA)-approved therapy. This novel screening approach represents a major advance in CAR engineering, enabling accelerated development of cell-based cancer immunotherapies.

In vitro re-challenge of CAR T cells

Chimeric antigen receptor (CAR) T cells (CAR T) have emerged as a potential therapy for cancer patients. CAR T cells are capable of recognizing membrane proteins on cancer cells which initiates a downstream signaling in T cells that ends in cancer cell death. Continuous antigen exposure over time, activation of inhibitory signaling pathways and/or chronic inflammation can lead to CAR T cell exhaustion. In this context, the design of CARs can have a great impact on the functionality of CAR T cells, on their potency and exhaustion. Here, using CD19CAR as model, we provide a re-challenge protocol where CAR T cells are cultured weekly with malignant lymphoid cell lines BL-41 and Nalm-6 to simulate them with continuous antigen pressure over a four-week period. This protocol can be value for assessing CAR T cell functionality and for the comparison of different CAR constructs.

Engineering enhanced chimeric antigen receptor-T cell therapy for solid tumors

The early clinical success and subsequent US Food and Drug Administration approval of chimeric antigen receptor (CAR)-T cell therapy for leukemia and lymphoma affirm that engineered T cells can be a powerful treatment for hematologic malignancies. Yet this success has not been replicated in solid tumors. Numerous challenges emerged from clinical experience and well-controlled preclinical animal models must be met to enable safe and efficacious CAR-T cell therapy in solid tumors. Here, we review recent advances in bioengineering strategies developed to enhance CAR-T cell therapy in solid tumors, focusing on targeted single-gene perturbation, genetic circuits design, cytokine engineering, and interactive biomaterials. These bioengineering approaches present a unique set of tools that synergize with CAR-T cells to overcome obstacles in solid tumors and achieve robust and long-lasting therapeutic efficacy.