Killer fatigue: Transition to NK-cell-like phenotype is a signature of CAR-T cell exhaustion.

Exhaustion of chimeric antigen receptor (CAR)-T cells hinders their therapeutic efficacy, especially in treating solid tumors. In this issue of Cell, Good et al. develop an in vitro model of antigen-driven CAR-T cell exhaustion to characterize signatures of dysfunction, including a transition to a natural killer (NK)-like phenotype, and suggest new gene targets to prevent exhaustion.

Increasing T Cell Versatility with SUPRA CARs.

Chimeric antigen receptor (CAR) T cells offer a promising treatment option for advanced cancers resistant to standard therapy. Here, Cho et al. report a split-CAR design that enables the engineering of multi-feature CAR-T cells, aiming to address current challenges limiting the safety and efficacy of CAR-T cells for cancer treatment.

Perception and Memory Reinstatement Engage Overlapping Face-Selective Regions within Human Ventral Temporal Cortex.

Humans have the remarkable ability to vividly retrieve sensory details of past events. According to the theory of sensory reinstatement, during remembering, brain regions specialized for processing specific sensory stimuli are reactivated to support content-specific retrieval. Recently, several studies have emphasized transformations in the spatial organization of these reinstated activity patterns. Specifically, studies of scene stimuli suggest a clear anterior shift in the location of retrieval activations compared with the activity observed during perception. However, it is not clear that such transformations occur universally, with inconsistent evidence for other important stimulus categories, particularly faces. One challenge in addressing this question is the careful delineation of face-selective cortices, which are interdigitated with other selective regions, in configurations that spatially differ across individuals. Therefore, we conducted a multisession neuroimaging study to first carefully map individual participants' (nine males and seven females) face-selective regions within ventral temporal cortex (VTC), followed by a second session to examine the activity patterns within these regions during face memory encoding and retrieval. While face-selective regions were expectedly engaged during face perception at encoding, memory retrieval engagement exhibited a more selective and constricted reinstatement pattern within these regions, but did not show any consistent direction of spatial transformation (e.g., anteriorization). We also report on unique human intracranial recordings from VTC under the same experimental conditions. These findings highlight the importance of considering the complex configuration of category-selective cortex in elucidating principles shaping the neural transformations that occur from perception to memory.

Successes and challenges in clinical gene therapy.

Despite the ups and downs in the field over three decades, the science of gene therapy has continued to advance and provide enduring treatments for increasing number of diseases. There are active clinical trials approaching a variety of inherited and acquired disorders of different organ systems. Approaches include ex vivo modification of hematologic stem cells (HSC), T lymphocytes and other immune cells, as well as in vivo delivery of genes or gene editing reagents to the relevant target cells by either local or systemic administration. In this article, we highlight success and ongoing challenges in three areas of high activity in gene therapy: inherited blood cell diseases by targeting hematopoietic stem cells, malignant disorders using immune effector cells genetically modified with chimeric antigen receptors, and ophthalmologic, neurologic, and coagulation disorders using in vivo administration of adeno-associated virus (AAV) vectors. In recent years, there have been true cures for many of these diseases, with sustained clinical benefit that exceed those from other medical approaches. Each of these treatments faces ongoing challenges, namely their high one-time costs and the complexity of manufacturing the therapeutic agents, which are biological viruses and cell products, at pharmacologic standards of quality and consistency. New models of reimbursement are needed to make these innovative treatments widely available to patients in need.

Handedness effects on imagery of dominant- versus non-dominant-hand movements: An electroencephalographic investigation.

Mental representations of our bodies are thought to influence how we interact with our surroundings. We can examine these mental representations through motor imagery, the imagination of movement using scalp EEG recordings. The visual modality of motor imagery emphasises 'seeing' the imagined movement and is associated with increased activity in the alpha rhythm (8-14 Hz) measured over the occipital regions. The kinaesthetic modality emphasises 'feeling' the movement and is associated with decreased activity in the mu rhythm (8-14 Hz) measured over the sensorimotor cortices. These two modalities can be engaged in isolation or together. We recorded EEG activity while 37 participants (17 left-hand dominant) completed an objective hand motor imagery task. Left-handers exhibited significant activity differences between occipital and motor regions only during imagery of right-hand (non-dominant-hand) movements. This difference was primarily driven by less oscillatory activity in the mu rhythm, which may reflect a shift in imagery strategy wherein participants placed more effort into generating the kinaesthetic sensations of non-dominant-hand imagery. Spatial features of 8-14 Hz activity generated from principal component analysis (PCA) provide further support for a strategy shift. Right-handers also exhibited significant differences between alpha and mu activity during imagery of non-dominant movements. However, this difference was not primarily driven by either rhythm, and no differences were observed in the group's PCA results. Together, these findings indicate that individuals imagine movement differently when it involves their dominant versus non-dominant hand, and left-handers may be more flexible in their motor imagery strategies.

Imagery-based strategies for memory for associations.

Cued recall of word pairs is improved by asking participants to combine items in an interactive image. Meanwhile, interactive images facilitate serial-recall (Link Method), but even better when each item is imagined alongside a previously learned peg-word (Peg List Method). We asked if a peg system could support memory for pairs, hypothesising it would outperform interactive imagery. Tested with cued recall, five study strategies were manipulated between-subjects, across two experiments: (1) Both words linked to one peg; (2) Each word linked to a different peg; (3) Peg list method but studying as a serial list; (4) Interactive imagery (within-pairs); (5) Link Method. Participants were able to apply peg-list strategies to pairs, as anticipated by mathematical modelling. Error-patterns spoke to mathematical models; peg lists exhibited distance-based confusability, characteristic of positional-coding models, and errors tended to preserve within-pair position, even for inter-item associative strategies, suggesting models of association should incorporate position. However, the peg list strategies came with a speed-accuracy tradeoff and did not challenge the superiority of the interactive imagery strategy. Without extensive practice with peg list strategies, interactive imagery remains superior for associations. Peg strategies may excel instead in tasks that primarily test serial order or with extensive training.

Predicting memory from study-related brain activity.

To isolate brain activity that may reflect effective cognitive processes during the study phase of a memory task, cognitive neuroscientists commonly contrast brain activity during study of later-remembered versus later-forgotten items. This "subsequent memory effect" method has been described as identifying brain activity "predictive" of memory outcome. However, the modern field of machine learning distinguishes between descriptive analysis, subject to overfitting, and true prediction, that can classify untrained data. First, we tested whether classic event-related potential signals were, in fact, predictive of later old/new recognition memory (N = 62, 225 items/participant); this produced significant but small predictive success. Next, pattern classification of the multivariate spatiotemporal features of the single-trial EEG waveform also succeeded in predicting memory. However, the prediction was still small in magnitude. In addition, topographic maps suggested individual differences in sources of predictive activity. These findings suggest that, on average, brain activity, measured by EEG, during the study phase is only marginally predictive of subsequent memory. It is possible that this predictive approach will succeed better when other experimental factors known to influence memory outcome are also integrated into the models.NEW & NOTEWORTHY For both basic and applied reasons, an important goal is to identify brain activity present while people study materials that enable us to predict whether they will remember those materials. We show that this is possible with the conventional event-related potential "subsequent-memory-effect" signals as well as with machine learning classifiers, but only to a small degree. This is in line with behavioral research, which supports many determinants of memory apart from the cognitive processes during study.

Rewiring T-cell responses to soluble factors with chimeric antigen receptors.

Chimeric antigen receptor (CAR)-expressing T cells targeting surface-bound tumor antigens have yielded promising clinical outcomes, with two CD19 CAR-T cell therapies recently receiving FDA approval for the treatment of B-cell malignancies. The adoption of CARs for the recognition of soluble ligands, a distinct class of biomarkers in physiology and disease, could considerably broaden the utility of CARs in disease treatment. In this study, we demonstrate that CAR-T cells can be engineered to respond robustly to diverse soluble ligands, including the CD19 ectodomain, GFP variants, and transforming growth factor beta (TGF-ß). We additionally show that CAR signaling in response to soluble ligands relies on ligand-mediated CAR dimerization and that CAR responsiveness to soluble ligands can be fine-tuned by adjusting the mechanical coupling between the CAR's ligand-binding and signaling domains. Our results support a role for mechanotransduction in CAR signaling and demonstrate an approach for systematically engineering immune-cell responses to soluble, extracellular ligands.

Regulation of T cell proliferation with drug-responsive microRNA switches.

As molecular and cellular therapies advance in the clinic, the role of genetic regulation is becoming increasingly important for controlling therapeutic potency and safety. The emerging field of mammalian synthetic biology provides promising tools for the construction of regulatory platforms that can intervene with endogenous pathways and control cell behavior. Recent work has highlighted the development of synthetic biological systems that integrate sensing of molecular signals to regulated therapeutic function in various disease settings. However, the toxicity and limited dosing of currently available molecular inducers have largely inhibited translation to clinical settings. In this work, we developed synthetic microRNA-based genetic systems that are controlled by the pharmaceutical drug leucovorin, which is readily available and safe for prolonged administration in clinical settings. We designed microRNA switches to target endogenous cytokine receptor subunits (IL-2Rß and γc) that mediate various signaling pathways in T cells. We demonstrate the function of these control systems by effectively regulating T cell proliferation with the drug input. Each control system produced unique functional responses, and combinatorial targeting of multiple receptor subunits exhibited greater repression of cell growth. This work highlights the potential use of drug-responsive genetic control systems to improve the management and safety of cellular therapeutics.

Efficient Gene Editing in Primary Human T Cells.

Recent advances in T-cell therapy for cancer, viral infections, and autoimmune diseases highlight the broad therapeutic potential of T-cell engineering. However, site-specific genetic manipulation in primary human T cells remains challenging. Two recent studies describe efficient genome editing in T cells using CRISPR and TALEN approaches.

Synthetic biology advances and applications in the biotechnology industry: a perspective.

Synthetic biology is a logical extension of what has been called recombinant DNA (rDNA) technology or genetic engineering since the 1970s. As rDNA technology has been the driver for the development of a thriving biotechnology industry today, starting with the commercialization of biosynthetic human insulin in the early 1980s, synthetic biology has the potential to take the industry to new heights in the coming years. Synthetic biology advances have been driven by dramatic cost reductions in DNA sequencing and DNA synthesis; by the development of sophisticated tools for genome editing, such as CRISPR/Cas9; and by advances in informatics, computational tools, and infrastructure to facilitate and scale analysis and design. Synthetic biology approaches have already been applied to the metabolic engineering of microorganisms for the production of industrially important chemicals and for the engineering of human cells to treat medical disorders. It also shows great promise to accelerate the discovery and development of novel secondary metabolites from microorganisms through traditional, engineered, and combinatorial biosynthesis. We anticipate that synthetic biology will continue to have broadening impacts on the biotechnology industry to address ongoing issues of human health, world food supply, renewable energy, and industrial chemicals and enzymes.

Rhythmic Activity and Individual Variability in Recognition Memory: Theta Oscillations Correlate with Performance whereas Alpha Oscillations Correlate with ERPs.

During study trials of a recognition memory task, alpha (∼10 Hz) oscillations decrease, and concurrently, theta (4-8 Hz) oscillations increase when later memory is successful versus unsuccessful (subsequent memory effect). Likewise, at test, reduced alpha and increased theta activity are associated with successful memory (retrieval success effect). Here we take an individual-differences approach to test three hypotheses about theta and alpha oscillations in verbal, old/new recognition, measuring the difference in oscillations between hit trials and miss trials. First, we test the hypothesis that theta and alpha oscillations have a moderately mutually exclusive relationship; but no support for this hypothesis was found. Second, we test the hypothesis that theta oscillations explain not only memory effects within participants, but also individual differences. Supporting this prediction, durations of theta (but not alpha) oscillations at study and at test correlated significantly with d' across participants. Third, we test the hypothesis that theta and alpha oscillations reflect familiarity and recollection processes by comparing oscillation measures to ERPs that are implicated in familiarity and recollection. The alpha-oscillation effects correlated with some ERP measures, but inversely, suggesting that the actions of alpha oscillations on memory processes are distinct from the roles of familiarity- and recollection-linked ERP signals. The theta-oscillation measures, despite differentiating hits from misses, did not correlate with any ERP measure; thus, theta oscillations may reflect elaborative processes not tapped by recollection-related ERPs. Our findings are consistent with alpha oscillations reflecting visual inattention, which can modulate memory, and with theta oscillations supporting recognition memory in ways that complement the most commonly studied ERPs.

Identification and selective expansion of functionally superior T cells expressing chimeric antigen receptors.

BACKGROUND: T cells expressing chimeric antigen receptors (CARs) have shown exciting promise in cancer therapy, particularly in the treatment of B-cell malignancies. However, optimization of CAR-T cell production remains a trial-and-error exercise due to a lack of phenotypic benchmarks that are clearly predictive of anti-tumor functionality. A close examination of the dynamic changes experienced by CAR-T cells upon stimulation can improve understanding of CAR-T-cell biology and identify potential points for optimization in the production of highly functional T cells. METHODS: Primary human T cells expressing a second-generation, anti-CD19 CAR were systematically examined for changes in phenotypic and functional responses to antigen exposure over time. Multi-color flow cytometry was performed to quantify dynamic changes in CAR-T cell viability, proliferation, as well as expression of various activation and exhaustion markers in response to varied antigen stimulation conditions. RESULTS: Stimulated CAR-T cells consistently bifurcate into two distinct subpopulations, only one of which (CAR(hi)/CD25(+)) exhibit anti-tumor functions. The use of central memory T cells as the starting population and the resilience-but not antigen density-of antigen-presenting cells used to expand CAR-T cells were identified as critical parameters that augment the production of functionally superior T cells. We further demonstrate that the CAR(hi)/CD25(+) subpopulation upregulates PD-1 but is resistant to PD-L1-induced dysfunction. CONCLUSIONS: CAR-T cells expanded ex vivo for adoptive T-cell therapy undergo dynamic phenotypic changes during the expansion process and result in two distinct populations with dramatically different functional capacities. Significant and sustained CD25 and CAR expression upregulation is predictive of robust anti-tumor functionality in antigen-stimulated T cells, despite their correlation with persistent PD-1 upregulation. The functionally superior subpopulation can be selectively augmented by careful calibration of antigen stimulation and the enrichment of central memory T-cell type.

Is what goes in what comes out? Encoding and retrieval event-related potentials together determine memory outcome.

Understanding memory function amounts to identifying how events (cognitive and neural) at study eventually influence events at test. Many of the proposed cognitive correlates of memory-related event-related potentials (ERPs) at study resemble proposed cognitive correlates of other memory-related ERPs, recorded at test. We wondered whether a given known ERP feature at study might in fact reflect an effective-encoding process that is, in turn, tapped by another specific ERP feature, recorded at test. To this end, we asked which pairs of known memory-related ERP features explain common variance across a large sample of participants, while they perform a word-recognition task. Two early ERP features, the Late Positive Component (study) and the FN400 (test), covaried significantly. These features also correlated with memory success (d' and response time). Two later ERP features, the Slow Wave (study) and the Late Parietal Positivity (test), also covaried when lures were incorporated into the analysis. Interestingly, these later features were uncorrelated with memory outcome. This novel approach, exploiting naturally occurring subject variability (in strategy and ERP amplitudes), informs our understanding of the memory functions of ERP features in several ways. Specifically, they strengthen the argument that the earlier ERP features may drive old/new recognition (but perhaps not the later features). Our findings suggest the Late Positive Component at study, in some degree, may cause the FN400 to increase at test, together producing effective recognition memory. The Slow Wave at study appears to relate the Left Parietal Positivity at test, but these may play roles in more complex memory judgments and may be less critical for simple old/new recognition.

CAR-T cell manufacturing: Major process parameters and next-generation strategies.

Chimeric antigen receptor (CAR)-T cell therapies have demonstrated strong curative potential and become a critical component in the array of B-cell malignancy treatments. Successful deployment of CAR-T cell therapies to treat hematologic and solid cancers, as well as other indications such as autoimmune diseases, is dependent on effective CAR-T cell manufacturing that impacts not only product safety and efficacy but also overall accessibility to patients in need. In this review, we discuss the major process parameters of autologous CAR-T cell manufacturing, as well as regulatory considerations and ongoing developments that will enable the next generation of CAR-T cell therapies.

Extracellular domains of CARs reprogramme T cell metabolism without antigen stimulation.

Metabolism is an indispensable part of T cell proliferation, activation and exhaustion, yet the metabolism of chimeric antigen receptor (CAR)-T cells remains incompletely understood. CARs are composed of extracellular domains-often single-chain variable fragments (scFvs)-that determine ligand specificity and intracellular domains that trigger signalling following antigen binding. Here, we show that CARs differing only in the scFv variously reprogramme T cell metabolism. Even without exposure to antigens, some CARs increase proliferation and nutrient uptake in T cells. Using stable isotope tracers and mass spectrometry, we observed basal metabolic fluxes through glycolysis doubling and amino acid uptake overtaking anaplerosis in CAR-T cells harbouring a rituximab scFv, unlike other similar anti-CD20 scFvs. Disparate rituximab and 14G2a-based anti-GD2 CAR-T cells are similarly hypermetabolic and channel excess nutrients to nitrogen overflow metabolism. Modest overflow metabolism of CAR-T cells and metabolic compatibility between cancer cells and CAR-T cells are identified as features of efficacious CAR-T cell therapy.

Self-regulating CAR-T cells modulate cytokine release syndrome in adoptive T-cell therapy.

Cytokine release syndrome (CRS) is a frequently observed side effect of chimeric antigen receptor (CAR)-T cell therapy. Here, we report self-regulating T cells that reduce CRS severity by secreting inhibitors of cytokines associated with CRS. With a humanized NSG-SGM3 mouse model, we show reduced CRS-related toxicity in mice treated with CAR-T cells secreting tocilizumab-derived single-chain variable fragment (Toci), yielding a safety profile superior to that of single-dose systemic tocilizumab administration. Unexpectedly, Toci-secreting CD19 CAR-T cells exhibit superior in vivo antitumor efficacy compared with conventional CD19 CAR-T cells. scRNA-seq analysis of immune cells recovered from tumor-bearing humanized mice revealed treatment with Toci-secreting CD19 CAR-T cells enriches for cytotoxic T cells while retaining memory T-cell phenotype, suggesting Toci secretion not only reduces toxicity but also significantly alters the overall T-cell composition. This approach of engineering T cells to self-regulate inflammatory cytokine production is a clinically compatible strategy with the potential to simultaneously enhance safety and efficacy of CAR-T cell therapy for cancer.

A yeast-based rapid prototype platform for gene control elements in mammalian cells.

Programming genetic circuits in mammalian cells requires flexible, tunable, and user-tailored gene-control systems. However, most existing control systems are either mechanistically specific for microbial organisms or must be laboriously re-engineered to function in mammalian cells. Here, we demonstrate a ribozyme-based device platform that can be directly transported from yeast to mammalian cells in a "plug-and-play" manner. Ribozyme switches previously prototyped in yeast are shown to regulate gene expression in a predictable, ligand-responsive manner in human HEK 293, HeLa, and U2OS cell lines without any change to device sequence nor further optimization. The ribozyme-based devices, which exhibit activation ratios comparable to the best RNA-based regulatory devices demonstrated in mammalian cells to-date, retain their prescribed functions (ON or OFF switch), tunability of regulatory stringency, and responsiveness to different small-molecule inputs in mammalian hosts. Furthermore, we observe strong correlations of device performance between yeast and all mammalian cell lines tested (R(2) = 0.63-0.97). Our unique device architecture can therefore act as a rapid prototyping platform (RPP) based on a yeast chassis, providing a well-developed and genetically tractable system that supports rapid and high-throughput screens for generating gene-controllers with a broad range of functions in mammalian cells. This platform will accelerate development of mammalian gene-controllers for diverse applications, including cell-based therapeutics and cell-fate reprogramming.

Design of small molecule-responsive microRNAs based on structural requirements for Drosha processing.

MicroRNAs (miRNAs) are prevalent regulatory RNAs that mediate gene silencing and play key roles in diverse cellular processes. While synthetic RNA-based regulatory systems that integrate regulatory and sensing functions have been demonstrated, the lack of detail on miRNA structure-function relationships has limited the development of integrated control systems based on miRNA silencing. Using an elucidated relationship between Drosha processing and the single-stranded nature of the miRNA basal segments, we developed a strategy for designing ligand-responsive miRNAs. We demonstrate that ligand binding to an aptamer integrated into the miRNA basal segments inhibits Drosha processing, resulting in titratable control over gene silencing. The generality of this control strategy was shown for three aptamer-small molecule ligand pairs. The platform can be extended to the design of synthetic miRNAs clusters, cis-acting miRNAs and self-targeting miRNAs that act both in cis and trans, enabling fine-tuning of the regulatory strength and dynamics. The ability of our ligand-responsive miRNA platform to respond to user-defined inputs, undergo regulatory performance tuning and display scalable combinatorial control schemes will help advance applications in biological research and applied medicine.

Genetic control of mammalian T-cell proliferation with synthetic RNA regulatory systems.

RNA molecules perform diverse regulatory functions in natural biological systems, and numerous synthetic RNA-based control devices that integrate sensing and gene-regulatory functions have been demonstrated, predominantly in bacteria and yeast. Despite potential advantages of RNA-based genetic control strategies in clinical applications, there has been limited success in extending engineered RNA devices to mammalian gene-expression control and no example of their application to functional response regulation in mammalian systems. Here we describe a synthetic RNA-based regulatory system and its application in advancing cellular therapies by linking rationally designed, drug-responsive, ribozyme-based regulatory devices to growth cytokine targets to control mouse and primary human T-cell proliferation. We further demonstrate the ability of our synthetic controllers to effectively modulate T-cell growth rate in response to drug input in vivo. Our RNA-based regulatory system exhibits unique properties critical for translation to therapeutic applications, including adaptability to diverse ligand inputs and regulatory targets, tunable regulatory stringency, and rapid response to input availability. By providing tight gene-expression control with customizable ligand inputs, RNA-based regulatory systems can greatly improve cellular therapies and advance broad applications in health and medicine.