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T cell receptors (TCRs) enable T cells to specifically recognize mutations in cancer cells 1 – 3 . Here we developed a clinical-grade approach based on CRISPR–Cas9 non-viral precision genome-editing to simultaneously knockout the two endogenous TCR genes TRAC (which encodes TCRα) and TRBC (which encodes TCRβ). We also inserted into the TRAC locus two chains of a neoantigen-specific TCR (neoTCR) isolated from circulating T cells of patients. The neoTCRs were isolated using a personalized library of soluble predicted neoantigen–HLA capture reagents. Sixteen patients with different refractory solid cancers received up to three distinct neoTCR transgenic cell products. Each product expressed a patient-specific neoTCR and was administered in a cell-dose-escalation, first-in-human phase I clinical trial ( NCT03970382 ). One patient had grade 1 cytokine release syndrome and one patient had grade 3 encephalitis. All participants had the expected side effects from the lymphodepleting chemotherapy. Five patients had stable disease and the other eleven had disease progression as the best response on the therapy. neoTCR transgenic T cells were detected in tumour biopsy samples after infusion at frequencies higher than the native TCRs before infusion. This study demonstrates the feasibility of isolating and cloning multiple TCRs that recognize mutational neoantigens. Moreover, simultaneous knockout of the endogenous TCR and knock-in of neoTCRs using single-step, non-viral precision genome-editing are achieved. The manufacture of neoTCR engineered T cells at clinical grade, the safety of infusing up to three gene-edited neoTCR T cell products and the ability of the transgenic T cells to traffic to the tumours of patients are also demonstrated. A first-in-human phase I clinical trial demonstrates the feasibility and safety of non-viral precision genome-engineering of a personalized adoptive cell transfer anticancer therapeutic.

A patient with progressive metastatic pancreatic cancer was treated with a single infusion of 16.2×10 9 autologous T cells that had been genetically engineered to clonally express two allogeneic HLA-C*08:02–restricted T-cell receptors (TCRs) targeting mutant KRAS G12D expressed by the tumors. The patient had regression of visceral metastases (overall partial response of 72% according to the Response Evaluation Criteria in Solid Tumors, version 1.1); the response was ongoing at 6 months. The engineered T cells constituted more than 2% of all the circulating peripheral-blood T cells 6 months after the cell transfer. In this patient, TCR gene therapy targeting the KRAS G12D driver mutation mediated the objective regression of metastatic pancreatic cancer. (Funded by the Providence Portland Medical Foundation.) A 71-year-old woman with progressive pancreatic adenocarcinoma containing a mutated KRAS oncogene was given adoptive cellular therapy of her own T cells that had been altered to express two different T-cell receptors specific for her HLA type and the mutated KRAS in the tumor. Six months after treatment, the tumor burden had decreased by 72%, and the response was ongoing.

It has recently become possible to simultaneously assay T‐cell specificity with respect to large sets of antigens and the T‐cell receptor sequence in high‐throughput single‐cell experiments. Leveraging this new type of data, we propose and benchmark a collection of deep learning architectures to model T‐cell specificity in single cells. In agreement with previous results, we found that models that treat antigens as categorical outcome variables outperform those that model the TCR and antigen sequence jointly. Moreover, we show that variability in single‐cell immune repertoire screens can be mitigated by modeling cell‐specific covariates. Lastly, we demonstrate that the number of bound pMHC complexes can be predicted in a continuous fashion providing a gateway to disentangle cell‐to‐dextramer binding strength and receptor‐to‐pMHC affinity. We provide these models in the Python package TcellMatch to allow imputation of antigen specificities in single‐cell RNA‐seq studies on T cells without the need for MHC staining. Synopsis TcellMatch is a deep‐learning based algorithm that predicts the antigen specificity of single T cells based on multimodal single‐cell experiments that measure pMHC binding and T‐cell receptor sequences among other properties. pMHC measurements are predicted in a large single‐cell data set with > 100,000 cells, additionally using TCR‐antigen pairs from IEDB and VDJdb. Benchmarking categorical models of antigens with antigen‐embedding models indicates that categorical models are often preferable. The study highlights the need to measure TCR specificity for a larger repertoire of antigens to generalize models to unseen antigens. Graphical Abstract TcellMatch is a deep‐learning based algorithm that predicts the antigen specificity of single T cells based on multimodal single‐cell experiments that measure pMHC binding and T‐cell receptor sequences among other properties.

Key Points Adoptive immunotherapy has rapidly evolved to harness modern genetic techniques to create T cells with enhanced specificity, efficacy and safety. Artificial expression of chimeric antigen receptors (CARs) or engineered T cell receptors (TCRs) in autologous T cells has enabled a new generation of targeted cellular therapeutics. Early clinical trials targeting B cell malignancies have shown great promise, generating unprecedented response rates to treatment of patients with relapsed and refractory B cell acute lymphoblastic leukaemia (B-ALL). As more patients with different B cell malignancies are treated, areas for further optimization are brought to light. Engineered T cell therapy has been adapted to treat non-B cell malignancies, including multiple myeloma and myeloid malignancies as well as solid tumours. To date, target selection has proved challenging as many tumour-conserved markers are also expressed on benign tissues (for example, mesothelin) and other tumour-specific markers are less uniformly expressed (for example, epidermal growth factor receptor variant III (EGFRvIII)). More precise targeting of tumour cell subsets, such as cancer stem cells, or targeting of portions of intracellular tumour markers in the context of the major histocompatibility complex (MHC), may enhance specificity and limit off-tumour effects. Combining non-specific and specific immune responses (for example, T cells redirected for universal cytokine killing (TRUCKs), fluorescein isothiocyanate (FITC)–folate plus FITC-CAR T cell) could further enhance antitumour immune response, while minimizing off-tumour effects. Although lentiviral and retroviral transduction are still the most common approaches to ex vivo T cell gene modification, DNA and RNA transfection have some advantages. In particular, RNA transfection of short guide RNAs enables CRISPR–Cas9 modification of T cells. This targeted gene disruption approach could help to create engineered T cells with supraphysiological antitumour capabilities. In addition to specificity-enhancing artificial receptor expression, the next generation of engineered T cells may include modifications to overcome tumour-mediated immune suppression, additional receptors to enable Boolean gating of signal transduction or safety switches to enhance precision control of in vivo engineered T cell activity. This Review assesses what we have learnt about adoptive cell transfer of engineered T cells for the treatment of patients with B cell malignancies and discusses how this therapy can be improved and applied to other malignancies, including solid tumours. The immune system evolved to distinguish non-self from self to protect the organism. As cancer is derived from our own cells, immune responses to dysregulated cell growth present a unique challenge. This is compounded by mechanisms of immune evasion and immunosuppression that develop in the tumour microenvironment. The modern genetic toolbox enables the adoptive transfer of engineered T cells to create enhanced anticancer immune functions where natural cancer-specific immune responses have failed. Genetically engineered T cells, so-called 'living drugs', represent a new paradigm in anticancer therapy. Recent clinical trials using T cells engineered to express chimeric antigen receptors (CARs) or engineered T cell receptors (TCRs) have produced stunning results in patients with relapsed or refractory haematological malignancies. In this Review we describe some of the most recent and promising advances in engineered T cell therapy with a particular emphasis on what the next generation of T cell therapy is likely to entail.

TCR-gene-transfer is an efficient strategy to produce therapeutic T cells of defined antigen specificity. However, there are substantial variations in the cell surface expression levels of human TCRs, which can impair the function of engineered T cells. Here we demonstrate that substitutions of 3 amino acid residues in the framework of the TCR variable domains consistently increase the expression of human TCRs on the surface of engineered T cells.The modified TCRs mediate enhanced T cell proliferation, cytokine production and cytotoxicity, while reducing the peptide concentration required for triggering effector function up to 3000-fold. Adoptive transfer experiments in mice show that modified TCRs control tumor growth more efficiently than wild-type TCRs. Our data indicate that simple variable domain modifications at a distance from the antigen-binding loops lead to increased TCR expression and improved effector function. This finding provides a generic platform to optimize the efficacy of TCR gene therapy in humans. Increasing TCR cell surface expression can potentiate T cell responses to low-concentrations of antigen. Here the authors identify aminoacids in human TCR variable domains that impact its surface expression, and demonstrate how editing these residues can improve T cell activation and effector function without altering antigen specificity.

Introducing chimeric antigen receptors into the endogenous T-cell receptor locus reduces tonic signalling, averts accelerated T-cell differentiation and delays T-cell exhaustion, leading to enhanced function and anti-tumour efficacy compared to random integrations. Making a CAR drive tumour rejection Using T cells transduced with synthetic chimeric antigen receptors (CARs) is a promising strategy for treating certain types of cancer. Here Michel Sadelain and colleagues provide evidence in a mouse tumour model that knocking the CAR into the endogenous T-cell receptor α constant locus reduces tonic signalling, avoids accelerated T-cell differentiation, and delays T-cell exhaustion. This results in enhanced function and anti-tumour efficacy compared with random integrations. Chimeric antigen receptors (CARs) are synthetic receptors that redirect and reprogram T cells to mediate tumour rejection 1 . The most successful CARs used to date are those targeting CD19 (ref. 2 ), which offer the prospect of complete remission in patients with chemorefractory or relapsed B-cell malignancies 3 . CARs are typically transduced into the T cells of a patient using γ-retroviral 4 vectors or other randomly integrating vectors 5 , which may result in clonal expansion, oncogenic transformation, variegated transgene expression and transcriptional silencing 6 , 7 , 8 . Recent advances in genome editing enable efficient sequence-specific interventions in human cells 9 , 10 , including targeted gene delivery to the CCR5 and AAVS1 loci 11 , 12 . Here we show that directing a CD19-specific CAR to the T-cell receptor α constant ( TRAC ) locus not only results in uniform CAR expression in human peripheral blood T cells, but also enhances T-cell potency, with edited cells vastly outperforming conventionally generated CAR T cells in a mouse model of acute lymphoblastic leukaemia. We further demonstrate that targeting the CAR to the TRAC locus averts tonic CAR signalling and establishes effective internalization and re-expression of the CAR following single or repeated exposure to antigen, delaying effector T-cell differentiation and exhaustion. These findings uncover facets of CAR immunobiology and underscore the potential of CRISPR/Cas9 genome editing to advance immunotherapies.

B cell receptor (BCR) signalling is crucial for normal B cell development and adaptive immunity. BCR signalling also supports the survival and growth of malignant B cells in patients with B cell leukaemias or lymphomas. The mechanism of BCR pathway activation in these diseases includes continuous BCR stimulation by microbial antigens or autoantigens present in the tissue microenvironment, activating mutations within the BCR complex or downstream signalling components and ligand-independent tonic BCR signalling. The most established agents targeting BCR signalling are Bruton tyrosine kinase (BTK) inhibitors and PI3K isoform-specific inhibitors, and their introduction into the clinic is rapidly changing how B cell malignancies are treated. B cells and BCR-related kinases, such as BTK, also play a role in the microenvironment of solid tumours, such as squamous cell carcinoma and pancreatic cancer, and therefore targeting B cells or BCR-related kinases may have anticancer activity beyond B cell malignancies.

The authors characterize epitope-specific T cell repertoires, identify shared and recognizable features of TCRs, and develop tools to classify antigen specificity on the basis of sequence analysis. Defining T cell receptor repertoires In this study, Paul Thomas and colleagues use molecular genetic tools to analyse the diversity of epitope-specific T cell repertoires to characterize features that enable the prediction of T cell epitope specificity immunity based on sequence analysis. This manuscript is of broad interest to various fields ranging from basic immunology to applied immunotherapeutics and translational medicine. Elsewhere in this issue, Mark Davis and colleagues address the question of how T cell receptor sequences relate to antigen specificity and create an algorithm that predicts the human leukocyte antigen (HLA) restriction of the T cell receptor targets and helps to identify specific peptide major histocompatibility complex ligands. T cells are defined by a heterodimeric surface receptor, the T cell receptor (TCR), that mediates recognition of pathogen-associated epitopes through interactions with peptide and major histocompatibility complexes (pMHCs). TCRs are generated by genomic rearrangement of the germline TCR locus, a process termed V(D)J recombination, that has the potential to generate marked diversity of TCRs (estimated to range from 10 15 (ref. 1 ) to as high as 10 61 (ref. 2 ) possible receptors). Despite this potential diversity, TCRs from T cells that recognize the same pMHC epitope often share conserved sequence features, suggesting that it may be possible to predictively model epitope specificity. Here we report the in-depth characterization of ten epitope-specific TCR repertoires of CD8 + T cells from mice and humans, representing over 4,600 in-frame single-cell-derived TCRαβ sequence pairs from 110 subjects. We developed analytical tools to characterize these epitope-specific repertoires: a distance measure on the space of TCRs that permits clustering and visualization, a robust repertoire diversity metric that accommodates the low number of paired public receptors observed when compared to single-chain analyses, and a distance-based classifier that can assign previously unobserved TCRs to characterized repertoires with robust sensitivity and specificity. Our analyses demonstrate that each epitope-specific repertoire contains a clustered group of receptors that share core sequence similarities, together with a dispersed set of diverse ‘outlier’ sequences. By identifying shared motifs in core sequences, we were able to highlight key conserved residues driving essential elements of TCR recognition. These analyses provide insights into the generalizable, underlying features of epitope-specific repertoires and adaptive immune recognition.

High-throughput single-cell RNA sequencing is a powerful technique but only generates short reads from one end of a cDNA template, limiting the reconstruction of highly diverse sequences such as antigen receptors. To overcome this limitation, we combined targeted capture and long-read sequencing of T-cell-receptor (TCR) and B-cell-receptor (BCR) mRNA transcripts with short-read transcriptome profiling of barcoded single-cell libraries generated by droplet-based partitioning. We show that Repertoire and Gene Expression by Sequencing (RAGE-Seq) can generate accurate full-length antigen receptor sequences at nucleotide resolution, infer B-cell clonal evolution and identify alternatively spliced BCR transcripts. We apply RAGE-Seq to 7138 cells sampled from the primary tumor and draining lymph node of a breast cancer patient to track transcriptome profiles of expanded lymphocyte clones across tissues. Our results demonstrate that RAGE-Seq is a powerful method for tracking the clonal evolution from large numbers of lymphocytes applicable to the study of immunity, autoimmunity and cancer. Single cell RNA sequencing generates short reads from one end of a template, providing incomplete transcript coverage and limiting identification of diverse sequences such as antigen receptors. Here the authors combine long read nanopore sequencing with short read profiling of barcoded libraries to generate full-length antigen receptor sequences.

The hallmarks of the adaptive immune response are specificity and memory. The cellular response is mediated by T cells which express cell surface T cell receptors (TCRs) that recognize peptide antigens in complex with major histocompatibility complex (MHC) molecules on antigen presenting cells (APCs). However, binding of cognate TCRs with MHC-peptide complexes alone (signal 1) does not trigger optimal T cell activation. In addition to signal 1, the binding of positive and negative costimulatory receptors to their ligands modulates T cell activation. This complex signaling network prevents aberrant activation of T cells. CD28 is the main positive costimulatory receptor on naïve T cells; upon activation, CTLA4 is induced but reduces T cell activation. Further studies led to the identification of additional negative costimulatory receptors known as checkpoints, e.g. PD1. This review chronicles the basic studies in T cell costimulation that led to the discovery of checkpoint inhibitors, i.e. antibodies to negative costimulatory receptors (e.g. CTLA4 and PD1) which reduce tumor growth. This discovery has been recognized with the award of the 2018 Nobel prize in Physiology/Medicine. This review highlights the structural and functional roles of costimulatory receptors, the mechanisms by which checkpoint inhibitors work, the challenges encountered and future prospects.