Structural interplay between germline interactions and adaptive recognition determines the bandwidth of TCR-peptide-MHC cross-reactivity

Characterizing the T Cell Repertoire in the Proximal Airway in Health and Disease

OBJECTIVES

Recent translational scientific efforts in subglottic stenosis (SGS) support a disease model where epithelial alterations facilitate microbiome displacement, dysregulated immune activation, and localized fibrosis. Given the observed immune cell infiltrate in SGS, we sought to test the hypothesis that SGS cases possessed a low diversity (highly clonal) adaptive immune response when compared with healthy controls.

METHODS

Single cell RNA sequencing (scRNA-seq) of subglottic mucosal scar in iSGS (n = 24), iLTS (n = 8), and healthy controls (n = 7) was performed. T cell receptor (TCR) sequences were extracted, analyzed, and used to construct repertoire structure, compare diversity, interrogate overlap, and define antigenic targets using the Immunarch bioinformatics pipeline.

RESULTS

The proximal airway mucosa in health and disease are equally diverse via Hill framework quantitation (iSGS vs. iLTS vs. Control, p > 0.05). Repertoires do not significantly overlap between individuals (Morisita <0.02). Among iSGS patients, clonality of the TCR repertoire is driven by CD8+ T cells, and iSGS patients possess numerous TCRs targeting viral and intercellular pathogens. High frequency clonotypes do not map to known targets in public datasets.

CONCLUSION

SGS cases do not possess a lower diversity adaptive immune infiltrate when compared with healthy controls. Interestingly, the TCR repertoire in both health and disease contains a restricted number of high frequency clonotypes that do not significantly overlap between individuals. The target of the high frequency clonotypes in health and disease remain unresolved.

LEVEL OF EVIDENCE

NA Laryngoscope, 134:1757-1764, 2024.

T-cell virtuosity in ''knowing thyself"

Major Histocompatibility Complex (MHC) I and II and the αβ T-cell antigen receptor (TCRαβ) govern fundamental traits of adaptive immunity. They form a membrane-borne ligand-receptor system weighing host proteome integrity to detect contamination by nonself proteins. MHC-I and -II exhibit the "MHC-fold", which is able to bind a large assortment of short peptides as proxies for self and nonself proteins. The ensuing varying surfaces are mandatory ligands for Ig-like TCRαβ highly mutable binding sites. Conserved molecular signatures guide TCRαβ ligand binding sites to focus on the MHC-fold (MHC-restriction) while leaving many opportunities for its most hypervariable determinants to contact the peptide. This riveting molecular strategy affords many options for binding energy compatible with specific recognition and signalling aimed to eradicated microbial pathogens and cancer cells. While the molecular foundations of αβ T-cell adaptive immunity are largely understood, uncertainty persists on how peptide-MHC binding induces the TCRαβ signals that instruct cell-fate decisions. Solving this mystery is another milestone for understanding αβ T-cells' self/nonself discrimination. Recent developments revealing the innermost links between TCRαβ structural dynamics and signalling modality should help dissipate this long-sought-after enigma.

BATMAN: Improved T cell receptor cross-reactivity prediction benchmarked on a comprehensive mutational scan database

Predicting T cell receptor (TCR) activation is challenging due to the lack of both unbiased benchmarking datasets and computational methods that are sensitive to small mutations to a peptide. To address these challenges, we curated a comprehensive database encompassing complete single amino acid mutational assays of 10,750 TCR-peptide pairs, centered around 14 immunogenic peptides against 66 TCRs. We then present an interpretable Bayesian model, called BATMAN, that can predict the set of peptides that activates a TCR. When validated on our database, BATMAN outperforms existing methods by 20% and reveals important biochemical predictors of TCR-peptide interactions.

T cell receptor therapeutics: immunological targeting of the intracellular cancer proteome

The T cell receptor (TCR) complex is a naturally occurring antigen sensor that detects, amplifies and coordinates cellular immune responses to epitopes derived from cell surface and intracellular proteins. Thus, TCRs enable the targeting of proteins selectively expressed by cancer cells, including neoantigens, cancer germline antigens and viral oncoproteins. As such, TCRs have provided the basis for an emerging class of oncology therapeutics. Herein, we review the current cancer treatment landscape using TCRs and TCR-like molecules. This includes adoptive cell transfer of T cells expressing endogenous or engineered TCRs, TCR bispecific engagers and antibodies specific for human leukocyte antigen (HLA)-bound peptides (TCR mimics). We discuss the unique complexities associated with the clinical development of these therapeutics, such as HLA restriction, TCR retrieval, potency assessment and the potential for cross-reactivity. In addition, we highlight emerging clinical data that establish the antitumour potential of TCR-based therapies, including tumour-infiltrating lymphocytes, for the treatment of diverse human malignancies. Finally, we explore the future of TCR therapeutics, including emerging genome editing methods to safely enhance potency and strategies to streamline patient identification.

Cellular and molecular imaging of CAR-T cell-based immunotherapy

Chimeric Antigen Receptor T cell (CAR-T) therapy has emerged as a transformative therapeutic strategy for hematological malignancies. However, its efficacy in treating solid tumors remains limited. An in-depth and comprehensive understanding of CAR-T cell signaling pathways and the ability to track CAR-T cell biodistribution and activation in real-time within the tumor microenvironment will be instrumental in designing the next generation of CAR-T cells for solid tumor therapy. This review summarizes the signaling network and the cellular and molecular imaging tools and platforms that are utilized in CAR-T cell-based immune therapies, covering both in vitro and in vivo studies. Firstly, we provide an overview of the existing understanding of the activation and cytotoxic mechanisms of CAR-T cells, compared to the mechanism of T cell receptor (TCR) signaling pathways. We further describe the commonly employed tools for live cell imaging, coupled with recent research progress, with a focus on genetically encoded fluorescent proteins (FPs) and biosensors. We then discuss the utility of diverse in vivo imaging modalities, including fluorescence and bioluminescence imaging, Magnetic Resonance Imaging (MRI), Positron Emission Tomography (PET), and photoacoustic (PA) imaging, for noninvasive monitoring of CAR-T cell dynamics within tumor tissues, thereby providing critical insights into therapy's strengths and weaknesses. Lastly, we discuss the current challenges and future directions of CAR-T cell therapy from the imaging perspective. We foresee that a comprehensive and integrative approach to CAR-T cell imaging will enable the development of more effective treatments for solid tumors in the future.

Conserved biophysical compatibility among the highly variable germline-encoded regions shapes TCR-MHC interactions

T cells are critically important components of the adaptive immune system primarily responsible for identifying and responding to pathogenic challenges. This recognition of pathogens is driven by the interaction between membrane-bound T cell receptors (TCRs) and antigenic peptides presented on major histocompatibility complex (MHC) molecules. The formation of the TCR-peptide-MHC complex (TCR-pMHC) involves interactions among germline-encoded and hypervariable amino acids. Germline-encoded and hypervariable regions can form contacts critical for complex formation, but only interactions between germline-encoded contacts are likely to be shared across many of all the possible productive TCR-pMHC complexes. Despite this, experimental investigation of these interactions have focused on only a small fraction of the possible interaction space. To address this, we analyzed every possible germline-encoded TCR-MHC contact in humans, thereby generating the first comprehensive characterization of these largely antigen-independent interactions. Our computational analysis suggests that germline-encoded TCR-MHC interactions that are conserved at the sequence level are rare due to the high amino acid diversity of the TCR CDR1 and CDR2 loops, and that such conservation is unlikely to dominate the dynamic protein-protein binding interface. Instead, we propose that binding properties such as the docking orientation are defined by regions of biophysical compatibility between these loops and the MHC surface.

Multi-tiered approach to detect autoimmune cross-reactivity of therapeutic T cell receptors

T cell receptor (TCR)-engineered T cell therapy using high-affinity TCRs is a promising treatment modality for cancer. Discovery of high-affinity TCRs especially against self-antigens can require approaches that circumvent central tolerance, which may increase the risk of cross-reactivity. Despite the potential for toxicity, no standardized approach to screen cross-reactivity has been established in the context of preclinical safety evaluation. Here, we describe a practical framework to prospectively detect clinically prohibitive cross-reactivity of therapeutic TCR candidates. Cross-reactivity screening consisted of multifaceted series of assays including assessment of p-MHC tetramer binding, cell line recognition, and reactivity against candidate peptide libraries. Peptide libraries were generated using conventional contact residue motif-guided search, amino acid substitution matrix-based search unguided by motif information, and combinatorial peptide library scan-guided search. We demonstrate the additive nature of a layered approach, which efficiently identifies unsafe cross-reactivity including one undetected by conventional motif-guided search. These findings have important implications for the safe development of TCR-based therapies.

Pre-existing T Cell Memory to Novel Pathogens

Immunological experiences lead to the development of specific T and B cell memory, which readies the host for a later pathogen rechallenge. Currently, immunological memory is best understood as a linear process whereby memory responses are generated by and directed against the same pathogen. However, numerous studies have identified memory cells that target pathogens in unexposed individuals. How "pre-existing memory" forms and impacts the outcome of infection remains unclear. In this review, we discuss differences in the composition of baseline T cell repertoire in mice and humans, factors that influence pre-existing immune states, and recent literature on their functional significance. We summarize current knowledge on the roles of pre-existing T cells in homeostasis and perturbation and their impacts on health and disease.

CrossDome: an interactive R package to predict cross-reactivity risk using immunopeptidomics databases

T-cell-based immunotherapies hold tremendous potential in the fight against cancer, thanks to their capacity to specifically targeting diseased cells. Nevertheless, this potential has been tempered with safety concerns regarding the possible recognition of unknown off-targets displayed by healthy cells. In a notorious example, engineered T-cells specific to MAGEA3 (EVDPIGHLY) also recognized a TITIN-derived peptide (ESDPIVAQY) expressed by cardiac cells, inducing lethal damage in melanoma patients. Such off-target toxicity has been related to T-cell cross-reactivity induced by molecular mimicry. In this context, there is growing interest in developing the means to avoid off-target toxicity, and to provide safer immunotherapy products. To this end, we present CrossDome, a multi-omics suite to predict the off-target toxicity risk of T-cell-based immunotherapies. Our suite provides two alternative protocols, i) a peptide-centered prediction, or ii) a TCR-centered prediction. As proof-of-principle, we evaluate our approach using 16 well-known cross-reactivity cases involving cancer-associated antigens. With CrossDome, the TITIN-derived peptide was predicted at the 99+ percentile rank among 36,000 scored candidates (p-value < 0.001). In addition, off-targets for all the 16 known cases were predicted within the top ranges of relatedness score on a Monte Carlo simulation with over 5 million putative peptide pairs, allowing us to determine a cut-off p-value for off-target toxicity risk. We also implemented a penalty system based on TCR hotspots, named contact map (CM). This TCR-centered approach improved upon the peptide-centered prediction on the MAGEA3-TITIN screening (e.g., from 27th to 6th, out of 36,000 ranked peptides). Next, we used an extended dataset of experimentally-determined cross-reactive peptides to evaluate alternative CrossDome protocols. The level of enrichment of validated cases among top 50 best-scored peptides was 63% for the peptide-centered protocol, and up to 82% for the TCR-centered protocol. Finally, we performed functional characterization of top ranking candidates, by integrating expression data, HLA binding, and immunogenicity predictions. CrossDome was designed as an R package for easy integration with antigen discovery pipelines, and an interactive web interface for users without coding experience. CrossDome is under active development, and it is available at https://github.com/AntunesLab/crossdome.

A class-mismatched TCR bypasses MHC restriction via an unorthodox but fully functional binding geometry

MHC restriction, which describes the binding of TCRs from CD4⁺ T cells to class II MHC proteins and TCRs from CD8⁺ T cells to class I MHC proteins, is a hallmark of immunology. Seemingly rare TCRs that break this paradigm exist, but mechanistic insight into their behavior is lacking. TIL1383I is a prototypical class-mismatched TCR, cloned from a CD4⁺ T cell but recognizing the tyrosinase tumor antigen presented by the class I MHC HLA-A2 in a fully functional manner. Here we find that TIL1383I binds this class I target with a highly atypical geometry. Despite unorthodox binding, TCR signaling, antigen specificity, and the ability to use CD8 are maintained. Structurally, a key feature of TIL1383I is an exceptionally long CDR3β loop that mediates functions that are traditionally performed separately by hypervariable and germline loops in canonical TCR structures. Our findings thus expand the range of known TCR binding geometries compatible with normal function and specificity, provide insight into the determinants of MHC restriction, and may help guide TCR selection and engineering for immunotherapy.

Peptide Centric Vβ Specific Germline Contacts Shape a Specialist T Cell Response

Certain CD8 T cell responses are particularly effective at controlling infection, as exemplified by elite control of HIV in individuals harboring HLA-B57. To understand the structural features that contribute to CD8 T cell elite control, we focused on a strongly protective CD8 T cell response directed against a parasite-derived peptide (HF10) presented by an atypical MHC-I molecule, H-2Ld. This response exhibits a focused TCR repertoire dominated by Vβ2, and a representative TCR (TG6) in complex with Ld-HF10 reveals an unusual structure in which both MHC and TCR contribute extensively to peptide specificity, along with a parallel footprint of TCR on its pMHC ligand. The parallel footprint is a common feature of Vβ2-containing TCRs and correlates with an unusual Vα-Vβ interface, CDR loop conformations, and Vβ2-specific germline contacts with peptides. Vβ2 and Ld may represent "specialist" components for antigen recognition that allows for particularly strong and focused T cell responses.

Validation and promise of a TCR mimic antibody for cancer immunotherapy of hepatocellular carcinoma

Monoclonal antibodies are at the vanguard of the most promising cancer treatments. Whereas traditional therapeutic antibodies have been limited to extracellular antigens, T cell receptor mimic (TCRm) antibodies can target intracellular antigens presented by cell surface major histocompatibility complex (MHC) proteins. TCRm antibodies can therefore target a repertoire of otherwise undruggable cancer antigens. However, the consequences of off-target peptide/MHC recognition with engineered T cell therapies are severe, and thus there are significant safety concerns with TCRm antibodies. Here we explored the specificity and safety profile of a new TCRm-based T cell therapy for hepatocellular carcinoma (HCC), a solid tumor for which no effective treatment exists. We targeted an alpha-fetoprotein peptide presented by HLA-A*02 with a highly specific TCRm, which crystallographic structural analysis showed binds directly over the HLA protein and interfaces with the full length of the peptide. We fused the TCRm to the γ and δ subunits of a TCR, producing a signaling AbTCR construct. This was combined with an scFv/CD28 co-stimulatory molecule targeting glypican-3 for increased efficacy towards tumor cells. This AbTCR + co-stimulatory T cell therapy showed potent activity against AFP-positive cancer cell lines in vitro and an in an in vivo model and undetectable activity against AFP-negative cells. In an in-human safety assessment, no significant adverse events or cytokine release syndrome were observed and evidence of efficacy was seen. Remarkably, one patient with metastatic HCC achieved a complete remission after nine months and ultimately qualified for a liver transplant.

Structural Prediction of Peptide-MHC Binding Modes

The immune system is constantly protecting its host from the invasion of pathogens and the development of cancer cells. The specific CD8⁺ T-cell immune response against virus-infected cells and tumor cells is based on the T-cell receptor recognition of antigenic peptides bound to class I major histocompatibility complexes (MHC) at the surface of antigen presenting cells. Consequently, the peptide binding specificities of the highly polymorphic MHC have important implications for the design of vaccines, for the treatment of autoimmune diseases, and for personalized cancer immunotherapy. Evidence-based machine-learning approaches have been successfully used for the prediction of peptide binders and are currently being developed for the prediction of peptide immunogenicity. However, understanding and modeling the structural details of peptide/MHC binding is crucial for a better understanding of the molecular mechanisms triggering the immunological processes, estimating peptide/MHC affinity using universal physics-based approaches, and driving the design of novel peptide ligands. Unfortunately, due to the large diversity of MHC allotypes and possible peptides, the growing number of 3D structures of peptide/MHC (pMHC) complexes in the Protein Data Bank only covers a small fraction of the possibilities. Consequently, there is a growing need for rapid and efficient approaches to predict 3D structures of pMHC complexes. Here, we review the key characteristics of the 3D structure of pMHC complexes before listing databases and other sources of information on pMHC structures and MHC specificities. Finally, we discuss some of the most prominent pMHC docking software.

Autoreactive T cell receptors with shared germline-like α chains in type 1 diabetes

Human islet antigen reactive CD4⁺ memory T cells (IAR T cells) play a key role in the pathogenesis of autoimmune type 1 diabetes (T1D). Using single-cell RNA sequencing (scRNA-Seq) to identify T cell receptors (TCRs) in IAR T cells, we have identified a class of TCRs that share TCRα chains between individuals (“public” chains). We isolated IAR T cells from blood of healthy, new-onset T1D and established T1D donors using multiplexed CD154 enrichment and identified paired TCRαβ sequences from 2767 individual cells. More than a quarter of cells shared TCR junctions between 2 or more cells (“expanded”), and 29/47 (~62%) of expanded TCRs tested showed specificity for islet antigen epitopes. Public TCRs sharing TCRα junctions were most prominent in new-onset T1D. Public TCR sequences were more germline like than expanded unique, or “private,” TCRs, and had shorter junction sequences, suggestive of fewer random nucleotide insertions. Public TCRα junctions were often paired with mismatched TCRβ junctions in TCRs; remarkably, a subset of these TCRs exhibited cross-reactivity toward distinct islet antigen peptides. Our findings demonstrate a prevalent population of IAR T cells with diverse specificities determined by TCRs with restricted TCRα junctions and germline-constrained antigen recognition properties. Since these “innate-like” TCRs differ from previously described immunodominant TCRβ chains in autoimmunity, they have implications for fundamental studies of disease mechanisms. Self-reactive restricted TCRα chains and their associated epitopes should be considered in fundamental and translational investigations of TCRs in T1D.

Engineering soluble T-cell receptors for therapy

Immunotherapy approaches that target peptide-human leukocyte antigen (pHLA) complexes are becoming highly attractive because of their potential to access virtually all foreign and cellular proteins. For this reason, there has been considerable interest in the development of the natural ligand for pHLA, the T-cell receptor (TCR), as a soluble drug to target disease-associated pHLA presented at the cell surface. However, native TCR stability is suboptimal for soluble drug development, and natural TCRs generally have weak affinities for pHLAs, limiting their potential to reach efficacious receptor occupancy levels as soluble drugs. To overcome these limitations and make full use of the TCR as a soluble drug platform, several protein engineering solutions have been applied to TCRs to enhance both their stability and affinity, with a focus on retaining target specificity and selectivity. Here, we review these advances and look to the future for the next generation of soluble TCR-based therapies that can target monomorphic HLA-like proteins presenting both peptide and nonpeptide antigens.

Synthetic Peptides with Inadvertent Chemical Modifications Can Activate Potentially Autoreactive T Cells

The human CD8+ T cell clone 6C5 has previously been shown to recognize the tert-butyl-modified Bax161-170 peptide LLSY(3-tBu)FGTPT presented by HLA-A*02:01. This nonnatural epitope was likely created as a by-product of fluorenylmethoxycarbonyl protecting group peptide synthesis and bound poorly to HLA-A*02:01. In this study, we used a systematic approach to identify and characterize natural ligands for the 6C5 TCR. Functional analyses revealed that 6C5 T cells only recognized the LLSYFGTPT peptide when tBu was added to the tyrosine residue and did not recognize the LLSYFGTPT peptide modified with larger (di-tBu) or smaller chemical groups (Me). Combinatorial peptide library screening further showed that 6C5 T cells recognized a series of self-derived peptides with dissimilar amino acid sequences to LLSY(3-tBu)FGTPT. Structural studies of LLSY(3-tBu)FGTPT and two other activating nonamers (IIGWMWIPV and LLGWVFAQV) in complex with HLA-A*02:01 demonstrated similar overall peptide conformations and highlighted the importance of the position (P) 4 residue for T cell recognition, particularly the capacity of the bulky amino acid tryptophan to substitute for the tBu-modified tyrosine residue in conjunction with other changes at P5 and P6. Collectively, these results indicated that chemical modifications directly altered the immunogenicity of a synthetic peptide via molecular mimicry, leading to the inadvertent activation of a T cell clone with unexpected and potentially autoreactive specificities.

TCR repertoire characteristics predict clinical response to adoptive CTL therapy against nasopharyngeal carcinoma

The past decade has witnessed the gradual and steady progress of adoptive T cell therapy in treating various types of cancer. In combination with gemcitabine and carboplatin chemotherapy, we previously conducted a clinical trial, NCT00690872, to treat Epstein-Barr virus (EBV)-positive nasopharyngeal carcinoma (NPC) patients with autologous EBV-expanded cytotoxic T lymphocytes (CTLs). While achieving a 2-year overall survival rate of 62.9%, this trial failed to induce an anti-tumor response in a sizable fraction of patients. Thus, the identification of benchmarks capable of evaluating CTL products and predicting clinical immunotherapeutic efficacy remains an urgent need. We conducted T cell receptor (TCR) repertoire sequencing to assess EBV-expanded infusion-ready CTL products. To depict the overall repertoire landscape, we evaluated the individual repertoire diversity by Shannon entropy, and, compared the inter-patient CDR3 similarity to estimate T cells expanded by common antigens. With a recently developed bioinformatics algorithm, termed Motif Analysis, we made a machine-learning prediction of structural regions within the CDR3 of TCRβ that associate with CTL therapy prognosis. We found that long term survivors, defined as patients surviving longer than two years, had a higher CTL repertoire diversity with reduced inter-patient similarity. Furthermore, TCR Motif Analysis identified 11 structural motifs distinguishing long term survivors from short term survivors. Specifically, two motifs with a high area under the curve (AUC) values were identified as potential predictive benchmarks for efficacious CTL production. Together, these results reveal that the presence of diverse TCR sequences containing a common core motif set is associated with a favorable response to CTL immunotherapy against EBV-positive NPC.

The discriminatory power of the T cell receptor

T cells use their T cell receptors (TCRs) to discriminate between lower-affinity self and higher-affinity non-self peptides presented on major histocompatibility complex (pMHC) antigens. Although the discriminatory power of the TCR is widely believed to be near-perfect, technical difficulties have hampered efforts to precisely quantify it. Here, we describe a method for measuring very low TCR/pMHC affinities and use it to measure the discriminatory power of the TCR and the factors affecting it. We find that TCR discrimination, although enhanced compared with conventional cell-surface receptors, is imperfect: primary human T cells can respond to pMHC with affinities as low as KD ∼ 1 mM. The kinetic proofreading mechanism fit our data, providing the first estimates of both the time delay (2.8 s) and number of biochemical steps (2.67) that are consistent with the extraordinary sensitivity of antigen recognition. Our findings explain why self pMHC frequently induce autoimmune diseases and anti-tumour responses, and suggest ways to modify TCR discrimination.

CD4+ T Cells Recognize Conserved Influenza A Epitopes through Shared Patterns of V-Gene Usage and Complementary Biochemical Features

T cell recognition of peptides presented by human leukocyte antigens (HLAs) is mediated by the highly variable T cell receptor (TCR). Despite this built-in TCR variability, individuals can mount immune responses against viral epitopes by using identical or highly related TCRs expressed on CD8⁺ T cells. Characterization of these TCRs has extended our understanding of the molecular mechanisms that govern the recognition of peptide-HLA. However, few examples exist for CD4⁺ T cells. Here, we investigate CD4⁺ T cell responses to the internal proteins of the influenza A virus that correlate with protective immunity. We identify five internal epitopes that are commonly recognized by CD4⁺ T cells in five HLA-DR1⁺ subjects and show conservation across viral strains and zoonotic reservoirs. TCR repertoire analysis demonstrates several shared gene usage biases underpinned by complementary biochemical features evident in a structural comparison. These epitopes are attractive targets for vaccination and other T cell therapies.

SARS-CoV-2 genome-wide T cell epitope mapping reveals immunodominance and substantial CD8+ T cell activation in COVID-19 patients

T cells are important for effective viral clearance, elimination of virus-infected cells and long-term disease protection. To examine the full-spectrum of CD8+ T cell immunity in COVID-19, we experimentally evaluated 3141 major histocompatibility (MHC) class I-binding peptides covering the complete SARS-CoV-2 genome. Using DNA-barcoded peptide-MHC complex (pMHC) multimers combined with a T cell phenotype panel, we report a comprehensive list of 122 immunogenic and a subset of immunodominant SARS-CoV-2 T cell epitopes. Substantial CD8+ T cell recognition was observed in COVID-19 patients, with up to 27% of all CD8+ lymphocytes interacting with SARS-CoV-2-derived epitopes. Most immunogenic regions were derived from open reading frame (ORF) 1 and ORF3, with ORF1 containing most of the immunodominant epitopes. CD8+ T cell recognition of lower affinity was also observed in healthy donors toward SARS-CoV-2-derived epitopes. This pre-existing T cell recognition signature was partially overlapping with the epitope landscape observed in COVID-19 patients and may drive the further expansion of T cell responses to SARS-CoV-2 infection. Importantly the phenotype of the SARS-CoV-2-specific CD8+ T cells, revealed a strong T cell activation in COVID-19 patients, while minimal T cell activation was seen in healthy individuals. We found that patients with severe disease displayed significantly larger SARS-CoV-2-specific T cell populations compared to patients with mild diseases and these T cells displayed a robust activation profile. These results further our understanding of T cell immunity to SARS-CoV-2 infection and hypothesize that strong antigen-specific T cell responses are associated with different disease outcomes.

Specificity of bispecific T cell receptors and antibodies targeting peptide-HLA

Tumor-associated peptide-human leukocyte antigen complexes (pHLAs) represent the largest pool of cell surface-expressed cancer-specific epitopes, making them attractive targets for cancer therapies. Soluble bispecific molecules that incorporate an anti-CD3 effector function are being developed to redirect T cells against these targets using 2 different approaches. The first achieves pHLA recognition via affinity-enhanced versions of natural TCRs (e.g., immune-mobilizing monoclonal T cell receptors against cancer [ImmTAC] molecules), whereas the second harnesses an antibody-based format (TCR-mimic antibodies). For both classes of reagent, target specificity is vital, considering the vast universe of potential pHLA molecules that can be presented on healthy cells. Here, we made use of structural, biochemical, and computational approaches to investigate the molecular rules underpinning the reactivity patterns of pHLA-targeting bispecifics. We demonstrate that affinity-enhanced TCRs engage pHLA using a comparatively broad and balanced energetic footprint, with interactions distributed over several HLA and peptide side chains. As ImmTAC molecules, these TCRs also retained a greater degree of pHLA selectivity, with less off-target activity in cellular assays. Conversely, TCR-mimic antibodies tended to exhibit binding modes focused more toward hot spots on the HLA surface and exhibited a greater degree of crossreactivity. Our findings extend our understanding of the basic principles that underpin pHLA selectivity and exemplify a number of molecular approaches that can be used to probe the specificity of pHLA-targeting molecules, aiding the development of future reagents.

Empirical and Rational Design of T Cell Receptor-Based Immunotherapies

The use of T cells reactive with intracellular tumor-associated or tumor-specific antigens has been a promising strategy for cancer immunotherapies in the past three decades, but the approach has been constrained by a limited understanding of the T cell receptor's (TCR) complex functions and specificities. Newer TCR and T cell-based approaches are in development, including engineered adoptive T cells with enhanced TCR affinities, TCR mimic antibodies, and T cell-redirecting bispecific agents. These new therapeutic modalities are exciting opportunities by which TCR recognition can be further exploited for therapeutic benefit. In this review we summarize the development of TCR-based therapeutic strategies and focus on balancing efficacy and potency versus specificity, and hence, possible toxicity, of these powerful therapeutic modalities.

T and B cell Epitope analysis of SARS-CoV-2 S protein based on immunoinformatics and experimental research

COVID-19 caused by SARS-CoV-2 is pandemic with a severe morbidity and mortality rate across the world. Despite the race for effective vaccine and drug against further expansion and fatality rate of this novel coronavirus, there is still lack of effective antiviral therapy. To this effect, we deemed it necessary to identify potential B and T cell epitopes from the envelope S protein. This can be used as potential targets to develop anti-SARS-CoV-2 vaccine preparations. In this study, we used immunoinformatics to identify conservative B and T cell epitopes for S proteins of SARS-CoV-2, which might play roles in the initiation of SARS-CoV-2 infection. We identified the B cell and T cell peptide epitopes of S protein and their antigenicity, as well as the interaction between the peptide epitopes and human leucocyte antigen (HLA). Among the B cell epitopes, 'EILDITPCSFGGVS' has the highest score of antigenicity and great immunogenicity. In T cell epitopes, MHC-I peptide 'KIADYNYKL' and MHC-II peptide 'LEILDITPC' were identified as high antigens. Besides, docking analysis showed that the predicted peptide 'KIADYNYKL' was closely bound to the HLA-A*0201. The results of molecular dynamics simulation through GROMACS software showed that 'HLA-A*0201~peptide' complex was very stable. And the peptide we selected could induce the T cell response similar to that of SARS-CoV-2 infection. Moreover, the predicted peptides were highly conserved in different isolates from different countries. The antigenic epitopes presumed in this study were effective new vaccine targets to prevent SARS-CoV-2 infection.

High-throughput modeling and scoring of TCR-pMHC complexes to predict cross-reactive peptides

MOTIVATION

The binding of T cell receptors (TCRs) to their target peptide MHC (pMHC) ligands initializes the cell-mediated immune response. In autoimmune diseases such as multiple sclerosis, the TCR erroneously recognizes self-peptides as foreign and activates an immune response against healthy cells. Such responses can be triggered by cross-recognition of the autoreactive TCR with foreign peptides. Hence, it would be desirable to identify such foreign-antigen triggers to provide a mechanistic understanding of autoimmune diseases. However, the large sequence space of foreign antigens presents an obstacle in the identification of cross-reactive peptides.

RESULTS

Here, we present an in silico modeling and scoring method which exploits the structural properties of TCR-pMHC complexes to predict the binding of cross-reactive peptides. We analyzed three mouse TCRs and one human TCR isolated from a patient with multiple sclerosis. Cross-reactive peptides for these TCRs were previously identified via yeast display coupled with deep sequencing, providing a robust dataset for evaluating our method. Modeling query peptides in their associated TCR-pMHC crystal structures, our method accurately selected the top binding peptides from sets containing more than a hundred thousand unique peptides.

AVAILABILITY AND IMPLEMENTATION

Analyses were performed using custom Python and R scripts available at https://github.com/tborrman/antigen-predict.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Structural and Biophysical Insights into the TCRαβ Complex in Chickens

In this work, chicken HPAIV H5N1 epitope-specific TCRαβ (ch-TCRαβ) was isolated and its structure was determined. The Cα domain of ch-TCRαβ does not exhibit the typical structure of human TCRαβ, and the DE loop extends outward, resulting in close proximity between the Cα domain of ch-TCRαβ and CD3εδ/γ. The FG loop of the Cβ domain of ch-TCRαβ is shorter. The changes in the C domains of ch-TCRαβ and the difference in chicken CD3εδ/γ confirm that the complexes formed by TCRαβ and CD3εδ/γ differ from those in humans. In the chicken complex, a positively charged cleft is formed between the two CDR3 loops that might accommodate the acidic side chains of the chicken pMHC-I-bound HPAIV epitope intermediate portion oriented toward ch-TCRαβ. This is the first reported structure of chicken TCRαβ, and it provides a structural model of the ancestral TCR system in the immune synapses between T cells and antigen-presenting cells in lower vertebrates.

Predicting Cross-Reactivity and Antigen Specificity of T Cell Receptors

Adaptive immune recognition is mediated by specific interactions between heterodimeric T cell receptors (TCRs) and their cognate peptide-MHC (pMHC) ligands, and the methods to accurately predict TCR:pMHC interaction would have profound clinical, therapeutic and pharmaceutical applications. Herein, we review recent developments in predicting cross-reactivity and antigen specificity of TCR recognition. We discuss current experimental and computational approaches to investigate cross-reactivity and antigen-specificity of TCRs and highlight how integrating kinetic, biophysical and structural features may offer valuable insights in modeling immunogenicity. We further underscore the close inter-relationship of these two interconnected notions and the need to investigate each in the light of the other for a better understanding of T cell responsiveness for the effective clinical applications.

HLA-Arena: A Customizable Environment for the Structural Modeling and Analysis of Peptide-HLA Complexes for Cancer Immunotherapy

PURPOSE

HLA protein receptors play a key role in cellular immunity. They bind intracellular peptides and display them for recognition by T-cell lymphocytes. Because T-cell activation is partially driven by structural features of these peptide-HLA complexes, their structural modeling and analysis are becoming central components of cancer immunotherapy projects. Unfortunately, this kind of analysis is limited by the small number of experimentally determined structures of peptide-HLA complexes. Overcoming this limitation requires developing novel computational methods to model and analyze peptide-HLA structures.

METHODS

Here we describe a new platform for the structural modeling and analysis of peptide-HLA complexes, called HLA-Arena, which we have implemented using Jupyter Notebook and Docker. It is a customizable environment that facilitates the use of computational tools, such as APE-Gen and DINC, which we have previously applied to peptide-HLA complexes. By integrating other commonly used tools, such as MODELLER and MHCflurry, this environment includes support for diverse tasks in structural modeling, analysis, and visualization.

RESULTS

To illustrate the capabilities of HLA-Arena, we describe 3 example workflows applied to peptide-HLA complexes. Leveraging the strengths of our tools, DINC and APE-Gen, the first 2 workflows show how to perform geometry prediction for peptide-HLA complexes and structure-based binding prediction, respectively. The third workflow presents an example of large-scale virtual screening of peptides for multiple HLA alleles.

CONCLUSION

These workflows illustrate the potential benefits of HLA-Arena for the structural modeling and analysis of peptide-HLA complexes. Because HLA-Arena can easily be integrated within larger computational pipelines, we expect its potential impact to vastly increase. For instance, it could be used to conduct structural analyses for personalized cancer immunotherapy, neoantigen discovery, or vaccine development.

Microbiota stimulation generates LCMV-specific memory CD8+ T cells in SPF mice and determines their TCR repertoire during LCMV infection

Both mouse and human harbour memory phenotype CD8⁺ T cells specific for antigens in hosts that have not been previously exposed to these antigens. The origin and the nature of the stimuli responsible for generation of CD44^hi CD8⁺ T cells in specific pathogen-free (SPF) mice remain controversial. It is known that microbiota plays a crucial role in the prevention and resolution of systemic infections by influencing myelopoiesis, regulating dendritic cells, inflammasome activation and promoting the production of type I and II interferons. By contrast, here we suggest that microbiota has a direct effect on generation of memory phenotype CD44^hiGP33⁺CD8⁺ T cells. In SPF mice, it generates a novel GP33⁺CD44^hiCD8⁺ T cell sub-population associating the properties of innate and genuine memory cells. These cells are highly enriched in the bone marrow, proliferate rapidly and express immediate effector functions. They dominate the response to LCMV and express particular TCRβ chains. The sequence of these selected TCRβ chains overlaps with that of GP33⁺CD8⁺ T cells directly selected by microbiota in the gut epithelium of SPF mice, demonstrating a common selection mechanism in gut and peripheral CD8⁺ T cell pool. Therefore microbiota has a direct role in priming T cell immunity in SPF mice and in the selection of TCRβ repertoires during systemic infection. We identify a mechanism that primes T cell immunity in SPF mice and may have a major role in colonization resistance and protection from infection.

Novel MHC-Independent αβTCRs Specific for CD48, CD102, and CD155 Self-Proteins and Their Selection in the Thymus

MHC-independent αβTCRs (TCRs) recognize conformational epitopes on native self-proteins and arise in mice lacking both MHC and CD4/CD8 coreceptor proteins. Although naturally generated in the thymus, these TCRs resemble re-engineered therapeutic chimeric antigen receptor (CAR) T cells in their specificity for MHC-independent ligands. Here we identify naturally arising MHC-independent TCRs reactive to three native self-proteins (CD48, CD102, and CD155) involved in cell adhesion. We report that naturally arising MHC-independent TCRs require high affinity TCR-ligand engagements in the thymus to signal positive selection and that high affinity positive selection generates a peripheral TCR repertoire with limited diversity and increased self-reactivity. We conclude that the affinity of TCR-ligand engagements required to signal positive selection in the thymus inversely determines the diversity and self-tolerance of the mature TCR repertoire that is selected.

Structural basis for oligoclonal T cell recognition of a shared p53 cancer neoantigen

Adoptive cell therapy (ACT) with tumor-specific T cells can mediate cancer regression. The main target of tumor-specific T cells are neoantigens arising from mutations in self-proteins. Although the majority of cancer neoantigens are unique to each patient, and therefore not broadly useful for ACT, some are shared. We studied oligoclonal T-cell receptors (TCRs) that recognize a shared neoepitope arising from a driver mutation in the p53 oncogene (p53R175H) presented by HLA-A2. Here we report structures of wild-type and mutant p53-HLA-A2 ligands, as well as structures of three tumor-specific TCRs bound to p53R175H-HLA-A2. These structures reveal how a driver mutation in p53 rendered a self-peptide visible to T cells. The TCRs employ structurally distinct strategies that are highly focused on the mutation to discriminate between mutant and wild-type p53. The TCR-p53R175H-HLA-A2 complexes provide a framework for designing TCRs to improve potency for ACT without sacrificing specificity.

Identification of the Targets of T-cell Receptor Therapeutic Agents and Cells by Use of a High-Throughput Genetic Platform

T-cell receptor (TCR)-based therapeutic cells and agents have emerged as a new class of effective cancer therapies. These therapies work on cells that express intracellular cancer-associated proteins by targeting peptides displayed on MHC receptors. However, cross-reactivities of these agents to off-target cells and tissues have resulted in serious, sometimes fatal, adverse events. We have developed a high-throughput genetic platform (termed "PresentER") that encodes MHC-I peptide minigenes for functional immunologic assays and determines the reactivities of TCR-like therapeutic agents against large libraries of MHC-I ligands. In this article, we demonstrated that PresentER could be used to identify the on-and-off targets of T cells and TCR-mimic (TCRm) antibodies using in vitro coculture assays or binding assays. We found dozens of MHC-I ligands that were cross-reactive with two TCRm antibodies and two native TCRs and that were not easily predictable by other methods.

TCRs with Distinct Specificity Profiles Use Different Binding Modes to Engage an Identical Peptide-HLA Complex

The molecular rules driving TCR cross-reactivity are poorly understood and, consequently, it is unclear the extent to which TCRs targeting the same Ag recognize the same off-target peptides. We determined TCR-peptide-HLA crystal structures and, using a single-chain peptide-HLA phage library, we generated peptide specificity profiles for three newly identified human TCRs specific for the cancer testis Ag NY-ESO-1_157-165-HLA-A2. Two TCRs engaged the same central peptide feature, although were more permissive at peripheral peptide positions and, accordingly, possessed partially overlapping peptide specificity profiles. The third TCR engaged a flipped peptide conformation, leading to the recognition of off-target peptides sharing little similarity with the cognate peptide. These data show that TCRs specific for a cognate peptide recognize discrete peptide repertoires and reconciles how an individual's limited TCR repertoire following negative selection in the thymus is able to recognize a vastly larger antigenic pool.

Identification of Antigenic Targets

The ideal cancer target antigen (Ag) is expressed at high copy numbers on neoplastic cells, absent on normal tissues, and contributes to the survival of cancer cells. Despite significant investments in the identification of cell surface Ags, there is a paucity of targets that meet such ideal cancer target criteria. Recent clinical trials in patients with cancer treated with immune checkpoint inhibitors (ICIs) indicate that cluster of differentiation (CD)8⁺ T cells, by means of their T cell receptors (TCRs) recognizing intracellular targets presented as peptides in the context of human leukocyte antigen (peptide-human leukocyte antigen complex; pHLA) molecules on tumor cells, can mediate deep and long-lasting antitumor responses in patients with solid tumors. Therefore, pHLA-target Ags may represent the long sought-after, ideal targets for solid tumor targeting by high-potency oncology compounds.

Inherent reactivity of unselected TCR repertoires to peptide-MHC molecules

The repertoire of αβ T cell antigen receptors (TCRs) on mature T cells is selected in the thymus where it is rendered both self-tolerant and restricted to the recognition of major histocompatibility complex molecules presenting peptide antigens (pMHC). It remains unclear whether germline TCR sequences exhibit an inherent bias to interact with pMHC prior to selection. Here, we isolated TCR libraries from unselected thymocytes and upon reexpression of these random TCR repertoires in recipient T cell hybridomas, interrogated their reactivities to antigen-presenting cell lines. While these random TCR combinations could potentially have reacted with any surface molecule on the cell lines, the hybridomas were stimulated most frequently by pMHC ligands. The nature and CDR3 loop composition of the TCRβ chain played a dominant role in determining pMHC-reactivity. Replacing the germline regions of mouse TCRβ chains with those of other jawed vertebrates preserved reactivity to mouse pMHC. Finally, introducing the CD4 coreceptor into the hybridomas increased the proportion of cells that could respond to pMHC ligands. Thus, αβ TCRs display an intrinsic and evolutionary conserved bias for pMHC molecules in the absence of any selective pressure, which is further strengthened in the presence of coreceptors.

Molecular evolution of peptides by yeast surface display technology

Genetically encoded peptides possess unique properties, such as a small molecular weight and ease of synthesis and modification, that make them suitable to a large variety of applications. However, despite these favorable qualities, naturally occurring peptides are often limited by intrinsic weak binding affinities, poor selectivity and low stability that ultimately restrain their final use. To overcome these limitations, a large variety of in vitro display methodologies have been developed over the past few decades to evolve genetically encoded peptide molecules with superior properties. Phage display, mRNA display, ribosome display, bacteria display, and yeast display are among the most commonly used methods to engineer peptides. While most of these in vitro methodologies have already been described in detail elsewhere, this review describes solely the yeast surface display technology and its valuable use for the evolution of a wide range of peptide formats.

T-cell-receptor cross-recognition and strategies to select safe T-cell receptors for clinical translation

Adoptive transfer of T-cell-receptor (TCR)-transduced T cells has shown promising results for cancer treatment, but has also produced severe immunotoxicities caused by on-target as well as off-target TCR recognition. Off-target toxicities are related to the ability of a single T cell to cross-recognize and respond to several different peptide–major histocompatibility complex (pMHC) antigens; a property that is essential for providing broad antigenic coverage despite a confined number of unique TCRs in the human body. However, this degeneracy makes it incredibly difficult to account for the range of targets that any TCR might recognize, which represents a major challenge for the clinical development of therapeutic TCRs. The prospect of using affinity-optimized TCRs has been impeded due to observations that affinity enhancement might alter the specificity of a TCR, thereby increasing the risk that it will cross-recognize endogenous tissue. Strategies for selecting safe TCRs for the clinic have included functional assessment after individual incubations with tissue-derived primary cells or with peptides substituted with single amino acids. However, these strategies have not been able to predict cross-recognition sufficiently, leading to fatal cross-reactivity in clinical trials. Novel technologies have emerged that enable extensive characterization of the exact interaction points of a TCR with pMHC, which provides a foundation from which to make predictions of the cross-recognition potential of individual TCRs. This review describes current advances in strategies for dissecting the molecular interaction points of TCRs, focusing on their potential as tools for predicting cross-recognition of TCRs in clinical development.

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T-cell-receptor (TCR) degeneracy plays a fundamental role in the capacity of our immune systems to recognize foreign antigens.

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TCR cross-reactivity provides an inherent risk in TCR–gene transfer cell therapies.

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Advances in description of TCR cross-recognition can guide the selection process for TCRs into clinical use.

Germline-Encoded TCR-MHC Contacts Promote TCR V Gene Bias in Umbilical Cord Blood T Cell Repertoire

T cells recognize antigens as peptides bound to major histocompatibility complex (MHC) proteins through T cell receptors (TCRs) on their surface. To recognize a wide range of pathogens, each individual possesses a substantial number of TCRs with an extremely high degree of variability. It remains controversial whether germline-encoded TCR repertoire is shaped by MHC polymorphism and, if so, what is the preference between MHC genetic variants and TCR V gene compatibility. To investigate the "net" genetic association between MHC variations and TRBV genes, we applied quantitative trait locus (QTL) mapping to test the associations between MHC polymorphism and TCR β chain V (TRBV) genes usage using umbilical cord blood (UCB) samples of 201 Chinese newborns. We found TRBV gene and MHC loci that are predisposed to interact with one another differ from previous conclusions. The majority of MHC amino acid residues associated with the TRBV gene usage show spatial proximities in known structures of TCR-pMHC complexes. These results show for the first time that MHC variants bias TRBV gene usage in UCB of Chinese ancestry and indicate that germline-encoded contacts influence TCR-MHC interactions in intact T cell repertoires.

TCR repertoire and CDR3 motif analyses depict the role of αβ T cells in Ankylosing spondylitis

Background

Ankylosing spondylitis (AS) is a chronic inflammatory disease with worldwide high prevalence. Although AS is strongly associated with HLA-B27 MHC-I antigen presentation, the role played by αβ T cells in AS remains elusive.

Methods

Utilizing TCRβ repertoire sequencing and bioinformatics tools developed in house, we analyzed overall TCR repertoire structures and antigen-recognizing CDR3 motifs in AS patients with different disease activities.

Findings

We found that disease progression is associated with both CD4+ and CD8+ T cell oligo-clonal expansion, which suggests that αβ T cell activation may mediate AS disease progression. By developing a bioinformatics platform to dissect antigen-specific responses, we discovered a cell population consisting of both CD4+ and CD8+ T cells expressing identical TCRs, herein termed CD4/8 T cells. CD4/8 clonotypes were highly enriched in the spondyloarthritic joint fluid of patients, and their expansion correlated with the activity of disease.

Interpretation

These results provide evidence on the T cell clone side to reveal the potential role of CD4/8 T cells in the etiology of AS development.

Single T Cell Sequencing Demonstrates the Functional Role of αβ TCR Pairing in Cell Lineage and Antigen Specificity

Although structural studies of individual T cell receptors (TCRs) have revealed important roles for both the α and β chain in directing MHC and antigen recognition, repertoire-level immunogenomic analyses have historically examined the β chain alone. To determine the amount of useful information about TCR repertoire function encoded within αβ pairings, we analyzed paired TCR sequences from nearly 100,000 unique CD4+ and CD8+ T cells captured using two different high-throughput, single-cell sequencing approaches. Our results demonstrate little overlap in the healthy CD4+ and CD8+ repertoires, with shared TCR sequences possessing significantly shorter CDR3 sequences corresponding to higher generation probabilities. We further utilized tools from information theory and machine learning to show that while α and β chains are only weakly associated with lineage, αβ pairings appear to synergistically drive TCR-MHC interactions. Vαβ gene pairings were found to be the TCR feature most informative of T cell lineage, supporting the existence of germline-encoded paired αβ TCR-MHC interaction motifs. Finally, annotating our TCR pairs using a database of sequences with known antigen specificities, we demonstrate that approximately a third of the T cells possess α and β chains that each recognize different known antigens, suggesting that αβ pairing is critical for the accurate inference of repertoire functionality. Together, these findings provide biological insight into the functional implications of αβ pairing and highlight the utility of single-cell sequencing in immunogenomics.

TCR-induced alteration of primary MHC peptide anchor residue

The HLA-A*02:01-restricted decapeptide EAAGIGILTV, derived from melanoma antigen recognized by T-cells-1 (MART-1) protein, represents one of the best-studied tumor associated T-cell epitopes, but clinical results targeting this peptide have been disappointing. This limitation may reflect the dominance of the nonapeptide, AAGIGILTV, at the melanoma cell surface. The decapeptide and nonapeptide are presented in distinct conformations by HLA-A*02:01 and TCRs from clinically relevant T-cell clones recognize the nonapeptide poorly. Here, we studied the MEL5 TCR that potently recognizes the nonapeptide. The structure of the MEL5-HLA-A*02:01-AAGIGILTV complex revealed an induced fit mechanism of antigen recognition involving altered peptide-MHC anchoring. This "flexing" at the TCR-peptide-MHC interface to accommodate the peptide antigen explains previously observed incongruences in this well-studied system and has important implications for future therapeutic approaches. Finally, this study expands upon the mechanisms by which molecular plasticity can influence antigen recognition by T cells.

Deciphering CD4+ T cell specificity using novel MHC-TCR chimeric receptors

αβ T cell antigen receptors (TCRs) bind complexes of peptide and major histocompatibility complex (pMHC) with low affinity, which poses a considerable challenge for the direct identification of αβ T cell cognate peptides. Here we describe a platform for the discovery of MHC class II epitopes based on the screening of engineered reporter cells expressing novel pMHC-TCR (MCR) hybrid molecules carrying cDNA-derived peptides. This technology identifies natural epitopes of CD4⁺ T cells in an unbiased and efficient manner and allows detailed analysis of TCR cross-reactivity that provides recognition patterns beyond discrete peptides. We determine the cognate peptides of virus- and tumor-specific T cells in mouse disease models and present a proof of concept for human T cells. Furthermore, we use MCR to identify immunogenic tumor neo-antigens and show that vaccination with a peptide naturally recognized by tumor-infiltrating lymphocytes efficiently protects mice from tumor challenge. Thus, the MCR technology holds promise for basic research and clinical applications, allowing the personalized identification of T cell-specific neo-antigens in patients.

The evolving landscape of biomarkers for checkpoint inhibitor immunotherapy

Checkpoint inhibitor-based immunotherapies that target cytotoxic T lymphocyte antigen 4 (CTLA4) or the programmed cell death 1 (PD1) pathway have achieved impressive success in the treatment of different cancer types. Yet, only a subset of patients derive clinical benefit. It is thus critical to understand the determinants driving response, resistance and adverse effects. In this Review, we discuss recent work demonstrating that immune checkpoint inhibitor efficacy is affected by a combination of factors involving tumour genomics, host germline genetics, PD1 ligand 1 (PDL1) levels and other features of the tumour microenvironment, as well as the gut microbiome. We focus on recently identified molecular and cellular determinants of response. A better understanding of how these variables cooperate to affect tumour-host interactions is needed to optimize the implementation of precision immunotherapy.

Improving T Cell Receptor On-Target Specificity via Structure-Guided Design

T cell receptors (TCRs) have emerged as a new class of immunological therapeutics. However, though antigen specificity is a hallmark of adaptive immunity, TCRs themselves do not possess the high specificity of monoclonal antibodies. Although a necessary function of T cell biology, the resulting cross-reactivity presents a significant challenge for TCR-based therapeutic development, as it creates the potential for off-target recognition and immune toxicity. Efforts to enhance TCR specificity by mimicking the antibody maturation process and enhancing affinity can inadvertently exacerbate TCR cross-reactivity. Here we demonstrate this concern by showing that even peptide-targeted mutations in the TCR can introduce new reactivities against peptides that bear similarity to the original target. To counteract this, we explored a novel structure-guided approach for enhancing TCR specificity independent of affinity. Tested with the MART-1-specific TCR DMF5, our approach had a small but discernible impact on cross-reactivity toward MART-1 homologs yet was able to eliminate DMF5 cross-recognition of more divergent, unrelated epitopes. Our study provides a proof of principle for the use of advanced structure-guided design techniques for improving TCR specificity, and it suggests new ways forward for enhancing TCRs for therapeutic use.

T cell receptor fingerprinting enables in-depth characterization of the interactions governing recognition of peptide-MHC complexes

The promiscuous nature of T-cell receptors (TCRs) allows T cells to recognize a large variety of pathogens, but makes it challenging to understand and control T-cell recognition. Existing technologies provide limited information about the key requirements for T-cell recognition and the ability of TCRs to cross-recognize structurally related elements. Here we present a 'one-pot' strategy for determining the interactions that govern TCR recognition of peptide-major histocompatibility complex (pMHC). We measured the relative affinities of TCRs to libraries of barcoded peptide-MHC variants and applied this knowledge to understand the recognition motif, here termed the TCR fingerprint. The TCR fingerprints of 16 different TCRs were identified and used to predict and validate cross-recognized peptides from the human proteome. The identified fingerprints differed among TCRs recognizing the same epitope, demonstrating the value of this strategy for understanding T-cell interactions and assessing potential cross-recognition before selection of TCRs for clinical development.

T cell receptor cross-reactivity expanded by dramatic peptide-MHC adaptability

T cell receptor cross-reactivity allows a fixed T cell repertoire to respond to a much larger universe of potential antigens. Recent work has emphasized the importance of peptide structural and chemical homology, as opposed to sequence similarity, in T cell receptor cross-reactivity. Surprisingly though, T cell receptors can also cross-react between ligands with little physiochemical commonalities. Studying the clinically relevant receptor DMF5, we demonstrate that cross-recognition of such divergent antigens can occur through mechanisms that involve heretofore unanticipated rearrangements in the peptide and presenting MHC protein, including binding-induced peptide register shifts and extensions from MHC peptide binding grooves. Moreover, cross-reactivity can proceed even when such dramatic rearrangements do not translate into structural or chemical molecular mimicry. Beyond demonstrating new principles of T cell receptor cross-reactivity, our results have implications for efforts to predict and control T cell specificity and cross-reactivity, and highlight challenges associated with predicting T cell reactivities.

Stress-testing the relationship between T cell receptor/peptide-MHC affinity and cross-reactivity using peptide velcro

T cell receptors (TCRs) bind to peptide-major histocompatibility complex (pMHC) with low affinity (K_d ∼ μM), which is generally assumed to facilitate cross-reactive TCR "scanning" of ligands. To understand the relationship between TCR/pMHC affinity and cross-reactivity, we sought to engineer an additional weak interaction, termed "velcro," between the TCR and pMHC to probe the specificities of TCRs at relatively low and high affinities. This additional interaction was generated through an eight-amino acid peptide library covalently linked to the N terminus of the MHC-bound peptide. Velcro was selected through an affinity-based isolation and was subsequently shown to enhance the cognate TCR/pMHC affinity in a peptide-dependent manner by ∼10-fold. This was sufficient to convert a nonstimulatory ultra-low-affinity ligand into a stimulatory ligand. An X-ray crystallographic structure revealed how velcro interacts with the TCR. To probe TCR cross-reactivity, we screened TCRs against yeast-displayed pMHC libraries with and without velcro, and found that the peptide cross-reactivity profiles of low-affinity (K_d > 100 μM) and high-affinity (K_d ∼ μM) TCR/pMHC interactions are remarkably similar. The conservation of recognition of the TCR for pMHC across affinities reveals the nature of low-affinity ligands for which there are important biological functions and has implications for understanding the specificities of affinity-matured TCRs.

Respiratory virus-induced heterologous immunity: Part of the problem or part of the solution?

Purpose

To provide current knowledge on respiratory virus-induced heterologous immunity (HI) with a focus on humoral and cellular cross-reactivity. Adaptive heterologous immune responses have broad implications on infection, autoimmunity, allergy and transplant immunology. A better understanding of the mechanisms involved might ultimately open up possibilities for disease prevention, for example by vaccination.

Methods

A structured literature search was performed using Medline and PubMed to provide an overview of the current knowledge on respiratory-virus induced adaptive HI.

Results

In HI the immune response towards one antigen results in an alteration of the immune response towards a second antigen. We provide an overview of respiratory virus-induced HI, including viruses such as respiratory syncytial virus (RSV), rhinovirus (RV), coronavirus (CoV) and influenza virus (IV). We discuss T cell receptor (TCR) and humoral cross-reactivity as mechanisms of HI involving those respiratory viruses. Topics covered include HI between respiratory viruses as well as between respiratory viruses and other pathogens. Newly developed vaccines, which have the potential to provide protection against multiple virus strains are also discussed. Furthermore, respiratory viruses have been implicated in the development of autoimmune diseases, such as narcolepsy, Guillain-Barré syndrome, type 1 diabetes or myocarditis. Finally, we discuss the role of respiratory viruses in asthma and the hygiene hypothesis, and review our recent findings on HI between IV and allergens, which leads to protection from experimental asthma.

Conclusion

Respiratory-virus induced HI may have protective but also detrimental effects on the host. Respiratory viral infections contribute to asthma or autoimmune disease development, but on the other hand, a lack of microbial encounter is associated with an increasing number of allergic as well as autoimmune diseases. Future research might help identify the elements which determine a protective or detrimental outcome in HI-based mechanisms.