A direct estimate of the human alphabeta T cell receptor diversity

Molecular mimicry in the pathogenesis of autoimmune rheumatic diseases

Autoimmune rheumatic diseases (ARDs) are a heterogeneous group of conditions characterized by excessive and misdirected immune responses against the body's own musculoskeletal tissues. Their exact aetiology remains unclear, with genetic, demographic, behavioural and environmental factors implicated in disease onset. One prominent hypothesis for the initial breach of immune tolerance (leading to autoimmunity) is molecular mimicry, which describes structural or sequence similarities between human and microbial proteins (mimotopes). This similarity can lead to cross-reactive antibodies and T-cell receptors, resulting in an immune response against autoantigens. Both commensal microbes in the human microbiome and pathogens can trigger molecular mimicry, thereby potentially contributing to the onset of ARDs. In this review, we focus on the role of molecular mimicry in the onset of rheumatoid arthritis and systemic lupus erythematosus. Moreover, implications of molecular mimicry are also briefly discussed for ankylosing spondylitis, systemic sclerosis and myositis.

Deciphering Autoimmune Diseases: Unveiling the Diagnostic, Therapeutic, and Prognostic Potential of Immune Repertoire Sequencing

Autoimmune diseases (AIDs) are immune system disorders where the body exhibits an immune response to its own antigens, causing damage to its own tissues and organs. The pathogenesis of AIDs is incompletely understood. However, recent advances in immune repertoire sequencing (IR-seq) technology have opened-up a new avenue to study the IR. These studies have revealed the prevalence in IR alterations, potentially inducing AIDs by disrupting immune tolerance and thereby contributing to our comprehension of AIDs. IR-seq harbors significant potential for the clinical diagnosis, personalized treatment, and prognosis of AIDs. This article reviews the application and progress of IR-seq in diseases, such as multiple sclerosis, systemic lupus erythematosus, rheumatoid arthritis, and type 1 diabetes, to enhance our understanding of the pathogenesis of AIDs and offer valuable references for the diagnosis and treatment of AIDs.

Origins of T-cell-mediated autoimmunity in acquired aplastic anaemia

Acquired aplastic anaemia (AA) is an autoimmune bone marrow failure disease resulting from a cytotoxic T-cell-mediated attack on haematopoietic stem and progenitor cells (HSPCs). Despite significant progress in understanding the T-cell repertoire alterations in AA, identifying specific pathogenic T cells in AA patients has remained elusive, primarily due to the unknown antigenic targets of the autoimmune attack. In this review, we will synthesize findings from several decades of research to critically evaluate the current knowledge on T-cell repertoires in AA. We will highlight new insights gained from recent in vitro studies of candidate autoreactive T cells isolated from AA patients and will discuss efforts to identify shared T-cell clonotypes in AA. Finally, we will discuss emerging evidence on the potential T-cell cross-reactivity between HSPC and common viral epitopes that may contribute to the development of AA in some patients. We conclude by highlighting the areas of consensus and limitations, as well as the ongoing uncertainties, and we identify promising directions for future research in the field.

Distinct cellular mechanisms underlie chemotherapies and PD-L1 blockade combinations in triple-negative breast cancer

Combining immune checkpoint blockade (ICB) with chemotherapy shows promise for treating triple-negative breast cancer (TNBC), though the mechanisms remain incompletely understood. Here, we integrate published and new single-cell RNA sequencing (scRNA-seq) data to investigate the tumor immune microenvironment (TIME) in TNBC patients treated with paclitaxel (PTX), nab-paclitaxel (Nab-PTX), and their combinations with the anti-PD-L1 antibody atezolizumab (ATZ). Compared to ATZ plus PTX, ATZ plus Nab-PTX rewires TCF7+ stem-like effector memory CD8+ T cells (Tsem) and CD4+ T follicular helper (Tfh) cells. Nab-paclitaxel, unlike PTX, also reshapes the myeloid compartment, expanding mast cells and pro-inflammatory macrophages. Our analyses in human TNBC and murine models underscore the crucial role of mast cells in orchestrating anti-tumor immune responses, likely by promoting the recruitment and activation of T and B cells. In vivo experiments demonstrate that activating mast cells alongside PD-L1 blockade attenuates TNBC progression, suggesting mast cells as a promising adjunct for enhancing ICB therapy efficacy.

Human memory CD4+ T-cells recognize Mycobacterium tuberculosis-infected macrophages amid broader pathogen-specific responses

Recognition of macrophages infected with Mycobacterium tuberculosis (Mtb) is essential for CD4+ T cells to prevent tuberculosis (TB). Yet not all antigen-specific T cells recognize infected macrophages in human and murine models. Using monocyte-derived macrophages (MDMs) and autologous memory CD4+ T cells from individuals with latent Mtb infection (LTBI), we quantify T cell activation in response to infected macrophages. T cell antigen receptor (TCR) sequencing revealed >70% of unique and >90% of total Mtb-specific TCR clonotypes in stable LTBI are linked to recognition of infected macrophages, while a subset required exogenous antigen exposure, suggesting incomplete recognition. Clonotypes specific for multiple Mtb antigens and other pathogens were identified, indicating Mtb-specific and non-specific activation. Single-cell transcriptomics demonstrates Mtb-specific T cells express signature effector functions dominated by IFNγ, TNF, IL-2, and GM-CSF or chemokine production and signaling. We propose TB vaccines that elicit T cells capable of recognizing infected macrophages and expressing these canonical effector functions will offer protection against TB.

Developing T Cell Epitope-Based Vaccines Against Infection: Challenging but Worthwhile

T cell epitope-based vaccines are designed to elicit long-lived pathogen-specific memory T cells that can quickly activate protective effector functions in response to subsequent infections. These vaccines have the potential to provide sustained protection against mutated variants, such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which are increasingly capable of evading neutralizing antibodies. Recent advancements in epitope discovery, T cell receptor analysis, and bioinformatics have enabled the precise selection of epitopes and the sophisticated design of epitope-based vaccines. This review outlines the development process for T cell epitope-based vaccines. We summarize the current progress in T cell epitope discovery technologies, highlighting the advantages and disadvantages of each method. We also examine advancements in the design and optimization of epitope-based vaccines, particularly through bioinformatics tools. Additionally, we discuss the challenges of validating the accurate processing and presentation of individual epitopes and establishing suitable rodent models to evaluate vaccine immunogenicity and protective efficacy.

A clinical-information-free method for early diagnosis of lung cancer from the patients with pulmonary nodules based on backpropagation neural network model

Lung cancer is the main cause of cancer-related deaths worldwide. Due to lack of obvious clinical symptoms in the early stage of the lung cancer, it is hard to distinguish between malignancy and pulmonary nodules. Understanding the immune responses in the early stage of malignant lung cancer patients may provide new insights for diagnosis. Here, using high-through-put sequencing, we obtained the TCRβ repertoires in the peripheral blood of 100 patients with Stage I lung cancer and 99 patients with benign pulmonary nodules. Our analysis revealed that the usage frequencies of TRBV, TRBJ genes, and V-J pairs and TCR diversities indicated by D50s, Shannon indexes, Simpson indexes, and the frequencies of the largest TCR clone in the malignant samples were significantly different from those in the benign samples. Furthermore, reduced TCR diversities were correlated with the size of pulmonary nodules. Moreover, we built a backpropagation neural network model with no clinical information to identify lung cancer cases from patients with pulmonary nodules using 15 characteristic TCR clones. Based on the model, we have created a web server named "Lung Cancer Prediction" (LCP), which can be accessed at http://i.uestc.edu.cn/LCP/index.html.

Pathophysiology and preclinical relevance of experimental graft-versus-host disease in humanized mice

Graft-versus-host disease (GVHD) is a life-threatening complication of allogeneic hematopoietic cell transplantations (allo-HCT) used for the treatment of hematological malignancies and other blood-related disorders. Until recently, the discovery of actionable molecular targets to treat GVHD and their preclinical testing was almost exclusively based on modeling allo-HCT in mice by transplanting bone marrow and splenocytes from donor mice into MHC-mismatched recipient animals. However, due to fundamental differences between human and mouse immunology, the translation of these molecular targets into the clinic can be limited. Therefore, humanized mouse models of GVHD were developed to circumvent this limitation. In these models, following the transplantation of human peripheral blood mononuclear cells (PBMCs) into immunodeficient mice, T cells recognize and attack mouse organs, inducing GVHD. Thereby, humanized mice provide a platform for the evaluation of the effects of candidate therapies on GVHD mediated by human immune cells in vivo. Understanding the pathophysiology of this xenogeneic GVHD is therefore crucial for the design and interpretation of experiments performed with this model. In this article, we comprehensively review the cellular and molecular mechanisms governing GVHD in the most commonly used model of xenogeneic GVHD: PBMC-engrafted NOD/LtSz-PrkdcscidIL2rγtm1Wjl (NSG) mice. By re-analyzing public sequencing data, we also show that the clonal expansion and the transcriptional program of T cells in humanized mice closely reflect those in humans. Finally, we highlight the strengths and limitations of this model, as well as arguments in favor of its biological relevance for studying T-cell reactions against healthy tissues or cancer cells.

The partitioning of TCR repertoires by thymic selection

αβ T cells are critical components of the adaptive immune system; they maintain tissue and immune homeostasis during health, provide sterilizing immunity after pathogen infection, and are capable of eliminating transformed tumor cells. Fundamental to these distinct functions is the ligand specificity of the unique antigen receptor expressed on each mature T cell (TCR), which endows lymphocytes with the ability to behave in a cell-autonomous, disease context-specific manner. Clone-specific behavioral properties are initially established during T cell development when thymocytes use TCR recognition of major histocompatibility complex (MHC) and MHC-like ligands to instruct survival versus death and to differentiate into a plethora of inflammatory and regulatory T cell lineages. Here, we review the ligand specificity of the preselection thymocyte repertoire and argue that developmental stage-specific alterations in TCR signaling control cross-reactivity and foreign versus self-specificity of T cell sublineages.

Imaging-Based Efficacy Evaluation of Cancer Immunotherapy in Engineered Tumor Platforms and Tumor Organoids

Cancer immunotherapy is used to treat tumors by modulating the immune system. Although the anticancer efficacy of cancer immunotherapy has been evaluated prior to clinical trials, conventional in vivo animal and endpoint models inadequately replicate the intricate process of tumor elimination and reflect human-specific immune systems. Therefore, more sophisticated models that mimic the complex tumor-immune microenvironment must be employed to assess the effectiveness of immunotherapy. Additionally, using real-time imaging technology, a step-by-step evaluation can be applied, allowing for a more precise assessment of treatment efficacy. Here, an overview of the various imaging-based evaluation platforms recently developed for cancer immunotherapeutic applications is presented. Specifically, a fundamental technique is discussed for stably observing immune cell-based tumor cell killing using direct imaging, a microwell that reproduces a confined space for spatial observation, a droplet assay that facilitates cell-cell interactions, and a 3D microphysiological system that reconstructs the vascular environment. Furthermore, it is suggested that future evaluation platforms pursue more human-like immune systems.

Antigen-specific T cells and autoimmunity

Autoimmune diseases (ADs) showcase the intricate balance between the immune system's protective functions and its potential for self-inflicted damage. These disorders arise from the immune system's erroneous targeting of the body's tissues, resulting in damage and disease. The ability of T cells to distinguish between self and non-self-antigens is pivotal to averting autoimmune reactions. Perturbations in this process contribute to AD development. Autoreactive T cells that elude thymic elimination are activated by mimics of self-antigens or are erroneously activated by self-antigens can trigger autoimmune responses. Various mechanisms, including molecular mimicry and bystander activation, contribute to AD initiation, with specific triggers and processes varying across the different ADs. In addition, the formation of neo-epitopes could also be implicated in the emergence of autoreactivity. The specificity of T cell responses centers on the antigen recognition sequences expressed by T cell receptors (TCRs), which recognize peptide fragments displayed by major histocompatibility complex (MHC) molecules. The assortment of TCR gene combinations yields a diverse array of T cell populations, each with distinct affinities for self and non-self antigens. However, new evidence challenges the traditional notion that clonal expansion solely steers the selection of higher-affinity T cells. Lower-affinity T cells also play a substantial role, prompting the "two-hit" hypothesis. High-affinity T cells incite initial responses, while their lower-affinity counterparts perpetuate autoimmunity. Precision treatments that target antigen-specific T cells hold promise for avoiding widespread immunosuppression. Nevertheless, detection of such antigen-specific T cells remains a challenge, and multiple technologies have been developed with different sensitivities while still harboring several drawbacks. In addition, elements such as human leukocyte antigen (HLA) haplotypes and validation through animal models are pivotal for advancing these strategies. In brief, this review delves into the intricate mechanisms contributing to ADs, accentuating the pivotal role(s) of antigen-specific T cells in steering immune responses and disease progression, as well as the novel strategies for the identification of antigen-specific cells and their possible future use in humans. Grasping the mechanisms behind ADs paves the way for targeted therapeutic interventions, potentially enhancing treatment choices while minimizing the risk of systemic immunosuppression.

Immune responses and immunotherapeutic approaches in the treatment against cancer

Cancer cells within a population are heterogeneous due to genomic mutations or epigenetic changes. The immune response to cancer especially the T cell repertoire within the cancer microenvionment is important to the control and growth of cancer cells. When a cancer clone breaks through the surveillance of the immune system, it wins the battle to overcome the host's immune system. In this review, the complicated profile of the cancer microenvironment is emphasized. The molecular evidence of immune responses to cancer has been recently established. Based on these molecular mechanisms of immune interactions with cancer, clinical trials based on checkpoint inhibition therapy against CTLA-4 and/or PD-1 versus PD-L1 have been successful in the treatment of melanoma, lung cancer and other types of cancer. The diversity of the T cell repertoire is described and the tumor infiltrating lymphocytes within the cancer may be expanded ex vivo and infused back to the patient as a treatment modality for adoptive immunotherapy.

The reverse TRBV30 gene of mammals: a defect or superiority in evolution?

At the 3' end of the C2 gene in the mammalian TRB locus, a distinct reverse TRBV30 gene (named TRBV31 in mice) has been conserved throughout evolution. In the fully annotated TRB locus of 14 mammals (including six orders), we observed noteworthy variations in the localization and quality of the reverse V30 genes and Recombination Signal Sequences (RSSs) in the gene trees of 13 mammals. Conversely, the forward V29 genes and RSSs were generally consistent with the species tree of their corresponding species. This finding suggested that the evolution of the reverse V30 gene was not synchronous and likely played a crucial role in regulating adaptive immune responses. To further investigate this possibility, we utilized single-cell TCR sequencing (scTCR-seq) and high-throughput sequencing (HTS) to analyze TCRβ CDR3 repertoires from both central and peripheral tissues of Primates (Homo sapiens and Macaca mulatta), Rodentia (Mus musculus: BALB/c, C57BL/6, and Kunming mice), Artiodactyla (Bos taurus and Bubalus bubalis), and Chiroptera (Rhinolophus affinis and Hipposideros armige). Our investigation revealed several novel observations: (1) The reverse V30 gene exhibits classical rearrangement patterns adhering to the '12/23 rule' and the 'D-J rearrangement preceding the V-(D-J) rearrangement'. This results in the formation of rearranged V30-D2J2, V30-D1J1, and V30-D1J2. However, we also identified 'special rearrangement patterns' wherein V30-D rearrangement preceding D-J rearrangement, giving rise to rearranged V30-D2-J1 and forward Vx-D2-J. (2) Compared to the 'deletional rearrangement' (looping out) of forward V1-V29 genes, the reverse V30 gene exhibits preferential utilization with 'inversional rearrangement'. This may be attributed to the shorter distance between the V30 gene and D gene and the 'inversional rearrangement' modes. In summary, in the mammalian TRB locus, the reverse V30 gene has been uniquely preserved throughout evolution and preferentially utilized in V(D)J recombination, potentially serving a significant role in adaptive immunity. These results will pave the way for novel and specialized research into the mechanisms, efficiency, and function of V(D)J recombination in mammals.

A multi-bin rarefying method for evaluating alpha diversities in TCR sequencing data

MOTIVATION

T cell receptors (TCRs) constitute a major component of our adaptive immune system, governing the recognition and response to internal and external antigens. Studying the TCR diversity via sequencing technology is critical for a deeper understanding of immune dynamics. However, library sizes differ substantially across samples, hindering the accurate estimation/comparisons of alpha diversities. To address this, researchers frequently use an overall rarefying approach in which all samples are sub-sampled to an even depth. Despite its pervasive application, its efficacy has never been rigorously assessed.

RESULTS

In this paper, we develop an innovative "multi-bin" rarefying approach that partitions samples into multiple bins according to their library sizes, conducts rarefying within each bin for alpha diversity calculations, and performs meta-analysis across bins. Extensive simulations using real-world data highlight the inadequacy of the overall rarefying approach in controlling the confounding effect of library size. Our method proves robust in addressing library size confounding, outperforming competing normalization strategies by achieving better-controlled type-I error rates and enhanced statistical power in association tests.

AVAILABILITY AND IMPLEMENTATION

The code is available at https://github.com/mli171/MultibinAlpha. The datasets are freely available at https://doi.org/10.21417/B7001Z and https://doi.org/10.21417/AR2019NC.

Shape of the art: TCR-repertoire after allogeneic hematopoietic cell transplantation

The human adaptive immune repertoire is characterized by specificity and diversity to provide immunity against past and future tasks. Such tasks are mainly infections but also malignant transformations of cells. With its multiple lines of defense, the human immune system contains both, rapid reaction forces and the potential to capture, disassemble and analyze strange structures in order to teach the adaptive immune system and mount a specific immune response. Prevention and mitigation of autoimmunity is of equal importance. In the context of allogeneic hematopoietic cell transplantation (HCT) specific challenges exist with the transfer of cells from the adapted donor immune system to the immunosuppressed recipient. Those challenges are immunogenetic disparity between donor and host, reconstitution of immunity early after HCT by expansion of mature immune effector cells, and impaired thymic function, if the recipient is an adult (as it is the case in most HCTs). The possibility to characterize the adaptive immune repertoire by massively parallel sequencing of T-cell receptor gene rearrangements allows for a much more detailed characterization of the T-cell repertoire. In addition, high-dimensional characterization of immune effector cells based on their immunophenotype and single cell RNA sequencing allow for much deeper insights in adaptive immune responses. We here review, existing - still incomplete - information on immune reconstitution after allogeneic HCT. Building on the technological advances much deeper insights into immune recovery after HCT and adaptive immune responses and can be expected in the coming years.

Characterisation of novel influenza-derived HLA-B*18:01-restricted epitopes

Objectives

Seasonal influenza viruses cause roughly 650 000 deaths annually despite available vaccines. CD8+ T cells typically recognise influenza-derived peptides from internal structural and non-structural influenza proteins and are an attractive avenue for future vaccine design as they could reduce the severity of disease following infection with diverse influenza strains. CD8+ T cells recognise peptides presented by the highly polymorphic Human Leukocyte Antigens class I molecules (HLA-I). Each HLA-I variant has distinct peptide binding preferences, representing a significant obstacle for designing vaccines that elicit CD8+ T cell responses across broad populations. Consequently, the rational design of a CD8+ T cell-mediated vaccine would require the identification of highly immunogenic peptides restricted to a range of different HLA molecules.

Methods

Here, we assessed the immunogenicity of six recently published novel influenza-derived peptides identified by mass-spectrometry and predicted to bind to the prevalent HLA-B*18:01 molecule.

Results

Using CD8+ T cell activation assays and protein biochemistry, we showed that 3/6 of the novel peptides were immunogenic in several HLA-B*18:01+ individuals and confirmed their HLA-B*18:01 restriction. We subsequently compared CD8+ T cell responses towards the previously identified highly immunogenic HLA-B*18:01-restricted NP219 peptide. Using X-ray crystallography, we solved the first crystal structures of HLA-B*18:01 presenting immunogenic influenza-derived peptides. Finally, we dissected the first TCR repertoires specific for HLA-B*18:01 restricted pathogen-derived peptides, identifying private and restricted repertoires against each of the four peptides.

Conclusion

Overall the characterisation of these novel immunogenic peptides provides additional HLA-B*18:01-restricted vaccine targets derived from the Matrix protein 1 and potentially the non-structural protein and the RNA polymerase catalytic subunit of influenza viruses.

Unified cross-modality integration and analysis of T cell receptors and T cell transcriptomes by low-resource-aware representation learning

Single-cell RNA sequencing (scRNA-seq) and T cell receptor sequencing (TCR-seq) are pivotal for investigating T cell heterogeneity. Integrating these modalities, which is expected to uncover profound insights in immunology that might otherwise go unnoticed with a single modality, faces computational challenges due to the low-resource characteristics of the multimodal data. Herein, we present UniTCR, a novel low-resource-aware multimodal representation learning framework designed for the unified cross-modality integration, enabling comprehensive T cell analysis. By designing a dual-modality contrastive learning module and a single-modality preservation module to effectively embed each modality into a common latent space, UniTCR demonstrates versatility in connecting TCR sequences with T cell transcriptomes across various tasks, including single-modality analysis, modality gap analysis, epitope-TCR binding prediction, and TCR profile cross-modality generation, in a low-resource-aware way. Extensive evaluations conducted on multiple scRNA-seq/TCR-seq paired datasets showed the superior performance of UniTCR, exhibiting the ability of exploring the complexity of immune system.

Detecting T-cell clonal expansions and quantifying clone survival using deep profiling of immune repertoires

An individual's T-cell repertoire constantly changes under the influence of external and internal factors. Cells that do not receive a stimulatory signal die, while those that encounter and recognize a pathogen or receive a co-stimulatory signal divide, resulting in clonal expansions. T-cell clones can be traced by monitoring the presence of their unique T-cell receptor (TCR) sequence, which is assembled de novo through a process known as V(D)J rearrangement. Tracking T cells can provide valuable insights into the survival of cells after hematopoietic stem cell transplantation (HSCT) or cancer treatment response and can indicate the induction of protective immunity by vaccination. In this study, we report a bioinformatic method for quantifying the T-cell repertoire dynamics from TCR sequencing data. We demonstrate its utility by measuring the T-cell repertoire stability in healthy donors, by quantifying the effect of donor lymphocyte infusion (DLI), and by tracking the fate of the different T-cell subsets in HSCT patients and the expansion of pathogen-specific clones in vaccinated individuals.

Deciphering Membrane-Protein Interactions and High-Throughput Antigen Identification with Cell Doublets

Deciphering cellular interactions is essential to both understand the mechanisms underlying a broad range of human diseases, but also to manipulate therapies targeting these diseases. Here, the formation of cell doublets resulting from specific membrane ligand-receptor interactions is discovered. Based on this phenomenon, the study developed DoubletSeeker, a novel high-throughput method for the reliable identification of ligand-receptor interactions. The study shows that DoubletSeeker can accurately identify T cell receptor (TCR)-antigen interactions with high sensitivity and specificity. Notably, DoubletSeeker effectively captured paired TCR-peptide major histocompatibility complex (pMHC) information during a highly complex library-on-library screening and successfully identified three mutant TCRs that specifically recognize the MART-1 epitope. In turn, DoubletSeeker can act as an antigen discovery platform that allows for the development of novel immunotherapy targets, making it valuable for investigating fundamental tumor immunology.

A comparison of clustering models for inference of T cell receptor antigen specificity

The vast potential sequence diversity of TCRs and their ligands has presented an historic barrier to computational prediction of TCR epitope specificity, a holy grail of quantitative immunology. One common approach is to cluster sequences together, on the assumption that similar receptors bind similar epitopes. Here, we provide the first independent evaluation of widely used clustering algorithms for TCR specificity inference, observing some variability in predictive performance between models, and marked differences in scalability. Despite these differences, we find that different algorithms produce clusters with high degrees of similarity for receptors recognising the same epitope. Our analysis strengthens the case for use of clustering models to identify signals of common specificity from large repertoires, whilst highlighting scope for improvement of complex models over simple comparators.

BCG immunization induces CX3CR1hi effector memory T cells to provide cross-protection via IFN-γ-mediated trained immunity

After a century of using the Bacillus Calmette-Guérin (BCG) vaccine, our understanding of its ability to provide protection against homologous (Mycobacterium tuberculosis) or heterologous (for example, influenza virus) infections remains limited. Here we show that systemic (intravenous) BCG vaccination provides significant protection against subsequent influenza A virus infection in mice. We further demonstrate that the BCG-mediated cross-protection against influenza A virus is largely due to the enrichment of conventional CD4+ effector CX3CR1hi memory αβ T cells in the circulation and lung parenchyma. Importantly, pulmonary CX3CR1hi T cells limit early viral infection in an antigen-independent manner via potent interferon-γ production, which subsequently enhances long-term antimicrobial activity of alveolar macrophages. These results offer insight into the unknown mechanism by which BCG has persistently displayed broad protection against non-tuberculosis infections via cross-talk between adaptive and innate memory responses.

A hepatic network of dendritic cells mediates CD4 T cell help outside lymphoid organs

While CD4+ T cells are a prerequisite for CD8+ T cell-mediated protection against intracellular hepatotropic pathogens, the mechanisms facilitating the transfer of CD4-help to intrahepatic CD8+ T cells are unknown. Here, we developed an experimental system to investigate cognate CD4+ and CD8+ T cell responses to a model-antigen expressed de novo in hepatocytes and reveal that after initial priming, effector CD4+ and CD8+ T cells migrate into portal tracts and peri-central vein regions of the liver where they cluster with type-1 conventional dendritic cells. These dendritic cells are locally licensed by CD4+ T cells and expand the number of CD8+ T cells in situ, resulting in larger effector and memory CD8+ T cell pools. These findings reveal that CD4+ T cells promote intrahepatic immunity by amplifying the CD8+ T cell response via peripheral licensing of hepatic type-1 conventional dendritic cells and identify intrahepatic perivascular compartments specialized in facilitating effector T cell-dendritic cell interactions.

Current Views about the Inflammatory Damage Triggered by Bacterial Superantigens and Experimental Attempts to Neutralize Superantigen-Mediated Toxic Effects with Natural and Biological Products

Superantigens, i.e., staphylococcal enterotoxins and toxic shock syndrome toxin-1, interact with T cells in a different manner in comparison to conventional antigens. In fact, they activate a larger contingent of T lymphocytes, binding outside the peptide-binding groove of the major histocompatibility complex class II. Involvement of many T cells by superantigens leads to a massive release of pro-inflammatory cytokines, such as interleukin (IL)-1, IL-2, IL-6, tumor necrosis factor-alpha and interferon-gamma. Such a storm of mediators has been shown to account for tissue damage, multiorgan failure and shock. Besides conventional drugs and biotherapeutics, experiments with natural and biological products have been undertaken to attenuate the toxic effects exerted by superantigens. In this review, emphasis will be placed on polyphenols, probiotics, beta-glucans and antimicrobial peptides. In fact, these substances share a common functional denominator, since they skew the immune response toward an anti-inflammatory profile, thus mitigating the cytokine wave evoked by superantigens. However, clinical applications of these products are still scarce, and more trials are needed to validate their usefulness in humans.

TEPCAM: Prediction of T-cell receptor-epitope binding specificity via interpretable deep learning

The recognition of T-cell receptor (TCR) on the surface of T cell to specific epitope presented by the major histocompatibility complex is the key to trigger the immune response. Identifying the binding rules of TCR-epitope pair is crucial for developing immunotherapies, including neoantigen vaccine and drugs. Accurate prediction of TCR-epitope binding specificity via deep learning remains challenging, especially in test cases which are unseen in the training set. Here, we propose TEPCAM (TCR-EPitope identification based on Cross-Attention and Multi-channel convolution), a deep learning model that incorporates self-attention, cross-attention mechanism, and multi-channel convolution to improve the generalizability and enhance the model interpretability. Experimental results demonstrate that our model outperformed several state-of-the-art models on two challenging tasks including a strictly split dataset and an external dataset. Furthermore, the model can learn some interaction patterns between TCR and epitope by extracting the interpretable matrix from cross-attention layer and mapping them to the three-dimensional structures. The source code and data are freely available at https://github.com/Chenjw99/TEPCAM.

Multi-variate model of T cell clonotype competition and homeostasis

Diversity of the naive T cell repertoire is maintained by competition for stimuli provided by self-peptides bound to major histocompatibility complexes (self-pMHCs). We extend an existing bi-variate competition model to a multi-variate model of the dynamics of multiple T cell clonotypes which share stimuli. In order to understand the late-time behaviour of the system, we analyse: (i) the dynamics until the extinction of the first clonotype, (ii) the time to the first extinction event, (iii) the probability of extinction of each clonotype, and (iv) the size of the surviving clonotypes when the first extinction event takes place. We also find the probability distribution of the number of cell divisions per clonotype before its extinction. The mean size of a new clonotype at quasi-steady state is an increasing function of the stimulus available to it, and a decreasing function of the fraction of stimuli it shares with other clonotypes. Thus, the probability of, and time to, extinction of a new clonotype entering the pool of T cell clonotypes is determined by the extent of competition for stimuli it experiences and by its initial number of cells.

Circulating pre-treatment T-cell receptor repertoire as a predictive biomarker in advanced or metastatic non-small-cell lung cancer patients treated with pembrolizumab alone or in combination with chemotherapy

BACKGROUND

The circulating T-cell receptor (TCR) repertoire is a dynamic representation of overall immune responses in an individual.

MATERIALS AND METHODS

We prospectively collected baseline blood from patients treated with first-line pembrolizumab monotherapy or in combination with chemotherapy. TCR repertoire metrics were correlated with clinical benefit rate (CBR), progression-free survival (PFS), overall survival (OS) and immune-related adverse events (irAEs). We built a logistic regression classifier by fitting all four TCR-β repertoire metrics to the immune checkpoint inhibitor (ICI) CBR data. In the subsequent receiver operating characteristic (ROC) analysis of the resulting logistic regression model probabilities, the best cut-off value was selected to maximise sensitivity to predict CBR to ICI.

RESULTS

We observed an association between reduced number of unique clones and CBR among patients treated with pembrolizumab monotherapy (cohort 1) [risk ratio = 2.86, 95% confidence interval (CI) 1.04-8.73, P = 0.039]. For patients treated with pembrolizumab plus chemotherapy (cohort 2), increased number of unique clones [hazard ratio (HR) = 2.96, 95% CI 1.28-6.88, P = 0.012] and Shannon diversity (HR = 2.73, 95% CI 1.08-6.87, P = 0.033), and reduced evenness (HR = 0.43, 95% CI 0.21-0.90, P = 0.025) and convergence (HR = 0.41, 95% CI 0.19-0.90, P = 0.027) were associated with improved PFS, while only an increased number of unique clones (HR = 4.62, 95% CI 1.52-14.02, P = 0.007) were associated with improved OS. Logistic regression models combining the TCR repertoire metrics improved the prediction of CBR (cohorts 1 and 2) and were strongly associated with PFS (cohort 1, HR = 0.38, 95% CI 0.19-0.78, P = 0.009) and OS (cohort 2, HR = 0.20, 95% CI 0.05-0.76, P < 0.0001). Reduced TCR conversion was associated with increased frequency of irAEs needing systemic steroid treatment.

CONCLUSION

Combined pre-treatment circulating TCR metrics might serve as a predictive biomarker for clinical outcomes among patients with advanced non-small-cell lung cancer treated with pembrolizumab alone or in combination with chemotherapy.

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.

Dominant CD4+ T cell receptors remain stable throughout antiretroviral therapy-mediated immune restoration in people with HIV

In people with HIV (PWH), the post-antiretroviral therapy (ART) window is critical for immune restoration and HIV reservoir stabilization. We employ deep immune profiling and T cell receptor (TCR) sequencing and examine proliferation to assess how ART impacts T cell homeostasis. In PWH on long-term ART, lymphocyte frequencies and phenotypes are mostly stable. By contrast, broad phenotypic changes in natural killer (NK) cells, γδ T cells, B cells, and CD4+ and CD8+ T cells are observed in the post-ART window. Whereas CD8+ T cells mostly restore, memory CD4+ T subsets and cytolytic NK cells show incomplete restoration 1.4 years post ART. Surprisingly, the hierarchies and frequencies of dominant CD4 TCR clonotypes (0.1%-11% of all CD4+ T cells) remain stable post ART, suggesting that clonal homeostasis can be independent of homeostatic processes regulating CD4+ T cell absolute number, phenotypes, and function. The slow restoration of host immunity post ART also has implications for the design of ART interruption studies.

Challenges and solutions for therapeutic TCR-based agents

Recent development of methods to discover and engineer therapeutic T-cell receptors (TCRs) or antibody mimics of TCRs, and to understand their immunology and pharmacology, lag two decades behind therapeutic antibodies. Yet we have every expectation that TCR-based agents will be similarly important contributors to the treatment of a variety of medical conditions, especially cancers. TCR engineered cells, soluble TCRs and their derivatives, TCR-mimic antibodies, and TCR-based CAR T cells promise the possibility of highly specific drugs that can expand the scope of immunologic agents to recognize intracellular targets, including mutated proteins and undruggable transcription factors, not accessible by traditional antibodies. Hurdles exist regarding discovery, specificity, pharmacokinetics, and best modality of use that will need to be overcome before the full potential of TCR-based agents is achieved. HLA restriction may limit each agent to patient subpopulations and off-target reactivities remain important barriers to widespread development and use of these new agents. In this review we discuss the unique opportunities for these new classes of drugs, describe their unique antigenic targets, compare them to traditional antibody therapeutics and CAR T cells, and review the various obstacles that must be overcome before full application of these drugs can be realized.

Better safe than sorry: Naive T-cell dynamics in healthy ageing

It is well-known that the functioning of the immune system gradually deteriorates with age, and we are increasingly confronted with its consequences as the life expectancy of the human population increases. Changes in the T-cell pool are among the most prominent features of the changing immune system during healthy ageing, and changes in the naive T-cell pool in particular are generally held responsible for its gradual deterioration. These changes in the naive T-cell pool are thought to be due to involution of the thymus. It is commonly believed that the gradual loss of thymic output induces compensatory mechanisms to maintain the number of naive T cells at a relatively constant level, and induces a loss of diversity in the T-cell repertoire. Here we review the studies that support or challenge this widely-held view of immune ageing and discuss the implications for vaccination strategies.

Sex- and age-specific aspects of human peripheral T-cell dynamics

Background

The diversity of the antigenic T cell receptor (TCR) repertoire clonally expressed on T lymphocytes is a key element of the adaptive immune system protective functions. A decline in diversity in the older adults is associated with health deterioration. This diversity is generated by the rearrangement of TRB genes coding for TCR chains during lymphocyte differentiation in the thymus, but is essentially maintained by peripheral T lymphocytes proliferation for most of life. Deep sequencing of rearranged TRB genes from blood cells allows the monitoring of peripheral T cell repertoire dynamics. We analysed two aspects of rearranged TRB diversity, related to T lymphocyte proliferation and to the distribution of the T cell clone size, in a collection of repertoires obtained from 1 to 74 years-old donors.

Results

Our results show that peripheral T lymphocytes expansion differs according to the recombination status of their TRB loci. Their proliferation rate changes with age, with different patterns in men and women. T cell clone size becomes more heterogeneous with time, and, in adults, is always more even in women. Importantly, a longitudinal analysis of TRB repertoires obtained at ten years intervals from individual men and women confirms the findings of this cross-sectional study.

Conclusions

Peripheral T lymphocyte proliferation partially depends on their thymic developmental history. The rate of proliferation of T cells differing in their TRB rearrangement status is different in men and women before the age of 18 years old, but similar thereafter.

Molecular mimicry and autoimmunity in the time of COVID-19

Infectious diseases are commonly implicated as potential initiators of autoimmune diseases (ADs) and represent the most commonly known factor in the development of autoimmunity in susceptible individuals. Epidemiological data and animal studies on multiple ADs suggest that molecular mimicry is one of the likely mechanisms for the loss of peripheral tolerance and the development of clinical disease. Besides molecular mimicry, other mechanisms such as defects in central tolerance, nonspecific bystander activation, epitope-determinant spreading, and/or constant antigenic stimuli, may also contribute for breach of tolerance and to the development of ADs. Linear peptide homology is not the only mechanism by which molecular mimicry is established. Peptide modeling (i.e., 3D structure), molecular docking analyses, and affinity estimation for HLAs are emerging as critical strategies when studying the links of molecular mimicry in the development of autoimmunity. In the current pandemic, several reports have confirmed an influence of SARS-CoV-2 on subsequent autoimmunity. Bioinformatic and experimental evidence support the potential role of molecular mimicry. Peptide dimensional analysis requires more research and will be increasingly important for designing and distributing vaccines and better understanding the role of environmental factors related to autoimmunity.

Beyond the amyloid hypothesis: how current research implicates autoimmunity in Alzheimer's disease pathogenesis

The amyloid hypothesis has so far been at the forefront of explaining the pathogenesis of Alzheimer's Disease (AD), a progressive neurodegenerative disorder that leads to cognitive decline and eventual death. Recent evidence, however, points to additional factors that contribute to the pathogenesis of this disease. These include the neurovascular hypothesis, the mitochondrial cascade hypothesis, the inflammatory hypothesis, the prion hypothesis, the mutational accumulation hypothesis, and the autoimmunity hypothesis. The purpose of this review was to briefly discuss the factors that are associated with autoimmunity in humans, including sex, the gut and lung microbiomes, age, genetics, and environmental factors. Subsequently, it was to examine the rise of autoimmune phenomena in AD, which can be instigated by a blood-brain barrier breakdown, pathogen infections, and dysfunction of the glymphatic system. Lastly, it was to discuss the various ways by which immune system dysregulation leads to AD, immunomodulating therapies, and future directions in the field of autoimmunity and neurodegeneration. A comprehensive account of the recent research done in the field was extracted from PubMed on 31 January 2022, with the keywords "Alzheimer's disease" and "autoantibodies" for the first search input, and "Alzheimer's disease" with "IgG" for the second. From the first search, 19 papers were selected, because they contained recent research on the autoantibodies found in the biofluids of patients with AD. From the second search, four papers were selected. The analysis of the literature has led to support the autoimmune hypothesis in AD. Autoantibodies were found in biofluids (serum/plasma, cerebrospinal fluid) of patients with AD with multiple methods, including ELISA, Mass Spectrometry, and microarray analysis. Through continuous research, the understanding of the synergistic effects of the various components that lead to AD will pave the way for better therapeutic methods and a deeper understanding of the disease.

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.

A novel statistical method for decontaminating T-cell receptor sequencing data

The T-cell receptor (TCR) repertoire is highly diverse among the population and plays an essential role in initiating multiple immune processes. TCR sequencing (TCR-seq) has been developed to profile the T cell repertoire. Similar to other high-throughput experiments, contamination can happen during several steps of TCR-seq, including sample collection, preparation and sequencing. Such contamination creates artifacts in the data, leading to inaccurate or even biased results. Most existing methods assume 'clean' TCR-seq data as the starting point with no ability to handle data contamination. Here, we develop a novel statistical model to systematically detect and remove contamination in TCR-seq data. We summarize the observed contamination into two sources, pairwise and cross-cohort. For both sources, we provide visualizations and summary statistics to help users assess the severity of the contamination. Incorporating prior information from 14 existing TCR-seq datasets with minimum contamination, we develop a straightforward Bayesian model to statistically identify contaminated samples. We further provide strategies for removing the impacted sequences to allow for downstream analysis, thus avoiding any need to repeat experiments. Our proposed model shows robustness in contamination detection compared with a few off-the-shelf detection methods in simulation studies. We illustrate the use of our proposed method on two TCR-seq datasets generated locally.

The good and the bad of T cell cross-reactivity: challenges and opportunities for novel therapeutics in autoimmunity and cancer

T cells are main actors of the immune system with an essential role in protection against pathogens and cancer. The molecular key event involved in this absolutely central task is the interaction of membrane-bound specific T cell receptors with peptide-MHC complexes which initiates T cell priming, activation and recall, and thus controls a range of downstream functions. While textbooks teach us that the repertoire of mature T cells is highly diverse, it is clear that this diversity cannot possibly cover all potential foreign peptides that might be encountered during life. TCR cross-reactivity, i.e. the ability of a single TCR to recognise different peptides, offers the best solution to this biological challenge. Reports have shown that indeed, TCR cross-reactivity is surprisingly high. Hence, the T cell dilemma is the following: be as specific as possible to target foreign danger and spare self, while being able to react to a large spectrum of body-threatening situations. This has major consequences for both autoimmune diseases and cancer, and significant implications for the development of T cell-based therapies. In this review, we will present essential experimental evidence of T cell cross-reactivity, implications for two opposite immune conditions, i.e. autoimmunity vs cancer, and how this can be differently exploited for immunotherapy approaches. Finally, we will discuss the tools available for predicting cross-reactivity and how improvements in this field might boost translational approaches.

Improved T cell receptor antigen pairing through data-driven filtering of sequencing information from single cells

Novel single-cell-based technologies hold the promise of matching T cell receptor (TCR) sequences with their cognate peptide-MHC recognition motif in a high-throughput manner. Parallel capture of TCR transcripts and peptide-MHC is enabled through the use of reagents labeled with DNA barcodes. However, analysis and annotation of such single-cell sequencing (SCseq) data are challenged by dropout, random noise, and other technical artifacts that must be carefully handled in the downstream processing steps. We here propose a rational, data-driven method termed ITRAP (improved T cell Receptor Antigen Paring) to deal with these challenges, filtering away likely artifacts, and enable the generation of large sets of TCR-pMHC sequence data with a high degree of specificity and sensitivity, thus outputting the most likely pMHC target per T cell. We have validated this approach across 10 different virus-specific T cell responses in 16 healthy donors. Across these samples, we have identified up to 1494 high-confident TCR-pMHC pairs derived from 4135 single cells.

TPBTE: A model based on convolutional Transformer for predicting the binding of TCR to epitope

T cell receptors (TCRs) selectively bind to antigens to fight pathogens with specific immunity. Current tools focus on the nature of amino acids within sequences and take less into account the nature of amino acids far apart and the relationship between sequences, leading to significant differences in the results from different datasets. We propose TPBTE, a model based on convolutional Transformer for Predicting the Binding of TCR to Epitope. It takes epitope sequences and the complementary decision region 3 (CDR3) sequences of TCRβ chain as inputs. And it uses a convolutional attention mechanism to learn amino acid representations between different positions of the sequences based on learning local features of the sequences. At the same time, it uses cross attention to learn the interaction information between TCR sequences and epitope sequences. A comprehensive evaluation of the TCR-epitope data shows that the average area under the curve of TPBTE outperforms the baseline model, and demonstrate an intentional performance. In addition, TPBTE can give the probability of binding TCR to epitopes, which can be used as the first step of epitope screening, narrowing the scope of epitope search and reducing the time of epitope search.

Molecular mimicry and cancer vaccine development

BACKGROUND

The development of cancer immunotherapeutic strategies relies on the identification and validation of optimal target tumor antigens, which should be tumor-specific as well as able to elicit a swift and potent anti-tumor immune response. The vast majority of such strategies are based on tumor associated antigens (TAAs) which are shared wild type cellular self-epitopes highly expressed on tumor cells. Indeed, TAAs can be used to develop off-the-shelf cancer vaccines appropriate to all patients affected by the same malignancy. However, given that they may be also presented by HLAs on the surface of non-malignant cells, they may be possibly affected by immunological tolerance or elicit autoimmune responses.

MAIN BODY

In order to overcome such limitations, analogue peptides with improved antigenicity and immunogenicity able to elicit a cross-reactive T cell response are needed. To this aim, non-self-antigens derived from microorganisms (MoAs) may be of great benefit.

Structural analysis of cancer-relevant TCR-CD3 and peptide-MHC complexes by cryoEM

The recognition of antigenic peptide-MHC (pMHC) molecules by T-cell receptors (TCR) initiates the T-cell mediated immune response. Structural characterization is key for understanding the specificity of TCR-pMHC interactions and informing the development of therapeutics. Despite the rapid rise of single particle cryoelectron microscopy (cryoEM), x-ray crystallography has remained the preferred method for structure determination of TCR-pMHC complexes. Here, we report cryoEM structures of two distinct full-length α/β TCR-CD3 complexes bound to their pMHC ligand, the cancer-testis antigen HLA-A2/MAGEA4 (230-239). We also determined cryoEM structures of pMHCs containing MAGEA4 (230-239) peptide and the closely related MAGEA8 (232-241) peptide in the absence of TCR, which provided a structural explanation for the MAGEA4 preference displayed by the TCRs. These findings provide insights into the TCR recognition of a clinically relevant cancer antigen and demonstrate the utility of cryoEM for high-resolution structural analysis of TCR-pMHC interactions.

T cell receptor signaling in the differentiation and plasticity of CD4+ T cells

CD4⁺ T cells are critical components of the adaptive immune system. The T cell receptor (TCR) and co-receptor signaling cascades shape the phenotype and functions of CD4⁺ T cells. TCR signaling plays a crucial role in T cell development, antigen recognition, activation, and differentiation upon recognition of foreign- or auto-antigens. In specific autoimmune conditions, altered TCR repertoire is reported and can predispose autoimmunity with organ-specific inflammation and tissue damage. TCR signaling modulates various signaling cascades and regulates epigenetic and transcriptional regulation during homeostasis and disease conditions. Understanding the mechanism by which coreceptors and cytokine signals control the magnitude of TCR signal amplification will aid in developing therapeutic strategies to treat inflammation and autoimmune diseases. This review focuses on the role of the TCR signaling cascade and its components in the activation, differentiation, and plasticity of various CD4⁺ T cell subsets.

The Function of Memory CD8+ T Cells in Immunotherapy for Human Diseases

Memory T (Tm) cells protect against Ags that they have previously contacted with a fast and robust response. Therefore, developing long-lived Tm cells is a prime goal for many vaccines and therapies to treat human diseases. The remarkable characteristics of Tm cells have led scientists and clinicians to devise methods to make Tm cells more useful. Recently, Tm cells have been highlighted for their role in coronavirus disease 2019 vaccines during the ongoing global pandemic. The importance of Tm cells in cancer has been emerging. However, the precise characteristics and functions of Tm cells in these diseases are not completely understood. In this review, we summarize the known characteristics of Tm cells and their implications in the development of vaccines and immunotherapies for human diseases. In addition, we propose to exploit the beneficial characteristics of Tm cells to develop strategies for effective vaccines and overcome the obstacles of immunotherapy.

Modeling and predicting the overlap of B- and T-cell receptor repertoires in healthy and SARS-CoV-2 infected individuals

Adaptive immunity's success relies on the extraordinary diversity of protein receptors on B and T cell membranes. Despite this diversity, the existence of public receptors shared by many individuals gives hope for developing population-wide vaccines and therapeutics. Using probabilistic modeling, we show many of these public receptors are shared by chance in healthy individuals. This predictable overlap is driven not only by biases in the random generation process of receptors, as previously reported, but also by their common functional selection. However, the model underestimates sharing between repertoires of individuals infected with SARS-CoV-2, suggesting strong specific antigen-driven convergent selection. We exploit this discrepancy to identify COVID-associated receptors, which we validate against datasets of receptors with known viral specificity. We study their properties in terms of sequence features and network organization, and use them to design an accurate diagnostic tool for predicting SARS-CoV-2 status from repertoire data.

Decoupling peptide binding from T cell receptor recognition with engineered chimeric MHC-I molecules

Major Histocompatibility Complex class I (MHC-I) molecules display self, viral or aberrant epitopic peptides to T cell receptors (TCRs), which employ interactions between complementarity-determining regions with both peptide and MHC-I heavy chain 'framework' residues to recognize specific Human Leucocyte Antigens (HLAs). The highly polymorphic nature of the HLA peptide-binding groove suggests a malleability of interactions within a common structural scaffold. Here, using structural data from peptide:MHC-I and pMHC:TCR structures, we first identify residues important for peptide and/or TCR binding. We then outline a fixed-backbone computational design approach for engineering synthetic molecules that combine peptide binding and TCR recognition surfaces from existing HLA allotypes. X-ray crystallography demonstrates that chimeric molecules bridging divergent HLA alleles can bind selected peptide antigens in a specified backbone conformation. Finally, in vitro tetramer staining and biophysical binding experiments using chimeric pMHC-I molecules presenting established antigens further demonstrate the requirement of TCR recognition on interactions with HLA framework residues, as opposed to interactions with peptide-centric Chimeric Antigen Receptors (CARs). Our results underscore a novel, structure-guided platform for developing synthetic HLA molecules with desired properties as screening probes for peptide-centric interactions with TCRs and other therapeutic modalities.

T-cell repertoire diversity: friend or foe for protective antitumor response?

Profiling the T-Cell Receptor (TCR) repertoire is establishing as a potent approach to investigate autologous and treatment-induced antitumor immune response. Technical and computational breakthroughs, including high throughput next-generation sequencing (NGS) approaches and spatial transcriptomics, are providing unprecedented insight into the mechanisms underlying antitumor immunity. A precise spatiotemporal variation of T-cell repertoire, which dynamically mirrors the functional state of the evolving host-cancer interaction, allows the tracking of the T-cell populations at play, and may identify the key cells responsible for tumor eradication, the evaluation of minimal residual disease and the identification of biomarkers of response to immunotherapy. In this review we will discuss the relationship between global metrics characterizing the TCR repertoire such as T-cell clonality and diversity and the resultant functional responses. In particular, we will explore how specific TCR repertoires in cancer patients can be predictive of prognosis or response to therapy and in particular how a given TCR re-arrangement, following immunotherapy, can predict a specific clinical outcome. Finally, we will examine current improvements in terms of T-cell sequencing, discussing advantages and challenges of current methodologies.

Rapid identification of CMV-specific TCRs via reverse TCR cloning system based on bulk TCR repertoire data

Advances in next-generation sequencing (NGS) have improved the resolution of T-cell receptor (TCR) repertoire analysis, and recent single-cell sequencing has made it possible to obtain information about TCR pairs. In our previous study, cytomegalovirus (CMV) pp65-specific T-cell response restricted by a single human leukocyte antigen (HLA) class I allotype was observed in an individual. Therefore, to effectively clone an antigen-specific TCR from these T cells, we developed a TCR cloning system that does not require a single cell level. First, we established the improved Jurkat reporter cell line, which was TCRαβ double knock-out and expressed CD8αβ molecules. Furthermore, functional TCRs were directly obtained by reverse TCR cloning using unique CDR3-specific PCR primers after bulk TCR sequencing of activation marker-positive CD8 T cells by NGS. A total of 15 TCRα and 14 TCRβ strands were successfully amplified by PCR from cDNA of 4-1BB-positive CD8 T cells restricted by HLA-A*02:01, HLA-A*02:06, HLA-B*07:02, and HLA-B*40:06. The panels with combinations of TCRα and TCRβ genes were investigated using Jurkat reporter cell line and artificial antigen-presenting cells (APCs). In two TCR pairs restricted by HLA-A*02:01, one TCR pair by HLA-A*02:06, four TCR pairs by HLA-B*07:02, and one TCR pair by HLA-B*40:06, their specificity and affinity were confirmed. The TCR pair of A*02:01/1-1 showed alloreactivity to HLA-A*02:06. The one TCR pair showed a higher response to the naturally processed antigen than that of the peptide pool. This reverse TCR cloning system will not only provide functional information to TCR repertoire analysis by NGS but also help in the development of TCR-T therapy.

An Attention Based Bidirectional LSTM Method to Predict the Binding of TCR and Epitope

The T-cell epitope prediction has always been a long-term challenge in immunoinformatics and bioinformatics. Studying the specific recognition between T-cell receptor (TCR) and peptide-major histocompatibility complex (p-MHC) complexes can help us better understand the immune mechanism, it's also make a signification contribution in developing vaccines and targeted drugs. Meanwhile, more advanced methods are needed for distinguishing TCRs binding from different epitopes. In this paper, we introduce a hybrid model composed of bidirectional long short-term memory networks (BiLSTM), attention and convolutional neural networks (CNN) that can identified the binding of TCRs to epitopes. The BiLSTM can more completely extract amino acid forward and backward information in the sequence, and attention mechanism can focus on amino acids at certain positions from complex sequences to capture the most important feature, then CNN was used to further extract salient features to predict the binding of TCR-epitope. In McPAS dataset, the AUC value (the area under ROC curve) of naive TCR-epitope binding is 0.974 and specific TCR-epitope binding is 0.887. The model has achieved better prediction results than other existing models (TCRGP, ERGO, NetTCR), and some experiments are used to analyze the advantages of our model. The algorithm is available at https://github.com/bijingshu/BiAttCNN.git.

Profiling genes encoding the adaptive immune receptor repertoire with gAIRR Suite

Adaptive immune receptor repertoire (AIRR) is encoded by T cell receptor (TR) and immunoglobulin (IG) genes. Profiling these germline genes encoding AIRR (abbreviated as gAIRR) is important in understanding adaptive immune responses but is challenging due to the high genetic complexity. Our gAIRR Suite comprises three modules. gAIRR-seq, a probe capture-based targeted sequencing pipeline, profiles gAIRR from individual DNA samples. gAIRR-call and gAIRR-annotate call alleles from gAIRR-seq reads and annotate whole-genome assemblies, respectively. We gAIRR-seqed TRV and TRJ of seven Genome in a Bottle (GIAB) DNA samples with 100% accuracy and discovered novel alleles. We also gAIRR-seqed and gAIRR-called the TR and IG genes of a subject from both the peripheral blood mononuclear cells (PBMC) and oral mucosal cells. The calling results from these two cell types have a high concordance (99% for all known gAIRR alleles). We gAIRR-annotated 36 genomes to unearth 325 novel TRV alleles and 29 novel TRJ alleles. We could further profile the flanking sequences, including the recombination signal sequence (RSS). We validated two structural variants for HG002 and uncovered substantial differences of gAIRR genes in references GRCh37 and GRCh38. gAIRR Suite serves as a resource to sequence, analyze, and validate germline TR and IG genes to study various immune-related phenotypes.

Evaluation and comparison of adaptive immunity through analyzing the diversities and clonalities of T-cell receptor repertoires in the peripheral blood

The adaptive immune system plays an important role in defending against different kinds of diseases, including infection and cancer. There has been a longtime need for a simple method to quantitatively evaluate the potency of adaptive immunity in our bodies. The tremendously diversified T-cell receptor (TCR) repertoires are the foundation of the adaptive immune system. In this study, we analyzed the expressed TCRβ repertoires in the peripheral blood of 582 healthy donors and 60 cancer patients. The TCR repertoire in each individual is different, with different usages of TCR Vβ and Jβ genes. Importantly, the TCR diversity and clonality change along with age and disease situation. Most elder individuals and cancer patients have elevated numbers of large TCRβ clones and reduced numbers of shared common clones, and thus, they have very low TCR diversity index (D₅₀) values. These results reveal the alteration of the expressed TCRβ repertoire with aging and oncogenesis, and thus, we hypothesize that the TCR diversity and clonality in the peripheral blood might be used to evaluate and compare the adaptive immunities among different individuals in clinical practice.

Human abdominal aortic aneurysm (AAA): Evidence for an autoimmune antigen-driven disease

Abdominal aortic aneurism (AAA) is a complex immunological disease with a strong genetic component, and one of the ten leading causes of death of individuals 55-74 years old worldwide. Strong evidence has been accumulated suggesting that AAA is an autoimmune specific antigen-driven disease. Mononuclear cells infiltrating AAA lesions comprised of T and B lymphocytes and other cells expressing early-, intermediate- and late-activation antigens, and the presence of antigen-presenting cells have been documented, demonstrating an ongoing immune response. The three components of the trimolecular complex, T-cell receptor (TCR)/peptide (antigen)/HLA have been identified in AAA, and specifically: (i) clonal expansions of T-cell clones in AAA lesions; (ii) the association of AAA with particular HLA Class I and Class II; and (iii) self or nonself putative AAA-associated antigens. IgG autoantibodies recognizing proteins present in normal aortic tissue have been reported in patients with AAA. Molecular mimicry, defined as the sharing of antigenic epitopes between microorganisms (bacteria, viruses) and self antigens, maybe is responsible for T-cell responses and antibody production in AAA. Also, the frequency and the suppressor activity of CD4 + CD25 + FOXP3+ Tregs and the expression of FOXP3 transcripts and protein have been reported to be significantly impaired in AAA patients vs normal donors.