Quantifiable predictive features define epitope-specific T cell receptor repertoires

Evolution and modulation of antigen-specific T cell responses in melanoma patients

Analyzing antigen-specific T cell responses at scale has been challenging. Here, we analyze three types of T cell receptor (TCR) repertoire data (antigen-specific TCRs, TCR-repertoire, and single-cell RNA + TCRαβ-sequencing data) from 515 patients with primary or metastatic melanoma and compare it to 783 healthy controls. Although melanoma-associated antigen (MAA) -specific TCRs are restricted to individuals, they share sequence similarities that allow us to build classifiers for predicting anti-MAA T cells. The frequency of anti-MAA T cells distinguishes melanoma patients from healthy and predicts metastatic recurrence from primary melanoma. Anti-MAA T cells have stem-like properties and frequent interactions with regulatory T cells and tumor cells via Galectin9-TIM3 and PVR-TIGIT -axes, respectively. In the responding patients, the number of expanded anti-MAA clones are higher after the anti-PD1(+anti-CTLA4) therapy and the exhaustion phenotype is rescued. Our systems immunology approach paves the way for understanding antigen-specific responses in human disorders.

Previous studies have characterized the diversity and dynamics of the T cell receptor (TCR) repertoire in patients with solid cancer. Here, by analyzing TCR repertoire data from multiple datasets, the authors report that melanoma-associated antigen-specific TCRs can be used to separate metastatic melanoma patients from healthy controls and to follow anti-tumor responses in patients treated with immunotherapy.

CD8+ T cell clonotypes from prior SARS-CoV-2 infection predominate during the cellular immune response to mRNA vaccination

Almost three years into the SARS-CoV-2 pandemic, hybrid immunity is highly prevalent worldwide and more protective than vaccination or prior infection alone. Given emerging resistance of variant strains to neutralizing antibodies (nAb), it is likely that T cells contribute to this protection. To understand how sequential SARS-CoV-2 infection and mRNA-vectored SARS-CoV-2 spike (S) vaccines affect T cell clonotype-level expansion kinetics, we identified and cross-referenced TCR sequences from thousands of S-reactive single cells against deeply sequenced peripheral blood TCR repertoires longitudinally collected from persons during COVID-19 convalescence through booster vaccination. Successive vaccinations recalled memory T cells and elicited antigen-specific T cell clonotypes not detected after infection. Vaccine-related recruitment of novel clonotypes and the expansion of S-specific clones were most strongly observed for CD8+ T cells. Severe COVID-19 illness was associated with a more diverse CD4+ T cell response to SARS-CoV-2 both prior to and after mRNA vaccination, suggesting imprinting of CD4+ T cells by severe infection. TCR sequence similarity search algorithms revealed myriad public TCR clusters correlating with human leukocyte antigen (HLA) alleles. Selected TCRs from distinct clusters functionally recognized S in the predicted HLA context, with fine viral peptide requirements differing between TCRs. Most subjects tested had S-specific T cells in the nasal mucosa after a 3rd mRNA vaccine dose. The blood and nasal T cell responses to vaccination revealed by clonal tracking were more heterogeneous than nAb boosts. Analysis of bulk and single cell TCR sequences reveals T cell kinetics and diversity at the clonotype level, without requiring prior knowledge of T cell epitopes or HLA restriction, providing a roadmap for rapid assessment of T cell responses to emerging pathogens.

T cell Repertoire Profiling and the Mechanism by which HLA-B27 Causes Ankylosing Spondylitis

Purpose of Review

Ankylosing spondylitis (AS) is strongly associated with the HLA-B27 gene. The canonical function of HLA-B27 is to present antigenic peptides to CD8 lymphocytes, leading to adaptive immune responses. The ‘arthritogenic peptide’ theory as to the mechanism by which HLA-B27 induces ankylosing spondylitis proposes that HLA-B27 presents peptides derived from exogenous sources such as bacteria to CD8 lymphocytes, which subsequently cross-react with antigens at the site of inflammation of the disease, causing inflammation. This review describes findings of studies in AS involving profiling of T cell expansions and discusses future research opportunities based on these findings.

Recent Findings

Consistent with this theory, there is an expanding body of data showing that expansion of a restricted pool of CD8 lymphocytes is found in most AS patients yet only in a small proportion of healthy HLA-B27 carriers.

Summary

These exciting findings strongly support the theory that AS is driven by presentation of antigenic peptides to the adaptive immune system by HLA-B27. They point to new potential approaches to identify the exogenous and endogenous antigens involved and to potential therapies for the disease.

Autoreactive CD8 T cells in NOD mice exhibit phenotypic heterogeneity but restricted TCR gene usage

Paired scRNA-seq and scTCR-seq reveals that diabetogenic CD8 T cells in the islets and spleens of NOD mice exhibit phenotypic and clonal heterogeneity despite restricted TCR gene usage. Expression of certain TCR genes correlates with clonal proliferation and effector phenotype.

Type 1 diabetes (T1D) is an autoimmune disorder defined by CD8 T cell–mediated destruction of pancreatic β cells. We have previously shown that diabetogenic CD8 T cells in the islets of non-obese diabetic mice are phenotypically heterogeneous, but clonal heterogeneity remains relatively unexplored. Here, we use paired single-cell RNA and T-cell receptor sequencing (scRNA-seq and scTCR-seq) to characterize autoreactive CD8 T cells from the islets and spleens of non-obese diabetic mice. scTCR-seq demonstrates that CD8 T cells targeting the immunodominant β-cell epitope IGRP_206-214 exhibit restricted TCR gene usage. scRNA-seq identifies six clusters of autoreactive CD8 T cells in the islets and six in the spleen, including memory and exhausted cells. Clonal overlap between IGRP_206-214–reactive CD8 T cells in the islets and spleen suggests these cells may circulate between the islets and periphery. Finally, we identify correlations between TCR genes and T-cell clonal expansion and effector fate. Collectively, our work demonstrates that IGRP_206-214–specific CD8 T cells are phenotypically heterogeneous but clonally restricted, raising the possibility of selectively targeting these TCR structures for therapeutic benefit.

Spike-specific T cells are enriched in breastmilk following SARS-CoV-2 mRNA vaccination

Human breastmilk is rich in T cells; however, their specificity and function are largely unknown. We compared the phenotype, diversity, and antigen specificity of T cells in the breastmilk and peripheral blood of lactating individuals who received SARS-CoV-2 mRNA vaccination. Relative to blood, breastmilk contained higher frequencies of T effector and central memory populations that expressed mucosal-homing markers. T cell receptor (TCR) sequence overlap was limited between blood and breastmilk. Overabundan t breastmilk clones were observed in all individuals, were diverse, and contained CDR3 sequences with known epitope specificity including to SARS-CoV-2 Spike. Spike-specific TCRs were more frequent in breastmilk compared to blood and expanded in breastmilk following a third mRNA vaccine dose. Our observations indicate that the lactating breast contains a distinct T cell population that can be modulated by maternal vaccination with potential implications for infant passive protection.

One-Sentence Summary

The breastmilk T cell repertoire is distinct and enriched for SARS-CoV-2 Spike-specificity after maternal mRNA vaccination.

Systematic pattern analyses of Vδ2+ TCRs reveal that shared “public” Vδ2+ γδ T cell clones are a consequence of rearrangement bias and a higher expansion status

Background

Vγ9Vδ2+ T cells are a major innate T cell subset in human peripheral blood. Their Vδ2+ VDJ-rearrangements are short and simple in the fetal thymus and gradually increase in diversity and CDR3 length along with development. So-called “public” versions of Vδ2+ TCRs are shared among individuals of all ages. However, it is unclear whether such frequently occurring “public” Vγ9Vδ2+ T cell clones are derived from the fetal thymus and whether they are fitter to proliferate and persist than infrequent “private” clones.

Methods

Shared “public” Vδ2+ TCRs were identified from Vδ2+ TCR-repertoires collected from 89 individuals, including newborns (cord blood), infants, and adults (peripheral blood). Distance matrices of Vδ2+ CDR3 were generated by TCRdist3 and then embedded into a UMAP for visualizing the heterogeneity of Vδ2+ TCRs.

Results

Vδ2+ CDR3 distance matrix embedded by UMAP revealed that the heterogeneity of Vδ2+ TCRs is primarily determined by the J-usage and CDR3aa length, while age or publicity-specific motifs were not found. The most prevalent public Vδ2+ TCRs showed germline-like rearrangement with low N-insertions. Age-related features were also identified. Public Vδ2+TRDJ1 TCRs from cord blood showed higher N-insertions and longer CDR3 lengths. Synonymous codons resulting from VDJ rearrangement also contribute to the generation of public Vδ2+ TCRs. Each public TCR was always produced by multiple different transcripts, even with different D gene usage, and the publicity of Vδ2+ TCRs was positively associated with expansion status.

Conclusion

To conclude, the heterogeneity of Vδ2+ TCRs is mainly determined by TRDJ-usage and the length of CDR3aa sequences. Public Vδ2+ TCRs result from germline-like rearrangement and synonymous codons, associated with a higher expansion status.

Inactivated tick-borne encephalitis vaccine elicits several overlapping waves of T cell response

The development and implementation of vaccines have been growing exponentially, remaining one of the major successes of healthcare over the last century. Nowadays, active regular immunizations prevent epidemics of many viral diseases, including tick-borne encephalitis (TBE). Along with the generation of virus-specific antibodies, a highly effective vaccine should induce T cell responses providing long-term immune defense. In this study, we performed longitudinal high-throughput T cell receptor (TCR) sequencing to characterize changes in individual T cell repertoires of 11 donors immunized with an inactivated TBE vaccine. After two-step immunization, we found significant clonal expansion of both CD4+ and CD8+ T cells, ranging from 302 to 1706 vaccine-associated TCRβ clonotypes in different donors. We detected several waves of T cell clonal expansion generated by distinct groups of vaccine-responding clones. Both CD4+ and CD8+ vaccine-responding T cell clones formed 17 motifs in TCRβ sequences shared by donors with identical HLA alleles. Our results indicate that TBE vaccination leads to a robust T cell response due to the production of a variety of T cell clones with a memory phenotype, which recognize a large set of epitopes.

Repertoire-scale measures of antigen binding

Antibodies and T cell receptors (TCRs) are the fundamental building blocks of adaptive immunity. Repertoire-scale functionality derives from their epitope-binding properties, just as macroscopic properties like temperature derive from microscopic molecular properties. However, most approaches to repertoire-scale measurement, including sequence diversity and entropy, are not based on antibody or TCR function in this way. Thus, they potentially overlook key features of immunological function. Here we present a framework that describes repertoires in terms of the epitope-binding properties of their constituent antibodies and TCRs, based on analysis of thousands of antibody-antigen and TCR-peptide-major-histocompatibility-complex binding interactions and over 400 high-throughput repertoires. We show that repertoires consist of loose overlapping classes of antibodies and TCRs with similar binding properties. We demonstrate the potential of this framework to distinguish specific responses vs. bystander activation in influenza vaccinees, stratify cytomegalovirus (CMV)-infected cohorts, and identify potential immunological "super-agers." Classes add a valuable dimension to the assessment of immune function.

Reference-based comparison of adaptive immune receptor repertoires

B and T cell receptor (immune) repertoires can represent an individual's immune history. While current repertoire analysis methods aim to discriminate between health and disease states, they are typically based on only a limited number of parameters. Here, we introduce immuneREF: a quantitative multidimensional measure of adaptive immune repertoire (and transcriptome) similarity that allows interpretation of immune repertoire variation by relying on both repertoire features and cross-referencing of simulated and experimental datasets. To quantify immune repertoire similarity landscapes across health and disease, we applied immuneREF to >2,400 datasets from individuals with varying immune states (healthy, [autoimmune] disease, and infection). We discovered, in contrast to the current paradigm, that blood-derived immune repertoires of healthy and diseased individuals are highly similar for certain immune states, suggesting that repertoire changes to immune perturbations are less pronounced than previously thought. In conclusion, immuneREF enables the population-wide study of adaptive immune response similarity across immune states.

Resolving SARS-CoV-2 CD4+ T cell specificity via reverse epitope discovery

The current strategy to detect immunodominant T cell responses focuses on the antigen, employing large peptide pools to screen for functional cell activation. However, these approaches are labor and sample intensive and scale poorly with increasing size of the pathogen peptidome. T cell receptors (TCRs) recognizing the same epitope frequently have highly similar sequences, and thus, the presence of large sequence similarity clusters in the TCR repertoire likely identify the most public and immunodominant responses. Here, we perform a meta-analysis of large, publicly available single-cell and bulk TCR datasets from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-infected individuals to identify public CD4+ responses. We report more than 1,200 αβTCRs forming six prominent similarity clusters and validate histocompatibility leukocyte antigen (HLA) restriction and epitope specificity predictions for five clusters using transgenic T cell lines. Collectively, these data provide information on immunodominant CD4+ T cell responses to SARS-CoV-2 and demonstrate the utility of the reverse epitope discovery approach.

The pre-exposure SARS-CoV-2-specific T cell repertoire determines the quality of the immune response to vaccination

SARS-CoV-2 infection and vaccination generates enormous host-response heterogeneity and an age-dependent loss of immune-response quality. How the pre-exposure T cell repertoire contributes to this heterogeneity is poorly understood. We combined analysis of SARS-CoV-2-specific CD4⁺ T cells pre- and post-vaccination with longitudinal T cell receptor tracking. We identified strong pre-exposure T cell variability that correlated with subsequent immune-response quality and age. High-quality responses, defined by strong expansion of high-avidity spike-specific T cells, high interleukin-21 production, and specific immunoglobulin G, depended on an intact naive repertoire and exclusion of pre-existing memory T cells. In the elderly, T cell expansion from both compartments was severely compromised. Our results reveal that an intrinsic defect of the CD4⁺ T cell repertoire causes the age-dependent decline of immune-response quality against SARS-CoV-2 and highlight the need for alternative strategies to induce high-quality T cell responses against newly arising pathogens in the elderly.

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.

Machine Learning Approaches to TCR Repertoire Analysis

Sparked by the development of genome sequencing technology, the quantity and quality of data handled in immunological research have been changing dramatically. Various data and database platforms are now driving the rapid progress of machine learning for immunological data analysis. Of various topics in immunology, T cell receptor repertoire analysis is one of the most important targets of machine learning for assessing the state and abnormalities of immune systems. In this paper, we review recent repertoire analysis methods based on machine learning and deep learning and discuss their prospects.

SARS-CoV-2-specific T cell memory with common TCRαβ motifs is established in unvaccinated children who seroconvert after infection

As the establishment of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-specific T cell memory in children remains largely unexplored, we recruited convalescent COVID-19 children and adults to define their circulating memory SARS-CoV-2-specific CD4+ and CD8+ T cells prior to vaccination. We analyzed epitope-specific T cells directly ex vivo using seven HLA class I and class II tetramers presenting SARS-CoV-2 epitopes, together with Spike-specific B cells. Unvaccinated children who seroconverted had comparable Spike-specific but lower ORF1a- and N-specific memory T cell responses compared with adults. This agreed with our TCR sequencing data showing reduced clonal expansion in children. A strong stem cell memory phenotype and common T cell receptor motifs were detected within tetramer-specific T cells in seroconverted children. Conversely, children who did not seroconvert had tetramer-specific T cells of predominantly naive phenotypes and diverse TCRαβ repertoires. Our study demonstrates the generation of SARS-CoV-2-specific T cell memory with common TCRαβ motifs in unvaccinated seroconverted children after their first virus encounter.

DECODE: a computational pipeline to discover T cell receptor binding rules

Motivation

Understanding the mechanisms underlying T cell receptor (TCR) binding is of fundamental importance to understanding adaptive immune responses. A better understanding of the biochemical rules governing TCR binding can be used, e.g. to guide the design of more powerful and safer T cell-based therapies. Advances in repertoire sequencing technologies have made available millions of TCR sequences. Data abundance has, in turn, fueled the development of many computational models to predict the binding properties of TCRs from their sequences. Unfortunately, while many of these works have made great strides toward predicting TCR specificity using machine learning, the black-box nature of these models has resulted in a limited understanding of the rules that govern the binding of a TCR and an epitope.

Results

We present an easy-to-use and customizable computational pipeline, DECODE, to extract the binding rules from any black-box model designed to predict the TCR-epitope binding. DECODE offers a range of analytical and visualization tools to guide the user in the extraction of such rules. We demonstrate our pipeline on a recently published TCR-binding prediction model, TITAN, and show how to use the provided metrics to assess the quality of the computed rules. In conclusion, DECODE can lead to a better understanding of the sequence motifs that underlie TCR binding. Our pipeline can facilitate the investigation of current immunotherapeutic challenges, such as cross-reactive events due to off-target TCR binding.

Availability and implementation

Code is available publicly at https://github.com/phineasng/DECODE.

Supplementary information

Supplementary data are available at Bioinformatics online.

T Cell Abnormalities in X-Linked Agammaglobulinaemia: an Updated Review

X-linked agammaglobulinaemia (XLA) is a primary immunodeficiency (PID) resulting from a defect in the B cell development. It has conventionally been thought that T cells play a major role in the development and function of the B cell compartment. However, it has also been shown that B cells and T cells undergo bidirectional interactions and B cells also influence the structure and function of the T cell compartment. Patients with XLA offer a unique opportunity to understand the effect of absent B cells on the T cell compartment. In this review, we provide an update on abnormalities in the T cell compartment in patients with XLA. Studies have shown impaired memory T cells, follicular helper T cells, T regulatory cells and T helper 17 in patients with XLA. In addition, these patients have also been reported to have abnormal delayed cell-mediated immune responses and vaccine-specific T cell-mediated immune responses; defective T helper cell polarization and impaired T cell receptor diversity. At present, the clinical significance of these T cell abnormalities has not been studied in detail. However, these abnormalities may result in an increased risk of viral infections, autoimmunity, autoinflammation and possibly chronic lung disease. Abnormal response to SARS-Cov2 vaccine in patients with XLA and prolonged persistence of SARS-Cov2 virus in the respiratory tract of these patients may be related to abnormalities in the T cell compartment.

A Deep Learning Model for Accurate Diagnosis of Infection Using Antibody Repertoires

The adaptive immune receptor repertoire consists of the entire set of an individual's BCRs and TCRs and is believed to contain a record of prior immune responses and the potential for future immunity. Analyses of TCR repertoires via deep learning (DL) methods have successfully diagnosed cancers and infectious diseases, including coronavirus disease 2019. However, few studies have used DL to analyze BCR repertoires. In this study, we collected IgG H chain Ab repertoires from 276 healthy control subjects and 326 patients with various infections. We then extracted a comprehensive feature set consisting of 10 subsets of repertoire-level features and 160 sequence-level features and tested whether these features can distinguish between infected individuals and healthy control subjects. Finally, we developed an ensemble DL model, namely, DL method for infection diagnosis (https://github.com/chenyuan0510/DeepID), and used this model to differentiate between the infected and healthy individuals. Four subsets of repertoire-level features and four sequence-level features were selected because of their excellent predictive performance. The DL method for infection diagnosis outperformed traditional machine learning methods in distinguishing between healthy and infected samples (area under the curve = 0.9883) and achieved a multiclassification accuracy of 0.9104. We also observed differences between the healthy and infected groups in V genes usage, clonal expansion, the complexity of reads within clone, the physical properties in the α region, and the local flexibility of the CDR3 amino acid sequence. Our results suggest that the Ab repertoire is a promising biomarker for the diagnosis of various infections.

Broadly recognized, cross-reactive SARS-CoV-2 CD4 T cell epitopes are highly conserved across human coronaviruses and presented by common HLA alleles

Sequence homology between SARS-CoV-2 and common-cold human coronaviruses (HCoVs) raises the possibility that memory responses to prior HCoV infection can affect T cell response in COVID-19. We studied T cell responses to SARS-CoV-2 and HCoVs in convalescent COVID-19 donors and identified a highly conserved SARS-CoV-2 sequence, S811-831, with overlapping epitopes presented by common MHC class II proteins HLA-DQ5 and HLA-DP4. These epitopes are recognized by low-abundance CD4 T cells from convalescent COVID-19 donors, mRNA vaccine recipients, and uninfected donors. TCR sequencing revealed a diverse repertoire with public TCRs. T cell cross-reactivity is driven by the high conservation across human and animal coronaviruses of T cell contact residues in both HLA-DQ5 and HLA-DP4 binding frames, with distinct patterns of HCoV cross-reactivity explained by MHC class II binding preferences and substitutions at secondary TCR contact sites. These data highlight S811-831 as a highly conserved CD4 T cell epitope broadly recognized across human populations.

Clonal evolution and TCR specificity of the human TFH cell response to Plasmodium falciparum CSP

T follicular helper (T_FH) cells play a crucial role in the development of long-lived, high-quality B cell responses after infection and vaccination. However, little is known about how antigen-specific T_FH cells clonally evolve in response to complex pathogens and what guides the targeting of different epitopes. Here, we assessed the cell phenotype, clonal dynamics, and T cell receptor (TCR) specificity of human circulating T_FH (cT_FH) cells during successive malaria immunizations with radiation-attenuated Plasmodium falciparum (Pf) sporozoites. Repeated parasite exposures induced a dynamic, polyclonal cT_FH response with high frequency of cells specific to a small number of epitopes in Pf circumsporozoite protein (PfCSP), the primary sporozoite surface protein and well-defined vaccine target. Human leukocyte antigen (HLA) restrictions and differences in TCR generation probability were associated with differences in the epitope targeting frequency and indicated the potential of amino acids 311 to 333 in the Th2R/T* region as a T cell supertope. But most of vaccine-induced anti-amino acid 311 to 333 TCRs, including convergent TCRs with high sequence similarity, failed to tolerate natural polymorphisms in their target peptide sequence, thus demonstrating that the T_FH cell response was limited to the vaccine strain. These data suggest that the high parasite diversity in endemic areas will limit boosting of the vaccine-induced T_FH cell response by natural infections. Our findings may guide the further design of PfCSP-based malaria vaccines able to induce potent T helper cell responses for broad, long-lasting antibody responses.

Identification of TCR repertoires in asymptomatic COVID-19 patients by single-cell T-cell receptor sequencing

The T cell-mediated immune responses associated with asymptomatic infection (AS) of SARS-CoV-2 remain largely unknown. The diversity of T-cell receptor (TCR) repertoire is essential for generating effective immunity against viral infections in T cell response. Here, we performed the single-cell TCR sequencing of the PBMC samples from five AS subjects, 33 symptomatic COVID-19 patients and eleven healthy controls to investigate the size and the diversity of TCR repertoire. We subsequently analyzed the TCR repertoire diversity, the V and J gene segment deference, and the dominant combination of αβ VJ gene pairing among these three study groups. Notably, we revealed significant TCR preference in the AS group, including the skewed usage of TRAV1-2-J33-TRBV6-4-J2-2 and TRAV1-2-J33-TRBV6-1-J2-3. Our findings may shed new light on understanding the immunopathogenesis of COVID-19 and help identify optimal TCRs for development of novel therapeutic strategies against SARS-CoV-2 infection.

Naive and memory T cells TCR-HLA-binding prediction

T cells recognize antigens through the interaction of their T cell receptor (TCR) with a peptide-major histocompatibility complex (pMHC) molecule. Following thymic-positive selection, TCRs in peripheral naive T cells are expected to bind MHC alleles of the host. Peripheral clonal selection is expected to further increase the frequency of antigen-specific TCRs that bind to the host MHC alleles. To check for a systematic preference for MHC-binding T cells in TCR repertoires, we developed Natural Language Processing-based methods to predict TCR-MHC binding independently of the peptide presented for Class I MHC alleles. We trained a classifier on published TCR-pMHC binding pairs and obtained a high area under curve (AUC) of over 0.90 on the test set. However, when applied to TCR repertoires, the accuracy of the classifier dropped. We thus developed a two-stage prediction model, based on large-scale naive and memory TCR repertoires, denoted TCR HLA-binding predictor (CLAIRE). Since each host carries multiple human leukocyte antigen (HLA) alleles, we first computed whether a TCR on a CD8 T cell binds an MHC from any of the host Class-I HLA alleles. We then performed an iteration, where we predict the binding with the most probable allele from the first round. We show that this classifier is more precise for memory than for naïve cells. Moreover, it can be transferred between datasets. Finally, we developed a CD4-CD8 T cell classifier to apply CLAIRE to unsorted bulk sequencing datasets and showed a high AUC of 0.96 and 0.90 on large datasets. CLAIRE is available through a GitHub at: https://github.com/louzounlab/CLAIRE, and as a server at: https://claire.math.biu.ac.il/Home.

Profiling the baseline performance and limits of machine learning models for adaptive immune receptor repertoire classification

BACKGROUND

Machine learning (ML) methodology development for the classification of immune states in adaptive immune receptor repertoires (AIRRs) has seen a recent surge of interest. However, so far, there does not exist a systematic evaluation of scenarios where classical ML methods (such as penalized logistic regression) already perform adequately for AIRR classification. This hinders investigative reorientation to those scenarios where method development of more sophisticated ML approaches may be required.

RESULTS

To identify those scenarios where a baseline ML method is able to perform well for AIRR classification, we generated a collection of synthetic AIRR benchmark data sets encompassing a wide range of data set architecture-associated and immune state-associated sequence patterns (signal) complexity. We trained ≈1,700 ML models with varying assumptions regarding immune signal on ≈1,000 data sets with a total of ≈250,000 AIRRs containing ≈46 billion TCRβ CDR3 amino acid sequences, thereby surpassing the sample sizes of current state-of-the-art AIRR-ML setups by two orders of magnitude. We found that L1-penalized logistic regression achieved high prediction accuracy even when the immune signal occurs only in 1 out of 50,000 AIR sequences.

CONCLUSIONS

We provide a reference benchmark to guide new AIRR-ML classification methodology by (i) identifying those scenarios characterized by immune signal and data set complexity, where baseline methods already achieve high prediction accuracy, and (ii) facilitating realistic expectations of the performance of AIRR-ML models given training data set properties and assumptions. Our study serves as a template for defining specialized AIRR benchmark data sets for comprehensive benchmarking of AIRR-ML methods.

Neoantigen quality predicts immunoediting in survivors of pancreatic cancer

Cancer immunoediting¹ is a hallmark of cancer² that predicts that lymphocytes kill more immunogenic cancer cells to cause less immunogenic clones to dominate a population. Although proven in mice^1,3, whether immunoediting occurs naturally in human cancers remains unclear. Here, to address this, we investigate how 70 human pancreatic cancers evolved over 10 years. We find that, despite having more time to accumulate mutations, rare long-term survivors of pancreatic cancer who have stronger T cell activity in primary tumours develop genetically less heterogeneous recurrent tumours with fewer immunogenic mutations (neoantigens). To quantify whether immunoediting underlies these observations, we infer that a neoantigen is immunogenic (high-quality) by two features—‘non-selfness’  based on neoantigen similarity to known antigens^4,5, and ‘selfness’  based on the antigenic distance required for a neoantigen to differentially bind to the MHC or activate a T cell compared with its wild-type peptide. Using these features, we estimate cancer clone fitness as the aggregate cost of T cells recognizing high-quality neoantigens offset by gains from oncogenic mutations. With this model, we predict the clonal evolution of tumours to reveal that long-term survivors of pancreatic cancer develop recurrent tumours with fewer high-quality neoantigens. Thus, we submit evidence that that the human immune system naturally edits neoantigens. Furthermore, we present a model to predict how immune pressure induces cancer cell populations to evolve over time. More broadly, our results argue that the immune system fundamentally surveils host genetic changes to suppress cancer.

The human immune system naturally edits cancers of high-quality neoantigens.

Utility of Bulk T-Cell Receptor Repertoire Sequencing Analysis in Understanding Immune Responses to COVID-19

Measuring immunity to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 19 (COVID-19), can rely on antibodies, reactive T cells and other factors, with T-cell-mediated responses appearing to have greater sensitivity and longevity. Because each T cell carries an essentially unique nucleic acid sequence for its T-cell receptor (TCR), we can interrogate sequence data derived from DNA or RNA to assess aspects of the immune response. This review deals with the utility of bulk, rather than single-cell, sequencing of TCR repertoires, considering the importance of study design, in terms of cohort selection, laboratory methods and analysis. The advances in understanding SARS-CoV-2 immunity that have resulted from bulk TCR repertoire sequencing are also be discussed. The complexity of sequencing data obtained by bulk repertoire sequencing makes analysis challenging, but simple descriptive analyses, clonal analysis, searches for specific sequences associated with immune responses to SARS-CoV-2, motif-based analyses, and machine learning approaches have all been applied. TCR repertoire sequencing has demonstrated early expansion followed by contraction of SARS-CoV-2-specific clonotypes, during active infection. Maintenance of TCR repertoire diversity, including the maintenance of diversity of anti-SARS-CoV-2 response, predicts a favourable outcome. TCR repertoire narrowing in severe COVID-19 is most likely a consequence of COVID-19-associated lymphopenia. It has been possible to follow clonotypic sequences longitudinally, which has been particularly valuable for clonotypes known to be associated with SARS-CoV-2 peptide/MHC tetramer binding or with SARS-CoV-2 peptide-induced cytokine responses. Closely related clonotypes to these previously identified sequences have been shown to respond with similar kinetics during infection. A possible superantigen-like effect of the SARS-CoV-2 spike protein has been identified, by means of observing V-segment skewing in patients with severe COVID-19, together with structural modelling. Such a superantigen-like activity, which is apparently absent from other coronaviruses, may be the basis of multisystem inflammatory syndrome and cytokine storms in COVID-19. Bulk TCR repertoire sequencing has proven to be a useful and cost-effective approach to understanding interactions between SARS-CoV-2 and the human host, with the potential to inform the design of therapeutics and vaccines, as well as to provide invaluable pathogenetic and epidemiological insights.

Mucosal immune responses to infection and vaccination in the respiratory tract

The lungs are constantly exposed to inhaled debris, allergens, pollutants, commensal or pathogenic microorganisms, and respiratory viruses. As a result, innate and adaptive immune responses in the respiratory tract are tightly regulated and are in continual flux between states of enhanced pathogen clearance, immune-modulation, and tissue repair. New single-cell-sequencing techniques are expanding our knowledge of airway cellular complexity and the nuanced connections between structural and immune cell compartments. Understanding these varied interactions is critical in treatment of human pulmonary disease and infections and in next-generation vaccine design. Here, we review the innate and adaptive immune responses in the lung and airways following infection and vaccination, with particular focus on influenza virus and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The ongoing SARS-CoV-2 pandemic has put pulmonary research firmly into the global spotlight, challenging previously held notions of respiratory immunity and helping identify new populations at high risk for respiratory distress.

SARS-CoV-2 antigen exposure history shapes phenotypes and specificity of memory CD8+ T cells

Although mRNA vaccine efficacy against severe coronavirus disease 2019 remains high, variant emergence has prompted booster immunizations. However, the effects of repeated exposures to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antigens on memory T cells are poorly understood. Here, we utilize major histocompatibility complex multimers with single-cell RNA sequencing to profile SARS-CoV-2-responsive T cells ex vivo from humans with one, two or three antigen exposures, including vaccination, primary infection and breakthrough infection. Exposure order determined the distribution between spike-specific and non-spike-specific responses, with vaccination after infection leading to expansion of spike-specific T cells and differentiation to CCR7-CD45RA+ effectors. In contrast, individuals after breakthrough infection mount vigorous non-spike-specific responses. Analysis of over 4,000 epitope-specific T cell antigen receptor (TCR) sequences demonstrates that all exposures elicit diverse repertoires characterized by shared TCR motifs, confirmed by monoclonal TCR characterization, with no evidence for repertoire narrowing from repeated exposure. Our findings suggest that breakthrough infections diversify the T cell memory repertoire and current vaccination protocols continue to expand and differentiate spike-specific memory.

Urinary extracellular vesicles contain mature transcriptome enriched in circular and long noncoding RNAs with functional significance in prostate cancer

Long noncoding (lnc)RNAs modulate gene expression alongside presenting unexpected source of neoantigens. Despite their immense interest, their ability to be transferred and control adjacent cells is unknown. Extracellular Vesicles (EVs) offer a protective environment for nucleic acids, with pro and antitumourigenic functions by controlling the immune response. In contrast to extracellular nonvesicular RNA, few studies have addressed the full RNA content within human fluids' EVs and have compared them with their tissue of origin. Here, we performed Total RNA-Sequencing on six Formalin-Fixed-Paraffin-Embedded (FFPE) prostate cancer (PCa) tumour tissues and their paired urinary (u)EVs to provide the first whole transcriptome comparison from the same patients. UEVs contain simplified transcriptome with intron-free cytoplasmic transcripts and enriched lnc/circular (circ)RNAs, strikingly common to an independent 20 patients' urinary cohort. Our full cellular and EVs transcriptome comparison within three PCa cell lines identified a set of overlapping 14 uEV-circRNAs characterized as essential for prostate cell proliferation in vitro and 28 uEV-lncRNAs belonging to the cancer-related lncRNA census (CLC2). In addition, we found 15 uEV-lncRNAs, predicted to encode 768 high-affinity neoantigens, and for which three of the encoded-ORF produced detectable unmodified peptides by mass spectrometry. Our dual analysis of EVs-lnc/circRNAs both in urines' and in vitro's EVs provides a fundamental resource for future uEV-lnc/circRNAs phenotypic characterization involved in PCa.

TCR-L: an analysis tool for evaluating the association between the T-cell receptor repertoire and clinical phenotypes

Background

T cell receptors (TCRs) play critical roles in adaptive immune responses, and recent advances in genome technology have made it possible to examine the T cell receptor (TCR) repertoire at the individual sequence level. The analysis of the TCR repertoire with respect to clinical phenotypes can yield novel insights into the etiology and progression of immune-mediated diseases. However, methods for association analysis of the TCR repertoire have not been well developed.

Methods

We introduce an analysis tool, TCR-L, for evaluating the association between the TCR repertoire and disease outcomes. Our approach is developed under a mixed effect modeling, where the fixed effect represents features that can be explicitly extracted from TCR sequences while the random effect represents features that are hidden in TCR sequences and are difficult to be extracted. Statistical tests are developed to examine the two types of effects independently, and then the p values are combined.

Results

Simulation studies demonstrate that (1) the proposed approach can control the type I error well; and (2) the power of the proposed approach is greater than approaches that consider fixed effect only or random effect only. The analysis of real data from a skin cutaneous melanoma study identifies an association between the TCR repertoire and the short/long-term survival of patients.

Conclusion

The TCR-L can accommodate features that can be extracted as well as features that are hidden in TCR sequences. TCR-L provides a powerful approach for identifying association between TCR repertoire and disease outcomes.

Genomic and TCR profiling data reveal the distinct molecular traits in epithelial ovarian cancer histotypes

Epithelial ovarian cancer (EOC) is classified into five major histotypes: high-grade serous (HGSOC), low-grade serous (LGSOC), clear cell (CCOC), endometrioid (ENOC), and mucinous (MOC). However, the landscape of molecular and immunological alterations in these histotypes, especially LGSOC, CCOC, ENOC, and MOC, is largely uncharacterized. We collected 101 treatment-naive EOC patients. The resected tumor tissues and paired preoperative peripheral blood samples were collected and subjected to target sequencing of 1021 cancer-associated genes and T cell repertoire sequencing. Distinct characteristics of mutations were identified among the five histotypes. Furthermore, tumor mutation burden (TMB) was found to be higher in CCOC and ENOC, but lower in LGSOC and HGSOC. Alterations associated with DNA damage repair (DDR) pathways and homologous recombination deficiencies (HRD) were prevalent in five histotypes. CCOC demonstrated increased level of T cell clonality compared with HSGOC. Interestingly, the proportion of the 100 most common T cell clones was associated with TMB and tumor neoantigen burden in CCOC, highlighting more sensitive anti-tumor responses in this histotype, which was also evidenced by the enhanced convergent recombination of T cell clones. These findings shed light on the molecular traits of genomic alteration and T cell repertoire in the five major EOC histotypes and may help optimize clinical management of EOC with different histotypes.

Pinpointing the tumor-specific T-cells via TCR clusters

Adoptive cell transfer (ACT) is a promising approach to cancer immunotherapy, but its efficiency fundamentally depends on the extent of tumor-specific T cell enrichment within the graft. This can be estimated via activation with identifiable neoantigens, tumor-associated antigens (TAAs), or living or lysed tumor cells, but these approaches remain laborious, time-consuming, and functionally limited, hampering clinical development of ACT. Here, we demonstrate that homology cluster analysis of T cell receptor (TCR) repertoires efficiently identifies tumor-reactive TCRs allowing to: (1) detect their presence within the pool of tumor-infiltrating lymphocytes (TILs); (2) optimize TIL culturing conditions, with IL-2_low/IL-21/anti-PD-1 combination showing increased efficiency; (3) investigate surface marker-based enrichment for tumor-targeting T cells in freshly isolated TILs (enrichment confirmed for CD4⁺ and CD8⁺ PD-1⁺/CD39⁺ subsets), or re-stimulated TILs (informs on enrichment in 4-1BB-sorted cells). We believe that this approach to the rapid assessment of tumor-specific TCR enrichment should accelerate T cell therapy development.

Analysis of T cell receptor clonotypes in tumor microenvironment identifies shared cancer-type-specific signatures

Despite the conventional view that a truly random V(D)J recombination process should generate a highly diverse immune repertoire, emerging reports suggest that there is a certain bias toward the generation of shared/public immune receptor chains. These studies were performed in viral diseases where public T cell receptors (TCR) appear to confer better protective responses. Selective pressures generating common TCR clonotypes are currently not well understood, but it is believed that they confer a growth advantage. As very little is known about public TCR clonotypes in cancer, here we set out to determine the extent of shared TCR clonotypes in the intra-tumor microenvironments of virus- and non-virus-driven head and neck cancers using TCR sequencing. We report that tumor-infiltrating T cell clonotypes were indeed shared across individuals with the same cancer type, where the majority of shared sequences were specific to the cancer type (i.e., viral versus non-viral). These shared clonotypes were not particularly enriched in EBV-associated nasopharynx cancer but, in both cancers, exhibited distinct characteristics, namely shorter CDR3 lengths, restricted V- and J-gene usages, and also demonstrated convergent V(D)J recombination. Many of these shared TCRs were expressed in patients with a shared HLA background. Pattern recognition of CDR3 amino acid sequences revealed strong convergence to specific pattern motifs, and these motifs were uniquely found to each cancer type. This suggests that they may be enriched for specificity to common antigens found in the tumor microenvironment of different cancers. The identification of shared TCRs in infiltrating tumor T cells not only adds to our understanding of the tumor-adaptive immune recognition but could also serve as disease-specific biomarkers and guide the development of future immunotherapies.

Phenotype-Based Isolation of Antigen-Specific CD4+ T Cells in Autoimmunity: A Study of Celiac Disease

The pathogenic immune response in celiac disease (CeD) is orchestrated by phenotypically distinct CD4+ T cells that recognize gluten epitopes in the context of disease-associated HLA-DQ allotypes. Cells with the same distinct phenotype, but with elusive specificities, are increased across multiple autoimmune conditions. Here, whether sorting of T cells based on their distinct phenotype (Tphe cells) yields gluten-reactive cells in CeD is tested. The method's efficiency is benchmarked by parallel isolation of gluten-reactive T cells (Ttet cells), using HLA-DQ:gluten peptide tetramers. From gut biopsies of 12 untreated HLA-DQ2.5+ CeD patients, Ttet+ /Tphe+ , Ttet- /Tphe+ , and Ttet- /Tphe- cells are sorted for single-cell T-cell receptor (TCR)-sequencing (n = 8) and T-cell clone (TCC)-generation (n = 5). The generated TCCs are TCR sequenced and tested for their reactivity against deamidated gluten. Gluten-reactivity is observed in 91.2% of Ttet+ /Tphe+ TCCs, 65.3% of Ttet- /Tphe+ TCCs and 0% of Ttet- /Tphe- TCCs. TCR sequencing reveals clonal expansion and sequence sharing across patients, features reflecting antigen-driven responses. The feasibility to isolate antigen-specific CD4+ T cells by the sole use of phenotypic markers in CeD outlines a potential avenue for characterizing disease-driving CD4+ T cells in autoimmune conditions.

Durable Expansion of TCR-δ Meta-Clonotypes After BCG Revaccination in Humans

Mycobacterium bovis bacille Calmette-Guérin (BCG) has been used for 100 years and prevents disseminated tuberculosis and death in young children. However, it shows only partial efficacy against pulmonary tuberculosis (TB) in adults, so new vaccines are urgently needed. The protective efficacy of BCG depends on T cells, which are typically activated by pathogen-derived protein antigens that bind to highly polymorphic major histocompatibility complex (MHC) molecules. Some T cells recognize non-protein antigens via antigen presenting systems that are independent of genetic background, leading to their designation as donor-unrestricted T (DURT) cells. Whether live whole cell vaccines, like BCG, can induce durable expansions of DURT cells in humans is not known. We used combinatorial tetramer staining, multi-parameter flow cytometry, and immunosequencing to comprehensively characterize the effect of BCG on activation and expansion of DURT cell subsets. We examined peripheral blood mononuclear cells (PBMC) derived from a Phase I study of South African adults in which samples were archived at baseline, 3 weeks, and 52 weeks post-BCG revaccination. We did not observe a change in the frequency of total mucosal-associated invariant T (MAIT) cells, invariant natural killer T (iNKT) cells, germline encoded mycolyl-reactive (GEM) T cells, or γδ T cells at 52 weeks post-BCG. However, immunosequencing revealed a set of TCR-δ clonotypes that were expanded at 52 weeks post-BCG revaccination. These expanded clones expressed the Vδ2 gene segment and could be further defined on the basis of biochemical similarity into several 'meta-clonotypes' that likely recognize similar epitopes. Our data reveal that BCG vaccination leads to durable expansion of DURT cell clonotypes despite a limited effect on total circulating frequencies in the blood and have implications for defining the immunogenicity of candidate whole cell TB vaccines.

Combining genotypes and T cell receptor distributions to infer genetic loci determining V(D)J recombination probabilities

Every T cell receptor (TCR) repertoire is shaped by a complex probabilistic tangle of genetically determined biases and immune exposures. T cells combine a random V(D)J recombination process with a selection process to generate highly diverse and functional TCRs. The extent to which an individual’s genetic background is associated with their resulting TCR repertoire diversity has yet to be fully explored. Using a previously published repertoire sequencing dataset paired with high-resolution genome-wide genotyping from a large human cohort, we infer specific genetic loci associated with V(D)J recombination probabilities using genome-wide association inference. We show that V(D)J gene usage profiles are associated with variation in the TCRB locus and, specifically for the functional TCR repertoire, variation in the major histocompatibility complex locus. Further, we identify specific variations in the genes encoding the Artemis protein and the TdT protein to be associated with biasing junctional nucleotide deletion and N-insertion, respectively. These results refine our understanding of genetically-determined TCR repertoire biases by confirming and extending previous studies on the genetic determinants of V(D)J gene usage and providing the first examples of trans genetic variants which are associated with modifying junctional diversity. Together, these insights lay the groundwork for further explorations into how immune responses vary between individuals.

Dual TCR-α Expression on Mucosal-Associated Invariant T Cells as a Potential Confounder of TCR Interpretation

Mucosal-associated invariant T (MAIT) cells are innate-like T cells that are highly abundant in human blood and tissues. Most MAIT cells have an invariant TCRα-chain that uses T cell receptor α-variable 1-2 (TRAV1-2) joined to TRAJ33/20/12 and recognizes metabolites from bacterial riboflavin synthesis bound to the Ag-presenting molecule MHC class I related (MR1). Our attempts to identify alternative MR1-presented Ags led to the discovery of rare MR1-restricted T cells with non-TRAV1-2 TCRs. Because altered Ag specificity likely alters affinity for the most potent known Ag, 5-(2-oxopropylideneamino)-6-d-ribitylaminouracil (5-OP-RU), we performed bulk TCRα- and TCRβ-chain sequencing and single-cell-based paired TCR sequencing on T cells that bound the MR1-5-OP-RU tetramer with differing intensities. Bulk sequencing showed that use of V genes other than TRAV1-2 was enriched among MR1-5-OP-RU tetramer^low cells. Although we initially interpreted these as diverse MR1-restricted TCRs, single-cell TCR sequencing revealed that cells expressing atypical TCRα-chains also coexpressed an invariant MAIT TCRα-chain. Transfection of each non-TRAV1-2 TCRα-chain with the TCRβ-chain from the same cell demonstrated that the non-TRAV1-2 TCR did not bind the MR1-5-OP-RU tetramer. Thus, dual TCRα-chain expression in human T cells and competition for the endogenous β-chain explains the existence of some MR1-5-OP-RU tetramer^low T cells. The discovery of simultaneous expression of canonical and noncanonical TCRs on the same T cell means that claims of roles for non-TRAV1-2 TCR in MR1 response must be validated by TCR transfer-based confirmation of Ag specificity.

TCR-sequencing in cancer and autoimmunity: barcodes and beyond

The T cell receptor (TCR) endows T cells with antigen specificity and is central to nearly all aspects of T cell function. Each naïve T cell has a unique TCR sequence that is stably maintained during cell division. In this way, the TCR serves as a molecular barcode that tracks processes such as migration, differentiation, and proliferation of T cells. Recent technological advances have enabled sequencing of the TCR from single cells alongside deep molecular phenotypes on an unprecedented scale. In this review, we discuss strengths and limitations of TCR sequences as molecular barcodes and their application to study immune responses following Programmed Death-1 (PD-1) blockade in cancer. Additionally, we consider applications of TCR data beyond use as a barcode.

Identification of T cell antigens in the 21st century, as difficult as ever

Identifying antigens recognized by T cells is still challenging, particularly for innate like T cells that do not recognize peptides but small metabolites or lipids in the context of MHC-like molecules or see non-MHC restricted antigens. The fundamental reason for this situation is the low affinity of T cell receptors for their ligands coupled with a level of degeneracy that makes them bind to similar surfaces on antigen presenting cells. Herein we will describe non-exhaustively some of the methods that were used to identify peptide antigens and briefly mention the high throughput methods more recently proposed for that purpose. We will then present how the molecules recognized by innate like T cells (NKT, MAIT and γδ T cells) were discovered. We will show that serendipity was instrumental in many cases.

SARS-CoV-2 mRNA vaccination elicits a robust and persistent T follicular helper cell response in humans

SARS-CoV-2 mRNA vaccines induce robust anti-spike (S) antibody and CD4+ T cell responses. It is not yet clear whether vaccine-induced follicular helper CD4+ T (TFH) cell responses contribute to this outstanding immunogenicity. Using fine-needle aspiration of draining axillary lymph nodes from individuals who received the BNT162b2 mRNA vaccine, we evaluated the T cell receptor sequences and phenotype of lymph node TFH. Mining of the responding TFH T cell receptor repertoire revealed a strikingly immunodominant HLA-DPB1∗04-restricted response to S167-180 in individuals with this allele, which is among the most common HLA alleles in humans. Paired blood and lymph node specimens show that while circulating S-specific TFH cells peak one week after the second immunization, S-specific TFH persist at nearly constant frequencies for at least six months. Collectively, our results underscore the key role that robust TFH cell responses play in establishing long-term immunity by this efficacious human vaccine.

Convergent clonal selection of donor- and recipient-derived CMV-specific T cells in hematopoietic stem cell transplant patients

An existing memory T cell population specific for a single epitope is sufficient to effectively curtail responses to any new antigens if the original epitope is present in a vaccination regimen or heterologous infections. We asked if T cell competition precludes recruitment of any new, naïve T cells to an existing memory T cell pool in context of cytomegalovirus-specific T cell responses in a cohort of transplant patients. Our data indicate that competition does not prevent recruitment of naïve T cells into the memory T cell pool but selects for T cells with nearly or fully congruent T cell receptor specificities. We discuss the implications of rejuvenating a memory T cell pool while preserving the T cell receptor repertoire.

Competition between antigen-specific T cells for peptide:MHC complexes shapes the ensuing T cell response. Mouse model studies provided compelling evidence that competition is a highly effective mechanism controlling the activation of naïve T cells. However, assessing the effect of T cell competition in the context of a human infection requires defined pathogen kinetics and trackable naïve and memory T cell populations of defined specificity. A unique cohort of nonmyeloablative hematopoietic stem cell transplant patients allowed us to assess T cell competition in response to cytomegalovirus (CMV) reactivation, which was documented with detailed virology data. In our cohort, hematopoietic stem cell transplant donors and recipients were CMV seronegative and positive, respectively, thus providing genetically distinct memory and naïve T cell populations. We used single-cell transcriptomics to track donor versus recipient-derived T cell clones over the course of 90 d. We found that donor-derived T cell clones proliferated and expanded substantially following CMV reactivation. However, for immunodominant CMV epitopes, recipient-derived memory T cells remained the overall dominant population. This dominance was maintained despite more robust clonal expansion of donor-derived T cells in response to CMV reactivation. Interestingly, the donor-derived T cells that were recruited into these immunodominant memory populations shared strikingly similar TCR properties with the recipient-derived memory T cells. This selective recruitment of identical and nearly identical clones from the naïve into the immunodominant memory T cell pool suggests that competition is in place but does not interfere with rejuvenating a memory T cell population. Instead, it results in selection of convergent clones to the memory T cell pool.

Antigen cross-presentation in young tumor-bearing hosts promotes CD8+ T cell terminal differentiation

The immune system undergoes a progressive functional remodeling with age. Understanding how age bias shapes antitumor immunity is essential in designing effective immunotherapies, especially for pediatric patients. Here, we explore antitumor CD8⁺ T cell responses generated in young (prepubescent) and adult (presenescent) mice. Using an MHCI-deficient tumor model, we observed that tumor-reactive CD8⁺ T cells expanded in young tumor-bearing (TB) mice acquired a terminally differentiated phenotype characterized by overexpression of inhibitory receptors and the transcription factor Tox1. Furthermore, tumor-infiltrating CD8⁺ T cells from young tumors yielded a poor cytokine response compared with CD8⁺ T cells infiltrating adult tumors. Young migratory dendritic cells (migDCs) from the draining lymph nodes (dLNs), and mononuclear phagocytic cells (MPCs) infiltrating young tumors, were more competent in capturing and cross-presenting tumor antigen, leading to enhanced priming of CD8⁺ T cells in dLNs and their subsequent terminal differentiation in the tumors. Single-cell transcriptional profiling of tumor-infiltrating MPCs demonstrated that young MPCs are polarized toward an inflammatory, effector phenotype. Consistent with our observations in young versus adult TB mice, analysis of immune infiltrates from pediatric solid tumors showed a correlation between tumor-infiltrating CD8⁺ T cells with an exhaustion phenotype and the frequency of PD-L1-expressing monocytes/macrophages. Collectively, these data indicate that a young tissue microenvironment contributes to the generation of an immune response skewed toward a less pliable terminal effector state, thus narrowing the window for immunotherapeutic interventions.

Implementing a Clinical Immunogenicity Strategy using Preclinical Risk Assessment Outputs

Immunogenicity to biologics is often observed following dosing in human subjects during clinical trials. Both product and host specific factors may be implicated in contributing to a potential immune response. However, even if such risk factors are identified and eliminated as part of the rational quality by design approaches, the outcome in clinic can be uncertain and challenging to predict. Several tools have been employed to identify these risk factors and consequent mitigation approaches implemented prior to dosing in humans. However, the complexity of the immune system with an interplay of network of immune cells involved in driving a long- term immune response as well as patient characteristics, can make it challenging to predict the outcome in clinic. This perspective will provide an insight into recent advances in the risk assessment approaches that are utilized during preclinical stage of development of a biologic. The outputs from such tools can help to rank order and select the most optimal candidate with the least likelihood of an immune response and can further drive the development of a clinical bioanalytical and immunogenicity monitoring strategy. Such a strategy can be proactively shared with the regulators along with the proposal to streamline clinical immunogenicity and personalizing the outcome based on pharmacogenomics and other patient-related factors. This paper provides a roadmap on performing risk assessments through a systematic identification of risks and their mitigations wherever possible. Recommendations on incorporating the key components of such risk assessments as part of the new regulatory submissions are also provided. Shorter abstract Immunogenicity to biologics is common during clinical trials. Both product and host specific factors have been implicated. Several risk assessment tools can be used to identify and mitigate the risk factors responsible for immunogenicity. An insight into recent advances in the risk assessment approaches will be presented. The outputs can define a risk score and guide the clinical bioanalytical and immunogenicity monitoring strategy. A roadmap on performing risk assessments through a systematic identification of risks and their mitigations wherever possible is provided. Best practices for a risk assessment strategy and recommendations on the content for IND and the Integrated summary of Immunogenicity are also provided.

Application of T cell receptor (TCR) repertoire analysis for the advancement of cancer immunotherapy

T cell receptor (TCR) sequencing has emerged as a powerful new technology in analysis of the host-tumour interaction. The advances in NextGen sequencing technologies, coupled with powerful novel bioinformatic tools, allow quantitative and reproducible characterisation of repertoires from tumour and blood samples from an increasing number of patients with a variety of solid cancers. In this review, we consider how global metrics such as T cell clonality and diversity can be extracted from these repertoires and used to give insight into the mechanism of action of immune checkpoint blockade. Furthermore, we explore how the analysis of TCR overlap between repertories can help define spatial and temporal heterogeneity of the anti-tumoural immune response. Finally, we review how analysis of TCR sequence and structure, either of individual TCRs or from sets of related TCRs can be used to annotate the antigenic specificity, with important implications for the development of personalised adoptive cellular immunotherapies.

Bystander T cells in cancer immunology and therapy

Cancer-specific T cells are required for effective anti-cancer immunity and have a central role in cancer immunotherapy. However, emerging evidence suggests that only a small fraction of tumor-infiltrating T cells are cancer specific, and T cells that recognize cancer-unrelated antigens (so-called 'bystanders') are abundant. Although the role of cancer-specific T cells in anti-cancer immunity has been well established, the implications of bystander T cells in tumors are only beginning to be understood. It is becoming increasingly clear that bystander T cells are not a homogeneous group of cells but, instead, they differ in their specificities, their activation states and effector functions. In this Perspective, we discuss recent studies of bystander T cells in tumors, including experimental and computational approaches that enable their identification and functional analysis and viewpoints on how these insights could be used to develop new therapeutic approaches for cancer immunotherapy.

SARS-CoV-2 antigen exposure history shapes phenotypes and specificity of memory CD8 T cells

Although mRNA vaccine efficacy against severe COVID-19 remains high, variant emergence and breakthrough infections have changed vaccine policy to include booster immunizations. However, the effect of diverse and repeated antigen exposures on SARS-CoV-2 memory T cells is poorly understood. Here, we utilize DNA-barcoded MHC-multimers combined with scRNAseq and scTCRseq to capture the ex vivo profile of SARS-CoV-2-responsive T cells within a cohort of individuals with one, two, or three antigen exposures, including vaccination, primary infection, and breakthrough infection. We found that the order of exposure determined the relative distribution between spike- and non-spike-specific responses, with vaccination after infection leading to further expansion of spike-specific T cells and differentiation to a CCR7-CD45RA+ effector phenotype. In contrast, individuals experiencing a breakthrough infection mount vigorous non-spike-specific responses. In-depth analysis of over 4,000 epitope-specific T cell receptor sequences demonstrates that all types of exposures elicit diverse repertoires characterized by shared, dominant TCR motifs, with no evidence for repertoire narrowing from repeated exposure. Our findings suggest that breakthrough infections diversify the T cell memory repertoire and that current vaccination protocols continue to expand and differentiate spike-specific memory responses.

Preexisting memory CD4 T cells in naïve individuals confer robust immunity upon hepatitis B vaccination

Antigen recognition through the T cell receptor (TCR) αβ heterodimer is one of the primary determinants of the adaptive immune response. Vaccines activate naïve T cells with high specificity to expand and differentiate into memory T cells. However, antigen-specific memory CD4 T cells exist in unexposed antigen-naïve hosts. In this study, we use high-throughput sequencing of memory CD4 TCRβ repertoire and machine learning to show that individuals with preexisting vaccine-reactive memory CD4 T cell clonotypes elicited earlier and higher antibody titers and mounted a more robust CD4 T cell response to hepatitis B vaccine. In addition, integration of TCRβ sequence patterns into a hepatitis B epitope-specific annotation model can predict which individuals will have an early and more vigorous vaccine-elicited immunity. Thus, the presence of preexisting memory T cell clonotypes has a significant impact on immunity and can be used to predict immune responses to vaccination.

Immune cells called CD4 T cells help the body build immunity to infections caused by bacteria and viruses, or after vaccination. Receptor proteins on the outside of the cells recognize pathogens, foreign molecules called antigens, or vaccine antigens. Vaccine antigens are usually inactivated bacteria or viruses, or fragments of these pathogens. After recognizing an antigen, CD4 T cells develop into memory CD4 T cells ready to defend against future infections with the pathogen.

People who have never been exposed to a pathogen, or have never been vaccinated against it, may nevertheless have preexisting memory cells ready to defend against it. This happens because CD4 T cells can recognize multiple targets, which enables the immune system to be ready to defend against both new and familiar pathogens.

Elias, Meysman, Bartholomeus et al. wanted to find out whether having preexisting memory CD4 T cells confers an advantage for vaccine-induced immunity. Thirty-four people who were never exposed to hepatitis B or vaccinated against it participated in the study. These individuals provided blood samples before vaccination, with 2 doses of the hepatitis B vaccine, and at 3 time points afterward. Using next generation immune sequencing and machine learning techniques, Elias et al. analyzed the individuals’ memory CD4 T cells before and after vaccination.

The experiments showed that preexisting memory CD4 T cells may determine vaccination outcomes, and people with more preexisting memory cells develop quicker and stronger immunity after vaccination against hepatitis B. This information may help scientists to better understand how people develop immunity to pathogens. It may guide them develop better vaccines or predict who will develop immunity after vaccination.

Allelic variation in class I HLA determines CD8+ T cell repertoire shape and cross-reactive memory responses to SARS-CoV-2

Effective presentation of antigens by HLA class I molecules to CD8⁺ T cells is required for viral elimination and generation of long-term immunological memory. In this study, we applied a single-cell, multi-omic technology to generate a unified ex vivo characterization of the CD8⁺ T cell response to SARS-CoV-2 across 4 major HLA class I alleles. We found that HLA genotype conditions key features of epitope specificity, TCR α/β sequence diversity, and the utilization of pre-existing SARS-CoV-2 reactive memory T cell pools. Single-cell transcriptomics revealed functionally diverse T cell phenotypes of SARS-CoV-2-reactive T cells, associated with both disease stage and epitope specificity. Our results show that HLA variations significantly influence the CD8⁺ T cell repertoire shape and utilization of immune recall upon SARS-CoV-2 infection.

Specificity of Adaptive Immune Responses in Central Nervous System Health, Aging and Diseases

The field of neuroimmunology endorses the involvement of the adaptive immune system in central nervous system (CNS) health, disease, and aging. While immune cell trafficking into the CNS is highly regulated, small numbers of antigen-experienced lymphocytes can still enter the cerebrospinal fluid (CSF)-filled compartments for regular immune surveillance under homeostatic conditions. Meningeal lymphatics facilitate drainage of brain-derived antigens from the CSF to deep cervical lymph nodes to prime potential adaptive immune responses. During aging and CNS disorders, brain barriers and meningeal lymphatic functions are impaired, and immune cell trafficking and antigen efflux are altered. In this context, alterations in the immune cell repertoire of blood and CSF and T and B cells primed against CNS-derived autoantigens have been observed in various CNS disorders. However, for many diseases, a causal relationship between observed immune responses and neuropathological findings is lacking. Here, we review recent discoveries about the association between the adaptive immune system and CNS disorders such as autoimmune neuroinflammatory and neurodegenerative diseases. We focus on the current challenges in identifying specific T cell epitopes in CNS diseases and discuss the potential implications for future diagnostic and treatment options.

Analysis of T-Cell Receptor Repertoire in Transplantation: Fingerprint of T Cell-mediated Alloresponse

T cells play a key role in determining allograft function by mediating allogeneic immune responses to cause rejection, and recent work pointed their role in mediating tolerance in transplantation. The unique T-cell receptor (TCR) expressed on the surface of each T cell determines the antigen specificity of the cell and can be the specific fingerprint for identifying and monitoring. Next-generation sequencing (NGS) techniques provide powerful tools for deep and high-throughput TCR profiling, and facilitate to depict the entire T cell repertoire profile and trace antigen-specific T cells in circulation and local tissues. Tailing T cell transcriptomes and TCR sequences at the single cell level provides a full landscape of alloreactive T-cell clones development and biofunction in alloresponse. Here, we review the recent advances in TCR sequencing techniques and computational tools, as well as the recent discovery in overall TCR profile and antigen-specific T cells tracking in transplantation. We further discuss the challenges and potential of using TCR sequencing-based assays to profile alloreactive TCR repertoire as the fingerprint for immune monitoring and prediction of rejection and tolerance.