Cross-Reactivity of TCR Repertoire: Current Concepts, Challenges, and Implication for Allotransplantation

Strengths and limitations of web servers for the modeling of TCRpMHC complexes

Cellular immunity relies on the ability of a T-cell receptor (TCR) to recognize a peptide (p) presented by a class I major histocompatibility complex (MHC) receptor on the surface of a cell. The TCR-peptide-MHC (TCRpMHC) interaction is a crucial step in activating T-cells, and the structural characteristics of these molecules play a significant role in determining the specificity and affinity of this interaction. Hence, obtaining 3D structures of TCRpMHC complexes offers valuable insights into various aspects of cellular immunity and can facilitate the development of T-cell-based immunotherapies. Here, we aimed to compare three popular web servers for modeling the structures of TCRpMHC complexes, namely ImmuneScape (IS), TCRpMHCmodels, and TCRmodel2, to examine their strengths and limitations. Each method employs a different modeling strategy, including docking, homology modeling, and deep learning. The accuracy of each method was evaluated by reproducing the 3D structures of a dataset of 87 TCRpMHC complexes with experimentally determined crystal structures available on the Protein Data Bank (PDB). All selected structures were limited to human MHC alleles, presenting a diverse set of peptide ligands. A detailed analysis of produced models was conducted using multiple metrics, including Root Mean Square Deviation (RMSD) and standardized assessments from CAPRI and DockQ. Special attention was given to the complementarity-determining region (CDR) loops of the TCRs and to the peptide ligands, which define most of the unique features and specificity of a given TCRpMHC interaction. Our study provides an optimistic view of the current state-of-the-art for TCRpMHC modeling but highlights some remaining challenges that must be addressed in order to support the future application of these tools for TCR engineering and computer-aided design of TCR-based immunotherapies.

Lowering maintenance immune suppression in elderly kidney transplant recipients; connecting the immunological and clinical dots

The management of long-term immune suppressive medication in kidney transplant recipients is a poorly explored field in the area of transplant medicine. In particular, older recipients are at an increased risk for side effects and have an exponentially increased risk of infection-related death. In contrast, an aged immune system decreases the risk of acute T-cell-mediated rejection in older recipients. Recent advances in alloimmunity research have shown a rapid and substantial decline in polyfunctional, high-risk CD4⁺ T cells post-transplantation. This lowers the direct alloreactivity responsible for T-cell-mediated rejection, also known as donor-specific hyporesponsiveness. Chronic antibody-mediated rejection (c-aABMR) is the most frequent cause of kidney graft loss in the long term. However, in older adults, c-aABMR as a cause of graft loss is outnumbered by death with a functioning graft. In addition, DSA development and a diagnosis of c-aABMR plateau ~10 years after transplantation, resulting in a very low risk for rejection thereafter. The intensity of immune suppression regimes could likely be reduced accordingly, but trials in this area are scarce. Tacrolimus monotherapy for 1 year after transplantation seems feasible in older kidney transplant recipients with standard immunological risk, showing the expected benefits of fewer infections and better vaccination responses.

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

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

Single-cell RNA-seq revealing the immune features of donor liver during liver transplantation

Immune cells, including T and B cells, are key factors in the success of liver transplantation. And the repertoire of T cells and B cells plays an essential function in mechanism of the immune response associated with organ transplantation. An exploration of their expression and distribution in donor organs could contribute to a better understanding of the altered immune microenvironment in grafts. In this study, using single-cell 5' RNA sequence and single-cell T cell receptor (TCR)/B cell receptor (BCR) repertoire sequence, we profiled immune cells and TCR/BCR repertoire in three pairs of donor livers pre- and post-transplantation. By annotating different immune cell types, we investigated the functional properties of monocytes/Kupffer cells, T cells and B cells in grafts. Bioinformatic characterization of differentially expressed genes (DEGs) between the transcriptomes of these cell subclusters were performed to explore the role of immune cells in inflammatory response or rejection. In addition, we also observed shifts in TCR/BCR repertoire after transplantation. In conclusion, we profiled the immune cell transcriptomics and TCR/BCR immune repertoire of liver grafts during transplantation, which may offer novel strategies for monitoring recipient immune function and treatment of rejection after liver transplantation.

Efficacy and safety of universal (TCRKO) ARI-0001 CAR-T cells for the treatment of B-cell lymphoma

Autologous T cells expressing the Chimeric Antigen Receptor (CAR) have been approved as advanced therapy medicinal products (ATMPs) against several hematological malignancies. However, the generation of patient-specific CAR-T products delays treatment and precludes standardization. Allogeneic off-the-shelf CAR-T cells are an alternative to simplify this complex and time-consuming process. Here we investigated safety and efficacy of knocking out the TCR molecule in ARI-0001 CAR-T cells, a second generation αCD19 CAR approved by the Spanish Agency of Medicines and Medical Devices (AEMPS) under the Hospital Exemption for treatment of patients older than 25 years with Relapsed/Refractory acute B cell lymphoblastic leukemia (B-ALL). We first analyzed the efficacy and safety issues that arise during disruption of the TCR gene using CRISPR/Cas9. We have shown that edition of TRAC locus in T cells using CRISPR as ribonuleorproteins allows a highly efficient TCR disruption (over 80%) without significant alterations on T cells phenotype and with an increased percentage of energetic mitochondria. However, we also found that efficient TCRKO can lead to on-target large and medium size deletions, indicating a potential safety risk of this procedure that needs monitoring. Importantly, TCR edition of ARI-0001 efficiently prevented allogeneic responses and did not detectably alter their phenotype, while maintaining a similar anti-tumor activity ex vivo and in vivo compared to unedited ARI-0001 CAR-T cells. In summary, we showed here that, although there are still some risks of genotoxicity due to genome editing, disruption of the TCR is a feasible strategy for the generation of functional allogeneic ARI-0001 CAR-T cells. We propose to further validate this protocol for the treatment of patients that do not fit the requirements for standard autologous CAR-T cells administration.

A Comparison of Ex Vivo Expanded Human Regulatory T Cells Using Allogeneic Stimulated B Cells or Monocyte-Derived Dendritic Cells

Alloreactive regulatory T cells (arTregs) are more potent than polyclonal Tregs at suppressing immune responses to transplant antigens. Human arTregs can be expanded with allogeneic CD40L-stimulated B cells (sBcs) or stimulated-matured monocyte-derived dendritic cells (sDCs). Here, we compared the expansion efficiency and properties of arTregs stimulated ex vivo using these two types of antigen-presenting cells. Compared to sBcs, sDCs stimulated Tregs to expand two times more in number. The superior expansion-inducing capacity of sDCs correlated with their higher expression of CD80, CD86, and T cell-attracting chemokines. sBc- and sDC-arTregs expressed comparable levels of FOXP3, HELIOS, CD25, CD27, and CD62L, demethylated FOXP3 enhancer and in vitro suppressive function. sBc- and sDCs-arTregs had similar gene expression profiles that were distinct from primary Tregs. sBc- and sDC-arTregs exhibited similar low frequencies of IFN-γ, IL-4, and IL-17A-producing cells, and the cytokine-producing arTregs expressed high levels of FOXP3. Almost all sBc- and sDC-arTregs expressed CXCR3, which may enable them traffic to inflammatory sites. Thus, sDCs-arTregs that expand more readily, are phenotypically similar to sBc-arTregs, supporting sDCs as a viable alternative for arTreg production for clinical evaluation.

Critical role of the CD44lowCD62Llow CD8+ T cell subset in restoring antitumor immunity in aged mice

CD8⁺ T cells play a central role in antitumor immune responses that kill cancer cells directly. In aged individuals, CD8⁺ T cell immunity is strongly suppressed, which is associated with cancer and other age-related diseases. The mechanism underlying this age-related decrease in immune function remains largely unknown. This study investigated the role of T cell function in age-related unresponsiveness to PD-1 blockade cancer therapy. We found inefficient generation of CD44^lowCD62L^low CD8⁺ T cell subset (P4) in draining lymph nodes of tumor-bearing aged mice. In vitro stimulation of naive CD8⁺ T cells first generated P4 cells, followed by effector/memory T cells. The P4 cells contained a unique set of genes related to enzymes involved in one-carbon (1C) metabolism, which is critical to antigen-specific T cell activation and mitochondrial function. Consistent with this finding, 1C-metabolism-related gene expression and mitochondrial respiration were down-regulated in aged CD8⁺ T cells compared with young CD8⁺ T cells. In aged OVA-specific T cell receptor (TCR) transgenic mice, ZAP-70 was not activated, even after inoculation with OVA-expressing tumor cells. The attenuation of TCR signaling appeared to be due to elevated expression of CD45RB phosphatase in aged CD8⁺ T cells. Surprisingly, strong stimulation by nonself cell injection into aged PD-1-deficient mice restored normal levels of CD45RB and ameliorated the emergence of P4 cells and 1C metabolic enzyme expression in CD8⁺ T cells, and antitumor activity. These findings indicate that impaired induction of the P4 subset may be responsible for the age-related resistance to PD-1 blockade, which can be rescued by strong TCR stimulation.

CD8+ T-Cell Repertoire in Human Leukocyte Antigen Class I-Mismatched Alloreactive Immune Response

In transplantation, direct allorecognition is a complex interplay between T-cell receptors (TCR) and HLA molecules and their bound peptides expressed on antigen-presenting cells. In analogy to HLA mismatched hematopoietic stem cell transplantation (HSCT), the TCR CDR3β repertoires of alloreactive cytotoxic CD8⁺ responder T cells, defined by the cell surface expression of CD137 and triggered in vitro by HLA mismatched stimulating cells, were analyzed in different HLA class I mismatched combinations. The same HLA mismatched stimulatory cells induced very different repertoires in distinct but HLA identical responders. Likewise, stimulator cells derived from HLA identical donors activated CD8⁺ cells expressing very different repertoires in the same mismatched responder. To mimic in vivo inflammation, expression of HLA class l antigens was upregulated in vitro on stimulating cells by the inflammatory cytokines TNFα and IFNβ. The repertoires differed whether the same responder cells were stimulated with cells treated or not with both cytokines. In conclusion, the selection and expansion of alloreactive cytotoxic T-cell clonotypes expressing a very diverse repertoire is observed repeatedly despite controlling for HLA disparities and is significantly influenced by the inflammatory status. This makes prediction of alloreactive T-cell repertoires a major challenge in HLA mismatched HSCT.

Predicting Cross-Reactivity and Antigen Specificity of T Cell Receptors

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

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

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSION

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

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

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

•

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

•

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

•

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

Foxp3+ Regulatory and Conventional CD4+ T Cells Display Similarly High Frequencies of Alloantigen-Reactive Cells

Foxp3⁺ regulatory T cells (Tregs) play a major role in acquired immune tolerance to allogenic transplants. Their suppressive activity is thought to require T cell receptor (TCR)-driven antigen recognition; little, however, is known about the fraction of Tregs able to recognize alloantigens within this T cell subset primarily educated against self-antigens. Performing transfer experiments of Tregs or conventional T cells (Tconv) into both lymphoreplete and lymphopenic mice, we observed a similarly high proportion of cells signaling through their TCR and proliferating in allogenic hosts. Furthermore, using an in vivo proliferation assay with limited T cell numbers infused into lymphopenic mice, we found that the overall frequency of alloreactive Tregs was similar if not higher to that of alloreactive Tconv. Overall our study highlights a noticeably high level of alloreactive Foxp3⁺ regulatory T cells accounting for their predominant role in transplantation tolerance.

APE-Gen: A Fast Method for Generating Ensembles of Bound Peptide-MHC Conformations

The Class I Major Histocompatibility Complex (MHC) is a central protein in immunology as it binds to intracellular peptides and displays them at the cell surface for recognition by T-cells. The structural analysis of bound peptide-MHC complexes (pMHCs) holds the promise of interpretable and general binding prediction (i.e., testing whether a given peptide binds to a given MHC). However, structural analysis is limited in part by the difficulty in modelling pMHCs given the size and flexibility of the peptides that can be presented by MHCs. This article describes APE-Gen (Anchored Peptide-MHC Ensemble Generator), a fast method for generating ensembles of bound pMHC conformations. APE-Gen generates an ensemble of bound conformations by iterated rounds of (i) anchoring the ends of a given peptide near known pockets in the binding site of the MHC, (ii) sampling peptide backbone conformations with loop modelling, and then (iii) performing energy minimization to fix steric clashes, accumulating conformations at each round. APE-Gen takes only minutes on a standard desktop to generate tens of bound conformations, and we show the ability of APE-Gen to sample conformations found in X-ray crystallography even when only sequence information is used as input. APE-Gen has the potential to be useful for its scalability (i.e., modelling thousands of pMHCs or even non-canonical longer peptides) and for its use as a flexible search tool. We demonstrate an example for studying cross-reactivity.

The variations of TRBV genes usages in the peripheral blood of a healthy population are associated with their evolution and single nucleotide polymorphisms

T cell receptors (TCRs) are a class of T cell surface molecules that recognize the antigen-derived peptides presented by the major histocompatibility complex (MHC) and are able to trigger a series of immune responses. TCRs are important members of the adaptive immune system that arose in the jawed fish 500 million years ago. T cell receptor beta variable (TRBV) genes have been widely used to characterize TCR repertoires. Studying the evolution of TRBV may help us to better understand the adaptive immune system. To investigate TRBV evolution and its impacts on the usages of TRBV genes in human populations, we compared the TRBV genes and their homologous sequences among humans, mouse, rhesus and chimpanzee, analyzed the single-nucleotide polymorphisms (SNPs) located at TRBV loci, and sequenced TCR repertoires in the peripheral blood of 97 healthy donors. We found that functional TRBVs are more evolutionarily conserved but possess more SNPs in human populations than do nonfunctional (pseudo) TRBVs. Based on the conservation levels in the four species, we classified the functional TRBVs into 2 groups: old (conserved between mouse and humans) and new (conserved only in primates). The new TRBVs evolve faster and possess more SNPs than the old TRBVs. The variations in TRBV genes frequencies in the peripheral blood of healthy donors are negatively correlated with SNP density. These observations suggest that TRBV usages may be influenced by TCR-MHC co-evolution.

Exploring the pre-immune landscape of antigen-specific T cells

Background

Adaptive immune responses to newly encountered pathogens depend on the mobilization of antigen-specific clonotypes from a vastly diverse pool of naive T cells. Using recent advances in immune repertoire sequencing technologies, models of the immune receptor rearrangement process, and a database of annotated T cell receptor (TCR) sequences with known specificities, we explored the baseline frequencies of T cells specific for defined human leukocyte antigen (HLA) class I-restricted epitopes in healthy individuals.

Methods

We used a database of TCR sequences with known antigen specificities and a probabilistic TCR rearrangement model to estimate the baseline frequencies of TCRs specific to distinct antigens epitopespecificT-cells. We verified our estimates using a publicly available collection of TCR repertoires from healthy individuals. We also interrogated a database of immunogenic and non-immunogenic peptides is used to link baseline T-cell frequencies with epitope immunogenicity.

Results

Our findings revealed a high degree of variability in the prevalence of T cells specific for different antigens that could be explained by the physicochemical properties of the corresponding HLA class I-bound peptides. The occurrence of certain rearrangements was influenced by ancestry and HLA class I restriction, and umbilical cord blood samples contained higher frequencies of common pathogen-specific TCRs. We also identified a quantitative link between specific T cell frequencies and the immunogenicity of cognate epitopes presented by defined HLA class I molecules.

Conclusions

Our results suggest that the population frequencies of specific T cells are strikingly non-uniform across epitopes that are known to elicit immune responses. This inference leads to a new definition of epitope immunogenicity based on specific TCR frequencies, which can be estimated with a high degree of accuracy in silico, thereby providing a novel framework to integrate computational and experimental genomics with basic and translational research efforts in the field of T cell immunology.

Electronic supplementary material

The online version of this article (10.1186/s13073-018-0577-7) contains supplementary material, which is available to authorized users.

General Prediction of Peptide-MHC Binding Modes Using Incremental Docking: A Proof of Concept

The class I major histocompatibility complex (MHC) is capable of binding peptides derived from intracellular proteins and displaying them at the cell surface. The recognition of these peptide-MHC (pMHC) complexes by T-cells is the cornerstone of cellular immunity, enabling the elimination of infected or tumoral cells. T-cell-based immunotherapies against cancer, which leverage this mechanism, can greatly benefit from structural analyses of pMHC complexes. Several attempts have been made to use molecular docking for such analyses, but pMHC structure remains too challenging for even state-of-the-art docking tools. To overcome these limitations, we describe the use of an incremental meta-docking approach for structural prediction of pMHC complexes. Previous methods applied in this context used specific constraints to reduce the complexity of this prediction problem, at the expense of generality. Our strategy makes no assumption and can potentially be used to predict binding modes for any pMHC complex. Our method has been tested in a re-docking experiment, reproducing the binding modes of 25 pMHC complexes whose crystal structures are available. This study is a proof of concept that incremental docking strategies can lead to general geometry prediction of pMHC complexes, with potential applications for immunotherapy against cancer or infectious diseases.

Preclinical Strategies to Identify Off-Target Toxicity of High-Affinity TCRs

Adoptive transfer of T cells engineered with a cancer-specific T cell receptor (TCR) has demonstrated clinical benefit. However, the risk for off-target toxicity of TCRs remains a concern. Here, we examined the cross-reactive profile of T cell clone (7B5) with a high functional sensitivity for the hematopoietic-restricted minor histocompatibility antigen HA-2 in the context of HLA-A*02:01. HA-2^pos Epstein-Barr virus-transformed B lymphoblastic cell lines (EBV-LCLs) and primary acute myeloid leukemia samples, but not hematopoietic HA-2^neg samples, are effectively recognized. However, we found unexpected off-target recognition of human fibroblasts and keratinocytes not expressing the HA-2 antigen. To uncover the origin of this off-target recognition, we performed an alanine scanning approach, identifying six out of nine positions to be important for peptide recognition. This indicates a low risk for broad cross-reactivity. However, using a combinatorial peptide library scanning approach, we identified a CDH13-derived peptide activating the 7B5 T cell clone. This was confirmed by recognition of CDH13-transduced EBV-LCLs and cell subsets endogenously expressing CDH13, such as proximal tubular epithelial cells. As such, we recommend the use of a combinatorial peptide library scan followed by screening against additional cell subsets to validate TCR specificity and detect off-target toxicity due to cross-reactivity directed against unrelated peptides before selecting candidate TCRs for clinical testing.

Structure-based Methods for Binding Mode and Binding Affinity Prediction for Peptide-MHC Complexes

Understanding the mechanisms involved in the activation of an immune response is essential to many fields in human health, including vaccine development and personalized cancer immunotherapy. A central step in the activation of the adaptive immune response is the recognition, by T-cell lymphocytes, of peptides displayed by a special type of receptor known as Major Histocompatibility Complex (MHC). Considering the key role of MHC receptors in T-cell activation, the computational prediction of peptide binding to MHC has been an important goal for many immunological applications. Sequence- based methods have become the gold standard for peptide-MHC binding affinity prediction, but structure-based methods are expected to provide more general predictions (i.e., predictions applicable to all types of MHC receptors). In addition, structural modeling of peptide-MHC complexes has the potential to uncover yet unknown drivers of T-cell activation, thus allowing for the development of better and safer therapies. In this review, we discuss the use of computational methods for the structural modeling of peptide-MHC complexes (i.e., binding mode prediction) and for the structure-based prediction of binding affinity.

Innovative Approaches to Improve Anti-Infective Vaccine Efficacy

Safe and efficacious vaccines are arguably the most successful medical interventions of all time. Yet the ongoing discovery of new pathogens, along with emergence of antibiotic-resistant pathogens and a burgeoning population at risk of such infections, imposes unprecedented public health challenges. To meet these challenges, innovative strategies to discover and develop new or improved anti-infective vaccines are necessary. These approaches must intersect the most meaningful insights into protective immunity and advanced technologies with capabilities to deliver immunogens for optimal immune protection. This goal is considered through several recent advances in host-pathogen relationships, conceptual strides in vaccinology, and emerging technologies. Given a clear and growing risk of pandemic disease should the threat of infection go unmet, developing vaccines that optimize protective immunity against high-priority and antibiotic-resistant pathogens represents an urgent and unifying imperative.

Interpreting T-Cell Cross-reactivity through Structure: Implications for TCR-Based Cancer Immunotherapy

Immunotherapy has become one of the most promising avenues for cancer treatment, making use of the patient’s own immune system to eliminate cancer cells. Clinical trials with T-cell-based immunotherapies have shown dramatic tumor regressions, being effective in multiple cancer types and for many different patients. Unfortunately, this progress was tempered by reports of serious (even fatal) side effects. Such therapies rely on the use of cytotoxic T-cell lymphocytes, an essential part of the adaptive immune system. Cytotoxic T-cells are regularly involved in surveillance and are capable of both eliminating diseased cells and generating protective immunological memory. The specificity of a given T-cell is determined through the structural interaction between the T-cell receptor (TCR) and a peptide-loaded major histocompatibility complex (MHC); i.e., an intracellular peptide–ligand displayed at the cell surface by an MHC molecule. However, a given TCR can recognize different peptide–MHC (pMHC) complexes, which can sometimes trigger an unwanted response that is referred to as T-cell cross-reactivity. This has become a major safety issue in TCR-based immunotherapies, following reports of melanoma-specific T-cells causing cytotoxic damage to healthy tissues (e.g., heart and nervous system). T-cell cross-reactivity has been extensively studied in the context of viral immunology and tissue transplantation. Growing evidence suggests that it is largely driven by structural similarities of seemingly unrelated pMHC complexes. Here, we review recent reports about the existence of pMHC “hot-spots” for cross-reactivity and propose the existence of a TCR interaction profile (i.e., a refinement of a more general TCR footprint in which some amino acid residues are more important than others in triggering T-cell cross-reactivity). We also make use of available structural data and pMHC models to interpret previously reported cross-reactivity patterns among virus-derived peptides. Our study provides further evidence that structural analyses of pMHC complexes can be used to assess the intrinsic likelihood of cross-reactivity among peptide-targets. Furthermore, we hypothesize that some apparent inconsistencies in reported cross-reactivities, such as a preferential directionality, might also be driven by particular structural features of the targeted pMHC complex. Finally, we explain why TCR-based immunotherapy provides a special context in which meaningful T-cell cross-reactivity predictions can be made.

Blood biomarkers of kidney transplant rejection, an endless search?

INTRODUCTION

The tailoring of immunosuppressive treatment is recognized as a promising strategy to improve long-term kidney graft outcome. To guide the standard care of transplant recipients, physicians need objective biomarkers that can identify an ongoing pathology with the graft or low intensity signals that will be later evolved to accelerated transplant rejection. The early identification of 'high-risk /low-risk' patients enables the adjustment of standard of caring, including managing the frequency of clinical visits and the immunosuppression dosing. Given their ease of availability and the compatibility with a large technical array, blood-based biomarkers have been widely scrutinized for use as potential predictive and diagnostic biomarkers. Areas covered: Here, the authors report on non-invasive biomarkers, such as modification of immune cell subsets and mRNA and miRNA profiles, identified in the blood of kidney transplant recipients collected before or after transplantation. Expert commentary: Combined with functional tests, the identification of biomarkers will improve our understanding of pathological processes and will contribute to a global improvement in clinical management.