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

A general pHLA-CD80 scaffold fusion protein to promote efficient antigen-specific T cell-based immunotherapy

Inadequate antigen-specific T cells activation hampers immunotherapy due to complex antigen presentation. In addition, therapeutic in vivo T cell expansion is constrained by slow expansion rates and limited functionality. Herein, we introduce a model fusion protein termed antigen-presenting cell-mimic fusion protein (APC-mimic), designed to greatly mimicking the natural antigen presentation pattern of antigen-presenting cells and directly expand T cells both in vitro and in vivo. The APC-mimic comprises the cognate peptide-human leukocyte antigen (pHLA) complex and the co-stimulatory marker CD80, which are natural ligands on APCs. Following a single stimulation, APC-mimic leads to an approximately 400-fold increase in the polyclonal expansion of antigen-specific T cells compared with the untreated group in vitro without the requirement for specialized antigen-presenting cells. Through the combination of single-cell TCR sequencing (scTCR-seq) and single-cell RNA sequencing (scRNA-seq), we identify an approximately 600-fold monoclonal expansion clonotype among these polyclonal clonotypes. It also exhibits suitability for in vivo applications confirmed in the OT-1 mouse model. Furthermore, T cells expanded by APC-mimic effectively inhibits tumor growth in adoptive cell transfer (ACT) murine models. These findings pave the way for the versatile APC-mimic platform for personalized therapeutics, enabling direct expansion of polyfunctional antigen-specific T cell subsets in vitro and in vivo.

Implications of MHC-restricted immunopeptidome in transplantation

The peptide presentation by donor and recipient major histocompatibility complex (MHC) molecules is the major driver of T-cell responses in transplantation. In this review, we address an emerging area of interest, the application of immunopeptidome in transplantation, and describe the potential opportunities that exist to use peptides for targeting alloreactive T cells. The immunopeptidome, the set of peptides presented on an individual's MHC, plays a key role in immune surveillance. In transplantation, the immunopeptidome is heavily influenced by MHC-derived peptides, delineating a key subset of the diverse peptide repertoire implicated in alloreactivity. A better understanding of the immunopeptidome in transplantation has the potential to open up new approaches to identify, characterize, longitudinally quantify, and therapeutically target donor-specific T cells and ultimately support more personalized immunotherapies to prevent rejection and promote allograft tolerance.

Structural basis for T cell recognition of cancer neoantigens and implications for predicting neoepitope immunogenicity

Adoptive cell therapy (ACT) with tumor-specific T cells has been shown to mediate durable cancer regression. Tumor-specific T cells are also the basis of other therapies, notably cancer vaccines. The main target of tumor-specific T cells are neoantigens resulting from mutations in self-antigens over the course of malignant transformation. The detection of neoantigens presents a major challenge to T cells because of their high structural similarity to self-antigens, and the need to avoid autoimmunity. How different a neoantigen must be from its wild-type parent for it to induce a T cell response is poorly understood. Here we review recent structural and biophysical studies of T cell receptor (TCR) recognition of shared cancer neoantigens derived from oncogenes, including p53R175H, KRASG12D, KRASG12V, HHATp8F, and PIK3CAH1047L. These studies have revealed that, in some cases, the oncogenic mutation improves antigen presentation by strengthening peptide-MHC binding. In other cases, the mutation is detected by direct interactions with TCR, or by energetically driven or other indirect strategies not requiring direct TCR contacts with the mutation. We also review antibodies designed to recognize peptide-MHC on cell surfaces (TCR-mimic antibodies) as an alternative to TCRs for targeting cancer neoantigens. Finally, we review recent computational advances in this area, including efforts to predict neoepitope immunogenicity and how these efforts may be advanced by structural information on peptide-MHC binding and peptide-MHC recognition by TCRs.

A robust deep learning workflow to predict CD8 + T-cell epitopes

BACKGROUND

T-cells play a crucial role in the adaptive immune system by triggering responses against cancer cells and pathogens, while maintaining tolerance against self-antigens, which has sparked interest in the development of various T-cell-focused immunotherapies. However, the identification of antigens recognised by T-cells is low-throughput and laborious. To overcome some of these limitations, computational methods for predicting CD8 + T-cell epitopes have emerged. Despite recent developments, most immunogenicity algorithms struggle to learn features of peptide immunogenicity from small datasets, suffer from HLA bias and are unable to reliably predict pathology-specific CD8 + T-cell epitopes.

METHODS

We developed TRAP (T-cell recognition potential of HLA-I presented peptides), a robust deep learning workflow for predicting CD8 + T-cell epitopes from MHC-I presented pathogenic and self-peptides. TRAP uses transfer learning, deep learning architecture and MHC binding information to make context-specific predictions of CD8 + T-cell epitopes. TRAP also detects low-confidence predictions for peptides that differ significantly from those in the training datasets to abstain from making incorrect predictions. To estimate the immunogenicity of pathogenic peptides with low-confidence predictions, we further developed a novel metric, RSAT (relative similarity to autoantigens and tumour-associated antigens), as a complementary to 'dissimilarity to self' from cancer studies.

RESULTS

TRAP was used to identify epitopes from glioblastoma patients as well as SARS-CoV-2 peptides, and it outperformed other algorithms in both cancer and pathogenic settings. TRAP was especially effective at extracting immunogenicity-associated properties from restricted data of emerging pathogens and translating them onto related species, as well as minimising the loss of likely epitopes in imbalanced datasets. We also demonstrated that the novel metric termed RSAT was able to estimate immunogenic of pathogenic peptides of various lengths and species. TRAP implementation is available at: https://github.com/ChloeHJ/TRAP .

CONCLUSIONS

This study presents a novel computational workflow for accurately predicting CD8 + T-cell epitopes to foster a better understanding of antigen-specific T-cell response and the development of effective clinical therapeutics.

A systematic safety pipeline for selection of T-cell receptors to enter clinical use

Cancer immunotherapy using T cell receptor-engineered T cells (TCR-Ts) represents a promising treatment option. However, technologies for pre-clinical safety assessment are incomplete or inaccessible to most laboratories. Here, TCR-T off-target reactivity was assessed in five steps: (1) Mapping target amino acids necessary for TCR-T recognition, followed by (2) a computational search for, and (3) reactivity screening against, candidate cross-reactive peptides in the human proteome. Natural processing and presentation of recognized peptides was evaluated using (4) short mRNAs, and (5) full-length proteins. TCR-Ts were screened for recognition of unintended HLA alleles, and as proxy for off-target reactivity in vivo, a syngeneic, HLA-A*02:01-transgenic mouse model was used. Validation demonstrated importance of studying recognition of full-length candidate off-targets, and that the clinically applied 1G4 TCR has a hitherto unknown reactivity to unintended HLA alleles, relevant for patient selection. This widely applicable strategy should facilitate evaluation of candidate therapeutic TCRs and inform clinical decision-making.

Defining and Studying B Cell Receptor and TCR Interactions

BCRs (Abs) and TCRs (or adaptive immune receptors [AIRs]) are the means by which the adaptive immune system recognizes foreign and self-antigens, playing an integral part in host defense, as well as the emergence of autoimmunity. Importantly, the interaction between AIRs and their cognate Ags defies a simple key-in-lock paradigm and is instead a complex many-to-many mapping between an individual's massively diverse AIR repertoire, and a similarly diverse antigenic space. Understanding how adaptive immunity balances specificity with epitopic coverage is a key challenge for the field, and terms such as broad specificity, cross-reactivity, and polyreactivity remain ill-defined and are used inconsistently. In this Immunology Notes and Resources article, a group of experimental, structural, and computational immunologists define commonly used terms associated with AIR binding, describe methodologies to study these binding modes, as well as highlight the implications of these different binding modes for therapeutic design.

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

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

Signatures of T cell immunity revealed using sequence similarity with TCRDivER algorithm

Changes in the T cell receptor (TCR) repertoires have become important markers for monitoring disease or therapy progression. With the rise of immunotherapy usage in cancer, infectious and autoimmune disease, accurate assessment and comparison of the "state" of the TCR repertoire has become paramount. One important driver of change within the repertoire is T cell proliferation following immunisation. A way of monitoring this is by investigating large clones of individual T cells believed to bind epitopes connected to the disease. However, as a single target can be bound by many different TCRs, monitoring individual clones cannot fully account for T cell cross-reactivity. Moreover, T cells responding to the same target often exhibit higher sequence similarity, which highlights the importance of accounting for TCR similarity within the repertoire. This complexity of binding relationships between a TCR and its target convolutes comparison of immune responses between individuals or comparisons of TCR repertoires at different timepoints. Here we propose TCRDivER algorithm (T cell Receptor Diversity Estimates for Repertoires), a global method of T cell repertoire comparison using diversity profiles sensitive to both clone size and sequence similarity. This approach allowed for distinction between spleen TCR repertoires of immunised and non-immunised mice, showing the need for including both facets of repertoire changes simultaneously. The analysis revealed biologically interpretable relationships between sequence similarity and clonality. These aid in understanding differences and separation of repertoires stemming from different biological context. With the rise of availability of sequencing data we expect our tool to find broad usage in clinical and research applications.

CD8 T cell function and cross-reactivity explored by stepwise increased peptide-HLA versus TCR affinity

Recruitment and activation of CD8 T cells occur through specific triggering of T cell receptor (TCR) by peptide-bound human leucocyte antigen (HLA) ligands. Within the generated trimeric TCR-peptide:HLA complex, the molecular binding affinities between peptide and HLA, and between TCR and peptide:HLA both impact T cell functional outcomes. However, how their individual and combined effects modulate immunogenicity and overall T cell responsiveness has not been investigated systematically. Here, we established two panels of human tumor peptide variants differing in their affinity to HLA. For precise characterization, we developed the “blue peptide assay”, an upgraded cell-based approach to measure the peptide:HLA affinity. These peptide variants were then used to investigate the cross-reactivity of tumor antigen-specific CD8 T cell clonotypes derived from blood of cancer patients after vaccination with either the native or an affinity-optimized Melan-A/MART-1 epitope, or isolated from tumor infiltrated lymph nodes (TILNs). Vaccines containing the native tumor epitope generated T cells with better functionality, and superior cross-reactivity against potential low affinity escape epitopes, as compared to T cells induced by vaccines containing an HLA affinity-optimized epitope. Comparatively, Melan-A/MART-1-specific TILN cells displayed functional and cross-reactive profiles that were heterogeneous and clonotype-dependent. Finally, we took advantage of a collection of T cells expressing affinity-optimized NY-ESO-1-specific TCRs to interrogate the individual and combined impact of peptide:HLA and TCR-pHLA affinities on overall CD8 T cell responses. We found profound and distinct effects of both biophysical parameters, with additive contributions and absence of hierarchical dominance. Altogether, the biological impact of peptide:HLA and TCR-pHLA affinities on T cell responses was carefully dissected in two antigenic systems, frequently targeted in human cancer immunotherapy. Our technology and stepwise comparison open new insights into the rational design and selection of vaccine-associated tumor-specific epitopes and highlight the functional and cross-reactivity profiles that endow T cells with best tumor control capacity.

T cell receptors (TCRs) employ diverse strategies to target a p53 cancer neoantigen

Adoptive cell therapy with tumor-specific T cells can mediate durable cancer regression. The prime target of tumor-specific T cells are neoantigens arising from mutations in self-proteins during malignant transformation. To understand T cell recognition of cancer neoantigens at the atomic level, we studied oligoclonal T cell receptors (TCRs) that recognize a neoepitope arising from a driver mutation in the p53 oncogene (p53R175H) presented by the major histocompatibility complex class I molecule HLA-A2. We previously reported the structures of three p53R175H-specific TCRs (38-10, 12-6, and 1a2) bound to p53R175H and HLA-A2. The structures showed that these TCRs discriminate between WT and mutant p53 by forming extensive interactions with the R175H mutation. Here, we report the structure of a fourth p53R175H-specific TCR (6-11) in complex with p53R175H and HLA-A2. In contrast to 38-10, 12-6, and 1a2, TCR 6-11 makes no direct contacts with the R175H mutation, yet is still able to distinguish mutant from WT p53. Structure-based in silico mutagenesis revealed that the 60-fold loss in 6-11 binding affinity for WT p53 compared to p53R175H is mainly due to the higher energetic cost of desolvating R175 in the WT p53 peptide during complex formation than H175 in the mutant. This indirect strategy for preferential neoantigen recognition by 6-11 is fundamentally different from the direct strategies employed by other TCRs and highlights the multiplicity of solutions to recognizing p53R175H with sufficient selectivity to mediate T cell killing of tumor but not normal cells.

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

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

The Anticancer Potential of T Cell Receptor-Engineered T Cells

Adoptively transferred T cell receptor (TCR)-transgenic T cells (TCR-T cells) are not restricted by cell surface expression of their targets and are therefore poised to become a main pillar of cellular cancer immunotherapies. Addressing clinical and laboratory data, we discuss emerging features for the efficient deployment of novel TCR-T therapies, such as selection of ideal TCRs targeting validated epitopes with well-characterized cancer cell expression and processing, enhancing TCR-T effector function, trafficking, expansion, persistence, and memory formation by strategic selection of substrate cells, and gene-engineering with synthetic co-stimulatory circuits. Overall, a better understanding of the relevant mechanisms of action and resistance will help prioritize the vast array of potential TCR-T optimizations for future clinical products.

Needle in a Haystack: The Naïve Repertoire as a Source of T Cell Receptors for Adoptive Therapy with Engineered T Cells

T cell engineering with antigen-specific T cell receptors (TCRs) has allowed the generation of increasingly specific, reliable, and versatile T cell products with near-physiological features. However, a broad applicability of TCR-based therapies in cancer is still limited by the restricted number of TCRs, often also of suboptimal potency, available for clinical use. In addition, targeting of tumor neoantigens with TCR-engineered T cell therapy moves the field towards a highly personalized treatment, as tumor neoantigens derive from somatic mutations and are extremely patient-specific. Therefore, relevant TCRs have to be de novo identified for each patient and within a narrow time window. The naïve repertoire of healthy donors would represent a reliable source due to its huge diverse TCR repertoire, which theoretically entails T cells for any antigen specificity, including tumor neoantigens. As a challenge, antigen-specific naïve T cells are of extremely low frequency and mostly of low functionality, making the identification of highly functional TCRs finding a "needle in a haystack." In this review, we present the technological advancements achieved in high-throughput mapping of patient-specific neoantigens and corresponding cognate TCRs and how these platforms can be used to interrogate the naïve repertoire for a fast and efficient identification of rare but therapeutically valuable TCRs for personalized adoptive T cell therapy.

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.

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

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