Changing the peptide specificity of a human T-cell receptor by directed evolution

RACER-m leverages structural features for sparse T cell specificity prediction

Reliable prediction of T cell specificity against antigenic signatures is a formidable task, complicated by the immense diversity of T cell receptor and antigen sequence space and the resulting limited availability of training sets for inferential models. Recent modeling efforts have demonstrated the advantage of incorporating structural information to overcome the need for extensive training sequence data, yet disentangling the heterogeneous TCR-antigen interface to accurately predict MHC-allele-restricted TCR-peptide interactions has remained challenging. Here, we present RACER-m, a coarse-grained structural model leveraging key biophysical information from the diversity of publicly available TCR-antigen crystal structures. Explicit inclusion of structural content substantially reduces the required number of training examples and maintains reliable predictions of TCR-recognition specificity and sensitivity across diverse biological contexts. Our model capably identifies biophysically meaningful point-mutant peptides that affect binding affinity, distinguishing its ability in predicting TCR specificity of point-mutants from alternative sequence-based methods. Its application is broadly applicable to studies involving both closely related and structurally diverse TCR-peptide pairs.

Enhanced T cell receptor specificity through framework engineering

Development of T cell receptors (TCRs) as immunotherapeutics is hindered by inherent TCR cross-reactivity. Engineering more specific TCRs has proven challenging, as unlike antibodies, improving TCR affinity does not usually improve specificity. Although various protein design approaches have been explored to surmount this, mutations in TCR binding interfaces risk broadening specificity or introducing new reactivities. Here we explored if TCR specificity could alternatively be tuned through framework mutations distant from the interface. Studying the 868 TCR specific for the HIV SL9 epitope presented by HLA-A2, we used deep mutational scanning to identify a framework mutation above the mobile CDR3β loop. This glycine to proline mutation had no discernable impact on binding affinity or functional avidity towards the SL9 epitope but weakened recognition of SL9 escape variants and led to fewer responses in a SL9-derived positional scanning library. In contrast, an interfacial mutation near the tip of CDR3α that also did not impact affinity or functional avidity towards SL9 weakened specificity. Simulations indicated that the specificity-enhancing mutation functions by reducing the range of loop motions, limiting the ability of the TCR to adjust to different ligands. Although our results are likely to be TCR dependent, using framework engineering to control TCR loop motions may be a viable strategy for improving the specificity of TCR-based immunotherapies.

Fluorescence labeling of anchor-modified Mart-1 peptide for increasing its affinity for HLA-A*0201: Hit two targets with one arrow

One of the most successful strategies in designing peptide-based cancer vaccines is modifying natural epitope peptides to increase their binding strength to human leukocyte antigens (HLAs). Anchor-modified Mart-1 peptide (ELAGIGILTV) is among the artificial epitope peptides with the highest binding affinity for HLA-A*0201. In this study, by fluorescence labeling of its either C- or N-terminus with Nε -(5-carboxyfluorescein)-l-lysine, we not only made it traceable but also drastically increased its binding strength to HLA-A*0201. HLA streptamer, for the first time, is introduced for measuring the binding constants (Ka ) of the labeled peptides. The affinity of the labeled peptides for the HLA-A*201 of the MCF-7 cells was extraordinarily high and co-incubating them with the highest possible amount of the unlabeled peptide, as a competitor, did not significantly prohibit them from binding to the HLA. The reproducibility of the obtained results was confirmed by using the T2 cell line. The HLA-deficient K562 cell line was used as the negative control. With in silico simulations, we found two hydrophobic pockets on both sides of HLA-A*0201 for anchoring the C- or N-terminal 5-carboxyfluorescein probe, which can explain the extraordinary affinity of the labeled peptides for the HLA-A*0201.

Protein engineering via sequence-performance mapping

Discovery and evolution of new and improved proteins has empowered molecular therapeutics, diagnostics, and industrial biotechnology. Discovery and evolution both require efficient screens and effective libraries, although they differ in their challenges because of the absence or presence, respectively, of an initial protein variant with the desired function. A host of high-throughput technologies-experimental and computational-enable efficient screens to identify performant protein variants. In partnership, an informed search of sequence space is needed to overcome the immensity, sparsity, and complexity of the sequence-performance landscape. Early in the historical trajectory of protein engineering, these elements aligned with distinct approaches to identify the most performant sequence: selection from large, randomized combinatorial libraries versus rational computational design. Substantial advances have now emerged from the synergy of these perspectives. Rational design of combinatorial libraries aids the experimental search of sequence space, and high-throughput, high-integrity experimental data inform computational design. At the core of the collaborative interface, efficient protein characterization (rather than mere selection of optimal variants) maps sequence-performance landscapes. Such quantitative maps elucidate the complex relationships between protein sequence and performance-e.g., binding, catalytic efficiency, biological activity, and developability-thereby advancing fundamental protein science and facilitating protein discovery and evolution.

The landscape of T cell antigens for cancer immunotherapy

The remarkable capacity of immunotherapies to induce durable regression in some patients with metastatic cancer relies heavily on T cell recognition of tumor-presented antigens. As checkpoint-blockade therapy has limited efficacy, tumor antigens have the potential to be exploited for complementary treatments, many of which are already in clinical trials. The surge of interest in this topic has led to the expansion of the tumor antigen landscape with the emergence of new antigen categories. Nonetheless, how different antigens compare in their ability to elicit efficient and safe clinical responses remains largely unknown. Here, we review known cancer peptide antigens, their attributes and the relevant clinical data and discuss future directions.

Rapid screening of TCR-pMHC interactions by the YAMTAD system

Personalized immunotherapy, such as cancer vaccine and TCR-T methods, demands rapid screening of TCR-pMHC interactions. While several screening approaches have been developed, their throughput is limited. Here, the Yeast Agglutination Mediated TCR antigen Discovery system (YAMTAD) was designed and demonstrated to allow fast and unbiased library-on-library screening of TCR-pMHC interactions. Our proof-of-principle study achieved high sensitivity and specificity in identifying antigens for a given TCR and identifying TCRs recognizing a given pMHC for modest library sizes. Finally, the enrichment of high-affinity TCR-pMHC interactions by YAMTAD in library-on-library screening was demonstrated. Given the high throughput (10⁶–10⁸ × 10⁶–10⁸ in theory) and simplicity (identifying TCR-pMHC interactions without purification of TCR and pMHC) of YAMTAD, this study provides a rapid but effective platform for TCR-pMHC interaction screening, with valuable applications in future personalized immunotherapy.

Engineering the T cell receptor for fun and profit: Uncovering complex biology, interrogating the immune system, and targeting disease

T cell receptors (TCRs) orchestrate cellular immunity by recognizing peptide antigens bound and presented by major histocompatibility complex (MHC) proteins. Due to the TCR's central role in immunity and tight connection with human health, there has been significant interest in modulating TCR properties through protein engineering methods. Complicating these efforts is the complexity and vast diversity of TCR-peptide/MHC interfaces, the interdependency between TCR affinity, specificity, and cross-reactivity, and the sophisticated relationships between TCR binding properties and T cell function, many aspects of which are not well understood. Here we review TCR engineering, starting with a brief historical overview followed by discussions of more recent developments, including new efforts and opportunities to engineer TCR affinity, modulate specificity, and develop novel TCR-based constructs.

Application of phage display for T-cell receptor discovery

The immune system is tasked to keep our body unharmed and healthy. In the immune system, B- and T-lymphocytes are the two main components working together to stop and eliminate invading threats like virus particles, bacteria, fungi and parasite from attacking our healthy cells. The function of antibodies is relatively more direct in target recognition as compared to T-cell receptors (TCR) which recognizes antigenic peptides being presented on the major histocompatibility complex (MHC). Although phage display has been widely applied for antibody presentation, this is the opposite in the case of TCR. The cell surface TCR is a relatively large and complex molecule, making presentation on phage surfaces challenging. Even so, recombinant versions and modifications have been introduced to allow the growing development of TCR in phage display. In addition, the increasing application of TCR for immunotherapy has made it an important binding motif to be developed by phage display. This review will emphasize on the application of phage display for TCR discovery as well as the engineering aspect of TCR for improved characteristics.

Directed Evolution: Methodologies and Applications

Directed evolution aims to expedite the natural evolution process of biological molecules and systems in a test tube through iterative rounds of gene diversifications and library screening/selection. It has become one of the most powerful and widespread tools for engineering improved or novel functions in proteins, metabolic pathways, and even whole genomes. This review describes the commonly used gene diversification strategies, screening/selection methods, and recently developed continuous evolution strategies for directed evolution. Moreover, we highlight some representative applications of directed evolution in engineering nucleic acids, proteins, pathways, genetic circuits, viruses, and whole cells. Finally, we discuss the challenges and future perspectives in directed evolution.

Engineering soluble T-cell receptors for therapy

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

Adoptive Immunotherapy beyond CAR T-Cells

Adoptive cell immunotherapy (ACT) is a vibrant field of cancer treatment that began progressive development in the 1980s. One of the most prominent and promising examples is chimeric antigen receptor (CAR) T-cell immunotherapy for the treatment of B-cell hematologic malignancies. Despite success in the treatment of B-cell lymphomas and leukemia, CAR T-cell therapy remains mostly ineffective for solid tumors. This is due to several reasons, such as the heterogeneity of the cellular composition in solid tumors, the need for directed migration and penetration of CAR T-cells against the pressure gradient in the tumor stroma, and the immunosuppressive microenvironment. To substantially improve the clinical efficacy of ACT against solid tumors, researchers might need to look closer into recent developments in the other branches of adoptive immunotherapy, both traditional and innovative. In this review, we describe the variety of adoptive cell therapies beyond CAR T-cell technology, i.e., exploitation of alternative cell sources with a high therapeutic potential against solid tumors (e.g., CAR M-cells) or aiming to be universal allogeneic (e.g., CAR NK-cells, γδ T-cells), tumor-infiltrating lymphocytes (TILs), and transgenic T-cell receptor (TCR) T-cell immunotherapies. In addition, we discuss the strategies for selection and validation of neoantigens to achieve efficiency and safety. We provide an overview of non-conventional TCRs and CARs, and address the problem of mispairing between the cognate and transgenic TCRs. Finally, we summarize existing and emerging approaches for manufacturing of the therapeutic cell products in traditional, semi-automated and fully automated Point-of-Care (PoC) systems.

An Engineered T Cell Receptor Variant Realizes the Limits of Functional Binding Modes

T cell receptors (TCRs) orchestrate cellular immunity by recognizing peptides presented by a range of major histocompatibility complex (MHC) proteins. Naturally occurring TCRs bind the composite peptide/MHC surface, recognizing peptides that are structurally and chemically compatible with the TCR binding site. Here we describe a molecularly evolved TCR variant that binds the human class I MHC protein HLA-A2 independent of the bound peptide, achieved by a drastic perturbation of the TCR binding geometry that places the molecule far from the peptide binding groove. This unique geometry is unsupportive of normal T cell signaling. A substantial divergence between affinity measurements in solution and in two dimensions between proximal cell membranes leads us to attribute the lack of signaling to steric hindrance that limits binding in the confines of a cell-cell interface. Our results provide an example of how receptor binding geometry can impact T cell function and provide further support for the view that germline-encoded residues in TCR binding loops evolved to drive productive TCR recognition and signaling.

Application of mass spectrometry-based MHC immunopeptidome profiling in neoantigen identification for tumor immunotherapy

One of the challenges for cancer vaccine and adoptive T-cell-based immunotherapy is to identify the major histocompatibility complex (MHC)-associated non-self neoantigens recognized by T cells. T cell epitope in silico prediction algorithms have been widely used for neoantigen prediction; nonetheless, this platform lacks the experimental evidence of directly identification of the presented epitopes on cell surface. Currently, mass spectrometry (MS)-based proteomics is an advanced analytical technology for large-scale peptide sequencing, which has become a powerful tool for directly profiling the immunopeptidome presented by MHC molecules. Integrating with next-generation sequencing, proteogenomic analysis provides the "gold standard" for neoantigen identification at protein level. This method discovers the tumor-specific neoantigens derived from somatic mutations, proteasome splicing, noncoding RNA, and post-translational modified antigens. Herein, we review basis of antigen processing and presentation, tumor antigen classification, existing approaches for neoantigen discovery, quantitative proteomics, epitope prediction programs, and advantages and drawbacks of proteomics workflow for MHC immunopeptidome profiling. Furthermore, we summarize 40 recently published reports addressing the fundamental theory, breakthrough and most advanced updates for the mass spectrometry-based neoantigen discovery for cancer immunotherapy.

T-cell Receptors Engineered De Novo for Peptide Specificity Can Mediate Optimal T-cell Activity without Self Cross-Reactivity

Despite progress in adoptive T-cell therapies, the identification of targets remains a challenge. Although chimeric antigen receptors recognize cell-surface antigens, T-cell receptors (TCR) have the advantage that they can target the array of intracellular proteins by binding to peptides associated with major histocompatibility complex (MHC) products (pepMHC). Although hundreds of cancer-associated peptides have been reported, it remains difficult to identify effective TCRs against each pepMHC complex. Conventional approaches require isolation of antigen-specific CD8⁺ T cells, followed by TCRαβ gene isolation and validation. To bypass this process, we used directed evolution to engineer TCRs with desired peptide specificity. Here, we compared the activity and cross-reactivity of two affinity-matured TCRs (T1 and RD1) with distinct origins. T1-TCR was isolated from a melanoma-reactive T-cell line specific for MART-1/HLA-A2, whereas RD1-TCR was derived de novo against MART-1/HLA-A2 by in vitro engineering. Despite their distinct origins, both TCRs exhibited similar peptide fine specificities, focused on the center of the MART-1 peptide. In CD4⁺ T cells, both TCRs mediated activity against MART-1 presented by HLA-A2. However, in CD8⁺ T cells, T1, but not RD1, demonstrated cross-reactivity with endogenous peptide/HLA-A2 complexes. Based on the fine specificity of these and other MART-1 binding TCRs, we conducted bioinformatics scans to identify structurally similar self-peptides in the human proteome. We showed that the T1-TCR cross-reacted with many of these self-peptides, whereas the RD1-TCR was rarely cross-reactive. Thus, TCRs such as RD1, generated de novo against cancer antigens, can serve as an alternative to TCRs generated from T-cell clones.

A stochastic individual-based model to explore the role of spatial interactions and antigen recognition in the immune response against solid tumours

Spatial interactions between cancer and immune cells, as well as the recognition of tumour antigens by cells of the immune system, play a key role in the immune response against solid tumours. The existing mathematical models generally focus only on one of these key aspects. We present here a spatial stochastic individual-based model that explicitly captures antigen expression and recognition. In our model, each cancer cell is characterised by an antigen profile which can change over time due to either epimutations or mutations. The immune response against the cancer cells is initiated by the dendritic cells that recognise the tumour antigens and present them to the cytotoxic T cells. Consequently, T cells become activated against the tumour cells expressing such antigens. Moreover, the differences in movement between inactive and active immune cells are explicitly taken into account by the model. Computational simulations of our model clarify the conditions for the emergence of tumour clearance, dormancy or escape, and allow us to assess the impact of antigenic heterogeneity of cancer cells on the efficacy of immune action. Ultimately, our results highlight the complex interplay between spatial interactions and adaptive mechanisms that underpins the immune response against solid tumours, and suggest how this may be exploited to further develop cancer immunotherapies.

Integrating Experiment and Theory to Understand TCR-pMHC Dynamics

The conformational dynamism of proteins is well established. Rather than having a single structure, proteins are more accurately described as a conformational ensemble that exists across a rugged energy landscape, where different conformational sub-states interconvert. The interaction between αβ T cell receptors (TCR) and cognate peptide-MHC (pMHC) is no exception, and is a dynamic process that involves substantial conformational change. This review focuses on technological advances that have begun to establish the role of conformational dynamics and dynamic allostery in TCR recognition of the pMHC and the early stages of signaling. We discuss how the marriage of molecular dynamics (MD) simulations with experimental techniques provides us with new ways to dissect and interpret the process of TCR ligation. Notably, application of simulation techniques lags behind other fields, but is predicted to make substantial contributions. Finally, we highlight integrated approaches that are being used to shed light on some of the key outstanding questions in the early events leading to TCR signaling.

Adoptive T Cell Therapy: New Avenues Leading to Safe Targets and Powerful Allies

Adoptive transfer of TCR-engineered T cells is a potent therapy, able to induce clinical responses in different human malignancies. Nevertheless, treatment toxicities may occur and, in particular for solid tumors, responses may be variable and often not durable. To address these challenges, it is imperative to carefully select target antigens and to immunologically interrogate the corresponding tumors when designing optimal T cell therapies. Here, we review recent advances, covering both omics- and laboratory tools that can enable the selection of optimal T cell epitopes and TCRs as well as the identification of dominant immune evasive mechanisms within tumor tissues. Furthermore, we discuss how these techniques may aid in a rational design of effective combinatorial adoptive T cell therapies.

Subtle changes at the variable domain interface of the T-cell receptor can strongly increase affinity

Most affinity-maturation campaigns for antibodies and T-cell receptors (TCRs) operate on the residues at the binding site, located within the loops known as complementarity-determining regions (CDRs). Accordingly, mutations in contact residues, or so-called "second shell" residues, that increase affinity are typically identified by directed evolution involving combinatorial libraries. To determine the impact of residues located at a distance from the binding site, here we used single-codon libraries of both CDR and non-CDR residues to generate a deep mutational scan of a human TCR against the cancer antigen MART-1·HLA-A2. Non-CDR residues included those at the interface of the TCR variable domains (Vα and Vβ) and surface-exposed framework residues. Mutational analyses showed that both Vα/Vβ interface and CDR residues were important in maintaining binding to MART-1·HLA-A2, probably due to either structural requirements for proper Vα/Vβ association or direct contact with the ligand. More surprisingly, many Vα/Vβ interface substitutions yielded improved binding to MART-1·HLA-A2. To further explore this finding, we constructed interface libraries and selected them for improved stability or affinity. Among the variants identified, one conservative substitution (F45βY) was most prevalent. Further analysis of F45βY showed that it enhanced thermostability and increased affinity by 60-fold. Thus, introducing a single hydroxyl group at the Vα/Vβ interface, at a significant distance from the TCR·peptide·MHC-binding site, remarkably affected ligand binding. The variant retained a high degree of specificity for MART-1·HLA-A2, indicating that our approach provides a general strategy for engineering improvements in either soluble or cell-based TCRs for therapeutic purposes.

Emerging Concepts in TCR Specificity: Rationalizing and (Maybe) Predicting Outcomes

T cell specificity emerges from a myriad of processes, ranging from the biological pathways that control T cell signaling to the structural and physical mechanisms that influence how TCRs bind peptides and MHC proteins. Of these processes, the binding specificity of the TCR is a key component. However, TCR specificity is enigmatic: TCRs are at once specific but also cross-reactive. Although long appreciated, this duality continues to puzzle immunologists and has implications for the development of TCR-based therapeutics. In this review, we discuss TCR specificity, emphasizing results that have emerged from structural and physical studies of TCR binding. We show how the TCR specificity/cross-reactivity duality can be rationalized from structural and biophysical principles. There is excellent agreement between predictions from these principles and classic predictions about the scope of TCR cross-reactivity. We demonstrate how these same principles can also explain amino acid preferences in immunogenic epitopes and highlight opportunities for structural considerations in predictive immunology.

Dynamical footprint of cross-reactivity in a human autoimmune T-cell receptor

The present work focuses on the dynamical aspects of cross-reactivity between myelin based protein (MBP) self-peptide and two microbial peptides (UL15, PMM) for Hy.1B11 T-cell receptor (TCR). This same TCR was isolated from a patient suffering from multiple sclerosis (MS). The study aims at highlighting the chemical interactions underlying recognition mechanisms between TCR and the peptides presented by Major Histocompatibility Complex (MHC) proteins, which form a crucial component in adaptive immune response against foreign antigens. Since the ability of a TCR to recognize different peptide antigens presented by MHC depends on its cross-reactivity, we used molecular dynamics methods to obtain atomistic detail on TCR-peptide-MHC complexes. Our results show how the dynamical basis of Hy.1B11 TCR’s cross-reactivity is rooted in a similar bridging interaction pattern across the TCR-peptide-MHC interface. Our simulations confirm the importance of TCR CDR3α E98 residue interaction with MHC and a predominant role of P6 peptide residue in MHC binding affinity. Altogether, our study provides energetic and dynamical insights into factors governing peptide recognition by the cross-reactive Hy.1B11 TCR, found in MS patient.

Deep Mutational Scans as a Guide to Engineering High Affinity T Cell Receptor Interactions with Peptide-bound Major Histocompatibility Complex

Proteins are often engineered to have higher affinity for their ligands to achieve therapeutic benefit. For example, many studies have used phage or yeast display libraries of mutants within complementarity-determining regions to affinity mature antibodies and T cell receptors (TCRs). However, these approaches do not allow rapid assessment or evolution across the entire interface. By combining directed evolution with deep sequencing, it is now possible to generate sequence fitness landscapes that survey the impact of every amino acid substitution across the entire protein-protein interface. Here we used the results of deep mutational scans of a TCR-peptide-MHC interaction to guide mutational strategies. The approach yielded stable TCRs with affinity increases of >200-fold. The substitutions with the greatest enrichments based on the deep sequencing were validated to have higher affinity and could be combined to yield additional improvements. We also conducted in silico binding analyses for every substitution to compare them with the fitness landscape. Computational modeling did not effectively predict the impacts of mutations distal to the interface and did not account for yeast display results that depended on combinations of affinity and protein stability. However, computation accurately predicted affinity changes for mutations within or near the interface, highlighting the complementary strengths of computational modeling and yeast surface display coupled with deep mutational scanning for engineering high affinity TCRs.

An Engineered Switch in T Cell Receptor Specificity Leads to an Unusual but Functional Binding Geometry

Utilizing a diverse binding site, T cell receptors (TCRs) specifically recognize a composite ligand comprised of a foreign peptide and a major histocompatibility complex protein (MHC). To help understand the determinants of TCR specificity, we studied a parental and engineered receptor whose peptide specificity had been switched via molecular evolution. Altered specificity was associated with a significant change in TCR-binding geometry, but this did not impact the ability of the TCR to signal in an antigen-specific manner. The determinants of binding and specificity were distributed among contact and non-contact residues in germline and hypervariable loops, and included disruption of key TCR-MHC interactions that bias αβ TCRs toward particular binding modes. Sequence-fitness landscapes identified additional mutations that further enhanced specificity. Our results demonstrate that TCR specificity arises from the distributed action of numerous sites throughout the interface, with significant implications for engineering therapeutic TCRs with novel and functional recognition properties.

Protein Engineering by Combined Computational and In Vitro Evolution Approaches

Two alternative strategies are commonly used to study protein-protein interactions (PPIs) and to engineer protein-based inhibitors. In one approach, binders are selected experimentally from combinatorial libraries of protein mutants that are displayed on a cell surface. In the other approach, computational modeling is used to explore an astronomically large number of protein sequences to select a small number of sequences for experimental testing. While both approaches have some limitations, their combination produces superior results in various protein engineering applications. Such applications include the design of novel binders and inhibitors, the enhancement of affinity and specificity, and the mapping of binding epitopes. The combination of these approaches also aids in the understanding of the specificity profiles of various PPIs.