Facile repurposing of peptide-MHC-restricted antibodies for cancer immunotherapy

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.

Fast on-rates of chimeric antigen receptors enhance the sensitivity to peptide MHC via antigen rebinding

Chimeric antigen receptor (CAR) is a synthetic receptor that induces T cell-mediated lysis of abnormal cells. As cancer driver proteins are present at low levels on the cell surface, they can cause weak CAR reactivity, resulting in antigen sensitivity defects and consequently limited therapeutic efficacy. Although affinity maturation enhances the efficacy of CAR-T cell therapy, it causes off-target cross-reactions resulting in adverse effects. Preferentially expressed antigen in melanoma (PRAME) is an intracellular oncoprotein that is overexpressed in various tumors and restricted in normal tissues, except the testis. Therefore, PRAME could be an ideal target for cancer immunotherapy. In this study, we developed an experimental CAR system comprising six single-chain variable fragments that specifically recognizes the PRAMEp301/HLA-A*24:02 complex. Cell-mediated cytotoxicity was demonstrated using a panel of CARs with a wide range of affinities (KD = 10-10-10-7 M) and affinity modulation. CAR-T cells with fast on-rates enhance antigen sensitivity by accelerating the killing rates of these cells. Alanine scanning data demonstrated the potential of genetically engineered CARs to reduce the risk of cross-reactivity, even among CARs with high affinities. Given the correlation between on-rates and dwell time that occurs in rebinding and cell-mediated cytotoxicity, it is proposed that CAR-binding characteristics, including on-rate, play a pivotal role in the lytic capacity of peptide-major histocompatibility complex-targeting CAR-T cells, thus facilitating the development of strategies whereby genetically engineered CARs target intracellular antigens in cancer cells to lyse the cells.

CRISPR-Cas9 screening reveals a distinct class of MHC-I binders with precise HLA-peptide recognition

Human leukocyte antigen (HLA) class-I molecules present fragments of the cellular proteome to the T cell receptor (TCR) of cytotoxic T cells to control infectious diseases and cancer. The large number of combinations of HLA class-I allotypes and peptides allows for highly specific and dedicated low-affinity interactions to a diverse array of TCRs and natural killer (NK) cell receptors. Whether the divergent HLA class-I peptide complex is exclusive for interactions with these proteins is unknown. Using genome-wide CRISPR-Cas9 activation and knockout screens, we identified peptide-specific HLA-C∗07 combinations that can interact with the surface molecules CD55 and heparan sulfate. These interactions closely resemble the HLA class-I interaction with the TCR regarding both the affinity range and the specificity of the peptide and HLA allele. These findings indicate that various proteins can specifically bind HLA class-I peptide complexes due to their polymorphic nature, which suggests there are more interactions like the ones we describe here.

Enzyme-Instructed Photoactivatable Supramolecular Antigens on Cancer Cell Membranes for Precision-Controlled T-Cell-Based Cancer Immunotherapy

Cancer immunotherapies based on cytotoxic CD8+ T lymphocytes (CTLs) are highly promising for cancer treatment. The specific interaction between T-cell receptors and peptide-MHC-I complexes (pMHC-I) on cancer cell membranes critically determines their therapeutic outcomes. However, the lack of appropriate endogenous antigens for MHC-I presentation disables tumor recognition by CTLs. By devising three antigen-loaded self-assembling peptides of pY-K(Ag)-ERGD, pY-K(Ag)-E, and Y-K(Ag)-ERGD to noncovalently generate light-activatable supramolecular antigens at tumor sites in different manners, we report pY-K(Ag)-ERGD as a promising candidate to endow tumor cells with pMHC-I targets on demand. Specifically, pY-K(Ag)-ERGD first generates low-antigenic supramolecular antigens on cancer cell membranes, and a successive light pulse allows antigen payloads to efficiently release from the supramolecular scaffold, directly producing antigenic pMHC-I. Intravenous administration of pY-K(Ag)-ERGD enables light-controlled tumor inhibition when combined with adoptively transferred antigen-specific CTLs. Our strategy is feasible for broadening tumor antigen repertoires for T-cell immunotherapies and advancing precision-controlled T-cell immunotherapies.

Dual role of the peptide-loading complex as proofreader and limiter of MHC-I presentation

Antigen presentation via major histocompatibility complex class I (MHC-I) molecules is essential for surveillance by the adaptive immune system. Central to this process is the peptide-loading complex (PLC), which translocates peptides from the cytosol to the endoplasmic reticulum and catalyzes peptide loading and proofreading of peptide-MHC-I (pMHC-I) complexes. Despite its importance, the impact of individual PLC components on the presented pMHC-I complexes is still insufficiently understood. Here, we used stoichiometrically defined antibody-nanobody complexes and engineered soluble T cell receptors (sTCRs) to quantify different MHC-I allomorphs and defined pMHC-I complexes, respectively. Thereby, we uncovered distinct effects of individual PLC components on the pMHC-I surface pool. Knockouts of components of the PLC editing modules, namely tapasin, ERp57, or calreticulin, changed the MHC-I surface composition to a reduced proportion of HLA-A*02:01 presentation compensated by a higher ratio of HLA-B*40:01 molecules. Intriguingly, these knockouts not only increased the presentation of suboptimally loaded HLA-A*02:01 complexes but also elevated the presentation of high-affinity peptides overexpressed in the cytosol. Our findings suggest that the components of the PLC editing module serve a dual role, acting not only as peptide proofreaders but also as limiters for abundant peptides. This dual function ensures the presentation of a broad spectrum of antigenic peptides.

Molecular basis for antibody recognition of multiple drug-peptide/MHC complexes

The HapImmuneTM platform exploits covalent inhibitors as haptens for creating major histocompatibility complex (MHC)-presented tumor-specific neoantigens by design, combining targeted therapies with immunotherapy for the treatment of drug-resistant cancers. A HapImmune antibody, R023, recognizes multiple sotorasib-conjugated KRAS(G12C) peptides presented by different human leukocyte antigens (HLAs). This high specificity to sotorasib, coupled with broad HLA-binding capability, enables such antibodies, when reformatted as T cell engagers, to potently and selectively kill sotorasib-resistant KRAS(G12C) cancer cells expressing different HLAs upon sotorasib treatment. The loosening of HLA restriction could increase the patient population that can benefit from this therapeutic approach. To understand the molecular basis for its unconventional binding capability, we used single-particle cryogenic electron microscopy to determine the structures of R023 bound to multiple sotorasib-peptide conjugates presented by different HLAs. R023 forms a pocket for sotorasib between the VH and VL domains, binds HLAs in an unconventional, angled way, with VL making most contacts with them, and makes few contacts with the peptide moieties. This binding mode enables the antibody to accommodate different hapten-peptide conjugates and to adjust its conformation to different HLAs presenting hapten-peptides. Deep mutational scanning validated the structures and revealed distinct levels of mutation tolerance by sotorasib- and HLA-binding residues. Together, our structural information and sequence landscape analysis reveal key features for achieving MHC-restricted recognition of multiple hapten-peptide antigens, which will inform the development of next-generation therapeutic antibodies.

Bispecific antibody drug conjugates: Making 1+1>2

Bispecific antibody‒drug conjugates (BsADCs) represent an innovative therapeutic category amalgamating the merits of antibody‒drug conjugates (ADCs) and bispecific antibodies (BsAbs). Positioned as the next-generation ADC approach, BsADCs hold promise for ameliorating extant clinical challenges associated with ADCs, particularly pertaining to issues such as poor internalization, off-target toxicity, and drug resistance. Presently, ten BsADCs are undergoing clinical trials, and initial findings underscore the imperative for ongoing refinement. This review initially delves into specific design considerations for BsADCs, encompassing target selection, antibody formats, and the linker-payload complex. Subsequent sections delineate the extant progress and challenges encountered by BsADCs, illustrated through pertinent case studies. The amalgamation of BsAbs with ADCs offers a prospective solution to prevailing clinical limitations of ADCs. Nevertheless, the symbiotic interplay among BsAb, linker, and payload necessitates further optimizations and coordination beyond a simplistic "1 + 1" to effectively surmount the extant challenges facing the BsADC domain.

Experimental Structures of Antibody/MHC-I Complexes Reveal Details of Epitopes Overlooked by Computational Prediction

mAbs to MHC class I (MHC-I) molecules have proved to be crucial reagents for tissue typing and fundamental studies of immune recognition. To augment our understanding of epitopic sites seen by a set of anti-MHC-I mAb, we determined X-ray crystal structures of four complexes of anti-MHC-I Fabs bound to peptide/MHC-I/β2-microglobulin (pMHC-I). An anti-H2-Dd mAb, two anti-MHC-I α3 domain mAbs, and an anti-β2-microglobulin mAb bind pMHC-I at sites consistent with earlier mutational and functional experiments, and the structures explain allelomorph specificity. Comparison of the experimentally determined structures with computationally derived models using AlphaFold Multimer showed that although predictions of the individual pMHC-I heterodimers were quite acceptable, the computational models failed to properly identify the docking sites of the mAb on pMHC-I. The experimental and predicted structures provide insight into strengths and weaknesses of purely computational approaches and suggest areas that merit additional attention.

The present and future of bispecific antibodies for cancer therapy

Bispecific antibodies (bsAbs) enable novel mechanisms of action and/or therapeutic applications that cannot be achieved using conventional IgG-based antibodies. Consequently, development of these molecules has garnered substantial interest in the past decade and, as of the end of 2023, 14 bsAbs have been approved: 11 for the treatment of cancer and 3 for non-oncology indications. bsAbs are available in different formats, address different targets and mediate anticancer function via different molecular mechanisms. Here, we provide an overview of recent developments in the field of bsAbs for cancer therapy. We focus on bsAbs that are approved or in clinical development, including bsAb-mediated dual modulators of signalling pathways, tumour-targeted receptor agonists, bsAb-drug conjugates, bispecific T cell, natural killer cell and innate immune cell engagers, and bispecific checkpoint inhibitors and co-stimulators. Finally, we provide an outlook into next-generation bsAbs in earlier stages of development, including trispecifics, bsAb prodrugs, bsAbs that induce degradation of tumour targets and bsAbs acting as cytokine mimetics.

Structural and Dynamic-Based Characterization of the Recognition Patterns of E7 and TRP-2 Epitopes by MHC Class I Receptors through Computational Approaches

A detailed comprehension of MHC-epitope recognition is essential for the design and development of new antigens that could be effectively used in immunotherapy. Yet, the high variability of the peptide together with the large abundance of MHC variants binding makes the process highly specific and large-scale characterizations extremely challenging by standard experimental techniques. Taking advantage of the striking predictive accuracy of AlphaFold, we report a structural and dynamic-based strategy to gain insights into the molecular basis that drives the recognition and interaction of MHC class I in the immune response triggered by pathogens and/or tumor-derived peptides. Here, we investigated at the atomic level the recognition of E7 and TRP-2 epitopes to their known receptors, thus offering a structural explanation for the different binding preferences of the studied receptors for specific residues in certain positions of the antigen sequences. Moreover, our analysis provides clues on the determinants that dictate the affinity of the same epitope with different receptors. Collectively, the data here presented indicate the reliability of the approach that can be straightforwardly extended to a large number of related systems.

Experimental structures of antibody/MHC-I complexes reveal details of epitopes overlooked by computational prediction

Monoclonal antibodies (mAb) to major histocompatibility complex class I (MHC-I) molecules have proved to be crucial reagents for tissue typing and fundamental studies of immune recognition. To augment our understanding of epitopic sites seen by a set of anti-MHC-I mAb, we determined X-ray crystal structures of four complexes of anti-MHC-I antigen-binding fragments (Fab) bound to peptide/MHC-I/β2m (pMHC-I). An anti-H2-Dd mAb, two anti-MHC-I α3 domain mAb, and an anti-β2-microglobulin (β2m) mAb bind pMHC-I at sites consistent with earlier mutational and functional experiments, and the structures explain allelomorph specificity. Comparison of the experimentally determined structures with computationally derived models using AlphaFold Multimer (AF-M) showed that although predictions of the individual pMHC-I heterodimers were quite acceptable, the computational models failed to properly identify the docking sites of the mAb on pMHC-I. The experimental and predicted structures provide insight into strengths and weaknesses of purely computational approaches and suggest areas that merit additional attention.

Structural principles of peptide-centric chimeric antigen receptor recognition guide therapeutic expansion

Peptide-centric chimeric antigen receptors (PC-CARs) recognize oncoprotein epitopes displayed by cell-surface human leukocyte antigens (HLAs) and offer a promising strategy for targeted cancer therapy. We have previously developed a PC-CAR targeting a neuroblastoma-associated PHOX2B peptide, leading to robust tumor cell lysis restricted by two common HLA allotypes. Here, we determine the 2.1-angstrom crystal structure of the PC-CAR-PHOX2B-HLA-A*24:02-β2m complex, which reveals the basis for antigen-specific recognition through interactions with CAR complementarity-determining regions (CDRs). This PC-CAR adopts a diagonal docking mode, where interactions with both conserved and polymorphic HLA framework residues permit recognition of multiple HLA allotypes from the A9 serological cross-reactive group, covering a combined global population frequency of up to 46.7%. Biochemical binding assays, molecular dynamics simulations, and structural and functional analyses demonstrate that high-affinity PC-CAR recognition of cross-reactive pHLAs necessitates the presentation of a specific peptide backbone, where subtle structural adaptations of the peptide are critical for high-affinity complex formation, and CAR T cell killing. Our results provide a molecular blueprint for engineering CARs with optimal recognition of tumor-associated antigens in the context of different HLAs, while minimizing cross-reactivity with self-epitopes.

T cell receptor therapeutics: immunological targeting of the intracellular cancer proteome

The T cell receptor (TCR) complex is a naturally occurring antigen sensor that detects, amplifies and coordinates cellular immune responses to epitopes derived from cell surface and intracellular proteins. Thus, TCRs enable the targeting of proteins selectively expressed by cancer cells, including neoantigens, cancer germline antigens and viral oncoproteins. As such, TCRs have provided the basis for an emerging class of oncology therapeutics. Herein, we review the current cancer treatment landscape using TCRs and TCR-like molecules. This includes adoptive cell transfer of T cells expressing endogenous or engineered TCRs, TCR bispecific engagers and antibodies specific for human leukocyte antigen (HLA)-bound peptides (TCR mimics). We discuss the unique complexities associated with the clinical development of these therapeutics, such as HLA restriction, TCR retrieval, potency assessment and the potential for cross-reactivity. In addition, we highlight emerging clinical data that establish the antitumour potential of TCR-based therapies, including tumour-infiltrating lymphocytes, for the treatment of diverse human malignancies. Finally, we explore the future of TCR therapeutics, including emerging genome editing methods to safely enhance potency and strategies to streamline patient identification.

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.

Challenges and solutions for therapeutic TCR-based agents

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

The screening, identification, design and clinical application of tumor-specific neoantigens for TCR-T cells

Recent advances in neoantigen research have accelerated the development of tumor immunotherapies, including adoptive cell therapies (ACTs), cancer vaccines and antibody-based therapies, particularly for solid tumors. With the development of next-generation sequencing and bioinformatics technology, the rapid identification and prediction of tumor-specific antigens (TSAs) has become possible. Compared with tumor-associated antigens (TAAs), highly immunogenic TSAs provide new targets for personalized tumor immunotherapy and can be used as prospective indicators for predicting tumor patient survival, prognosis, and immune checkpoint blockade response. Here, the identification and characterization of neoantigens and the clinical application of neoantigen-based TCR-T immunotherapy strategies are summarized, and the current status, inherent challenges, and clinical translational potential of these strategies are discussed.

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.

Structural principles of peptide-centric Chimeric Antigen Receptor recognition guide therapeutic expansion

Peptide-Centric Chimeric Antigen Receptors (PC-CARs), which recognize oncoprotein epitopes displayed by human leukocyte antigens (HLAs) on the cell surface, offer a promising strategy for targeted cancer therapy ¹ . We have previously developed a PC-CAR targeting a neuroblastoma- associated PHOX2B peptide, leading to robust tumor cell lysis restricted by two common HLA allotypes ² . Here, we determine the 2.1 Å structure of the PC-CAR:PHOX2B/HLA-A*24:02/β2m complex, which reveals the basis for antigen-specific recognition through interactions with CAR complementarity-determining regions (CDRs). The PC-CAR adopts a diagonal docking mode, where interactions with both conserved and polymorphic HLA framework residues permit recognition of multiple HLA allotypes from the A9 serological cross-reactivity group, covering a combined American population frequency of up to 25.2%. Comprehensive characterization using biochemical binding assays, molecular dynamics simulations, and structural and functional analyses demonstrate that high-affinity PC-CAR recognition of cross-reactive pHLAs necessitates the presentation of a specific peptide backbone, where subtle structural adaptations of the peptide are critical for high-affinity complex formation and CAR-T cell killing. Our results provide a molecular blueprint for engineering CARs with optimal recognition of tumor-associated antigens in the context of different HLAs, while minimizing cross-reactivity with self-epitopes.