1
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McMaster B, Thorpe C, Ogg G, Deane CM, Koohy H. Can AlphaFold's breakthrough in protein structure help decode the fundamental principles of adaptive cellular immunity? Nat Methods 2024; 21:766-776. [PMID: 38654083 DOI: 10.1038/s41592-024-02240-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2023] [Accepted: 03/08/2024] [Indexed: 04/25/2024]
Abstract
T cells are essential immune cells responsible for identifying and eliminating pathogens. Through interactions between their T-cell antigen receptors (TCRs) and antigens presented by major histocompatibility complex molecules (MHCs) or MHC-like molecules, T cells discriminate foreign and self peptides. Determining the fundamental principles that govern these interactions has important implications in numerous medical contexts. However, reconstructing a map between T cells and their antagonist antigens remains an open challenge for the field of immunology, and success of in silico reconstructions of this relationship has remained incremental. In this Perspective, we discuss the role that new state-of-the-art deep-learning models for predicting protein structure may play in resolving some of the unanswered questions the field faces linking TCR and peptide-MHC properties to T-cell specificity. We provide a comprehensive overview of structural databases and the evolution of predictive models, and highlight the breakthrough AlphaFold provided the field.
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Affiliation(s)
- Benjamin McMaster
- MRC Translational Immune Discovery Unit, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
- Department of Statistics, University of Oxford, Oxford, UK
| | - Christopher Thorpe
- Open Targets, Wellcome Genome Campus, Hinxton, UK
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, UK
| | - Graham Ogg
- MRC Translational Immune Discovery Unit, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
- Chinese Academy of Medical Sciences Oxford Institute, University of Oxford, Oxford, UK
| | | | - Hashem Koohy
- MRC Translational Immune Discovery Unit, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK.
- Alan Turning Fellow in Health and Medicine, University of Oxford, Oxford, UK.
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2
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Rosenberg AM, Ayres CM, Medina-Cucurella AV, Whitehead TA, Baker BM. Enhanced T cell receptor specificity through framework engineering. Front Immunol 2024; 15:1345368. [PMID: 38545094 PMCID: PMC10967027 DOI: 10.3389/fimmu.2024.1345368] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Accepted: 02/15/2024] [Indexed: 04/12/2024] Open
Abstract
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.
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Affiliation(s)
- Aaron M. Rosenberg
- Department of Chemistry and Biochemistry and the Harper Cancer Research Institute, University of Notre Dame, Notre Dame, IN, United States
| | - Cory M. Ayres
- Department of Chemistry and Biochemistry and the Harper Cancer Research Institute, University of Notre Dame, Notre Dame, IN, United States
| | | | - Timothy A. Whitehead
- Department of Chemical and Biological Engineering, University of Colorado Boulder, Boulder, CO, United States
| | - Brian M. Baker
- Department of Chemistry and Biochemistry and the Harper Cancer Research Institute, University of Notre Dame, Notre Dame, IN, United States
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3
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Klebanoff CA, Chandran SS, Baker BM, Quezada SA, Ribas A. T cell receptor therapeutics: immunological targeting of the intracellular cancer proteome. Nat Rev Drug Discov 2023; 22:996-1017. [PMID: 37891435 PMCID: PMC10947610 DOI: 10.1038/s41573-023-00809-z] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/08/2023] [Indexed: 10/29/2023]
Abstract
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.
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Affiliation(s)
- Christopher A Klebanoff
- Memorial Sloan Kettering Cancer Center (MSKCC), Human Oncology and Pathogenesis Program, New York, NY, USA.
| | - Smita S Chandran
- Memorial Sloan Kettering Cancer Center (MSKCC), Human Oncology and Pathogenesis Program, New York, NY, USA
- Parker Institute for Cancer Immunotherapy, New York, NY, USA
- Weill Cornell Medical College, Cornell University, New York, NY, USA
| | - Brian M Baker
- Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, ID, USA
- The Harper Cancer Research Institute, University of Notre Dame, Notre Dame, ID, USA
| | - Sergio A Quezada
- Cancer Immunology Unit, Research Department of Haematology, University College London Cancer Institute, London, UK
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Achilles Therapeutics, London, UK
| | - Antoni Ribas
- Jonsson Comprehensive Cancer Center at the University of California, Los Angeles (UCLA), Los Angeles, CA, USA
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4
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Qi J, Zhu H, Li Y, Guan X, He Y, Ren G, Guo Q, Liu L, Gu Y, Dong X, Liu Y. Creation of a High-Throughput Microfluidic Platform for Single-Cell Transcriptome Sequencing of Cell-Cell Interactions. SMALL METHODS 2023; 7:e2300730. [PMID: 37712212 DOI: 10.1002/smtd.202300730] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/10/2023] [Revised: 08/21/2023] [Indexed: 09/16/2023]
Abstract
Cell-cell interaction is one of the major modalities for transmitting information between cells and activating the effects of functional cells. However, the construction of high-throughput analysis technologies from cell omics focusing on the impact of interactions of functional cells on targets has been relatively unexplored. Here, they propose a droplet-based microfluidic platform for cell-cell interaction sequencing (c-c-seq) and screening in vitro to address this challenge. A class of interacting cells is pre-labeled using cell molecular tags, and additional single-cell sequencing reagents are introduced to quickly form functional droplet mixes. Lastly, gene expression analysis is used to deduce the impact of the interaction, while molecular sequence tracing identifies the type of interaction. Research into the active effect between antigen-presenting cells and T cells, one of the most common cell-to-cell interactions, is crucial for the advancement of cancer therapy, particularly T cell receptor-engineered T cell therapy. As it allows for high throughput, this platform is superior to well plates as a research platform for cell-to-cell interactions. When combined with the next generation of sequencing, the platform may be able to more accurately evaluate interactions between epitopes and receptors and verify their functional relevance.
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Affiliation(s)
- Jingyu Qi
- BGI Research, Shenzhen, 518083, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
| | | | - Yijian Li
- BGI Research, Shenzhen, 518083, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Xiangyu Guan
- BGI Research, Shenzhen, 518083, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Ying He
- Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, 518116, China
| | - Guanhua Ren
- China National Institute of Standardization, Beijing, 100191, China
| | - Qiang Guo
- BGI Research, Shenzhen, 518083, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
| | | | - Ying Gu
- BGI Research, Shenzhen, 518083, China
| | - Xuan Dong
- BGI Research, Shenzhen, 518083, China
- Guangdong Provincial Key Laboratory of Human Disease Genomics, Shenzhen Key Laboratory of Genomics, Shenzhen, 518083, China
| | - Ya Liu
- BGI Research, Shenzhen, 518083, China
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5
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Gupta S, Nerli S, Kutti Kandy S, Mersky GL, Sgourakis NG. HLA3DB: comprehensive annotation of peptide/HLA complexes enables blind structure prediction of T cell epitopes. Nat Commun 2023; 14:6349. [PMID: 37816745 PMCID: PMC10564892 DOI: 10.1038/s41467-023-42163-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Accepted: 09/29/2023] [Indexed: 10/12/2023] Open
Abstract
The class I proteins of the major histocompatibility complex (MHC-I) display epitopic peptides derived from endogenous proteins on the cell surface for immune surveillance. Accurate modeling of peptides bound to the human MHC, HLA, has been mired by conformational diversity of the central peptide residues, which are critical for recognition by T cell receptors. Here, analysis of X-ray crystal structures within our curated database (HLA3DB) shows that pHLA complexes encompassing multiple HLA allotypes present a discrete set of peptide backbone conformations. Leveraging these backbones, we employ a regression model trained on terms of a physically relevant energy function to develop a comparative modeling approach for nonamer pHLA structures named RepPred. Our method outperforms the top pHLA modeling approach by up to 19% in structural accuracy, and consistently predicts blind targets not included in our training set. Insights from our work may be applied towards predicting antigen immunogenicity, and receptor cross-reactivity.
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Affiliation(s)
- Sagar Gupta
- Center for Computational and Genomic Medicine, Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- College of Arts and Sciences, University of Pennsylvania, Philadelphia, PA, USA
| | - Santrupti Nerli
- Center for Computational and Genomic Medicine, Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Sreeja Kutti Kandy
- Center for Computational and Genomic Medicine, Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Glenn L Mersky
- Center for Computational and Genomic Medicine, Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Nikolaos G Sgourakis
- Center for Computational and Genomic Medicine, Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA.
- Department of Biochemistry and Biophysics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
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6
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Gouttefangeas C, Klein R, Maia A. The good and the bad of T cell cross-reactivity: challenges and opportunities for novel therapeutics in autoimmunity and cancer. Front Immunol 2023; 14:1212546. [PMID: 37409132 PMCID: PMC10319254 DOI: 10.3389/fimmu.2023.1212546] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Accepted: 05/24/2023] [Indexed: 07/07/2023] Open
Abstract
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.
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Affiliation(s)
- Cécile Gouttefangeas
- Nencki Institute of Experimental Biology of the Polish Academy of Sciences, Warsaw, Poland
- Cluster of Excellence iFIT (EXC2180) “Image-Guided and Functionally Instructed Tumor Therapies”, University of Tübingen, Tübingen, Germany
- German Cancer Consortium (DKTK) and German Cancer Research Center (DKFZ) partner site Tübingen, Tübingen, Germany
| | - Reinhild Klein
- Department of Hematology, Oncology, Clinical Immunology and Rheumatology, University Hospital Tübingen, Tübingen, Germany
| | - Ana Maia
- Nencki Institute of Experimental Biology of the Polish Academy of Sciences, Warsaw, Poland
- Cluster of Excellence iFIT (EXC2180) “Image-Guided and Functionally Instructed Tumor Therapies”, University of Tübingen, Tübingen, Germany
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7
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Fonseca AF, Antunes DA. CrossDome: an interactive R package to predict cross-reactivity risk using immunopeptidomics databases. Front Immunol 2023; 14:1142573. [PMID: 37377956 PMCID: PMC10291144 DOI: 10.3389/fimmu.2023.1142573] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Accepted: 05/23/2023] [Indexed: 06/29/2023] Open
Abstract
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.
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8
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Kazmirchuk TDD, Bradbury-Jost C, Withey TA, Gessese T, Azad T, Samanfar B, Dehne F, Golshani A. Peptides of a Feather: How Computation Is Taking Peptide Therapeutics under Its Wing. Genes (Basel) 2023; 14:1194. [PMID: 37372372 DOI: 10.3390/genes14061194] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Revised: 05/24/2023] [Accepted: 05/26/2023] [Indexed: 06/29/2023] Open
Abstract
Leveraging computation in the development of peptide therapeutics has garnered increasing recognition as a valuable tool to generate novel therapeutics for disease-related targets. To this end, computation has transformed the field of peptide design through identifying novel therapeutics that exhibit enhanced pharmacokinetic properties and reduced toxicity. The process of in-silico peptide design involves the application of molecular docking, molecular dynamics simulations, and machine learning algorithms. Three primary approaches for peptide therapeutic design including structural-based, protein mimicry, and short motif design have been predominantly adopted. Despite the ongoing progress made in this field, there are still significant challenges pertaining to peptide design including: enhancing the accuracy of computational methods; improving the success rate of preclinical and clinical trials; and developing better strategies to predict pharmacokinetics and toxicity. In this review, we discuss past and present research pertaining to the design and development of in-silico peptide therapeutics in addition to highlighting the potential of computation and artificial intelligence in the future of disease therapeutics.
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Affiliation(s)
- Thomas David Daniel Kazmirchuk
- Department of Biology, and the Ottawa Institute of Systems Biology (OISB), Carleton University, Ottawa, ON K1S 5B6, Canada
| | - Calvin Bradbury-Jost
- Department of Biology, and the Ottawa Institute of Systems Biology (OISB), Carleton University, Ottawa, ON K1S 5B6, Canada
| | - Taylor Ann Withey
- Department of Biology, and the Ottawa Institute of Systems Biology (OISB), Carleton University, Ottawa, ON K1S 5B6, Canada
| | - Tadesse Gessese
- Department of Biology, and the Ottawa Institute of Systems Biology (OISB), Carleton University, Ottawa, ON K1S 5B6, Canada
| | - Taha Azad
- Department of Microbiology and Infectious Diseases, Université de Sherbrooke, Sherbrooke, QC J1E 4K8, Canada
- Centre de Recherche du Centre Hospitalier Universitaire de Sherbrooke (CHUS), Sherbrooke, QC J1H 5N4, Canada
| | - Bahram Samanfar
- Department of Biology, and the Ottawa Institute of Systems Biology (OISB), Carleton University, Ottawa, ON K1S 5B6, Canada
- Agriculture and Agri-Food Canada, Ottawa Research and Development Centre (ORDC), Ottawa, ON K1A 0C6, Canada
| | - Frank Dehne
- School of Computer Science, Carleton University, Ottawa, ON K1S 5B6, Canada
| | - Ashkan Golshani
- Department of Biology, and the Ottawa Institute of Systems Biology (OISB), Carleton University, Ottawa, ON K1S 5B6, Canada
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9
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Saotome K, Dudgeon D, Colotti K, Moore MJ, Jones J, Zhou Y, Rafique A, Yancopoulos GD, Murphy AJ, Lin JC, Olson WC, Franklin MC. Structural analysis of cancer-relevant TCR-CD3 and peptide-MHC complexes by cryoEM. Nat Commun 2023; 14:2401. [PMID: 37100770 PMCID: PMC10132440 DOI: 10.1038/s41467-023-37532-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Accepted: 03/21/2023] [Indexed: 04/28/2023] Open
Abstract
The recognition of antigenic peptide-MHC (pMHC) molecules by T-cell receptors (TCR) initiates the T-cell mediated immune response. Structural characterization is key for understanding the specificity of TCR-pMHC interactions and informing the development of therapeutics. Despite the rapid rise of single particle cryoelectron microscopy (cryoEM), x-ray crystallography has remained the preferred method for structure determination of TCR-pMHC complexes. Here, we report cryoEM structures of two distinct full-length α/β TCR-CD3 complexes bound to their pMHC ligand, the cancer-testis antigen HLA-A2/MAGEA4 (230-239). We also determined cryoEM structures of pMHCs containing MAGEA4 (230-239) peptide and the closely related MAGEA8 (232-241) peptide in the absence of TCR, which provided a structural explanation for the MAGEA4 preference displayed by the TCRs. These findings provide insights into the TCR recognition of a clinically relevant cancer antigen and demonstrate the utility of cryoEM for high-resolution structural analysis of TCR-pMHC interactions.
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Affiliation(s)
- Kei Saotome
- Regeneron Pharmaceuticals, Inc., Tarrytown, NY, 10591, USA.
| | - Drew Dudgeon
- Regeneron Pharmaceuticals, Inc., Tarrytown, NY, 10591, USA
| | | | | | - Jennifer Jones
- Regeneron Pharmaceuticals, Inc., Tarrytown, NY, 10591, USA
| | - Yi Zhou
- Regeneron Pharmaceuticals, Inc., Tarrytown, NY, 10591, USA
| | | | | | | | - John C Lin
- Regeneron Pharmaceuticals, Inc., Tarrytown, NY, 10591, USA
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10
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Gupta S, Nerli S, Kandy SK, Mersky GL, Sgourakis NG. HLA3DB: comprehensive annotation of peptide/HLA complexes enables blind structure prediction of T cell epitopes. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.20.533510. [PMID: 36993660 PMCID: PMC10055217 DOI: 10.1101/2023.03.20.533510] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/31/2023]
Abstract
The class I proteins of the major histocompatibility complex (MHC-I) display epitopic peptides derived from endogenous proteins on the cell surface for immune surveillance. Accurate modeling of peptide/HLA (pHLA, the human MHC) structures has been mired by conformational diversity of the central peptide residues, which are critical for recognition by T cell receptors. Here, analysis of X-ray crystal structures within a curated database (HLA3DB) shows that pHLA complexes encompassing multiple HLA allotypes present a discrete set of peptide backbone conformations. Leveraging these representative backbones, we employ a regression model trained on terms of a physically relevant energy function to develop a comparative modeling approach for nonamer peptide/HLA structures named RepPred. Our method outperforms the top pHLA modeling approach by up to 19% in terms of structural accuracy, and consistently predicts blind targets not included in our training set. Insights from our work provide a framework for linking conformational diversity with antigen immunogenicity and receptor cross-reactivity.
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11
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Berman DM, Bell JI. Redirecting Polyclonal T Cells against Cancer with Soluble T-Cell Receptors. Clin Cancer Res 2023; 29:697-704. [PMID: 36255733 PMCID: PMC9932579 DOI: 10.1158/1078-0432.ccr-22-0028] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Revised: 08/30/2022] [Accepted: 10/05/2022] [Indexed: 11/16/2022]
Abstract
Cancer cells accumulate genetic mutations in coding proteins that may be presented by HLA as neoantigenic peptides (peptide HLA, pHLA). T cells scan for neoantigenic pHLA by the T-cell receptor (TCR):CD3 complex. This complex has the dual function of binding pHLA, by the TCR, and triggering T-cell activation by CD3. Checkpoint therapy activates exhausted T cells to kill cancer cells and generally work best against tumors with high neoantigen burden and in patients with neoantigenic-reactive T cells. TCR T-cell engagers (TCE) are a novel class of immunotherapy that bypasses these two requirements by redirecting polyclonal T cells, regardless of their native specificity, to kill a cancer cell independent of neoantigen burden. This is accomplished through deconstructing the membrane-bound TCR:CD3 complex into a soluble bispecific protein comprised of a targeting domain (TCR) and activating domain (usually anti-CD3 single-chain variable fragment). The pool of targets for TCR TCE is larger than for antibody therapeutics and includes >90% of human intra- or extracellular proteins. Most tumor-associated antigens for solid tumors are intracellular and accessible only by a TCR therapeutic. Tebentafusp, a TCR TCE directed to a peptide derived from the gp100 melanoma protein presented by HLA*A02:01, demonstrated a survival benefit in metastatic uveal melanoma (mUM). This survival benefit highlights the promise of TCR TCEs because mUM is a solid tumor with a very low neoantigen burden and has poor response to checkpoints and chemotherapy. Other TCR TCE programs are now in clinical studies for a broader range of tumors.
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Affiliation(s)
| | - John I. Bell
- Oxford University, Oxford, United Kingdom.,Corresponding Author: John I. Bell, Office of Regius Professor, Richard Doll Building, Old Road Campus, Oxford, OX3 7DG, United Kingdom. E-mail:
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12
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Baulu E, Gardet C, Chuvin N, Depil S. TCR-engineered T cell therapy in solid tumors: State of the art and perspectives. SCIENCE ADVANCES 2023; 9:eadf3700. [PMID: 36791198 PMCID: PMC9931212 DOI: 10.1126/sciadv.adf3700] [Citation(s) in RCA: 74] [Impact Index Per Article: 74.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Accepted: 01/06/2023] [Indexed: 05/25/2023]
Abstract
T cell engineering has changed the landscape of cancer immunotherapy. Chimeric antigen receptor T cells have demonstrated a remarkable efficacy in the treatment of B cell malignancies in hematology. However, their clinical impact on solid tumors has been modest so far. T cells expressing an engineered T cell receptor (TCR-T cells) represent a promising therapeutic alternative. The target repertoire is not limited to membrane proteins, and intrinsic features of TCRs such as high antigen sensitivity and near-to-physiological signaling may improve tumor cell detection and killing while improving T cell persistence. In this review, we present the clinical results obtained with TCR-T cells targeting different tumor antigen families. We detail the different methods that have been developed to identify and optimize a TCR candidate. We also discuss the challenges of TCR-T cell therapies, including toxicity assessment and resistance mechanisms. Last, we share some perspectives and highlight future directions in the field.
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Affiliation(s)
- Estelle Baulu
- Centre de Recherche en Cancérologie de Lyon, Lyon, France
- ErVaccine Technologies, Lyon, France
| | - Célia Gardet
- Centre de Recherche en Cancérologie de Lyon, Lyon, France
| | | | - Stéphane Depil
- Centre de Recherche en Cancérologie de Lyon, Lyon, France
- ErVaccine Technologies, Lyon, France
- Centre Léon Bérard, Lyon, France
- Université Claude Bernard Lyon 1, Lyon, France
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13
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Zhang J, Liu M, Chen Y, Zhou Z, Wang P, Yu Y, Jiao S. Epitope identification for p53R273C mutant. Immun Inflamm Dis 2022; 11:e752. [PMID: 36705409 PMCID: PMC9761341 DOI: 10.1002/iid3.752] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Revised: 11/08/2022] [Accepted: 12/02/2022] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND With the rise of immunotherapy based on cancer neoantigen, identification of neoepitopes has become an urgent problem to be solved. The TP53 R273C mutation is one of the hotspot mutations of TP53, however, the immunogenicity of this mutation is not yet clear. The aim of this study is to identify potential epitopes for p53R273C mutant. METHODS In this study, bioinformatic methods, peptide exchange assay, and peptide-immunized human leukocyte antigen (HLA) transgenic mouse model were used to explore the immunogenicity of this mutation. RESULTS Peptides with higher affinity to common HLA-A alleles (A*11:01, A*02:01) were discovered by computational prediction. All the 8-11 mer peptides contain the mutation site were synthesized and soluble peptides were used in the peptide exchange assay. However, the exchange efficiencies of these predicted peptides to HLAs were lower. Fortunately, other peptides with higher exchange efficiency were discovered. Then, the immunogenicity of these peptides was validated with the HLA-A2 transgenic mice model. CONCLUSION We identified three potential neoepitopes of p53R273C for HLA-A*02:01, one potential neoepitope for HLA-A*11:01 and no neoepitope for HLA-A*24:02.
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Affiliation(s)
- Jian Zhang
- School of MedicineNankai UniversityTianjinChina,Department of Oncology, Oncology LaboratoryChinese PLA General HospitalBeijingChina,Research and Development DepartmentBeijing DCTY Biotech Co., Ltd.BeijingPeople's Republic of China
| | - Minglu Liu
- Department of Oncology, Oncology LaboratoryChinese PLA General HospitalBeijingChina
| | - Yin Chen
- Research and Development DepartmentBeijing DCTY Biotech Co., Ltd.BeijingPeople's Republic of China
| | - Zishan Zhou
- Research and Development DepartmentBeijing DCTY Biotech Co., Ltd.BeijingPeople's Republic of China
| | - Ping Wang
- Research and Development DepartmentBeijing DCTY Biotech Co., Ltd.BeijingPeople's Republic of China
| | - Yang Yu
- Research and Development DepartmentBeijing DCTY Biotech Co., Ltd.BeijingPeople's Republic of China
| | - Shunchang Jiao
- School of MedicineNankai UniversityTianjinChina,Department of Oncology, Oncology LaboratoryChinese PLA General HospitalBeijingChina
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14
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Simister PC, Border EC, Vieira JF, Pumphrey NJ. Structural insights into engineering a T-cell receptor targeting MAGE-A10 with higher affinity and specificity for cancer immunotherapy. J Immunother Cancer 2022; 10:jitc-2022-004600. [PMID: 35851311 PMCID: PMC9295655 DOI: 10.1136/jitc-2022-004600] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/17/2022] [Indexed: 11/22/2022] Open
Abstract
BACKGROUND T-cell receptor (TCR) immunotherapy is becoming a viable modality in cancer treatment with efficacy in clinical trials. The safety of patients is paramount, so innovative cell engineering methods are being employed to exploit adaptive immunity while controlling the factors governing antigen receptor (ie, TCR) specificity and cross-reactivity. We recently reported a TCR engineering campaign and selectivity profiling assay (X-scan) targeting a melanoma antigen gene (MAGE)-A10 peptide. This helped to distinguish between two well-performing TCRs based on cross-reactivity potential during preclinical drug evaluation, allowing one to be advanced to T-cell immunotherapeutic clinical trials. Here, we present three-dimensional structural information on those TCRs, highlighting engineering improvements and molecular mechanisms likely underpinning differential selectivity. METHODS Parental and engineered TCRs were purified and crystallized either alone or complexed to human leucocyte antigen (HLA)-A*02:01 presenting the MAGE-A10 9-mer peptide, GLYDGMEHL (pHLA/MAGE-A10-9). Using X-ray diffraction, we solved four high-resolution crystal structures and evaluated them relative to previously reported functional results. RESULTS The unligated parental TCR displayed similar complementarity-determining region (CDR) loop conformations when bound to pHLA/MAGE-A10-9; a rigid-body movement of TCR beta chain variable domain (TRBV) relative to TCR alpha chain variable domain helped optimal pHLA engagement. This first view of an HLA-bound MAGE-A10 peptide revealed an intrachain non-covalent 'staple' between peptide Tyr3 and Glu7. A subtle Glu31-Asp mutation in βCDR1 of the parental TCR generated a high-affinity derivative. Its pHLA-complexed structure shows that the shorter Asp leans toward the pHLA with resulting rigid-body TRBV shift, creating localized changes around the peptide's C-terminus. Structural comparison with a less selective TCR indicated that differential cross-reactivity to MAGE-A10 peptide variants is most readily explained by alterations in surface electrostatics, and the size and geometry of TCR-peptide interfacial cavities. CONCLUSIONS Modest changes in engineered TCRs targeting MAGE-A10 produced significantly different properties. Conformational invariance of TCR and antigen peptide plus more space-filling CDR loop sequences may be desirable properties for clinically relevant TCR-pHLA systems to reduce the likelihood of structurally similar peptide mimics being tolerated by a TCR. Such properties may partially explain why the affinity-enhanced, in vitro-selected TCR has been generally well tolerated in patients.
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15
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Liu C, Liu H, Dasgupta M, Hellman LM, Zhang X, Qu K, Xue H, Wang Y, Fan F, Chang Q, Yu D, Ge L, Zhang Y, Cui Z, Zhang P, Heller B, Zhang H, Shi B, Baker BM, Liu C. Validation and promise of a TCR mimic antibody for cancer immunotherapy of hepatocellular carcinoma. Sci Rep 2022; 12:12068. [PMID: 35840635 PMCID: PMC9287321 DOI: 10.1038/s41598-022-15946-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2022] [Accepted: 07/01/2022] [Indexed: 11/30/2022] Open
Abstract
Monoclonal antibodies are at the vanguard of the most promising cancer treatments. Whereas traditional therapeutic antibodies have been limited to extracellular antigens, T cell receptor mimic (TCRm) antibodies can target intracellular antigens presented by cell surface major histocompatibility complex (MHC) proteins. TCRm antibodies can therefore target a repertoire of otherwise undruggable cancer antigens. However, the consequences of off-target peptide/MHC recognition with engineered T cell therapies are severe, and thus there are significant safety concerns with TCRm antibodies. Here we explored the specificity and safety profile of a new TCRm-based T cell therapy for hepatocellular carcinoma (HCC), a solid tumor for which no effective treatment exists. We targeted an alpha-fetoprotein peptide presented by HLA-A*02 with a highly specific TCRm, which crystallographic structural analysis showed binds directly over the HLA protein and interfaces with the full length of the peptide. We fused the TCRm to the γ and δ subunits of a TCR, producing a signaling AbTCR construct. This was combined with an scFv/CD28 co-stimulatory molecule targeting glypican-3 for increased efficacy towards tumor cells. This AbTCR + co-stimulatory T cell therapy showed potent activity against AFP-positive cancer cell lines in vitro and an in an in vivo model and undetectable activity against AFP-negative cells. In an in-human safety assessment, no significant adverse events or cytokine release syndrome were observed and evidence of efficacy was seen. Remarkably, one patient with metastatic HCC achieved a complete remission after nine months and ultimately qualified for a liver transplant.
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Affiliation(s)
- Chang Liu
- The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi Province, China
| | - Hong Liu
- Eureka Therapeutics Inc., 5858 Horton Street, Suite 170, Emeryville, CA, USA
| | - Moumita Dasgupta
- Department of Chemistry & Biochemistry and the Harper Cancer Research Institute, University of Notre Dame, 251 Nieuwland Science Hall, Notre Dame, IN, USA
| | - Lance M Hellman
- Department of Chemistry & Biochemistry and the Harper Cancer Research Institute, University of Notre Dame, 251 Nieuwland Science Hall, Notre Dame, IN, USA
| | - Xiaogang Zhang
- The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi Province, China
| | - Kai Qu
- The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi Province, China
| | - Hui Xue
- The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi Province, China
| | - Yun Wang
- The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi Province, China
| | - Fenling Fan
- The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi Province, China
| | - Qi Chang
- Eureka Therapeutics Inc., 5858 Horton Street, Suite 170, Emeryville, CA, USA
| | - Duo Yu
- Eureka Therapeutics Inc., 5858 Horton Street, Suite 170, Emeryville, CA, USA
| | - Linhu Ge
- Eureka Therapeutics Inc., 5858 Horton Street, Suite 170, Emeryville, CA, USA
| | - Yu Zhang
- Eureka Therapeutics Inc., 5858 Horton Street, Suite 170, Emeryville, CA, USA
| | - Ziyou Cui
- Eureka Therapeutics Inc., 5858 Horton Street, Suite 170, Emeryville, CA, USA
| | - Pengbo Zhang
- Eureka Therapeutics Inc., 5858 Horton Street, Suite 170, Emeryville, CA, USA
| | - Bradley Heller
- Eureka Therapeutics Inc., 5858 Horton Street, Suite 170, Emeryville, CA, USA
| | - Hongbing Zhang
- Eureka Therapeutics Inc., 5858 Horton Street, Suite 170, Emeryville, CA, USA
| | - Bingyin Shi
- The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi Province, China
| | - Brian M Baker
- Department of Chemistry & Biochemistry and the Harper Cancer Research Institute, University of Notre Dame, 251 Nieuwland Science Hall, Notre Dame, IN, USA.
| | - Cheng Liu
- Eureka Therapeutics Inc., 5858 Horton Street, Suite 170, Emeryville, CA, USA.
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16
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Rollins ZA, Huang J, Tagkopoulos I, Faller R, George SC. A Computational Algorithm to Assess the Physiochemical Determinants of T Cell Receptor Dissociation Kinetics. Comput Struct Biotechnol J 2022; 20:3473-3481. [PMID: 35860406 PMCID: PMC9278023 DOI: 10.1016/j.csbj.2022.06.048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Revised: 06/20/2022] [Accepted: 06/21/2022] [Indexed: 11/29/2022] Open
Abstract
The rational design of T Cell Receptors (TCRs) for immunotherapy has stagnated due to a limited understanding of the dynamic physiochemical features of the TCR that elicit an immunogenic response. The physiochemical features of the TCR-peptide major histocompatibility complex (pMHC) bond dictate bond lifetime which, in turn, correlates with immunogenicity. Here, we: i) characterize the force-dependent dissociation kinetics of the bond between a TCR and a set of pMHC ligands using Steered Molecular Dynamics (SMD); and ii) implement a machine learning algorithm to identify which physiochemical features of the TCR govern dissociation kinetics. Our results demonstrate that the total number of hydrogen bonds between the CDR2β-MHC⍺(β), CDR1α-Peptide, and CDR3β-Peptide are critical features that determine bond lifetime.
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Affiliation(s)
| | - Jun Huang
- University of California, Davis, Davis, California, Pritzker School of Molecular Engineering, University of Chicago, Chicago, IL
| | | | | | - Steven C. George
- Department of Biomedical Engineering
- Corresponding author at: Department of Biomedical Engineering, 451 E. Health Sciences Drive, room 2315, University of California, Davis, Davis, CA 95616.
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17
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Keller GLJ, Weiss LI, Baker BM. Physicochemical Heuristics for Identifying High Fidelity, Near-Native Structural Models of Peptide/MHC Complexes. Front Immunol 2022; 13:887759. [PMID: 35547730 PMCID: PMC9084917 DOI: 10.3389/fimmu.2022.887759] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Accepted: 03/29/2022] [Indexed: 11/13/2022] Open
Abstract
There is long-standing interest in accurately modeling the structural features of peptides bound and presented by class I MHC proteins. This interest has grown with the advent of rapid genome sequencing and the prospect of personalized, peptide-based cancer vaccines, as well as the development of molecular and cellular therapeutics based on T cell receptor recognition of peptide-MHC. However, while the speed and accessibility of peptide-MHC modeling has improved substantially over the years, improvements in accuracy have been modest. Accuracy is crucial in peptide-MHC modeling, as T cell receptors are highly sensitive to peptide conformation and capturing fine details is therefore necessary for useful models. Studying nonameric peptides presented by the common class I MHC protein HLA-A*02:01, here we addressed a key question common to modern modeling efforts: from a set of models (or decoys) generated through conformational sampling, which is best? We found that the common strategy of decoy selection by lowest energy can lead to substantial errors in predicted structures. We therefore adopted a data-driven approach and trained functions capable of predicting near native decoys with exceptionally high accuracy. Although our implementation is limited to nonamer/HLA-A*02:01 complexes, our results serve as an important proof of concept from which improvements can be made and, given the significance of HLA-A*02:01 and its preference for nonameric peptides, should have immediate utility in select immunotherapeutic and other efforts for which structural information would be advantageous.
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Affiliation(s)
- Grant L J Keller
- Department of Chemistry & Biochemistry and the Harper Cancer Research Institute, University of Notre Dame, Notre Dame, IN, United States
| | - Laura I Weiss
- Department of Chemistry & Biochemistry and the Harper Cancer Research Institute, University of Notre Dame, Notre Dame, IN, United States
| | - Brian M Baker
- Department of Chemistry & Biochemistry and the Harper Cancer Research Institute, University of Notre Dame, Notre Dame, IN, United States
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18
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Shafer P, Kelly LM, Hoyos V. Cancer Therapy With TCR-Engineered T Cells: Current Strategies, Challenges, and Prospects. Front Immunol 2022; 13:835762. [PMID: 35309357 PMCID: PMC8928448 DOI: 10.3389/fimmu.2022.835762] [Citation(s) in RCA: 69] [Impact Index Per Article: 34.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Accepted: 02/10/2022] [Indexed: 12/23/2022] Open
Abstract
To redirect T cells against tumor cells, T cells can be engineered ex vivo to express cancer-antigen specific T cell receptors (TCRs), generating products known as TCR-engineered T cells (TCR T). Unlike chimeric antigen receptors (CARs), TCRs recognize HLA-presented peptides derived from proteins of all cellular compartments. The use of TCR T cells for adoptive cellular therapies (ACT) has gained increased attention, especially as efforts to treat solid cancers with ACTs have intensified. In this review, we describe the differing mechanisms of T cell antigen recognition and signal transduction mediated through CARs and TCRs. We describe the classes of cancer antigens recognized by current TCR T therapies and discuss both classical and emerging pre-clinical strategies for antigen-specific TCR discovery, enhancement, and validation. Finally, we review the current landscape of clinical trials for TCR T therapy and discuss what these current results indicate for the development of future engineered TCR approaches.
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Affiliation(s)
- Paul Shafer
- Center for Cell and Gene Therapy, Baylor College of Medicine, Texas Children's Hospital and Houston Methodist Hospital, Houston, TX, United States.,Dan L. Duncan Cancer Center, Baylor College of Medicine, Houston, TX, United States.,Program in Immunology, Baylor College of Medicine, Houston, TX, United States
| | - Lauren M Kelly
- Center for Cell and Gene Therapy, Baylor College of Medicine, Texas Children's Hospital and Houston Methodist Hospital, Houston, TX, United States.,Dan L. Duncan Cancer Center, Baylor College of Medicine, Houston, TX, United States.,Program in Cancer & Cell Biology, Baylor College of Medicine, Houston, TX, United States
| | - Valentina Hoyos
- Center for Cell and Gene Therapy, Baylor College of Medicine, Texas Children's Hospital and Houston Methodist Hospital, Houston, TX, United States.,Dan L. Duncan Cancer Center, Baylor College of Medicine, Houston, TX, United States
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19
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Rollins ZA, Faller R, George SC. Using Molecular Dynamics Simulations to Interrogate T Cell Receptor Non-Equilibrium Kinetics. Comput Struct Biotechnol J 2022; 20:2124-2133. [PMID: 35832631 PMCID: PMC9092387 DOI: 10.1016/j.csbj.2022.04.018] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Revised: 04/13/2022] [Accepted: 04/13/2022] [Indexed: 11/30/2022] Open
Abstract
Insights into the atomic-scale interaction of the T Cell Receptor with the peptide Major Histocompatibility Complex. Investigation of the physiochemical features that correspond with T Cell Receptor recognition during dynamic dissociation. Implications of force-dependent non-equilibrium kinetics on T Cell Receptor mechanosensing.
An atomic-scale mechanism of T Cell Receptor (TCR) mechanosensing of peptides in the binding groove of the peptide-major histocompatibility complex (pMHC) may inform the design of novel TCRs for immunotherapies. Using steered molecular dynamics simulations, our study demonstrates that mutations to peptides in the binding groove of the pMHC – which are known to discretely alter the T cell response to an antigen – alter the MHC conformation at equilibrium. This subsequently impacts the overall strength (duration and length) of the TCR-pMHC bond under constant load. Moreover, physiochemical features of the TCR-pMHC dynamic bond strength, such as hydrogen bonds and Lennard-Jones contacts, correlate with the immunogenic response elicited by the specific peptide in the MHC groove. Thus, formation of transient TCR-pMHC bonds is characteristic of immunogenic peptides, and steered molecular dynamics simulations can be used in the overall design strategy of TCRs for immunotherapies.
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Affiliation(s)
- Zachary A. Rollins
- Department of Chemical Engineering, University of California, Davis, 1 Shields Ave, Bainer Hall, Davis, CA 95616, United States
| | - Roland Faller
- Department of Chemical Engineering, University of California, Davis, 1 Shields Ave, Bainer Hall, Davis, CA 95616, United States
| | - Steven C. George
- Department of Biomedical Engineering, University of California, Davis, 451 E. Health Sciences Dr., GBSF 2303, Davis, CA 95616, United States
- Corresponding author at: Department of Biomedical Engineering, 451 E. Health Sciences Drive, Room 2315, University of California, Davis, CA 95616, United States.
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20
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Engineering the T cell receptor for fun and profit: Uncovering complex biology, interrogating the immune system, and targeting disease. Curr Opin Struct Biol 2022; 74:102358. [PMID: 35344834 DOI: 10.1016/j.sbi.2022.102358] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Revised: 02/13/2022] [Accepted: 02/21/2022] [Indexed: 11/21/2022]
Abstract
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.
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21
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Crean RM, Pudney CR, Cole DK, van der Kamp MW. Reliable In Silico Ranking of Engineered Therapeutic TCR Binding Affinities with MMPB/GBSA. J Chem Inf Model 2022; 62:577-590. [PMID: 35049312 PMCID: PMC9097153 DOI: 10.1021/acs.jcim.1c00765] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
![]()
Accurate
and efficient in silico ranking of protein–protein
binding affinities is useful for protein design with applications
in biological therapeutics. One popular approach to rank binding affinities
is to apply the molecular mechanics Poisson–Boltzmann/generalized
Born surface area (MMPB/GBSA) method to molecular dynamics (MD) trajectories.
Here, we identify protocols that enable the reliable evaluation of
T-cell receptor (TCR) variants binding to their target, peptide-human
leukocyte antigens (pHLAs). We suggest different protocols for variant
sets with a few (≤4) or many mutations, with entropy corrections
important for the latter. We demonstrate how potential outliers could
be identified in advance and that just 5–10 replicas of short
(4 ns) MD simulations may be sufficient for the reproducible and accurate
ranking of TCR variants. The protocols developed here can be applied
toward in silico screening during the optimization
of therapeutic TCRs, potentially reducing both the cost and time taken
for biologic development.
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Affiliation(s)
| | | | - David K. Cole
- Immunocore Ltd., Milton Park, Abingdon OX14 4RY, U.K
- Division of Infection & Immunity, Cardiff University, Cardiff CF14 4XN, U.K
| | - Marc W. van der Kamp
- School of Biochemistry, University of Bristol, Biomedical Sciences Building, Bristol BS8 1TD, U.K
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22
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Alonso JA, Smith AR, Baker BM. Tumor rejection properties of gp100 209-specific T cells correlate with T cell receptor binding affinity towards the wild type rather than anchor-modified antigen. Mol Immunol 2021; 135:365-372. [PMID: 33990005 DOI: 10.1016/j.molimm.2021.05.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Revised: 05/03/2021] [Accepted: 05/03/2021] [Indexed: 10/21/2022]
Abstract
Although there are exceptions and outliers, T cell functional responses generally correlate with the affinity of a TCR for a peptide/MHC complex. In one recently described outlier case, the most promising clinical candidate in a series of TCRs specific for the gp100209 melanoma antigen bound with the weakest solution affinity and produced the least amount of cytokine in vitro. Hypotheses for this outlier behavior included unusual cytokine expression patterns arising from an atypical TCR binding geometry. Studying this instance in more detail, we found here that outlier behavior is attributable not to unusual cytokine patterns or TCR binding, but the use of a position 2 anchor-modified peptide variant in in vitro experiments instead of the wild type antigen that is present in vivo. Although the anchor-modified variant has been widely used in basic and clinical immunology as a surrogate for the wild type peptide, prior work has shown that TCRs can clearly distinguish between the two. We show that when this differential recognition is accounted for, the functional properties of gp100209-specific TCRs track with their affinity towards the peptide/MHC complex. Beyond demonstrating the correlates with T cell function for a clinically relevant TCR, our results provide important considerations for selection of TCRs for immunotherapy and the use of modified peptides in immunology.
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Affiliation(s)
- Jesus A Alonso
- Department of Chemistry & Biochemistry and the Harper Cancer Research Institute, University of Notre Dame, Notre Dame, IN, USA
| | - Angela R Smith
- Department of Chemistry & Biochemistry and the Harper Cancer Research Institute, University of Notre Dame, Notre Dame, IN, USA
| | - Brian M Baker
- Department of Chemistry & Biochemistry and the Harper Cancer Research Institute, University of Notre Dame, Notre Dame, IN, USA.
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23
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Pearlman AH, Hwang MS, Konig MF, Hsiue EHC, Douglass J, DiNapoli SR, Mog BJ, Bettegowda C, Pardoll DM, Gabelli SB, Papadopoulos N, Kinzler KW, Vogelstein B, Zhou S. Targeting public neoantigens for cancer immunotherapy. NATURE CANCER 2021; 2:487-497. [PMID: 34676374 PMCID: PMC8525885 DOI: 10.1038/s43018-021-00210-y] [Citation(s) in RCA: 76] [Impact Index Per Article: 25.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/22/2020] [Accepted: 04/13/2021] [Indexed: 02/06/2023]
Abstract
Several current immunotherapy approaches target private neoantigens derived from mutations that are unique to individual patients' tumors. However, immunotherapeutic agents can also be developed against public neoantigens derived from recurrent mutations in cancer driver genes. The latter approaches target proteins that are indispensable for tumor growth, and each therapeutic agent can be applied to numerous patients. Here we review the opportunities and challenges involved in the identification of suitable public neoantigen targets and the development of therapeutic agents targeting them.
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Affiliation(s)
- Alexander H Pearlman
- Ludwig Center, Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Lustgarten Pancreatic Cancer Research Laboratory, Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
| | - Michael S Hwang
- Ludwig Center, Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Lustgarten Pancreatic Cancer Research Laboratory, Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
- Genentech, Inc., South San Francisco, CA, USA
| | - Maximilian F Konig
- Ludwig Center, Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Lustgarten Pancreatic Cancer Research Laboratory, Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
- Division of Rheumatology, Department of Medicine, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Emily Han-Chung Hsiue
- Ludwig Center, Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Lustgarten Pancreatic Cancer Research Laboratory, Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
| | - Jacqueline Douglass
- Ludwig Center, Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Lustgarten Pancreatic Cancer Research Laboratory, Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
| | - Sarah R DiNapoli
- Ludwig Center, Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Lustgarten Pancreatic Cancer Research Laboratory, Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
| | - Brian J Mog
- Ludwig Center, Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Lustgarten Pancreatic Cancer Research Laboratory, Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Chetan Bettegowda
- Ludwig Center, Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Lustgarten Pancreatic Cancer Research Laboratory, Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Neurosurgery, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Oncology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Drew M Pardoll
- Department of Oncology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Bloomberg~Kimmel Institute for Cancer Immunotherapy, Sidney Kimmel Comprehensive Cancer Center, Baltimore, MD, USA
| | - Sandra B Gabelli
- Department of Oncology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Biophysics and Biophysical Chemistry, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Medicine, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Nicholas Papadopoulos
- Ludwig Center, Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Lustgarten Pancreatic Cancer Research Laboratory, Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Bloomberg~Kimmel Institute for Cancer Immunotherapy, Sidney Kimmel Comprehensive Cancer Center, Baltimore, MD, USA
- Department of Pathology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Sol Goldman Pancreatic Cancer Research Center, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Kenneth W Kinzler
- Ludwig Center, Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Lustgarten Pancreatic Cancer Research Laboratory, Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Oncology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Bloomberg~Kimmel Institute for Cancer Immunotherapy, Sidney Kimmel Comprehensive Cancer Center, Baltimore, MD, USA
- Sol Goldman Pancreatic Cancer Research Center, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Bert Vogelstein
- Ludwig Center, Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Lustgarten Pancreatic Cancer Research Laboratory, Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
- Department of Oncology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Bloomberg~Kimmel Institute for Cancer Immunotherapy, Sidney Kimmel Comprehensive Cancer Center, Baltimore, MD, USA
- Department of Pathology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Sol Goldman Pancreatic Cancer Research Center, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Shibin Zhou
- Ludwig Center, Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.
- Lustgarten Pancreatic Cancer Research Laboratory, Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.
- Department of Oncology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.
- Bloomberg~Kimmel Institute for Cancer Immunotherapy, Sidney Kimmel Comprehensive Cancer Center, Baltimore, MD, USA.
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24
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Akbar R, Robert PA, Pavlović M, Jeliazkov JR, Snapkov I, Slabodkin A, Weber CR, Scheffer L, Miho E, Haff IH, Haug DTT, Lund-Johansen F, Safonova Y, Sandve GK, Greiff V. A compact vocabulary of paratope-epitope interactions enables predictability of antibody-antigen binding. Cell Rep 2021; 34:108856. [PMID: 33730590 DOI: 10.1016/j.celrep.2021.108856] [Citation(s) in RCA: 75] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2020] [Revised: 11/29/2020] [Accepted: 02/22/2021] [Indexed: 12/16/2022] Open
Abstract
Antibody-antigen binding relies on the specific interaction of amino acids at the paratope-epitope interface. The predictability of antibody-antigen binding is a prerequisite for de novo antibody and (neo-)epitope design. A fundamental premise for the predictability of antibody-antigen binding is the existence of paratope-epitope interaction motifs that are universally shared among antibody-antigen structures. In a dataset of non-redundant antibody-antigen structures, we identify structural interaction motifs, which together compose a commonly shared structure-based vocabulary of paratope-epitope interactions. We show that this vocabulary enables the machine learnability of antibody-antigen binding on the paratope-epitope level using generative machine learning. The vocabulary (1) is compact, less than 104 motifs; (2) distinct from non-immune protein-protein interactions; and (3) mediates specific oligo- and polyreactive interactions between paratope-epitope pairs. Our work leverages combined structure- and sequence-based learning to demonstrate that machine-learning-driven predictive paratope and epitope engineering is feasible.
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Affiliation(s)
- Rahmad Akbar
- Department of Immunology, University of Oslo, Oslo, Norway.
| | | | - Milena Pavlović
- Department of Informatics, University of Oslo, Oslo, Norway; Centre for Bioinformatics, University of Oslo, Norway; K.G. Jebsen Centre for Coeliac Disease Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | | | - Igor Snapkov
- Department of Immunology, University of Oslo, Oslo, Norway
| | | | - Cédric R Weber
- Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland
| | - Lonneke Scheffer
- Department of Informatics, University of Oslo, Oslo, Norway; Centre for Bioinformatics, University of Oslo, Norway
| | - Enkelejda Miho
- Institute of Medical Engineering and Medical Informatics, School of Life Sciences, FHNW University of Applied Sciences and Arts Northwestern Switzerland, Muttenz, Switzerland
| | | | | | | | - Yana Safonova
- Computer Science and Engineering Department, University of California, San Diego, La Jolla, CA, USA
| | - Geir K Sandve
- Department of Informatics, University of Oslo, Oslo, Norway; Centre for Bioinformatics, University of Oslo, Norway; K.G. Jebsen Centre for Coeliac Disease Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Victor Greiff
- Department of Immunology, University of Oslo, Oslo, Norway.
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25
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Zhu Y, Huang C, Su M, Ge Z, Gao L, Shi Y, Wang X, Chen J. Characterization of amino acid residues of T-cell receptors interacting with HLA-A*02-restricted antigen peptides. ANNALS OF TRANSLATIONAL MEDICINE 2021; 9:495. [PMID: 33850892 PMCID: PMC8039679 DOI: 10.21037/atm-21-835] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
Background The present study aimed to explore residues’ properties interacting with HLA-A*02-restricted peptides on T-cell receptors (TCRs) and their effects on bond types of interaction and binding free energy. Methods We searched the crystal structures of HLA-A*02-restricted peptide-TCR complexes from the Protein Data Bank (PDB) database and subsequently collected relevant parameters. We then employed Schrodinger to analyze the bond types of interaction and Gromacs 2019 to evaluate the TCR-antigen peptide complex’s molecular dynamics simulation. Finally, we compared the changes of bond types of interaction and binding free energy before and after residue substitution to ensure consistency of the conditions before and after residue substitution. Results The main sites on the antigen peptides that formed the intermolecular interaction [hydrogen bond (HB) and pi stack] with TCRs were P4, P8, P2, and P6. The hydrophobicity of the amino acids inside or outside the disulfide bond of TCRs may be related to the intermolecular interaction and binding free energy between TCRs and peptides. Residues located outside the disulfide bond of TCR α or β chains and forming pi stack force played favorable roles in the complex intermolecular interaction and binding free energy. The residues of the TCR α or β chains that interacted with peptides were replaced by alanine (Ala) or glycine (Gly), and their intermolecular binding free energy of the complex had been improved. However, it had nothing to do with the formation of HB. Conclusions The findings of this study suggest that the hydrophobic nature of the amino acids inside or outside the disulfide bonds on the TCR may be associated with the intermolecular interaction and binding between the TCR and polypeptide. The residues located outside the TCR α or β single-chain disulfide bond and forming the pi-stack force showed a beneficial effect on the intermolecular interaction and binding of the complex. In addition, the part of the residues on the TCR α or β single chain that produced bond types of interaction with the polypeptide after being replaced by Ala or Gly, the intermolecular binding free energy of the complex was increased, regardless of whether HB was formed.
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Affiliation(s)
- Ying Zhu
- Department of Oncology, First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, China
| | - Changxin Huang
- Department of Oncology, Affiliated Hospital of Hangzhou Normal University, Hangzhou, China
| | - Meng Su
- Master Class, Zhejiang Chinese Medical University, Fourth School of Clinical Medicine, Hangzhou, China
| | - Zuanmin Ge
- Master Class, Hangzhou Normal University, School of Medicine, Hangzhou, China
| | - Lanlan Gao
- Master Class, Hangzhou Normal University, School of Medicine, Hangzhou, China
| | - Yanfei Shi
- Master Class, Hangzhou Normal University, School of Medicine, Hangzhou, China
| | - Xuechun Wang
- Master Class, Zhejiang Chinese Medical University, Fourth School of Clinical Medicine, Hangzhou, China
| | - Jianfeng Chen
- Department of Proctology, Affiliated Hospital of Hangzhou Normal University, Hangzhou, China
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26
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Robinson RA, McMurran C, McCully ML, Cole DK. Engineering soluble T-cell receptors for therapy. FEBS J 2021; 288:6159-6173. [PMID: 33624424 PMCID: PMC8596704 DOI: 10.1111/febs.15780] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2020] [Revised: 02/11/2021] [Accepted: 02/22/2021] [Indexed: 12/15/2022]
Abstract
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.
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27
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Borrman T, Pierce BG, Vreven T, Baker BM, Weng Z. High-throughput modeling and scoring of TCR-pMHC complexes to predict cross-reactive peptides. Bioinformatics 2020; 36:5377-5385. [PMID: 33355667 PMCID: PMC8016493 DOI: 10.1093/bioinformatics/btaa1050] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2020] [Revised: 11/23/2020] [Accepted: 12/08/2020] [Indexed: 01/14/2023] Open
Abstract
MOTIVATION The binding of T cell receptors (TCRs) to their target peptide MHC (pMHC) ligands initializes the cell-mediated immune response. In autoimmune diseases such as multiple sclerosis, the TCR erroneously recognizes self-peptides as foreign and activates an immune response against healthy cells. Such responses can be triggered by cross-recognition of the autoreactive TCR with foreign peptides. Hence, it would be desirable to identify such foreign-antigen triggers to provide a mechanistic understanding of autoimmune diseases. However, the large sequence space of foreign antigens presents an obstacle in the identification of cross-reactive peptides. RESULTS Here, we present an in silico modeling and scoring method which exploits the structural properties of TCR-pMHC complexes to predict the binding of cross-reactive peptides. We analyzed three mouse TCRs and one human TCR isolated from a patient with multiple sclerosis. Cross-reactive peptides for these TCRs were previously identified via yeast display coupled with deep sequencing, providing a robust dataset for evaluating our method. Modeling query peptides in their associated TCR-pMHC crystal structures, our method accurately selected the top binding peptides from sets containing more than a hundred thousand unique peptides. AVAILABILITY AND IMPLEMENTATION Analyses were performed using custom Python and R scripts available at https://github.com/tborrman/antigen-predict. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Tyler Borrman
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA, USA
| | - Brian G Pierce
- University of Maryland Institute for Bioscience and Biotechnology Research, Rockville, MD, USA.,Department of Cell Biology and Molecular Genetics, University of Maryland, College Park, MD, USA
| | - Thom Vreven
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA, USA
| | - Brian M Baker
- Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, IN, USA.,Harper Cancer Research Institute, University of Notre Dame, Notre Dame, IN, USA
| | - Zhiping Weng
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA, USA
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28
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Leon E, Ranganathan R, Savoldo B. Adoptive T cell therapy: Boosting the immune system to fight cancer. Semin Immunol 2020; 49:101437. [PMID: 33262066 DOI: 10.1016/j.smim.2020.101437] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/12/2020] [Revised: 11/19/2020] [Accepted: 11/19/2020] [Indexed: 01/06/2023]
Abstract
Cellular therapies have shown increasing promise as a cancer treatment. Encouraging results against hematologic malignancies are paving the way to move into solid tumors. In this review, we will focus on T-cell therapies starting from tumor infiltrating lymphocytes (TILs) to optimized T-cell receptor-modified (TCR) cells and chimeric antigen receptor-modified T cells (CAR-Ts). We will discuss the positive preclinical and clinical findings of these approaches, along with some of the persisting barriers that need to be overcome to improve outcomes.
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Affiliation(s)
- Ernesto Leon
- Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.
| | - Raghuveer Ranganathan
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States; Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA, United States
| | - Barbara Savoldo
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States; Department of Immunology and Microbiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States; Department of Pediatrics, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
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29
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Lee CH, Salio M, Napolitani G, Ogg G, Simmons A, Koohy H. Predicting Cross-Reactivity and Antigen Specificity of T Cell Receptors. Front Immunol 2020; 11:565096. [PMID: 33193332 PMCID: PMC7642207 DOI: 10.3389/fimmu.2020.565096] [Citation(s) in RCA: 40] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2020] [Accepted: 09/07/2020] [Indexed: 12/13/2022] Open
Abstract
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.
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Affiliation(s)
- Chloe H. Lee
- MRC Human Immunology Unit, Medical Research Council (MRC) Weatherall Institute of Molecular Medicine (WIMM), John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom
- MRC WIMM Centre for Computational Biology, Medical Research Council (MRC) Weatherall Institute of Molecular Medicine, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom
| | - Mariolina Salio
- MRC Human Immunology Unit, Medical Research Council (MRC) Weatherall Institute of Molecular Medicine (WIMM), John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom
| | - Giorgio Napolitani
- MRC Human Immunology Unit, Medical Research Council (MRC) Weatherall Institute of Molecular Medicine (WIMM), John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom
| | - Graham Ogg
- MRC Human Immunology Unit, Medical Research Council (MRC) Weatherall Institute of Molecular Medicine (WIMM), John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom
| | - Alison Simmons
- MRC Human Immunology Unit, Medical Research Council (MRC) Weatherall Institute of Molecular Medicine (WIMM), John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom
- Translational Gastroenterology Unit, John Radcliffe Hospital, Oxford, United Kingdom
| | - Hashem Koohy
- MRC Human Immunology Unit, Medical Research Council (MRC) Weatherall Institute of Molecular Medicine (WIMM), John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom
- MRC WIMM Centre for Computational Biology, Medical Research Council (MRC) Weatherall Institute of Molecular Medicine, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom
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30
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Singh NK, Alonso JA, Harris DT, Anderson SD, Ma J, Hellman LM, Rosenberg AM, Kolawole EM, Evavold BD, Kranz DM, Baker BM. An Engineered T Cell Receptor Variant Realizes the Limits of Functional Binding Modes. Biochemistry 2020; 59:4163-4175. [PMID: 33074657 DOI: 10.1021/acs.biochem.0c00689] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2023]
Abstract
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.
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Affiliation(s)
- Nishant K Singh
- Department of Chemistry and Biochemistry and Harper Cancer Research Institute, University of Notre Dame, Notre Dame, Indiana 46556, United States
| | - Jesus A Alonso
- Department of Chemistry and Biochemistry and Harper Cancer Research Institute, University of Notre Dame, Notre Dame, Indiana 46556, United States
| | - Daniel T Harris
- Department of Biochemistry and Cancer Center at Illinois, University of Illinois, Urbana, Illinois 61801, United States
| | - Scott D Anderson
- Department of Biochemistry and Cancer Center at Illinois, University of Illinois, Urbana, Illinois 61801, United States
| | - Jiaqi Ma
- Department of Chemistry and Biochemistry and Harper Cancer Research Institute, University of Notre Dame, Notre Dame, Indiana 46556, United States
| | - Lance M Hellman
- Department of Chemistry and Biochemistry and Harper Cancer Research Institute, University of Notre Dame, Notre Dame, Indiana 46556, United States
| | - Aaron M Rosenberg
- Department of Chemistry and Biochemistry and Harper Cancer Research Institute, University of Notre Dame, Notre Dame, Indiana 46556, United States
| | - Elizabeth M Kolawole
- Division of Microbiology and Immunology, Department of Pathology, University of Utah, Salt Lake City, Utah 84112, United States
| | - Brian D Evavold
- Division of Microbiology and Immunology, Department of Pathology, University of Utah, Salt Lake City, Utah 84112, United States
| | - David M Kranz
- Department of Biochemistry and Cancer Center at Illinois, University of Illinois, Urbana, Illinois 61801, United States
| | - Brian M Baker
- Department of Chemistry and Biochemistry and Harper Cancer Research Institute, University of Notre Dame, Notre Dame, Indiana 46556, United States
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31
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Crean RM, MacLachlan BJ, Madura F, Whalley T, Rizkallah PJ, Holland CJ, McMurran C, Harper S, Godkin A, Sewell AK, Pudney CR, van der Kamp MW, Cole DK. Molecular Rules Underpinning Enhanced Affinity Binding of Human T Cell Receptors Engineered for Immunotherapy. Mol Ther Oncolytics 2020; 18:443-456. [PMID: 32913893 PMCID: PMC7452143 DOI: 10.1016/j.omto.2020.07.008] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2020] [Accepted: 07/27/2020] [Indexed: 10/25/2022] Open
Abstract
Immuno-oncology approaches that utilize T cell receptors (TCRs) are becoming highly attractive because of their potential to target virtually all cellular proteins, including cancer-specific epitopes, via the recognition of peptide-human leukocyte antigen (pHLA) complexes presented at the cell surface. However, because natural TCRs generally recognize cancer-derived pHLAs with very weak affinities, efforts have been made to enhance their binding strength, in some cases by several million-fold. In this study, we investigated the mechanisms underpinning human TCR affinity enhancement by comparing the crystal structures of engineered enhanced affinity TCRs with those of their wild-type progenitors. Additionally, we performed molecular dynamics simulations to better understand the energetic mechanisms driving the affinity enhancements. These data demonstrate that supra-physiological binding affinities can be achieved without altering native TCR-pHLA binding modes via relatively subtle modifications to the interface contacts, often driven through the addition of buried hydrophobic residues. Individual energetic components of the TCR-pHLA interaction governing affinity enhancements were distinct and highly variable for each TCR, often resulting from additive, or knock-on, effects beyond the mutated residues. This comprehensive analysis of affinity-enhanced TCRs has important implications for the future rational design of engineered TCRs as efficacious and safe drugs for cancer treatment.
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Affiliation(s)
- Rory M. Crean
- Department of Biology and Biochemistry, University of Bath, Bath, BA2 7AY, UK
- Doctoral Training Centre in Sustainable Chemical Technologies, University of Bath, Bath, BA2 7AY, UK
| | | | - Florian Madura
- Division of Infection & Immunity, Cardiff University, Cardiff, CF14 4XN, UK
| | - Thomas Whalley
- Division of Infection & Immunity, Cardiff University, Cardiff, CF14 4XN, UK
| | | | | | | | | | - Andrew Godkin
- Division of Infection & Immunity, Cardiff University, Cardiff, CF14 4XN, UK
| | - Andrew K. Sewell
- Division of Infection & Immunity, Cardiff University, Cardiff, CF14 4XN, UK
| | - Christopher R. Pudney
- Department of Biology and Biochemistry, University of Bath, Bath, BA2 7AY, UK
- Centre for Therapeutic Innovation, University of Bath, Bath, BA2 7AY, UK
| | - Marc W. van der Kamp
- School of Biochemistry, University of Bristol, Biomedical Sciences Building, University Walk, Bristol, BS8 1TD, UK
| | - David K. Cole
- Division of Infection & Immunity, Cardiff University, Cardiff, CF14 4XN, UK
- Immunocore, Ltd., Abingdon, OX14 4RY, UK
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32
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Wu D, Gallagher DT, Gowthaman R, Pierce BG, Mariuzza RA. Structural basis for oligoclonal T cell recognition of a shared p53 cancer neoantigen. Nat Commun 2020; 11:2908. [PMID: 32518267 PMCID: PMC7283474 DOI: 10.1038/s41467-020-16755-y] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2020] [Accepted: 05/19/2020] [Indexed: 01/21/2023] Open
Abstract
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.
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Affiliation(s)
- Daichao Wu
- W.M. Keck Laboratory for Structural Biology, University of Maryland Institute for Bioscience and Biotechnology Research, Rockville, MD, 20850, USA
- Department of Histology and Embryology, Hengyang Medical College, University of South China, Hengyang, Hunan, 421001, China
- Department of Cell Biology and Molecular Genetics, University of Maryland, College Park, MD, 20742, USA
| | - D Travis Gallagher
- W.M. Keck Laboratory for Structural Biology, University of Maryland Institute for Bioscience and Biotechnology Research, Rockville, MD, 20850, USA
- National Institute of Standards and Technology, Gaitherburg, MD, 20899, USA
| | - Ragul Gowthaman
- W.M. Keck Laboratory for Structural Biology, University of Maryland Institute for Bioscience and Biotechnology Research, Rockville, MD, 20850, USA
- Department of Cell Biology and Molecular Genetics, University of Maryland, College Park, MD, 20742, USA
| | - Brian G Pierce
- W.M. Keck Laboratory for Structural Biology, University of Maryland Institute for Bioscience and Biotechnology Research, Rockville, MD, 20850, USA
- Department of Cell Biology and Molecular Genetics, University of Maryland, College Park, MD, 20742, USA
| | - Roy A Mariuzza
- W.M. Keck Laboratory for Structural Biology, University of Maryland Institute for Bioscience and Biotechnology Research, Rockville, MD, 20850, USA.
- Department of Cell Biology and Molecular Genetics, University of Maryland, College Park, MD, 20742, USA.
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33
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Hoffmann MM, Slansky JE. T-cell receptor affinity in the age of cancer immunotherapy. Mol Carcinog 2020; 59:862-870. [PMID: 32386086 DOI: 10.1002/mc.23212] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2020] [Revised: 04/30/2020] [Accepted: 04/30/2020] [Indexed: 12/13/2022]
Abstract
The strength of the interaction between T-cell receptors (TCRs) and their ligands, peptide/major histocompatibility complex complexes (pMHCs), is one of the most frequently discussed and investigated features of T cells in immuno-oncology today. Although there are many molecules on the surface of T cells that interact with ligands on other cells, the TCR/pMHC is the only receptor-ligand pair that offers antigen specificity and dictates the functional response of the T cell. The strength of the TCR/pMHC interaction, along with the environment in which this interaction takes place, is key to how the T cell will respond. The TCR repertoire of T cells that interact with tumor-associated antigens is vast, although typically of low affinity. Here, we focus on the low-affinity interactions between TCRs from CD8+ T cells and different models used in immuno-oncology.
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Affiliation(s)
- Michele M Hoffmann
- Department of Immunology and Microbiology, University of Colorado School of Medicine, Aurora, Colorado
| | - Jill E Slansky
- Department of Immunology and Microbiology, University of Colorado School of Medicine, Aurora, Colorado
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34
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Spear TT, Evavold BD, Baker BM, Nishimura MI. Understanding TCR affinity, antigen specificity, and cross-reactivity to improve TCR gene-modified T cells for cancer immunotherapy. Cancer Immunol Immunother 2019; 68:1881-1889. [PMID: 31595324 PMCID: PMC11028285 DOI: 10.1007/s00262-019-02401-0] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2019] [Accepted: 09/20/2019] [Indexed: 12/19/2022]
Abstract
Adoptive cell transfer (ACT) using T cell receptor (TCR) gene-modified T cells is an exciting and rapidly evolving field. Numerous preclinical and clinical studies have demonstrated various levels of feasibility, safety, and efficacy using TCR-engineered T cells to treat cancer and viral infections. Although evidence suggests their use can be effective, to what extent and how to improve these therapeutics are still matters of investigation. As TCR affinity has been generally accepted as the central role in defining T cell specificity and sensitivity, selection for and generation of high affinity TCRs has remained a fundamental approach to design more potent T cells. However, traditional methods for affinity-enhancement by random mutagenesis can induce undesirable cross-reactivity causing on- and off-target adverse events, generate exhausted effectors by overstimulation, and ignore other kinetic and cellular parameters that have been shown to impact antigen specificity. In this Focussed Research Review, we comment on the preclinical and clinical potential of TCR gene-modified T cells, summarize our contributions challenging the role TCR affinity plays in antigen recognition, and explore how structure-guided design can be used to manipulate antigen specificity and TCR cross-reactivity to improve the safety and efficacy of TCR gene-modified T cells used in ACT.
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Affiliation(s)
- Timothy T Spear
- Department of Surgery, Cardinal Bernardin Cancer Center, Loyola University Chicago, 2160 S. 1st Ave, Bldg 112, Room 308, Maywood, IL, 60153, USA.
| | - Brian D Evavold
- Department of Pathology, Microbiology and Immunology, University of Utah, Salt Lake City, UT, 84112, USA
| | - Brian M Baker
- Department of Chemistry and Biochemistry, Harper Cancer Research Institute, University of Notre Dame, Notre Dame, IN, 46530, USA
| | - Michael I Nishimura
- Department of Surgery, Cardinal Bernardin Cancer Center, Loyola University Chicago, 2160 S. 1st Ave, Bldg 112, Room 308, Maywood, IL, 60153, USA
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35
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Bentzen AK, Hadrup SR. T-cell-receptor cross-recognition and strategies to select safe T-cell receptors for clinical translation. IMMUNO-ONCOLOGY AND TECHNOLOGY 2019; 2:1-10. [PMID: 35036898 PMCID: PMC8741623 DOI: 10.1016/j.iotech.2019.06.003] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
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.
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