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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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Ribeiro-Filho HV, Jara GE, Guerra JVS, Cheung M, Felbinger NR, Pereira JGC, Pierce BG, Lopes-de-Oliveira PS. Exploring the Potential of Structure-Based Deep Learning Approaches for T cell Receptor Design. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.19.590222. [PMID: 38712216 PMCID: PMC11071404 DOI: 10.1101/2024.04.19.590222] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2024]
Abstract
Deep learning methods, trained on the increasing set of available protein 3D structures and sequences, have substantially impacted the protein modeling and design field. These advancements have facilitated the creation of novel proteins, or the optimization of existing ones designed for specific functions, such as binding a target protein. Despite the demonstrated potential of such approaches in designing general protein binders, their application in designing immunotherapeutics remains relatively unexplored. A relevant application is the design of T cell receptors (TCRs). Given the crucial role of T cells in mediating immune responses, redirecting these cells to tumor or infected target cells through the engineering of TCRs has shown promising results in treating diseases, especially cancer. However, the computational design of TCR interactions presents challenges for current physics-based methods, particularly due to the unique natural characteristics of these interfaces, such as low affinity and cross-reactivity. For this reason, in this study, we explored the potential of two structure-based deep learning protein design methods, ProteinMPNN and ESM-IF, in designing fixed-backbone TCRs for binding target antigenic peptides presented by the MHC through different design scenarios. To evaluate TCR designs, we employed a comprehensive set of sequence- and structure-based metrics, highlighting the benefits of these methods in comparison to classical physics-based design methods and identifying deficiencies for improvement.
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Affiliation(s)
- Helder V. Ribeiro-Filho
- Brazilian Biosciences National Laboratory, Brazilian Center for Research in Energy and Materials, Campinas 13083-100, Brazil
| | - Gabriel E. Jara
- Brazilian Biosciences National Laboratory, Brazilian Center for Research in Energy and Materials, Campinas 13083-100, Brazil
| | - João V. S. Guerra
- Brazilian Biosciences National Laboratory, Brazilian Center for Research in Energy and Materials, Campinas 13083-100, Brazil
- Graduate Program in Pharmaceutical Sciences, Faculty of Pharmaceutical Sciences, University of Campinas, Campinas, São Paulo, 13083-871, Brazil
| | - Melyssa Cheung
- Institute for Bioscience and Biotechnology Research, University of Maryland, Rockville, Maryland 20850, USA
- Department of Chemistry and Biochemistry, University of Maryland, College Park, Maryland 20742, USA
| | - Nathaniel R. Felbinger
- Institute for Bioscience and Biotechnology Research, University of Maryland, Rockville, Maryland 20850, USA
- Department of Cell Biology and Molecular Genetics, University of Maryland, College Park, Maryland 20742, USA
| | - José G. C. Pereira
- Brazilian Biosciences National Laboratory, Brazilian Center for Research in Energy and Materials, Campinas 13083-100, Brazil
| | - Brian G. Pierce
- Institute for Bioscience and Biotechnology Research, University of Maryland, Rockville, Maryland 20850, USA
- Department of Cell Biology and Molecular Genetics, University of Maryland, College Park, Maryland 20742, USA
| | - Paulo S. Lopes-de-Oliveira
- Brazilian Biosciences National Laboratory, Brazilian Center for Research in Energy and Materials, Campinas 13083-100, Brazil
- Graduate Program in Pharmaceutical Sciences, Faculty of Pharmaceutical Sciences, University of Campinas, Campinas, São Paulo, 13083-871, Brazil
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3
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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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4
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Foldvari Z, Knetter C, Yang W, Gjerdingen TJ, Bollineni RC, Tran TT, Lund-Johansen F, Kolstad A, Drousch K, Klopfleisch R, Leisegang M, Olweus J. A systematic safety pipeline for selection of T-cell receptors to enter clinical use. NPJ Vaccines 2023; 8:126. [PMID: 37607971 PMCID: PMC10444760 DOI: 10.1038/s41541-023-00713-y] [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: 10/19/2022] [Accepted: 07/31/2023] [Indexed: 08/24/2023] Open
Abstract
Cancer immunotherapy using T cell receptor-engineered T cells (TCR-Ts) represents a promising treatment option. However, technologies for pre-clinical safety assessment are incomplete or inaccessible to most laboratories. Here, TCR-T off-target reactivity was assessed in five steps: (1) Mapping target amino acids necessary for TCR-T recognition, followed by (2) a computational search for, and (3) reactivity screening against, candidate cross-reactive peptides in the human proteome. Natural processing and presentation of recognized peptides was evaluated using (4) short mRNAs, and (5) full-length proteins. TCR-Ts were screened for recognition of unintended HLA alleles, and as proxy for off-target reactivity in vivo, a syngeneic, HLA-A*02:01-transgenic mouse model was used. Validation demonstrated importance of studying recognition of full-length candidate off-targets, and that the clinically applied 1G4 TCR has a hitherto unknown reactivity to unintended HLA alleles, relevant for patient selection. This widely applicable strategy should facilitate evaluation of candidate therapeutic TCRs and inform clinical decision-making.
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Affiliation(s)
- Zsofia Foldvari
- Department of Cancer Immunology, Institute for Cancer Research, Oslo University Hospital Radiumhospitalet, Oslo, Norway
- Precision Immunotherapy Alliance, University of Oslo, Oslo, Norway
| | - Cathrine Knetter
- Department of Cancer Immunology, Institute for Cancer Research, Oslo University Hospital Radiumhospitalet, Oslo, Norway
- Precision Immunotherapy Alliance, University of Oslo, Oslo, Norway
| | - Weiwen Yang
- Department of Cancer Immunology, Institute for Cancer Research, Oslo University Hospital Radiumhospitalet, Oslo, Norway
- Precision Immunotherapy Alliance, University of Oslo, Oslo, Norway
| | - Thea Johanne Gjerdingen
- Department of Cancer Immunology, Institute for Cancer Research, Oslo University Hospital Radiumhospitalet, Oslo, Norway
- Precision Immunotherapy Alliance, University of Oslo, Oslo, Norway
| | - Ravi Chand Bollineni
- Department of Cancer Immunology, Institute for Cancer Research, Oslo University Hospital Radiumhospitalet, Oslo, Norway
- Precision Immunotherapy Alliance, University of Oslo, Oslo, Norway
| | - Trung The Tran
- Precision Immunotherapy Alliance, University of Oslo, Oslo, Norway
- Department of Immunology, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Fridtjof Lund-Johansen
- Precision Immunotherapy Alliance, University of Oslo, Oslo, Norway
- Department of Immunology, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Arne Kolstad
- Department of Oncology, Oslo University Hospital Radiumhospitalet, Oslo, Norway
| | - Kimberley Drousch
- Institute of Immunology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Robert Klopfleisch
- Institute of Veterinary Pathology, Freie Universität Berlin, Berlin, Germany
| | - Matthias Leisegang
- Institute of Immunology, Charité - Universitätsmedizin Berlin, Berlin, Germany.
- David and Etta Jonas Center for Cellular Therapy, The University of Chicago, Chicago, IL, USA.
- German Cancer Consortium (DKTK), partner site Berlin, and German Cancer Research Center (DKFZ), Heidelberg, Germany.
| | - Johanna Olweus
- Department of Cancer Immunology, Institute for Cancer Research, Oslo University Hospital Radiumhospitalet, Oslo, Norway.
- Precision Immunotherapy Alliance, University of Oslo, Oslo, Norway.
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5
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T. RR, Smith JC. Structural patterns in class 1 major histocompatibility complex‐restricted nonamer peptide binding to T‐cell receptors. Proteins 2022; 90:1645-1654. [DOI: 10.1002/prot.26343] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Revised: 03/12/2022] [Accepted: 03/27/2022] [Indexed: 11/09/2022]
Affiliation(s)
- Rajitha Rajeshwar T.
- Department of Biochemistry and Cellular and Molecular Biology University of Tennessee Knoxville Tennessee USA
- UT/ORNL Center for Molecular Biophysics Oak Ridge National Laboratory Oak Ridge Tennessee USA
| | - Jeremy C. Smith
- Department of Biochemistry and Cellular and Molecular Biology University of Tennessee Knoxville Tennessee USA
- UT/ORNL Center for Molecular Biophysics Oak Ridge National Laboratory Oak Ridge Tennessee USA
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6
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Seliger B, Massa C. Modulation of Lymphocyte Functions in the Microenvironment by Tumor Oncogenic Pathways. Front Immunol 2022; 13:883639. [PMID: 35663987 PMCID: PMC9160824 DOI: 10.3389/fimmu.2022.883639] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2022] [Accepted: 04/19/2022] [Indexed: 01/10/2023] Open
Abstract
Despite the broad application of different immunotherapeutic strategies for the treatment of solid as well as hematopoietic cancers, the efficacy of these therapies is still limited, with only a minority of patients having a long-term benefit resulting in an improved survival rate. In order to increase the response rates of patients to the currently available immunotherapies, a better understanding of the molecular mechanisms underlying the intrinsic and/or extrinsic resistance to treatment is required. There exist increasing evidences that activation of different oncogenic pathways as well as inactivation of tumor suppressor genes (TSG) in tumor cells inhibit the immune cell recognition and influegnce the composition of the tumor microenvironment (TME), thus leading to an impaired anti-tumoral immune response. A deeper understanding of the link between the tumor milieu and genomic alterations of TSGs and oncogenes is indispensable for the optimization of immunotherapies and to predict the patients’ response to these treatments. This review summarizes the role of different cancer-related, oncogene- and TSG-controlled pathways in the context of anti-tumoral immunity and response to different immunotherapies.
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Affiliation(s)
- Barbara Seliger
- Institute of Medical Immunology, Martin Luther University Halle-Wittenberg, Halle (Saale), Germany.,Fraunhofer Institute for Cell Therapy and Immunology, Leipzig, Germany
| | - Chiara Massa
- Institute of Medical Immunology, Martin Luther University Halle-Wittenberg, Halle (Saale), Germany
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7
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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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8
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van Diest E, Hernández López P, Meringa AD, Vyborova A, Karaiskaki F, Heijhuurs S, Gumathi Bormin J, van Dooremalen S, Nicolasen MJT, Gatti LCDE, Johanna I, Straetemans T, Sebestyén Z, Beringer DX, Kuball J. Gamma delta TCR anti-CD3 bispecific molecules (GABs) as novel immunotherapeutic compounds. J Immunother Cancer 2021; 9:jitc-2021-003850. [PMID: 34815357 PMCID: PMC8611453 DOI: 10.1136/jitc-2021-003850] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/02/2021] [Indexed: 01/13/2023] Open
Abstract
Background γ9δ2 T cells hold great promise as cancer therapeutics because of their unique capability of reacting to metabolic changes with tumor cells. However, it has proven very difficult to translate this promise into clinical success. Methods In order to better utilize the tumor reactivity of γ9δ2T cells and combine this with the great potential of T cell engager molecules, we developed a novel bispecific molecule by linking the extracellular domains of tumor-reactive γ9δ2TCRs to a CD3-binding moiety, creating gamma delta TCR anti-CD3 bispecific molecules (GABs). GABs were tested in vitro and in vivo for ability to redirect T lymphocytes to a variety of tumor cell lines and primary patient material. Results GABs utilizing naturally occurring high affinity γ9δ2TCRs efficiently induced αβT cell mediated phosphoantigen-dependent recognition of tumor cells. Reactivity was substantially modulated by variations in the Vδ2 CDR3-region and the BTN2A1-binding HV4-region between CDR2 and CDR3 of the γ-chain was crucial for functionality. GABs redirected αβT cells against a broad range of hematopoietic and solid tumor cell lines and primary acute myeloid leukemia. Furthermore, they enhanced infiltration of immune cells in a 3D bone marrow niche and left healthy tissues intact, while eradicating primary multiple myeloma cells. Lastly, GABs constructed from natural high affinity γ9δ2TCR sequences significantly reduced tumor growth in vivo in a subcutaneous myeloma xenograft model. Conclusions We conclude that GABs allow for the introduction of metabolic targeting of cancer cells to the field of T cell engagers.
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Affiliation(s)
- Eline van Diest
- Center for Translational Immunology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Patricia Hernández López
- Center for Translational Immunology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Angelo D Meringa
- Center for Translational Immunology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Anna Vyborova
- Center for Translational Immunology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Froso Karaiskaki
- Center for Translational Immunology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Sabine Heijhuurs
- Center for Translational Immunology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Jan Gumathi Bormin
- Center for Translational Immunology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Sanne van Dooremalen
- Center for Translational Immunology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Mara J T Nicolasen
- Center for Translational Immunology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Lucrezia C D E Gatti
- Center for Translational Immunology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Inez Johanna
- Center for Translational Immunology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Trudy Straetemans
- Center for Translational Immunology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Zsolt Sebestyén
- Center for Translational Immunology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Dennis X Beringer
- Center for Translational Immunology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Jürgen Kuball
- Center for Translational Immunology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands .,Department of Hematology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
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9
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Ch'ng ACW, Lam P, Alassiri M, Lim TS. Application of phage display for T-cell receptor discovery. Biotechnol Adv 2021; 54:107870. [PMID: 34801662 DOI: 10.1016/j.biotechadv.2021.107870] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Revised: 10/23/2021] [Accepted: 11/15/2021] [Indexed: 12/13/2022]
Abstract
The immune system is tasked to keep our body unharmed and healthy. In the immune system, B- and T-lymphocytes are the two main components working together to stop and eliminate invading threats like virus particles, bacteria, fungi and parasite from attacking our healthy cells. The function of antibodies is relatively more direct in target recognition as compared to T-cell receptors (TCR) which recognizes antigenic peptides being presented on the major histocompatibility complex (MHC). Although phage display has been widely applied for antibody presentation, this is the opposite in the case of TCR. The cell surface TCR is a relatively large and complex molecule, making presentation on phage surfaces challenging. Even so, recombinant versions and modifications have been introduced to allow the growing development of TCR in phage display. In addition, the increasing application of TCR for immunotherapy has made it an important binding motif to be developed by phage display. This review will emphasize on the application of phage display for TCR discovery as well as the engineering aspect of TCR for improved characteristics.
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Affiliation(s)
- Angela Chiew Wen Ch'ng
- Institute for Research in Molecular Medicine, Universiti Sains Malaysia, 11800 Penang, Malaysia
| | - Paula Lam
- CellVec Private Limited, 118518, Singapore; National University of Singapore, Department of Physiology, 117597, Singapore; Duke-NUS Graduate Medical School, Cancer and Stem Cells Biology Program, 169857, Singapore
| | - Mohammed Alassiri
- Department of Basic Sciences, College of Science and Health Professions, King Saud bin Abdulaziz University for Health Sciences (KSAU-HS), Riyadh, Saudi Arabia; King Abdullah International Medical Research Center (KAIMRC), Riyadh, Saudi Arabia
| | - Theam Soon Lim
- Institute for Research in Molecular Medicine, Universiti Sains Malaysia, 11800 Penang, Malaysia; Analytical Biochemistry Research Centre, Universiti Sains Malaysia, 11800 Penang, Malaysia.
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10
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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] [MESH Headings] [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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11
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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: 77] [Impact Index Per Article: 25.7] [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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12
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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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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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14
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Gerber HP, Sibener LV, Lee LJ, Gee MH. Identification of Antigenic Targets. Trends Cancer 2020; 6:299-318. [PMID: 32209445 DOI: 10.1016/j.trecan.2020.01.002] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2019] [Accepted: 01/06/2020] [Indexed: 12/31/2022]
Abstract
The ideal cancer target antigen (Ag) is expressed at high copy numbers on neoplastic cells, absent on normal tissues, and contributes to the survival of cancer cells. Despite significant investments in the identification of cell surface Ags, there is a paucity of targets that meet such ideal cancer target criteria. Recent clinical trials in patients with cancer treated with immune checkpoint inhibitors (ICIs) indicate that cluster of differentiation (CD)8+ T cells, by means of their T cell receptors (TCRs) recognizing intracellular targets presented as peptides in the context of human leukocyte antigen (peptide-human leukocyte antigen complex; pHLA) molecules on tumor cells, can mediate deep and long-lasting antitumor responses in patients with solid tumors. Therefore, pHLA-target Ags may represent the long sought-after, ideal targets for solid tumor targeting by high-potency oncology compounds.
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Affiliation(s)
| | - Leah V Sibener
- 3T Biosciences, 1455 Adams Drive, Menlo Park, CA 94025, USA
| | - Luke J Lee
- 3T Biosciences, 1455 Adams Drive, Menlo Park, CA 94025, USA
| | - Marvin H Gee
- 3T Biosciences, 1455 Adams Drive, Menlo Park, CA 94025, USA
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15
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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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16
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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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17
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Hellman LM, Foley KC, Singh NK, Alonso JA, Riley TP, Devlin JR, Ayres CM, Keller GLJ, Zhang Y, Vander Kooi CW, Nishimura MI, Baker BM. Improving T Cell Receptor On-Target Specificity via Structure-Guided Design. Mol Ther 2018; 27:300-313. [PMID: 30617019 DOI: 10.1016/j.ymthe.2018.12.010] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2018] [Revised: 12/05/2018] [Accepted: 12/08/2018] [Indexed: 12/30/2022] Open
Abstract
T cell receptors (TCRs) have emerged as a new class of immunological therapeutics. However, though antigen specificity is a hallmark of adaptive immunity, TCRs themselves do not possess the high specificity of monoclonal antibodies. Although a necessary function of T cell biology, the resulting cross-reactivity presents a significant challenge for TCR-based therapeutic development, as it creates the potential for off-target recognition and immune toxicity. Efforts to enhance TCR specificity by mimicking the antibody maturation process and enhancing affinity can inadvertently exacerbate TCR cross-reactivity. Here we demonstrate this concern by showing that even peptide-targeted mutations in the TCR can introduce new reactivities against peptides that bear similarity to the original target. To counteract this, we explored a novel structure-guided approach for enhancing TCR specificity independent of affinity. Tested with the MART-1-specific TCR DMF5, our approach had a small but discernible impact on cross-reactivity toward MART-1 homologs yet was able to eliminate DMF5 cross-recognition of more divergent, unrelated epitopes. Our study provides a proof of principle for the use of advanced structure-guided design techniques for improving TCR specificity, and it suggests new ways forward for enhancing TCRs for therapeutic use.
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Affiliation(s)
- Lance M Hellman
- Department of Chemistry and Biochemistry and the Harper Cancer Research Institute, University of Notre Dame, Notre Dame, IN, USA
| | - Kendra C Foley
- Department of Surgery and the Cardinal Bernardin Cancer Center, Loyola University of Chicago, Maywood, IL, USA
| | - Nishant K Singh
- Department of Chemistry and Biochemistry and the Harper Cancer Research Institute, University of Notre Dame, Notre Dame, IN, USA
| | - Jesus A Alonso
- Department of Chemistry and Biochemistry and the Harper Cancer Research Institute, University of Notre Dame, Notre Dame, IN, USA
| | - Timothy P Riley
- Department of Chemistry and Biochemistry and the Harper Cancer Research Institute, University of Notre Dame, Notre Dame, IN, USA
| | - Jason R Devlin
- Department of Chemistry and Biochemistry and the Harper Cancer Research Institute, University of Notre Dame, Notre Dame, IN, USA
| | - Cory M Ayres
- Department of Chemistry and Biochemistry and the Harper Cancer Research Institute, University of Notre Dame, Notre Dame, IN, USA
| | - Grant L J Keller
- Department of Chemistry and Biochemistry and the Harper Cancer Research Institute, University of Notre Dame, Notre Dame, IN, USA
| | - Yuting Zhang
- Department of Chemistry and Biochemistry and the Harper Cancer Research Institute, University of Notre Dame, Notre Dame, IN, USA
| | - Craig W Vander Kooi
- Department of Molecular and Cellular Biochemistry, University of Kentucky, Lexington, KY, USA
| | - Michael I Nishimura
- Department of Surgery and the Cardinal Bernardin Cancer Center, Loyola University of Chicago, Maywood, IL, USA
| | - Brian M Baker
- Department of Chemistry and Biochemistry and the Harper Cancer Research Institute, University of Notre Dame, Notre Dame, IN, USA.
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