1
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McShan AC, Flores-Solis D, Sun Y, Garfinkle SE, Toor JS, Young MC, Sgourakis NG. Conformational plasticity of RAS Q61 family of neoepitopes results in distinct features for targeted recognition. Nat Commun 2023; 14:8204. [PMID: 38081856 PMCID: PMC10713829 DOI: 10.1038/s41467-023-43654-9] [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: 08/28/2022] [Accepted: 11/15/2023] [Indexed: 12/18/2023] Open
Abstract
The conformational landscapes of peptide/human leucocyte antigen (pHLA) protein complexes encompassing tumor neoantigens provide a rationale for target selection towards autologous T cell, vaccine, and antibody-based therapeutic modalities. Here, using complementary biophysical and computational methods, we characterize recurrent RAS55-64 Q61 neoepitopes presented by the common HLA-A*01:01 allotype. We integrate sparse NMR restraints with Rosetta docking to determine the solution structure of NRASQ61K/HLA-A*01:01, which enables modeling of other common RAS55-64 neoepitopes. Hydrogen/deuterium exchange mass spectrometry experiments alongside molecular dynamics simulations reveal differences in solvent accessibility and conformational plasticity across a panel of common Q61 neoepitopes that are relevant for recognition by immunoreceptors. Finally, we predict binding and provide structural models of NRASQ61K antigens spanning the entire HLA allelic landscape, together with in vitro validation for HLA-A*01:191, HLA-B*15:01, and HLA-C*08:02. Our work provides a basis to delineate the solution surface features and immunogenicity of clinically relevant neoepitope/HLA targets for cancer therapy.
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Affiliation(s)
- Andrew C McShan
- Center for Computational and Genomic Medicine, Department of Pathology and Laboratory Medicine, The Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
- Department of Biochemistry and Biophysics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- School of Chemistry & Biochemistry, Georgia Institute of Technology, 901 Atlantic Dr NW, Atlanta, GA, 30318, USA
| | - David Flores-Solis
- Department of Chemistry and Biochemistry, University of California, Santa Cruz, CA, 95064, USA
- German Center for Neurodegenerative Diseases (DZNE), Von-Siebold Straße 3A, 37075, Göttingen, Germany
| | - Yi Sun
- Center for Computational and Genomic Medicine, Department of Pathology and Laboratory Medicine, The Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
- Department of Biochemistry and Biophysics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Samuel E Garfinkle
- Center for Computational and Genomic Medicine, Department of Pathology and Laboratory Medicine, The Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
- Department of Biochemistry and Biophysics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Jugmohit S Toor
- Department of Chemistry and Biochemistry, University of California, Santa Cruz, CA, 95064, USA
- Immunology Research Program, Henry Ford Cancer Institute, Henry Ford Health, Detroit, MI, 48202, USA
| | - Michael C Young
- Center for Computational and Genomic Medicine, Department of Pathology and Laboratory Medicine, The Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Nikolaos G Sgourakis
- Center for Computational and Genomic Medicine, Department of Pathology and Laboratory Medicine, The Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA.
- Department of Biochemistry and Biophysics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
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2
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Yarmarkovich M, Marshall QF, Warrington JM, Premaratne R, Farrel A, Groff D, Li W, di Marco M, Runbeck E, Truong H, Toor JS, Tripathi S, Nguyen S, Shen H, Noel T, Church NL, Weiner A, Kendsersky N, Martinez D, Weisberg R, Christie M, Eisenlohr L, Bosse KR, Dimitrov DS, Stevanovic S, Sgourakis NG, Kiefel BR, Maris JM. Targeting of intracellular oncoproteins with peptide-centric CARs. Nature 2023; 623:820-827. [PMID: 37938771 PMCID: PMC10665195 DOI: 10.1038/s41586-023-06706-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Accepted: 10/03/2023] [Indexed: 11/09/2023]
Abstract
The majority of oncogenic drivers are intracellular proteins, constraining their immunotherapeutic targeting to mutated peptides (neoantigens) presented by individual human leukocyte antigen (HLA) allotypes1. However, most cancers have a modest mutational burden that is insufficient for generating responses using neoantigen-based therapies2,3. Neuroblastoma is a paediatric cancer that harbours few mutations and is instead driven by epigenetically deregulated transcriptional networks4. Here we show that the neuroblastoma immunopeptidome is enriched with peptides derived from proteins essential for tumorigenesis. We focused on targeting the unmutated peptide QYNPIRTTF discovered on HLA-A*24:02, which is derived from the neuroblastoma-dependency gene and master transcriptional regulator PHOX2B. To target QYNPIRTTF, we developed peptide-centric chimeric antigen receptors (PC-CARs) through a counter panning strategy using predicted potentially cross-reactive peptides. We further proposed that PC-CARs can recognize peptides on additional HLA allotypes when presenting a similar overall molecular surface. Informed by our computational modelling results, we show that PHOX2B PC-CARs also recognize QYNPIRTTF presented by HLA-A*23:01, the most common non-A2 allele in people with African ancestry. Finally, we demonstrate potent and specific killing of neuroblastoma cells expressing these HLAs in vitro and complete tumour regression in mice. These data suggest that PC-CARs have the potential to expand the pool of immunotherapeutic targets to include non-immunogenic intracellular oncoproteins and allow targeting through additional HLA allotypes in a clinical setting.
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Affiliation(s)
- Mark Yarmarkovich
- Perlmutter Cancer Center, New York University Grossman School of Medicine, New York, NY, USA.
- Division of Oncology and Center for Childhood Cancer Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA.
| | - Quinlen F Marshall
- Division of Oncology and Center for Childhood Cancer Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - John M Warrington
- Division of Oncology and Center for Childhood Cancer Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | | | - Alvin Farrel
- Division of Oncology and Center for Childhood Cancer Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Biomedical and Health Informatics, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - David Groff
- Division of Oncology and Center for Childhood Cancer Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Wei Li
- University of Pittsburgh, Pittsburgh, PA, USA
| | | | - Erin Runbeck
- Division of Oncology and Center for Childhood Cancer Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Hau Truong
- Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
- Department of Pathology and Lab Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Jugmohit S Toor
- Department of Chemistry and Biochemistry, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Sarvind Tripathi
- Department of Chemistry and Biochemistry, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Son Nguyen
- Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Helena Shen
- Division of Oncology and Center for Childhood Cancer Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Tiffany Noel
- Division of Oncology and Center for Childhood Cancer Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | | | - Amber Weiner
- Division of Oncology and Center for Childhood Cancer Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Nathan Kendsersky
- Division of Oncology and Center for Childhood Cancer Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Dan Martinez
- Department of Pathology and Lab Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Rebecca Weisberg
- Division of Oncology and Center for Childhood Cancer Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Molly Christie
- Division of Oncology and Center for Childhood Cancer Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Laurence Eisenlohr
- Department of Pathology and Lab Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Kristopher R Bosse
- Division of Oncology and Center for Childhood Cancer Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | | | | | - Nikolaos G Sgourakis
- Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
- Department of Pathology and Lab Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | | | - John M Maris
- Division of Oncology and Center for Childhood Cancer Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA.
- Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA.
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3
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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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4
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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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5
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Gao K, Wang R, Chen J, Cheng L, Frishcosy J, Huzumi Y, Qiu Y, Schluckbier T, Wei X, Wei GW. Methodology-Centered Review of Molecular Modeling, Simulation, and Prediction of SARS-CoV-2. Chem Rev 2022; 122:11287-11368. [PMID: 35594413 PMCID: PMC9159519 DOI: 10.1021/acs.chemrev.1c00965] [Citation(s) in RCA: 30] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Despite tremendous efforts in the past two years, our understanding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), virus-host interactions, immune response, virulence, transmission, and evolution is still very limited. This limitation calls for further in-depth investigation. Computational studies have become an indispensable component in combating coronavirus disease 2019 (COVID-19) due to their low cost, their efficiency, and the fact that they are free from safety and ethical constraints. Additionally, the mechanism that governs the global evolution and transmission of SARS-CoV-2 cannot be revealed from individual experiments and was discovered by integrating genotyping of massive viral sequences, biophysical modeling of protein-protein interactions, deep mutational data, deep learning, and advanced mathematics. There exists a tsunami of literature on the molecular modeling, simulations, and predictions of SARS-CoV-2 and related developments of drugs, vaccines, antibodies, and diagnostics. To provide readers with a quick update about this literature, we present a comprehensive and systematic methodology-centered review. Aspects such as molecular biophysics, bioinformatics, cheminformatics, machine learning, and mathematics are discussed. This review will be beneficial to researchers who are looking for ways to contribute to SARS-CoV-2 studies and those who are interested in the status of the field.
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Affiliation(s)
- Kaifu Gao
- Department
of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States
| | - Rui Wang
- Department
of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States
| | - Jiahui Chen
- Department
of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States
| | - Limei Cheng
- Clinical
Pharmacology and Pharmacometrics, Bristol
Myers Squibb, Princeton, New Jersey 08536, United States
| | - Jaclyn Frishcosy
- Department
of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States
| | - Yuta Huzumi
- Department
of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States
| | - Yuchi Qiu
- Department
of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States
| | - Tom Schluckbier
- Department
of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States
| | - Xiaoqi Wei
- Department
of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States
| | - Guo-Wei Wei
- Department
of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States
- Department
of Electrical and Computer Engineering, Michigan State University, East Lansing, Michigan 48824, United States
- Department
of Biochemistry and Molecular Biology, Michigan
State University, East Lansing, Michigan 48824, United States
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6
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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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7
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Yarmarkovich M, Marshall QF, Warrington JM, Premaratne R, Farrel A, Groff D, Li W, di Marco M, Runbeck E, Truong H, Toor JS, Tripathi S, Nguyen S, Shen H, Noel T, Church NL, Weiner A, Kendsersky N, Martinez D, Weisberg R, Christie M, Eisenlohr L, Bosse KR, Dimitrov DS, Stevanovic S, Sgourakis NG, Kiefel BR, Maris JM. Cross-HLA targeting of intracellular oncoproteins with peptide-centric CARs. Nature 2021; 599:477-484. [PMID: 34732890 PMCID: PMC8599005 DOI: 10.1038/s41586-021-04061-6] [Citation(s) in RCA: 79] [Impact Index Per Article: 26.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2021] [Accepted: 09/23/2021] [Indexed: 12/27/2022]
Abstract
The majority of oncogenic drivers are intracellular proteins, thus constraining their immunotherapeutic targeting to mutated peptides (neoantigens) presented by individual human leukocyte antigen (HLA) allotypes1. However, most cancers have a modest mutational burden that is insufficient to generate responses using neoantigen-based therapies2,3. Neuroblastoma is a paediatric cancer that harbours few mutations and is instead driven by epigenetically deregulated transcriptional networks4. Here we show that the neuroblastoma immunopeptidome is enriched with peptides derived from proteins that are essential for tumourigenesis and focus on targeting the unmutated peptide QYNPIRTTF, discovered on HLA-A*24:02, which is derived from the neuroblastoma dependency gene and master transcriptional regulator PHOX2B. To target QYNPIRTTF, we developed peptide-centric chimeric antigen receptors (CARs) using a counter-panning strategy with predicted potentially cross-reactive peptides. We further hypothesized that peptide-centric CARs could recognize peptides on additional HLA allotypes when presented in a similar manner. Informed by computational modelling, we showed that PHOX2B peptide-centric CARs also recognize QYNPIRTTF presented by HLA-A*23:01 and the highly divergent HLA-B*14:02. Finally, we demonstrated potent and specific killing of neuroblastoma cells expressing these HLAs in vitro and complete tumour regression in mice. These data suggest that peptide-centric CARs have the potential to vastly expand the pool of immunotherapeutic targets to include non-immunogenic intracellular oncoproteins and widen the population of patients who would benefit from such therapy by breaking conventional HLA restriction.
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Affiliation(s)
- Mark Yarmarkovich
- Division of Oncology and Center for Childhood Cancer Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Quinlen F Marshall
- Division of Oncology and Center for Childhood Cancer Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - John M Warrington
- Division of Oncology and Center for Childhood Cancer Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | | | - Alvin Farrel
- Division of Oncology and Center for Childhood Cancer Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Biomedical and Health Informatics, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - David Groff
- Division of Oncology and Center for Childhood Cancer Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Wei Li
- University of Pittsburgh, Pittsburgh, PA, USA
| | | | - Erin Runbeck
- Division of Oncology and Center for Childhood Cancer Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Hau Truong
- Division of Oncology and Center for Childhood Cancer Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Jugmohit S Toor
- Department of Chemistry and Biochemistry, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Sarvind Tripathi
- Department of Chemistry and Biochemistry, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Son Nguyen
- Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Helena Shen
- Division of Oncology and Center for Childhood Cancer Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Tiffany Noel
- Division of Oncology and Center for Childhood Cancer Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | | | - Amber Weiner
- Division of Oncology and Center for Childhood Cancer Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Nathan Kendsersky
- Division of Oncology and Center for Childhood Cancer Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Dan Martinez
- Department of Pathology and Lab Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Rebecca Weisberg
- Division of Oncology and Center for Childhood Cancer Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Molly Christie
- Division of Oncology and Center for Childhood Cancer Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Laurence Eisenlohr
- Department of Pathology and Lab Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Kristopher R Bosse
- Division of Oncology and Center for Childhood Cancer Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | | | | | - Nikolaos G Sgourakis
- Division of Oncology and Center for Childhood Cancer Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | | | - John M Maris
- Division of Oncology and Center for Childhood Cancer Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA.
- Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA.
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8
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Kniga AE, Polyakov IV, Nemukhin AV. [In silico specificity determination of neoantigen-reactive T-lymphocytes]. BIOMEDIT︠S︡INSKAI︠A︡ KHIMII︠A︡ 2021; 67:251-258. [PMID: 34142532 DOI: 10.18097/pbmc20216703251] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
Effective personalized immunotherapies of the future will need to capture not only the peculiarities of the patient's tumor but also of his immune response to it. In this study, using results of in vitro high-throughput specificity assays, and combining comparative models of pMHCs and TCRs using molecular docking, we have constructed all-atom models for the putative complexes of all their possible pairwise TCR-pMHC combinations. For the models obtained we have calculated a dataset of physics-based scores and have trained binary classifiers that perform better compared to their solely sequence-based counterparts. These structure-based classifiers pinpoint the most prominent energetic terms and structural features characterizing the type of protein-protein interactions that underlies the immune recognition of tumors by T cells.
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Affiliation(s)
- A E Kniga
- M.V. Lomonosov Moscow State University, Moscow, Russia; N.M. Emanuel Institute of Biochemical Physics RAS, Moscow, Russia
| | - I V Polyakov
- M.V. Lomonosov Moscow State University, Moscow, Russia; N.M. Emanuel Institute of Biochemical Physics RAS, Moscow, Russia
| | - A V Nemukhin
- M.V. Lomonosov Moscow State University, Moscow, Russia; N.M. Emanuel Institute of Biochemical Physics RAS, Moscow, Russia
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9
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Botta C, Agostino RM, Dattola V, Cianci V, Calandruccio ND, Bianco G, Mafodda A, Maisano R, Iuliano E, Orizzonte G, Mazzacuva D, Falzea AC, Saladino RE, Giannicola R, Restifo G, Aguglia U, Caraglia M, Correale P. Myositis/Myasthenia after Pembrolizumab in a Bladder Cancer Patient with an Autoimmunity-Associated HLA: Immune-Biological Evaluation and Case Report. Int J Mol Sci 2021; 22:6246. [PMID: 34200673 PMCID: PMC8230397 DOI: 10.3390/ijms22126246] [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: 05/21/2021] [Revised: 06/03/2021] [Accepted: 06/07/2021] [Indexed: 02/07/2023] Open
Abstract
Pembrolizumab (mAb to PD-1) has been recently approved for the therapy of pretreated urothelial cancer. Despite the efficacy, it is often accompanied by unpredictable and sometime severe immune-related (ir) adverse events (AEs). Here, we report the clinical and immune-biological characterization of a patient with a metastatic bladder cancer who developed myositis signs (M) and a myasthenia-like syndrome (MLS) during treatment with pembrolizumab. The patient presented an autoimmunity-associated HLA haplotype (HLA-A*02/HLA-B*08/HLA-C*07/HLA-DRB1*03) and experienced an increase in activated CD8 T-cells along the treatment. The symptomatology regressed after pembrolizumab discontinuation and a pyridostigmine and steroids-based therapy. This is the first report of concurrent M and MLS appearance in cancer patients receiving pembrolizumab. More efforts are needed to define early the risk and the clinical meaning of irAEs in this setting.
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Affiliation(s)
- Cirino Botta
- Unit of Hematology, Azienda Ospedaliera “Annunziata”, 87100 Cosenza, Italy
- Hematology Unit, Department of Health Promotion, Mother and Child Care, Internal Medicine and Medical Specialties (PROMISE), University of Palermo, 90128 Palermo, Italy
| | - Rita Maria Agostino
- Unit of Oncology, Unit. Grand Metropolitan Hospital “Bianchi Melacrino Morelli”, 89124 Reggio Calabria, Italy; (R.M.A.); (N.D.C.); (G.B.); (A.M.); (R.M.); (E.I.); (G.O.); (A.C.F.); (R.G.)
| | - Vincenzo Dattola
- Unit of Neurology, Unit. Grand Metropolitan Hospital “Bianchi Melacrino Morelli”, 89124 Reggio Calabria, Italy; (V.D.); (V.C.); (U.A.)
| | - Vittoria Cianci
- Unit of Neurology, Unit. Grand Metropolitan Hospital “Bianchi Melacrino Morelli”, 89124 Reggio Calabria, Italy; (V.D.); (V.C.); (U.A.)
| | - Natale Daniele Calandruccio
- Unit of Oncology, Unit. Grand Metropolitan Hospital “Bianchi Melacrino Morelli”, 89124 Reggio Calabria, Italy; (R.M.A.); (N.D.C.); (G.B.); (A.M.); (R.M.); (E.I.); (G.O.); (A.C.F.); (R.G.)
| | - Giovanna Bianco
- Unit of Oncology, Unit. Grand Metropolitan Hospital “Bianchi Melacrino Morelli”, 89124 Reggio Calabria, Italy; (R.M.A.); (N.D.C.); (G.B.); (A.M.); (R.M.); (E.I.); (G.O.); (A.C.F.); (R.G.)
| | - Antonino Mafodda
- Unit of Oncology, Unit. Grand Metropolitan Hospital “Bianchi Melacrino Morelli”, 89124 Reggio Calabria, Italy; (R.M.A.); (N.D.C.); (G.B.); (A.M.); (R.M.); (E.I.); (G.O.); (A.C.F.); (R.G.)
| | - Roberto Maisano
- Unit of Oncology, Unit. Grand Metropolitan Hospital “Bianchi Melacrino Morelli”, 89124 Reggio Calabria, Italy; (R.M.A.); (N.D.C.); (G.B.); (A.M.); (R.M.); (E.I.); (G.O.); (A.C.F.); (R.G.)
| | - Eleonora Iuliano
- Unit of Oncology, Unit. Grand Metropolitan Hospital “Bianchi Melacrino Morelli”, 89124 Reggio Calabria, Italy; (R.M.A.); (N.D.C.); (G.B.); (A.M.); (R.M.); (E.I.); (G.O.); (A.C.F.); (R.G.)
| | - Giovanna Orizzonte
- Unit of Oncology, Unit. Grand Metropolitan Hospital “Bianchi Melacrino Morelli”, 89124 Reggio Calabria, Italy; (R.M.A.); (N.D.C.); (G.B.); (A.M.); (R.M.); (E.I.); (G.O.); (A.C.F.); (R.G.)
| | - Domenico Mazzacuva
- Laboratory of Autoimmunity, Unit. Grand Metropolitan Hospital “Bianchi Melacrino Morelli”, 89124 Reggio Calabria, Italy;
| | - Antonia Consuelo Falzea
- Unit of Oncology, Unit. Grand Metropolitan Hospital “Bianchi Melacrino Morelli”, 89124 Reggio Calabria, Italy; (R.M.A.); (N.D.C.); (G.B.); (A.M.); (R.M.); (E.I.); (G.O.); (A.C.F.); (R.G.)
| | - Rita Emilena Saladino
- HLA Tissue Typing Laboratory, Unit. Grand Metropolitan Hospital “Bianchi Melacrino Morelli”, 89124 Reggio Calabria, Italy;
| | - Rocco Giannicola
- Unit of Oncology, Unit. Grand Metropolitan Hospital “Bianchi Melacrino Morelli”, 89124 Reggio Calabria, Italy; (R.M.A.); (N.D.C.); (G.B.); (A.M.); (R.M.); (E.I.); (G.O.); (A.C.F.); (R.G.)
| | - Giorgio Restifo
- Nuclear Medicine Unit, Grand Metropolitan Hospital “Bianchi Melacrino Morelli”, 89124 Reggio Calabria, Italy;
| | - Umberto Aguglia
- Unit of Neurology, Unit. Grand Metropolitan Hospital “Bianchi Melacrino Morelli”, 89124 Reggio Calabria, Italy; (V.D.); (V.C.); (U.A.)
| | - Michele Caraglia
- Department of Precision Medicine, University of Campania “L. Vanvitelli”, 80138 Naples, Italy;
- Laboratory of Precision and Molecular Oncology, Biogem Scarl, Institute of Genetic Research, 83031 Ariano Irpino, Italy
| | - Pierpaolo Correale
- Unit of Oncology, Unit. Grand Metropolitan Hospital “Bianchi Melacrino Morelli”, 89124 Reggio Calabria, Italy; (R.M.A.); (N.D.C.); (G.B.); (A.M.); (R.M.); (E.I.); (G.O.); (A.C.F.); (R.G.)
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10
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Mobini Kesheh M, Shavandi S, Hosseini P, Kakavand-Ghalehnoei R, Keyvani H. Bioinformatic HLA Studies in the Context of SARS-CoV-2 Pandemic and Review on Association of HLA Alleles with Preexisting Medical Conditions. BIOMED RESEARCH INTERNATIONAL 2021; 2021:6693909. [PMID: 34136572 PMCID: PMC8162251 DOI: 10.1155/2021/6693909] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 11/16/2020] [Revised: 02/10/2021] [Accepted: 05/06/2021] [Indexed: 12/15/2022]
Abstract
After the announcement of a new coronavirus in China in December 2019, which was then called SARS-CoV-2, this virus changed to a global concern and it was then declared as a pandemic by WHO. Human leukocyte antigen (HLA) alleles, which are one of the most polymorphic genes, play a pivotal role in both resistance and vulnerability of the body against viruses and other infections as well as chronic diseases. The association between HLA alleles and preexisting medical conditions such as cardiovascular diseases and diabetes mellitus is reported in various studies. In this review, we focused on the bioinformatic HLA studies to summarize the HLA alleles which responded to SARS-CoV-2 peptides and have been used to design vaccines. We also reviewed HLA alleles that are associated with comorbidities and might be related to the high mortality rate among COVID-19 patients. Since both genes and patients' medical conditions play a key role in both severity of the disease and the mortality rate in COVID-19 patients, a better understanding of the connection between HLA alleles and SARS-CoV-2 can provide a wider perspective on the behavior of the virus. Such understanding can help scientists, especially in terms of protecting healthcare workers and designing effective vaccines.
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Affiliation(s)
- Mina Mobini Kesheh
- Department of Virology, School of Medicine, Iran University of Medical Sciences, Tehran, Iran
| | - Sara Shavandi
- Department of Industrial and Environmental Biotechnology, National Institute of Genetic Engineering and Biotechnology, Tehran, Iran
| | - Parastoo Hosseini
- Department of Virology, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
| | | | - Hossein Keyvani
- Department of Virology, School of Medicine, Iran University of Medical Sciences, Tehran, Iran
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11
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Khan MT, Islam MJ, Parihar A, Islam R, Jerin TJ, Dhote R, Ali MA, Laura FK, Halim MA. Immunoinformatics and molecular modeling approach to design universal multi-epitope vaccine for SARS-CoV-2. INFORMATICS IN MEDICINE UNLOCKED 2021; 24:100578. [PMID: 33898733 PMCID: PMC8057924 DOI: 10.1016/j.imu.2021.100578] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2020] [Revised: 04/12/2021] [Accepted: 04/13/2021] [Indexed: 02/08/2023] Open
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly transmittable and pathogenic human coronavirus that caused a pandemic situation of acute respiratory syndrome, called COVID-19, which has posed a significant threat to global health security. The aim of the present study is to computationally design an effective peptide-based multi-epitope vaccine (MEV) against SARS-CoV-2. The overall model quality of the vaccine candidate, immunogenicity, allergenicity, and physiochemical analysis have been conducted and validated. Molecular dynamics studies confirmed the stability of the candidate vaccine. The docked complexes during the simulation revealed a strong and stable binding interactions of MEV with human and mice toll-like receptors (TLR), TLR3 and TLR4. Finally, candidate vaccine codons have been optimized for their in silico cloning in E. coli expression system, to confirm increased expression. The proposed MEV can be a potential candidate against SARS-CoV-2, but experimental validation is needed to ensure its safety and immunogenicity status.
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Affiliation(s)
- Md Tahsin Khan
- Division of Infectious Diseases, The Red-Green Research Centre, BICCB, 16 Tejkunipara, Tejgaon, Dhaka, 1215, Bangladesh
- Department of Genetic Engineering and Biotechnology, Shahjalal University of Science and Technology, Sylhet, 3114, Bangladesh
| | - Md Jahirul Islam
- Division of Infectious Diseases, The Red-Green Research Centre, BICCB, 16 Tejkunipara, Tejgaon, Dhaka, 1215, Bangladesh
| | - Arpana Parihar
- Department of Genetics, Barkatullah University, Bhopal, Madhya Pradesh, 462026, India
| | - Rahatul Islam
- Department of Genetic Engineering and Biotechnology, Shahjalal University of Science and Technology, Sylhet, 3114, Bangladesh
| | - Tarhima Jahan Jerin
- Department of Biotechnology and Genetic Engineering, Mawlana Bhashani Science and Technology University, Tangail, 1902, Bangladesh
| | - Rupali Dhote
- Department of Genetics, Barkatullah University, Bhopal, Madhya Pradesh, 462026, India
| | - Md Ackas Ali
- Division of Infectious Diseases, The Red-Green Research Centre, BICCB, 16 Tejkunipara, Tejgaon, Dhaka, 1215, Bangladesh
| | - Fariha Khan Laura
- Division of Infectious Diseases, The Red-Green Research Centre, BICCB, 16 Tejkunipara, Tejgaon, Dhaka, 1215, Bangladesh
| | - Mohammad A Halim
- Division of Infectious Diseases, The Red-Green Research Centre, BICCB, 16 Tejkunipara, Tejgaon, Dhaka, 1215, Bangladesh
- Department of Physical Sciences, University of Arkansas-Fort Smith, Fort Smith, AR, USA
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