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Zhu L, Cui X, Yan Z, Tao Y, Shi L, Zhang X, Yao Y, Shi L. Design and evaluation of a multi-epitope DNA vaccine against HPV16. Hum Vaccin Immunother 2024; 20:2352908. [PMID: 38780076 PMCID: PMC11123455 DOI: 10.1080/21645515.2024.2352908] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2024] [Accepted: 05/05/2024] [Indexed: 05/25/2024] Open
Abstract
Cervical cancer, among the deadliest cancers affecting women globally, primarily arises from persistent infection with high-risk human papillomavirus (HPV). To effectively combat persistent infection and prevent the progression of precancerous lesions into malignancy, a therapeutic HPV vaccine is under development. This study utilized an immunoinformatics approach to predict epitopes of cytotoxic T lymphocytes (CTLs) and helper T lymphocytes (HTLs) using the E6 and E7 oncoproteins of the HPV16 strain as target antigens. Subsequently, through meticulous selection of T-cell epitopes and other necessary elements, a multi-epitope vaccine was constructed, exhibiting good immunogenic, physicochemical, and structural characteristics. Furthermore, in silico simulations showed that the vaccine not only interacted well with toll-like receptors (TLR2/TLR3/TLR4), but also induced a strong innate and adaptive immune response characterized by elevated Th1-type cytokines, such as interferon-gamma (IFN-γ) and interleukin-2 (IL2). Additionally, our study investigated the effects of different immunization intervals on immune responses, aiming to optimize a time-efficient immunization program. In animal model experiments, the vaccine exhibited robust immunogenic, therapeutic, and prophylactic effects. Administered thrice, it consistently induced the expansion of specific CD4 and CD8 T cells, resulting in substantial cytokines release and increased proliferation of memory T cell subsets in splenic cells. Overall, our findings support the potential of this multi-epitope vaccine in combating HPV16 infection and signify its candidacy for future HPV vaccine development.
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Affiliation(s)
- Lanfang Zhu
- Department of Immunogenetics, Institute of Medical Biology, Chinese Academy of Medical Sciences & Peking Union Medical College, Kunming, China
| | - Xiangjie Cui
- Department of Immunogenetics, Institute of Medical Biology, Chinese Academy of Medical Sciences & Peking Union Medical College, Kunming, China
| | - Zhiling Yan
- Department of Gynaecologic Oncology, The No. 3 Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Yufen Tao
- Department of Immunogenetics, Institute of Medical Biology, Chinese Academy of Medical Sciences & Peking Union Medical College, Kunming, China
| | - Lei Shi
- Department of Immunogenetics, Institute of Medical Biology, Chinese Academy of Medical Sciences & Peking Union Medical College, Kunming, China
| | - Xinwen Zhang
- Department of Immunogenetics, Institute of Medical Biology, Chinese Academy of Medical Sciences & Peking Union Medical College, Kunming, China
| | - Yufeng Yao
- Yunnan Key Laboratory of Vaccine Research & Development on Severe Infectious Disease, Institute of Medical Biology, Chinese Academy of Medical Sciences & Peking Union Medical College, Kunming, China
| | - Li Shi
- Department of Immunogenetics, Institute of Medical Biology, Chinese Academy of Medical Sciences & Peking Union Medical College, Kunming, China
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2
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Nielsen JC, Hjo Rringgaard C, Nygaard MMR, Wester A, Elster L, Porsgaard T, Mikkelsen RB, Rasmussen S, Madsen AN, Schlein M, Vrang N, Rigbolt K, Dalbo Ge LS. Machine-Learning-Guided Peptide Drug Discovery: Development of GLP-1 Receptor Agonists with Improved Drug Properties. J Med Chem 2024. [PMID: 38977267 DOI: 10.1021/acs.jmedchem.4c00417] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/10/2024]
Abstract
Peptide-based drug discovery has surged with the development of peptide hormone-derived analogs for the treatment of diabetes and obesity. Machine learning (ML)-enabled quantitative structure-activity relationship (QSAR) approaches have shown great promise in small molecule drug discovery but have been less successful in peptide drug discovery due to limited data availability. We have developed a peptide drug discovery platform called streaMLine, enabling rigorous design, synthesis, screening, and ML-driven analysis of large peptide libraries. Using streaMLine, this study systematically explored secretin as a peptide backbone to generate potent, selective, and long-acting GLP-1R agonists with improved physicochemical properties. We synthesized and screened a total of 2688 peptides and applied ML-guided QSAR to identify multiple options for designing stable and potent GLP-1R agonists. One candidate, GUB021794, was profiled in vivo (S.C., 10 nmol/kg QD) and showed potent body weight loss in diet-induced obese mice and a half-life compatible with once-weekly dosing.
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Affiliation(s)
| | | | | | - Anita Wester
- Gubra, Ho̷rsholm Kongevej 11B, Ho̷rsholm 2970, Denmark
| | | | | | | | | | | | | | - Niels Vrang
- Gubra, Ho̷rsholm Kongevej 11B, Ho̷rsholm 2970, Denmark
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Machaca V, Goyzueta V, Cruz MG, Sejje E, Pilco LM, López J, Túpac Y. Transformers meets neoantigen detection: a systematic literature review. J Integr Bioinform 2024; 0:jib-2023-0043. [PMID: 38960869 DOI: 10.1515/jib-2023-0043] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Accepted: 03/20/2024] [Indexed: 07/05/2024] Open
Abstract
Cancer immunology offers a new alternative to traditional cancer treatments, such as radiotherapy and chemotherapy. One notable alternative is the development of personalized vaccines based on cancer neoantigens. Moreover, Transformers are considered a revolutionary development in artificial intelligence with a significant impact on natural language processing (NLP) tasks and have been utilized in proteomics studies in recent years. In this context, we conducted a systematic literature review to investigate how Transformers are applied in each stage of the neoantigen detection process. Additionally, we mapped current pipelines and examined the results of clinical trials involving cancer vaccines.
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Affiliation(s)
| | | | | | - Erika Sejje
- Universidad Nacional de San Agustín, Arequipa, Perú
| | | | | | - Yván Túpac
- 187038 Universidad Católica San Pablo , Arequipa, Perú
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Bulashevska A, Nacsa Z, Lang F, Braun M, Machyna M, Diken M, Childs L, König R. Artificial intelligence and neoantigens: paving the path for precision cancer immunotherapy. Front Immunol 2024; 15:1394003. [PMID: 38868767 PMCID: PMC11167095 DOI: 10.3389/fimmu.2024.1394003] [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: 02/29/2024] [Accepted: 05/13/2024] [Indexed: 06/14/2024] Open
Abstract
Cancer immunotherapy has witnessed rapid advancement in recent years, with a particular focus on neoantigens as promising targets for personalized treatments. The convergence of immunogenomics, bioinformatics, and artificial intelligence (AI) has propelled the development of innovative neoantigen discovery tools and pipelines. These tools have revolutionized our ability to identify tumor-specific antigens, providing the foundation for precision cancer immunotherapy. AI-driven algorithms can process extensive amounts of data, identify patterns, and make predictions that were once challenging to achieve. However, the integration of AI comes with its own set of challenges, leaving space for further research. With particular focus on the computational approaches, in this article we have explored the current landscape of neoantigen prediction, the fundamental concepts behind, the challenges and their potential solutions providing a comprehensive overview of this rapidly evolving field.
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Affiliation(s)
- Alla Bulashevska
- Host-Pathogen-Interactions, Paul-Ehrlich-Institut, Langen, Germany
| | - Zsófia Nacsa
- Host-Pathogen-Interactions, Paul-Ehrlich-Institut, Langen, Germany
| | - Franziska Lang
- TRON - Translational Oncology at the University Medical Center of the Johannes Gutenberg University gGmbH, Mainz, Germany
| | - Markus Braun
- Host-Pathogen-Interactions, Paul-Ehrlich-Institut, Langen, Germany
| | - Martin Machyna
- Host-Pathogen-Interactions, Paul-Ehrlich-Institut, Langen, Germany
| | - Mustafa Diken
- TRON - Translational Oncology at the University Medical Center of the Johannes Gutenberg University gGmbH, Mainz, Germany
| | - Liam Childs
- Host-Pathogen-Interactions, Paul-Ehrlich-Institut, Langen, Germany
| | - Renate König
- Host-Pathogen-Interactions, Paul-Ehrlich-Institut, Langen, Germany
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Luo T, Xin C, Liu H, Li C, Chen H, Xia C, Gao C. Potential SLA Hp-4.0 haplotype-restricted CTL epitopes identified from the membrane protein of PRRSV induce cell immune responses. Front Microbiol 2024; 15:1404558. [PMID: 38841061 PMCID: PMC11150780 DOI: 10.3389/fmicb.2024.1404558] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2024] [Accepted: 05/03/2024] [Indexed: 06/07/2024] Open
Abstract
Swine leukocyte antigen (SLA) class I molecule-restricted T-cell epitopes, which induce cytotoxic T lymphocyte (CTL) responses, play a critical role in the clearance of porcine reproductive and respiratory syndrome virus (PRRSV) and the development of efficient protective vaccines. The SLA-1*04:01:01, SLA-2*04:01, and SLA-3*04:01 alleles, assigned the Hp-4.0 haplotype, are highly prevalent and usually present in all pig breeds. However, the SLA Hp-4.0 haplotype-restricted CTL epitopes in the structural membrane (M) protein of PRRSV are still unknown. In this study, we predicted 27 possible 9-mer epitope peptides in M protein with high binding scores for SLA-1*04:01:01 using CTL epitope prediction tools. In total, 45 SLA class I complexes, comprising the predicted peptide, extracellular region of the SLA-I molecules, and β2-microglobulin, were constructed in vitro to detect the specific binding of these peptides to SLA-1*04:01:01 (27 complexes), SLA-2*04:01 (9 complexes), and SLA-3*04:01 (9 complexes), respectively. Our results showed that the M27 (T91WKFITSRC), M39 (N130HAFVVRRP), and M49 (G158RKAVKQGV) peptides bind specifically to SLA-1*04:01:01, SLA-2*04:01, and SLA-3*04:01, respectively. Subsequently, using peripheral blood mononuclear cells (PBMCs) isolated from the homozygous Hp-4.0 and Hp-26.0 haplotype piglets vaccinated with commercial PRRSV HuN4-F112 strain, we determined the capacities of these 27 potential peptides to stimulate their proliferation with a Cell Counting Kit-8 and their secretion and expression of interferon gamma (IFN-γ) with an ELISpot assay and real-time qPCR, respectively. The immunological activities of M27, M39, and M49 were therefore confirmed when they efficiently induced PBMC proliferation and IFN-γ secretion in PBMCs from piglets with the prevalent SLA Hp-4.0 haplotype. The amino acid sequence alignment revealed that M27, M39, and M49 are highly conserved among 248 genotype II PRRSV strains collected between 1998 and 2019. These findings contribute to the understanding of the mechanisms of cell-mediated immune responses to PRRSV. Our study also provides a novel strategy for identifying and confirming potential SLA haplotype-restricted CTL epitopes that could be used to develop novel peptide-based vaccines against swine diseases.
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Affiliation(s)
| | | | | | | | | | - Changyou Xia
- State Key Laboratory for Animal Disease Control and Prevention, Heilongjiang Provincial Key Laboratory of Laboratory Animal and Comparative Medicine, National Poultry Laboratory Animal Resource Center, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences (CAAS), Harbin, China
| | - Caixia Gao
- State Key Laboratory for Animal Disease Control and Prevention, Heilongjiang Provincial Key Laboratory of Laboratory Animal and Comparative Medicine, National Poultry Laboratory Animal Resource Center, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences (CAAS), Harbin, China
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Wickland DP, McNinch C, Jessen E, Necela B, Shreeder B, Lin Y, Knutson KL, Asmann YW. Comprehensive profiling of cancer neoantigens from aberrant RNA splicing. J Immunother Cancer 2024; 12:e008988. [PMID: 38754917 PMCID: PMC11097882 DOI: 10.1136/jitc-2024-008988] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/29/2024] [Indexed: 05/18/2024] Open
Abstract
BACKGROUND Cancer neoantigens arise from protein-altering somatic mutations in tumor and rank among the most promising next-generation immuno-oncology agents when used in combination with immune checkpoint inhibitors. We previously developed a computational framework, REAL-neo, for identification, quality control, and prioritization of both class-I and class-II human leucocyte antigen (HLA)-presented neoantigens resulting from somatic single-nucleotide mutations, small insertions and deletions, and gene fusions. In this study, we developed a new module, SPLICE-neo, to identify neoantigens from aberrant RNA transcripts from two distinct sources: (1) DNA mutations within splice sites and (2) de novo RNA aberrant splicings. METHODS First, SPLICE-neo was used to profile all DNA splice-site mutations in 11,892 tumors from The Cancer Genome Atlas (TCGA) and identified 11 profiles of splicing donor or acceptor site gains or losses. Transcript isoforms resulting from the top seven most frequent profiles were computed using novel logic models. Second, SPLICE-neo identified de novo RNA splicing events using RNA sequencing reads mapped to novel exon junctions from either single, double, or multiple exon-skipping events. The aberrant transcripts from both sources were then ranked based on isoform expression levels and z-scores assuming that individual aberrant splicing events are rare. Finally, top-ranked novel isoforms were translated into protein, and the resulting neoepitopes were evaluated for neoantigen potential using REAL-neo. The top splicing neoantigen candidates binding to HLA-A*02:01 were validated using in vitro T2 binding assays. RESULTS We identified abundant splicing neoantigens in four representative TCGA cancers: BRCA, LUAD, LUSC, and LIHC. In addition to their substantial contribution to neoantigen load, several splicing neoantigens were potent tumor antigens with stronger bindings to HLA compared with the positive control of antigens from influenza virus. CONCLUSIONS SPLICE-neo is the first tool to comprehensively identify and prioritize splicing neoantigens from both DNA splice-site mutations and de novo RNA aberrant splicings. There are two major advances of SPLICE-neo. First, we developed novel logic models that assemble and prioritize full-length aberrant transcripts from DNA splice-site mutations. Second, SPLICE-neo can identify exon-skipping events involving more than two exons, which account for a quarter to one-third of all skipping events.
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Affiliation(s)
- Daniel P Wickland
- Department of Quantitative Health Sciences, Mayo Clinic, Jacksonville, Florida, USA
| | - Colton McNinch
- National Institute of Allergy and Infectious Diseases, Bethesda, Maryland, USA
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota, USA
| | - Erik Jessen
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota, USA
| | - Brian Necela
- Department of Immunology, Mayo Clinic, Jacksonville, Florida, USA
| | - Barath Shreeder
- Department of Immunology, Mayo Clinic, Jacksonville, Florida, USA
| | - Yi Lin
- Division of Hematology, Department of Internal Medicine, Mayo Clinic, Rochester, Minnesota, USA
| | - Keith L Knutson
- Department of Immunology, Mayo Clinic, Jacksonville, Florida, USA
| | - Yan W Asmann
- Department of Quantitative Health Sciences, Mayo Clinic, Jacksonville, Florida, USA
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Samri A, Bandeira AC, Gois LL, Silva CGR, Rousseau A, Corneau A, Tarantino N, Maucourant C, Queiroz GAN, Vieillard V, Yssel H, Campos GS, Sardi S, Autran B, Rios Grassi MF. Comprehensive analysis of early T cell responses to acute Zika Virus infection during the first epidemic in Bahia, Brazil. PLoS One 2024; 19:e0302684. [PMID: 38722858 PMCID: PMC11081376 DOI: 10.1371/journal.pone.0302684] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Accepted: 04/05/2024] [Indexed: 05/13/2024] Open
Abstract
BACKGROUND In most cases, Zika virus (ZIKV) causes a self-limited acute illness in adults, characterized by mild clinical symptoms that resolve within a few days. Immune responses, both innate and adaptive, play a central role in controlling and eliminating virus-infected cells during the early stages of infection. AIM To test the hypothesis that circulating T cells exhibit phenotypic and functional activation characteristics during the viremic phase of ZIKV infection. METHODS A comprehensive analysis using mass cytometry was performed on peripheral blood mononuclear cells obtained from patients with acute ZIKV infection (as confirmed by RT-PCR) and compared with that from healthy donors (HD). The frequency of IFN-γ-producing T cells in response to peptide pools covering immunogenic regions of structural and nonstructural ZIKV proteins was quantified using an ELISpot assay. RESULTS Circulating CD4+ and CD8+ T lymphocytes from ZIKV-infected patients expressed higher levels of IFN-γ and pSTAT-5, as well as cell surface markers associated with proliferation (Ki-67), activation ((HLA-DR, CD38) or exhaustion (PD1 and CTLA-4), compared to those from HD. Activation of CD4+ and CD8+ memory T cell subsets, including Transitional Memory T Cells (TTM), Effector Memory T cells (TEM), and Effector Memory T cells Re-expressing CD45RA (TEMRA), was prominent among CD4+ T cell subset of ZIKV-infected patients and was associated with increased levels of IFN-γ, pSTAT-5, Ki-67, CTLA-4, and PD1, as compared to HD. Additionally, approximately 30% of ZIKV-infected patients exhibited a T cell response primarily directed against the ZIKV NS5 protein. CONCLUSION Circulating T lymphocytes spontaneously produce IFN-γ and express elevated levels of pSTAT-5 during the early phase of ZIKV infection whereas recognition of ZIKV antigen results in the generation of virus-specific IFN-γ-producing T cells.
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Affiliation(s)
- Assia Samri
- Sorbonne-Université, Inserm 1135, CNRS ERL8255, Centre d’immunologie et des Maladies Infectieuses, Cimi, Paris, France
| | - Antonio Carlos Bandeira
- Secretaria de Saúde da Bahia, Salvador, Bahia, Brazil
- Instituto Gonçalo Moniz, Fundação Oswaldo Cruz (FIOCRUZ), Salvador, Brazil
| | - Luana Leandro Gois
- Instituto Gonçalo Moniz, Fundação Oswaldo Cruz (FIOCRUZ), Salvador, Brazil
- Escola Bahiana de Medicina e Saúde Pública (EBMSP), Salvador, Brazil
- Departamento de Biointeração, Instituto de Ciências da Saúde, Universidade Federal da Bahia, Salvador, Brazil
| | | | - Alice Rousseau
- Sorbonne-Université, Inserm 1135, CNRS ERL8255, Centre d’immunologie et des Maladies Infectieuses, Cimi, Paris, France
| | - Aurelien Corneau
- Faculté de Médecine Pierre et Marie Curie, Plateforme de Cytométrie (CyPS), UMS30–LUMIC, Paris, France
| | - Nadine Tarantino
- Sorbonne-Université, Inserm 1135, CNRS ERL8255, Centre d’immunologie et des Maladies Infectieuses, Cimi, Paris, France
| | - Christopher Maucourant
- Sorbonne-Université, Inserm 1135, CNRS ERL8255, Centre d’immunologie et des Maladies Infectieuses, Cimi, Paris, France
| | - Gabriel Andrade Nonato Queiroz
- Instituto Gonçalo Moniz, Fundação Oswaldo Cruz (FIOCRUZ), Salvador, Brazil
- Escola Bahiana de Medicina e Saúde Pública (EBMSP), Salvador, Brazil
| | - Vincent Vieillard
- Sorbonne-Université, Inserm 1135, CNRS ERL8255, Centre d’immunologie et des Maladies Infectieuses, Cimi, Paris, France
| | - Hans Yssel
- Sorbonne-Université, Inserm 1135, CNRS ERL8255, Centre d’immunologie et des Maladies Infectieuses, Cimi, Paris, France
| | - Gubio Soares Campos
- Departamento de Biointeração, Instituto de Ciências da Saúde, Universidade Federal da Bahia, Salvador, Brazil
| | - Silvia Sardi
- Departamento de Biointeração, Instituto de Ciências da Saúde, Universidade Federal da Bahia, Salvador, Brazil
| | - Brigitte Autran
- Sorbonne-Université, Inserm 1135, CNRS ERL8255, Centre d’immunologie et des Maladies Infectieuses, Cimi, Paris, France
| | - Maria Fernanda Rios Grassi
- Instituto Gonçalo Moniz, Fundação Oswaldo Cruz (FIOCRUZ), Salvador, Brazil
- Escola Bahiana de Medicina e Saúde Pública (EBMSP), Salvador, Brazil
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Matern BM, Niemann M. PIRCHE application major versions 3 and 4 lead to equivalent T cell epitope mismatch scores in solid organ and stem cell transplantation modules. Hum Immunol 2024; 85:110789. [PMID: 38521663 DOI: 10.1016/j.humimm.2024.110789] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2024] [Revised: 03/01/2024] [Accepted: 03/15/2024] [Indexed: 03/25/2024]
Abstract
PIRCHE scores in organ and stem cell transplantation have been shown to correlate with increased risk of donor-specific HLA antibodies and graft-versus-host disease, respectively. With advancements of the PIRCHE application server, it is critical to compare the predicted scores with previous versions. This manuscript compares the newly introduced PIRCHE version 4.2 with its predecessor version 3.3, which was widely used in retrospective studies, using a virtual cohort of 10,000 transplant pairs. In the stem cell transplantation module, both versions yield identical results in 100% of the test population. In the solid organ module, 97% of the test population has identical PIRCHE scores. The deviating cases (3%) were attributed to refinements in the PIRCHE algorithm's specification. Furthermore, the magnitude of the difference is likely to be below the detection limit for clinical effects, confirming the equivalence in PIRCHE scores between versions 3.3 and 4.2.
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Guo N, Niu Z, Yan Z, Liu W, Shi L, Li C, Yao Y, Shi L. Immunoinformatics Design and In Vivo Immunogenicity Evaluation of a Conserved CTL Multi-Epitope Vaccine Targeting HPV16 E5, E6, and E7 Proteins. Vaccines (Basel) 2024; 12:392. [PMID: 38675774 PMCID: PMC11053576 DOI: 10.3390/vaccines12040392] [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: 02/02/2024] [Revised: 04/01/2024] [Accepted: 04/07/2024] [Indexed: 04/28/2024] Open
Abstract
Human papillomavirus type 16 (HPV16) infection is responsible for more than 50% of global cervical cancer cases. The development of a vaccine based on cytotoxic T-lymphocyte (CTL) epitopes is a promising strategy for eliminating pre-existing HPV infections and treating patients with cervical cancer. In this study, an immunoinformatics approach was used to predict HLA-I-restricted CTL epitopes in HPV16 E5, E6, and E7 proteins, and a set of conserved CTL epitopes co-restricted by human/murine MHCs was screened and characterized, with the set containing three E5, four E6, and four E7 epitopes. Subsequently, the immunogenicity of the epitope combination was assessed in mice, and the anti-tumor effects of the multi-epitope peptide vaccine E5E6E7pep11 and the recombinant protein vaccine CTB-Epi11E567 were evaluated in the TC-1 mouse tumor model. The results demonstrated that mixed epitope peptides could induce antigen-specific IFN-γ secretion in mice. Prophylactic immunization with E5E6E7pep11 and CTB-Epi11E567 was found to provide 100% protection against tumor growth in mice. Moreover, both types of the multi-epitope vaccine significantly inhibited tumor growth and prolonged mouse survival. In conclusion, in this study, a multi-epitope vaccine targeting HPV16 E5, E6, and E7 proteins was successfully designed and evaluated, demonstrating potential immunogenicity and anti-tumor effects and providing a promising strategy for immunotherapy against HPV-associated tumors.
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Affiliation(s)
- Ni Guo
- Yunnan Key Laboratory of Vaccine Research & Development on Severe Infectious Disease, Institute of Medical Biology, Chinese Academy of Medical Sciences & Peking Union Medical College, Kunming 650118, China; (N.G.); (Z.N.); (W.L.); (C.L.)
| | - Zhixin Niu
- Yunnan Key Laboratory of Vaccine Research & Development on Severe Infectious Disease, Institute of Medical Biology, Chinese Academy of Medical Sciences & Peking Union Medical College, Kunming 650118, China; (N.G.); (Z.N.); (W.L.); (C.L.)
| | - Zhiling Yan
- Department of Gynaecologic Oncology, Peking University Cancer Hospital Yunnan & Yunnan Cancer Hospital & The Third Affiliated Hospital of Kunming Medical University, Kunming 650118, China;
| | - Weipeng Liu
- Yunnan Key Laboratory of Vaccine Research & Development on Severe Infectious Disease, Institute of Medical Biology, Chinese Academy of Medical Sciences & Peking Union Medical College, Kunming 650118, China; (N.G.); (Z.N.); (W.L.); (C.L.)
| | - Lei Shi
- Department of Immunogenetics, Institute of Medical Biology, Chinese Academy of Medical Sciences & Peking Union Medical College, Kunming 650118, China;
| | - Chuanyin Li
- Yunnan Key Laboratory of Vaccine Research & Development on Severe Infectious Disease, Institute of Medical Biology, Chinese Academy of Medical Sciences & Peking Union Medical College, Kunming 650118, China; (N.G.); (Z.N.); (W.L.); (C.L.)
| | - Yufeng Yao
- Yunnan Key Laboratory of Vaccine Research & Development on Severe Infectious Disease, Institute of Medical Biology, Chinese Academy of Medical Sciences & Peking Union Medical College, Kunming 650118, China; (N.G.); (Z.N.); (W.L.); (C.L.)
| | - Li Shi
- Department of Immunogenetics, Institute of Medical Biology, Chinese Academy of Medical Sciences & Peking Union Medical College, Kunming 650118, China;
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Yazdani Z, Rafiei A, Ghoreyshi M, Abediankenari S. In Silico Analysis of a Candidate Multi-epitope Peptide Vaccine Against Human Brucellosis. Mol Biotechnol 2024; 66:769-783. [PMID: 36940016 PMCID: PMC10026239 DOI: 10.1007/s12033-023-00698-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Accepted: 02/13/2023] [Indexed: 03/21/2023]
Abstract
Brucellosis is one of the neglected endemic zoonoses in the world. Vaccination appears to be a promising health strategy to prevent it. This study used advanced computational techniques to develop a potent multi-epitope vaccine for human brucellosis. Seven epitopes from four main brucella species that infect humans were selected. They had significant potential to induce cellular and humoral responses. They showed high antigenic ability without the allergenic characteristic. In order to improve its immunogenicity, suitable adjuvants were also added to the structure of the vaccine. The physicochemical and immunological properties of the vaccine were evaluated. Then its two and three-dimensional structure was predicted. The vaccine was docked with toll-like receptor4 to assess its ability to stimulate innate immune responses. For successful expression of the vaccine protein in Escherichia coli, in silico cloning, codon optimization, and mRNA stability were evaluated. The immune simulation was performed to reveal the immune response profile of the vaccine after injection. The designed vaccine showed the high ability to induce immune response, especially cellular responses to human brucellosis. It showed the appropriate physicochemical properties, a high-quality structure, and a high potential for expression in a prokaryotic system.
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Affiliation(s)
- Zahra Yazdani
- Department of Immunology, Molecular and Cell Biology Research Center, School of Medicine, Mazandaran University of Medical Sciences, Sari, Iran
- Students Research Committee, Mazandaran University of Medical Sciences, Sari, Iran
| | - Alireza Rafiei
- Department of Immunology, Molecular and Cell Biology Research Center, School of Medicine, Mazandaran University of Medical Sciences, Sari, Iran.
| | - Mehrafarin Ghoreyshi
- Students Research Committee, Mazandaran University of Medical Sciences, Sari, Iran
| | - Saeid Abediankenari
- Immunogenetics Research Center, Department of Immunology, Faculty of Medicine, Mazandaran University of Medical Sciences, Sari, Iran
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11
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Zhang L, Song W, Zhu T, Liu Y, Chen W, Cao Y. ConvNeXt-MHC: improving MHC-peptide affinity prediction by structure-derived degenerate coding and the ConvNeXt model. Brief Bioinform 2024; 25:bbae133. [PMID: 38561979 PMCID: PMC10985285 DOI: 10.1093/bib/bbae133] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Revised: 02/11/2024] [Accepted: 03/02/2024] [Indexed: 04/04/2024] Open
Abstract
Peptide binding to major histocompatibility complex (MHC) proteins plays a critical role in T-cell recognition and the specificity of the immune response. Experimental validation such peptides is extremely resource-intensive. As a result, accurate computational prediction of binding peptides is highly important, particularly in the context of cancer immunotherapy applications, such as the identification of neoantigens. In recent years, there is a significant need to continually improve the existing prediction methods to meet the demands of this field. We developed ConvNeXt-MHC, a method for predicting MHC-I-peptide binding affinity. It introduces a degenerate encoding approach to enhance well-established panspecific methods and integrates transfer learning and semi-supervised learning methods into the cutting-edge deep learning framework ConvNeXt. Comprehensive benchmark results demonstrate that ConvNeXt-MHC outperforms state-of-the-art methods in terms of accuracy. We expect that ConvNeXt-MHC will help us foster new discoveries in the field of immunoinformatics in the distant future. We constructed a user-friendly website at http://www.combio-lezhang.online/predict/, where users can access our data and application.
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Affiliation(s)
- Le Zhang
- College of Computer Science, Sichuan University, Chengdu 610065, China
| | - Wenkai Song
- College of Computer Science, Sichuan University, Chengdu 610065, China
| | - Tinghao Zhu
- College of Computer Science, Sichuan University, Chengdu 610065, China
- Nuclear Power Institute of China, Chengdu 610213, China
| | - Yang Liu
- Center of Growth, Metabolism and Aging, Key Laboratory of Bio-Resource and Eco-Environment of Ministry of Education, College of Life Sciences, Sichuan University, No. 29 Wangjiang Road, Chengdu 610065, China
| | - Wei Chen
- Innovative Institute of Chinese Medicine and Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China
| | - Yang Cao
- Center of Growth, Metabolism and Aging, Key Laboratory of Bio-Resource and Eco-Environment of Ministry of Education, College of Life Sciences, Sichuan University, No. 29 Wangjiang Road, Chengdu 610065, China
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12
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Sng CCT, Kallor AA, Simpson BS, Bedran G, Alfaro J, Litchfield K. Untranslated regions (UTRs) are a potential novel source of neoantigens for personalised immunotherapy. Front Immunol 2024; 15:1347542. [PMID: 38558815 PMCID: PMC10978585 DOI: 10.3389/fimmu.2024.1347542] [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: 12/01/2023] [Accepted: 02/19/2024] [Indexed: 04/04/2024] Open
Abstract
Background Neoantigens, mutated tumour-specific antigens, are key targets of anti-tumour immunity during checkpoint inhibitor (CPI) treatment. Their identification is fundamental to designing neoantigen-directed therapy. Non-canonical neoantigens arising from the untranslated regions (UTR) of the genome are an overlooked source of immunogenic neoantigens. Here, we describe the landscape of UTR-derived neoantigens and release a computational tool, PrimeCUTR, to predict UTR neoantigens generated by start-gain and stop-loss mutations. Methods We applied PrimeCUTR to a whole genome sequencing dataset of pre-treatment tumour samples from CPI-treated patients (n = 341). Cancer immunopeptidomic datasets were interrogated to identify MHC class I presentation of UTR neoantigens. Results Start-gain neoantigens were predicted in 72.7% of patients, while stop-loss mutations were found in 19.3% of patients. While UTR neoantigens only accounted 2.6% of total predicted neoantigen burden, they contributed 12.4% of neoantigens with high dissimilarity to self-proteome. More start-gain neoantigens were found in CPI responders, but this relationship was not significant when correcting for tumour mutational burden. While most UTR neoantigens are private, we identified two recurrent start-gain mutations in melanoma. Using immunopeptidomic datasets, we identify two distinct MHC class I-presented UTR neoantigens: one from a recurrent start-gain mutation in melanoma, and one private to Jurkat cells. Conclusion PrimeCUTR is a novel tool which complements existing neoantigen discovery approaches and has potential to increase the detection yield of neoantigens in personalised therapeutics, particularly for neoantigens with high dissimilarity to self. Further studies are warranted to confirm the expression and immunogenicity of UTR neoantigens.
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Affiliation(s)
- Christopher C. T. Sng
- Cancer Research UK Lung Cancer Centre of Excellence, University College London (UCL) Cancer Institute, London, United Kingdom
| | - Ashwin Adrian Kallor
- International Center for Cancer Vaccine Science, University of Gdansk, Gdansk, Poland
| | - Benjamin S. Simpson
- Cancer Research UK Lung Cancer Centre of Excellence, University College London (UCL) Cancer Institute, London, United Kingdom
| | - Georges Bedran
- International Center for Cancer Vaccine Science, University of Gdansk, Gdansk, Poland
| | - Javier Alfaro
- International Center for Cancer Vaccine Science, University of Gdansk, Gdansk, Poland
- Department of Biochemistry and Microbiology, University of Victoria, Victoria, BC, Canada
- Institute for Adaptive and Neural Computation, School of Informatics, University of Edinburgh, Edinburgh, United Kingdom
| | - Kevin Litchfield
- Cancer Research UK Lung Cancer Centre of Excellence, University College London (UCL) Cancer Institute, London, United Kingdom
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13
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Jiang Y, Dong YH, Zhao SW, Liu DY, Zhang JY, Xu XY, Chen H, Chen H, Jin JB. Multiregion WES of metastatic pancreatic neuroendocrine tumors revealed heterogeneity in genomic alterations, immune microenvironment and evolutionary patterns. Cell Commun Signal 2024; 22:164. [PMID: 38448900 PMCID: PMC10916270 DOI: 10.1186/s12964-024-01545-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Accepted: 02/25/2024] [Indexed: 03/08/2024] Open
Abstract
Pancreatic neuroendocrine tumors (PanNETs), though uncommon, have a high likelihood of spreading to other body parts. Previously, the genetic diversity and evolutionary patterns in metastatic PanNETs were not well understood. To investigate this, we performed multiregion sampling whole-exome sequencing (MRS-WES) on samples from 10 patients who had not received prior treatment for metastatic PanNETs. This included 29 primary tumor samples, 31 lymph node metastases, and 15 liver metastases. We used the MSK-MET dataset for survival analysis and validation of our findings. Our research indicates that mutations in the MEN1/DAXX genes might trigger the early stages of PanNET development. We categorized the patients based on the presence (MEN1/DAXXmut, n = 7) or absence (MEN1/DAXXwild, n = 3) of these mutations. Notable differences were observed between the two groups in terms of genetic alterations and clinically relevant mutations, confirmed using the MSK-MET dataset. Notably, patients with mutations in MEN1/DAXX/ATRX genes had a significantly longer median overall survival compared to those without these mutations (median not reached vs. 43.63 months, p = 0.047). Multiplex immunohistochemistry (mIHC) analysis showed a more prominent immunosuppressive environment in metastatic tumors, especially in patients with MEN1/DAXX mutations. These findings imply that MEN1/DAXX mutations lead PanNETs through a unique evolutionary path. The disease's progression pattern indicates that PanNETs can spread early, even before clinical detection, highlighting the importance of identifying biomarkers related to metastasis to guide personalized treatment strategies.
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Affiliation(s)
- Yu Jiang
- Department of General Surgery, Pancreatic Disease Center, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, 197 Ruijn 2nd Road, Shanghai, 200025, People's Republic of China
| | - Yi-Han Dong
- Department of Pathology, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, People's Republic of China
| | - Shi-Wei Zhao
- Department of General Surgery, Pancreatic Disease Center, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, 197 Ruijn 2nd Road, Shanghai, 200025, People's Republic of China
| | - Dong-Yu Liu
- Department of Clinical and Translational Medicine, 3D Medicines Inc., Shanghai, 201114, People's Republic of China
| | - Ji-Yang Zhang
- Department of Clinical and Translational Medicine, 3D Medicines Inc., Shanghai, 201114, People's Republic of China
| | - Xiao-Ya Xu
- Department of Clinical and Translational Medicine, 3D Medicines Inc., Shanghai, 201114, People's Republic of China
| | - Hao Chen
- Bioinformatics Department, JMDNA Inc., Building 23, 500 Furonghua Road, Shanghai, 201203, People's Republic of China.
| | - Hao Chen
- Department of General Surgery, Pancreatic Disease Center, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, 197 Ruijn 2nd Road, Shanghai, 200025, People's Republic of China.
| | - Jia-Bin Jin
- Department of General Surgery, Pancreatic Disease Center, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, 197 Ruijn 2nd Road, Shanghai, 200025, People's Republic of China.
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14
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Plata-Pineda SE, Cárdenas-Munévar LX, Castro-Cavadía CJ, Buitrago SP, Garzón-Ospina D. Evaluating the genetic diversity of the Plasmodium vivax siap2 locus: A promising candidate for an effective malaria vaccine? Acta Trop 2024; 251:107111. [PMID: 38151069 DOI: 10.1016/j.actatropica.2023.107111] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Revised: 11/27/2023] [Accepted: 12/24/2023] [Indexed: 12/29/2023]
Abstract
Malaria is the deadliest parasitic disease in the world. Traditional control measures have become less effective; hence, there is a need to explore alternative strategies, such as antimalarial vaccines. However, designing an anti-Plasmodium vivax vaccine is considered a challenge due to the complex parasite biology and the antigens' high genetic diversity. Recently, the sporozoite invasion-associated protein 2 (SIAP2) has been suggested as a potential antigen to be considered in vaccine design due to its significance during hepatocyte invasion. However, its use may be limited by the incomplete understanding of gene/protein diversity. Here, the genetic diversity of pvsiap2 using P. vivax DNA samples from Colombia was assessed. Through PCR amplification and sequencing, we compared the Colombian sequences with available worldwide sequences, revealing that pvsiap2 displays low genetic diversity. Molecular evolutionary analyses showed that pvsiap2 appears to be influenced by directional selection. Moreover, the haplotypes found differ by a few mutational steps and several of them were shared between different geographical areas. On the other hand, several conserved regions within PvSIAP2 were predicted as potential B-cell or T-cell epitopes. Considering these characteristics and its role in hepatocyte invasion, the PvSIAP2 protein emerges as a promising antigen to be considered in a multi-antigen-multi-stage (multivalent) fully effective vaccine against P. vivax malaria.
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Affiliation(s)
- Sergio E Plata-Pineda
- School of Biological Sciences, Grupo de Estudios en Genética y Biología Molecular (GEBIMOL), Universidad Pedagógica y Tecnológica de Colombia - UPTC, Tunja, Boyacá, Colombia
| | - Laura X Cárdenas-Munévar
- School of Biological Sciences, Grupo de Estudios en Genética y Biología Molecular (GEBIMOL), Universidad Pedagógica y Tecnológica de Colombia - UPTC, Tunja, Boyacá, Colombia
| | - Carlos J Castro-Cavadía
- Grupo de Investigaciones Microbiológicas y Biomédicas de Córdoba (GIMBIC), School of Health Sciences, Universidad de Córdoba, Montería, Córdoba, Colombia
| | - Sindy P Buitrago
- School of Biological Sciences, Grupo de Estudios en Genética y Biología Molecular (GEBIMOL), Universidad Pedagógica y Tecnológica de Colombia - UPTC, Tunja, Boyacá, Colombia; Population Genetics And Molecular Evolution (PGAME), Fundación Scient, Tunja, Boyacá, Colombia
| | - Diego Garzón-Ospina
- School of Biological Sciences, Grupo de Estudios en Genética y Biología Molecular (GEBIMOL), Universidad Pedagógica y Tecnológica de Colombia - UPTC, Tunja, Boyacá, Colombia; Population Genetics And Molecular Evolution (PGAME), Fundación Scient, Tunja, Boyacá, Colombia.
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15
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Feng Y, Ho KL, Zhang M, Sundaresha NB, Cavanagh HL, Zhao S. Canine major histocompatibility complex class I (MHC-I) diversity landscape. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.14.580220. [PMID: 38405923 PMCID: PMC10888748 DOI: 10.1101/2024.02.14.580220] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/27/2024]
Abstract
The genes of the Major Histocompatibility Complex class I (MHC-I) are among the most diverse in the mammalian genome, playing a crucial role in immunology. Understanding the diversity landscape of MHC-I is therefore of paramount importance. The dog is a key translational model in various biomedical fields. However, our understanding of the canine MHC-I diversity landscape lags significantly behind that of humans. To address this deficiency, we used our newly developed software, KPR de novo assembler and genotyper, to genotype 1,325 samples from 1,025 dogs with paired-end RNA-seq data from 43 BioProjects, after extensive quality control. Among 926 dogs that pass the QC, 591 dogs (64%) have at least one allele genotyped, and a total of 97 known alleles and 52 putative new alleles were identified. Further analysis reveals that DLA-I gene expression levels vary among the tissues, with lowest for testis and brain tissues and highest for blood, corpus luteum, and spleen. We identified dominant alleles in each of the 17 canine breeds, as well as among the entire canine population. Furthermore, our analysis also identifies breed-specific alleles and mutually co-occurred/exclusive alleles. Our study indicates that canine DLA-88 is as diversified as human HLA-A/B/C genes within the entire population, but less diversified within a breed than with HLA-A/B/C within an ethnic group. Lastly, we examined the hypervariable regions (HVR) within or across human/canine MHC-I alleles and found that 80% of the HVRs overlap between the two species. We further noted that 80% of the HVRs are within 4A contact with the peptides, and that the dog-human difference overlaps with only 20% HVRs. Our research offers valuable insights for immunological studies involving dogs.
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16
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Leong SL, Gras S, Grant EJ. Fighting flu: novel CD8 + T-cell targets are required for future influenza vaccines. Clin Transl Immunology 2024; 13:e1491. [PMID: 38362528 PMCID: PMC10867544 DOI: 10.1002/cti2.1491] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Revised: 01/29/2024] [Accepted: 01/30/2024] [Indexed: 02/17/2024] Open
Abstract
Seasonal influenza viruses continue to cause severe medical and financial complications annually. Although there are many licenced influenza vaccines, there are billions of cases of influenza infection every year, resulting in the death of over half a million individuals. Furthermore, these figures can rise in the event of a pandemic, as seen throughout history, like the 1918 Spanish influenza pandemic (50 million deaths) and the 1968 Hong Kong influenza pandemic (~4 million deaths). In this review, we have summarised many of the currently licenced influenza vaccines available across the world and current vaccines in clinical trials. We then briefly discuss the important role of CD8+ T cells during influenza infection and why future influenza vaccines should consider targeting CD8+ T cells. Finally, we assess the current landscape of known immunogenic CD8+ T-cell epitopes and highlight the knowledge gaps required to be filled for the design of rational future influenza vaccines that incorporate CD8+ T cells.
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Affiliation(s)
- Samuel Liwei Leong
- Department of Biochemistry and Chemistry, La Trobe Institute for Molecular ScienceLa Trobe UniversityBundooraVICAustralia
| | - Stephanie Gras
- Department of Biochemistry and Chemistry, La Trobe Institute for Molecular ScienceLa Trobe UniversityBundooraVICAustralia
- Department of Biochemistry and Molecular Biology, Biomedicine Discovery InstituteMonash UniversityClaytonVICAustralia
| | - Emma J Grant
- Department of Biochemistry and Chemistry, La Trobe Institute for Molecular ScienceLa Trobe UniversityBundooraVICAustralia
- Department of Biochemistry and Molecular Biology, Biomedicine Discovery InstituteMonash UniversityClaytonVICAustralia
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17
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Chuwdhury GS, Guo Y, Chiang CL, Lam KO, Kam NW, Liu Z, Dai W. ImmuneMirror: A machine learning-based integrative pipeline and web server for neoantigen prediction. Brief Bioinform 2024; 25:bbae024. [PMID: 38343325 PMCID: PMC10859690 DOI: 10.1093/bib/bbae024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Revised: 12/05/2023] [Accepted: 01/16/2024] [Indexed: 02/15/2024] Open
Abstract
Neoantigens are derived from somatic mutations in the tumors but are absent in normal tissues. Emerging evidence suggests that neoantigens can stimulate tumor-specific T-cell-mediated antitumor immune responses, and therefore are potential immunotherapeutic targets. We developed ImmuneMirror as a stand-alone open-source pipeline and a web server incorporating a balanced random forest model for neoantigen prediction and prioritization. The prediction model was trained and tested using known immunogenic neopeptides collected from 19 published studies. The area under the curve of our trained model was 0.87 based on the testing data. We applied ImmuneMirror to the whole-exome sequencing and RNA sequencing data obtained from gastrointestinal tract cancers including 805 tumors from colorectal cancer (CRC), esophageal squamous cell carcinoma (ESCC) and hepatocellular carcinoma patients. We discovered a subgroup of microsatellite instability-high (MSI-H) CRC patients with a low neoantigen load but a high tumor mutation burden (> 10 mutations per Mbp). Although the efficacy of PD-1 blockade has been demonstrated in advanced MSI-H patients, almost half of such patients do not respond well. Our study identified a subset of MSI-H patients who may not benefit from this treatment with lower neoantigen load for major histocompatibility complex I (P < 0.0001) and II (P = 0.0008) molecules, respectively. Additionally, the neopeptide YMCNSSCMGV-TP53G245V, derived from a hotspot mutation restricted by HLA-A02, was identified as a potential actionable target in ESCC. This is so far the largest study to comprehensively evaluate neoantigen prediction models using experimentally validated neopeptides. Our results demonstrate the reliability and effectiveness of ImmuneMirror for neoantigen prediction.
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Affiliation(s)
- Gulam Sarwar Chuwdhury
- Department of Clinical Oncology, Center of Cancer Medicine, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong (SAR), P. R. China
| | - Yunshan Guo
- Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut, USA
| | - Chi-Leung Chiang
- Department of Clinical Oncology, Center of Cancer Medicine, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong (SAR), P. R. China
| | - Ka-On Lam
- Department of Clinical Oncology, Center of Cancer Medicine, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong (SAR), P. R. China
| | - Ngar-Woon Kam
- Department of Clinical Oncology, Center of Cancer Medicine, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong (SAR), P. R. China
- Laboratory for Synthetic Chemistry and Chemical Biology Limited, Hong Kong Science Park, Shatin, Hong Kong
| | - Zhonghua Liu
- Department of Biostatistics, Columbia University, New York, NY, USA
| | - Wei Dai
- Department of Clinical Oncology, Center of Cancer Medicine, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong (SAR), P. R. China
- University of Hong Kong-Shenzhen Hospital, Shenzhen, P. R. China
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18
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Conev A, Fasoulis R, Hall-Swan S, Ferreira R, Kavraki LE. HLAEquity: Examining biases in pan-allele peptide-HLA binding predictors. iScience 2024; 27:108613. [PMID: 38188519 PMCID: PMC10770483 DOI: 10.1016/j.isci.2023.108613] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Revised: 11/13/2023] [Accepted: 11/29/2023] [Indexed: 01/09/2024] Open
Abstract
Peptide-HLA (pHLA) binding prediction is essential in screening peptide candidates for personalized peptide vaccines. Machine learning (ML) pHLA binding prediction tools are trained on vast amounts of data and are effective in screening peptide candidates. Most ML models report the ability to generalize to HLA alleles unseen during training ("pan-allele" models). However, the use of datasets with imbalanced allele content raises concerns about biased model performance. First, we examine the data bias of two ML-based pan-allele pHLA binding predictors. We find that the pHLA datasets overrepresent alleles from geographic populations of high-income countries. Second, we show that the identified data bias is perpetuated within ML models, leading to algorithmic bias and subpar performance for alleles expressed in low-income geographic populations. We draw attention to the potential therapeutic consequences of this bias, and we challenge the use of the term "pan-allele" to describe models trained with currently available public datasets.
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Affiliation(s)
- Anja Conev
- Department of Computer Science, Rice University, Houston, TX, USA
| | - Romanos Fasoulis
- Department of Computer Science, Rice University, Houston, TX, USA
| | - Sarah Hall-Swan
- Department of Computer Science, Rice University, Houston, TX, USA
| | - Rodrigo Ferreira
- Department of Computer Science, Rice University, Houston, TX, USA
| | - Lydia E. Kavraki
- Department of Computer Science, Rice University, Houston, TX, USA
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19
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Ricker CA, Meli K, Van Allen EM. Historical perspective and future directions: computational science in immuno-oncology. J Immunother Cancer 2024; 12:e008306. [PMID: 38191244 PMCID: PMC10826578 DOI: 10.1136/jitc-2023-008306] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/07/2023] [Indexed: 01/10/2024] Open
Abstract
Immuno-oncology holds promise for transforming patient care having achieved durable clinical response rates across a variety of advanced and metastatic cancers. Despite these achievements, only a minority of patients respond to immunotherapy, underscoring the importance of elucidating molecular mechanisms responsible for response and resistance to inform the development and selection of treatments. Breakthroughs in molecular sequencing technologies have led to the generation of an immense amount of genomic and transcriptomic sequencing data that can be mined to uncover complex tumor-immune interactions using computational tools. In this review, we discuss existing and emerging computational methods that contextualize the composition and functional state of the tumor microenvironment, infer the reactivity and clonal dynamics from reconstructed immune cell receptor repertoires, and predict the antigenic landscape for immune cell recognition. We further describe the advantage of multi-omics analyses for capturing multidimensional relationships and artificial intelligence techniques for integrating omics data with histopathological and radiological images to encapsulate patterns of treatment response and tumor-immune biology. Finally, we discuss key challenges impeding their widespread use and clinical application and conclude with future perspectives. We are hopeful that this review will both serve as a guide for prospective researchers seeking to use existing tools for scientific discoveries and inspire the optimization or development of novel tools to enhance precision, ultimately expediting advancements in immunotherapy that improve patient survival and quality of life.
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Affiliation(s)
- Cora A Ricker
- Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA
| | - Kevin Meli
- Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
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20
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Barra C, Nilsson JB, Saksager A, Carri I, Deleuran S, Garcia Alvarez HM, Høie MH, Li Y, Clifford JN, Wan YTR, Moreta LS, Nielsen M. In Silico Tools for Predicting Novel Epitopes. Methods Mol Biol 2024; 2813:245-280. [PMID: 38888783 DOI: 10.1007/978-1-0716-3890-3_17] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/20/2024]
Abstract
Identifying antigens within a pathogen is a critical task to develop effective vaccines and diagnostic methods, as well as understanding the evolution and adaptation to host immune responses. Historically, antigenicity was studied with experiments that evaluate the immune response against selected fragments of pathogens. Using this approach, the scientific community has gathered abundant information regarding which pathogenic fragments are immunogenic. The systematic collection of this data has enabled unraveling many of the fundamental rules underlying the properties defining epitopes and immunogenicity, and has resulted in the creation of a large panel of immunologically relevant predictive (in silico) tools. The development and application of such tools have proven to accelerate the identification of novel epitopes within biomedical applications reducing experimental costs. This chapter introduces some basic concepts about MHC presentation, T cell and B cell epitopes, the experimental efforts to determine those, and focuses on state-of-the-art methods for epitope prediction, highlighting their strengths and limitations, and catering instructions for their rational use.
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Affiliation(s)
- Carolina Barra
- Section for Bioinformatics, Health Tech, Technical University of Denmark, Lyngby, Denmark.
| | | | - Astrid Saksager
- Section for Bioinformatics, Health Tech, Technical University of Denmark, Lyngby, Denmark
| | - Ibel Carri
- Instituto de Investigaciones Biotecnológicas, Universidad Nacional de San Martín (UNSAM) - Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), San Martín, Argentina
| | - Sebastian Deleuran
- Section for Bioinformatics, Health Tech, Technical University of Denmark, Lyngby, Denmark
| | - Heli M Garcia Alvarez
- Instituto de Investigaciones Biotecnológicas, Universidad Nacional de San Martín (UNSAM) - Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), San Martín, Argentina
| | - Magnus Haraldson Høie
- Section for Bioinformatics, Health Tech, Technical University of Denmark, Lyngby, Denmark
| | - Yuchen Li
- Section for Bioinformatics, Health Tech, Technical University of Denmark, Lyngby, Denmark
| | | | - Yat-Tsai Richie Wan
- Section for Bioinformatics, Health Tech, Technical University of Denmark, Lyngby, Denmark
| | - Lys Sanz Moreta
- Section for Bioinformatics, Health Tech, Technical University of Denmark, Lyngby, Denmark
| | - Morten Nielsen
- Section for Bioinformatics, Health Tech, Technical University of Denmark, Lyngby, Denmark
- Instituto de Investigaciones Biotecnológicas, Universidad Nacional de San Martín (UNSAM) - Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), San Martín, Argentina
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21
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Roved J. MHCtools 1.5: Analysis of MHC Sequencing Data in R. Methods Mol Biol 2024; 2809:275-295. [PMID: 38907904 DOI: 10.1007/978-1-0716-3874-3_18] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/24/2024]
Abstract
The genes of the major histocompatibility complex (MHC) play a vital role in the vertebrate immune system and have attracted considerable interest in evolutionary biology. While the MHC has been characterized in detail in humans (human leukocyte antigen, HLA) and in model organisms such as the mouse, studies in non-model organisms often lack prior knowledge about structure, genetic variability, and evolutionary properties of this locus. MHC genotyping in non-model species commonly relies on PCR-based amplicon sequencing, and while several published protocols facilitate generation of MHC sequence data, there is a lack of transparent and standardized tools for downstream data analysis.Here, I present the R package MHCtools version 1.5, which contains 15 tools that (i) assist accurate MHC genotyping from high-throughput amplicon sequencing data, and provide standardized methods to analyze (ii) MHC diversity, (iii) MHC supertypes, and (iv) MHC haplotypes.I hope that MHCtools will be helpful in future studies of the MHC in non-model species and that it may help to advance our understanding of the important roles of the MHC in ecology and evolution.
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Affiliation(s)
- Jacob Roved
- Section for Molecular Ecology and Evolution, GLOBE Institute, University of Copenhagen, Copenhagen, Denmark.
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22
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Sulfianti A, Karimah N, Nurhasanah A. In silico analysis of HLA-1 and HLA-2 recognition of a designed recombinant human papillomavirus vaccine based on L1 protein HPV subtype 45. J Genet Eng Biotechnol 2023; 21:167. [PMID: 38091180 PMCID: PMC10719189 DOI: 10.1186/s43141-023-00593-8] [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: 07/11/2022] [Accepted: 11/06/2023] [Indexed: 12/17/2023]
Abstract
BACKGROUND Human leukocyte antigen (HLA) can bind and present the processed antigenic peptide derived from the vaccine to the T cell receptor, and this capability is crucial in determining the effectivity of the vaccine to terminate virus-infected cells, activate macrophages, and induce B cells to produce antibodies. A recombinant vaccine candidate based on protein L1 HPV45 was designed and analysed whether it is recognisable by T cells through the binding of their epitopes to HLAs. METHODS The study consisted of two parts: part one was the analysis of the L1 recombinant protein binding to HLA-1 and 2 epitopes, whereas part two was the distribution analysis of HPV-linked HLA allele. HLA allele sets found at high frequency in the general population and in specific Indonesian population were listed for the binding analysis of the recombinant L1 HPV45 protein. In part one, immunoepitope servers from IEDB were used to predict the binding of the designed proteins to HLA alleles. The prediction method for MHC-I binding prediction was the NetMHCpan EL 4.1 whilst for MHC-II binding prediction was the Consensus approach. Antigenicity analysis for each peptide was conducted using VaxiJen 2.0 with the threshold 1.0 to select the highly antigenic peptides, and positions of these epitopes in the secondary and tertiary structure of the recombinant protein were also predicted. The percent population coverage of the alleles capable of binding to these epitopes worldwide was also estimated. In part two, the worldwide distribution and frequency of HPV-related HLA-1 and 2 were studied. RESULT Two highly antigenic peptides (EEYDLQFIF and KLKFWTVDLK) were recognised by high-frequency HLA-1 alleles in both, the general and Western Javanese. In addition to these two epitopes, a few more peptides are also recognised by the high-frequency Western Javanese HLA-1 alleles, which are not in Weiskopf's list of high-frequency HLA-1 alleles in the general population. Analysis of the highly antigenic epitopes binding to HLA-DRB1 alleles in general (YIKGTSANM) and Western Javanese (LRRRPTIGP) populations showed that these peptide cores associate to HLA-DRB1*04, albeit the different sub-types, due to the presence of different allele in each population group. Analysis of the epitopes and the positive binding alleles showed on average 25.65% population coverage. CONCLUSION The recombinant vaccine candidate based on protein L1 HPV45 is presumed to contain highly antigenic peptides that can bind to high-frequency HLA-1 and 2 alleles present in general and Western Javanese populations. It was expected that the protein is capable of eliciting T cell-mediated responses in both populations; however, in vitro study is needed to prove the protectiveness of the designed recombinant protein.
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Affiliation(s)
- Asri Sulfianti
- Centre for Vaccine and Drug Research, National Research and Innovation Agency Republic of Indonesia, LAPTIAB 1, Gedung 611, Kawasan Puspiptek Serpong, Tangerang Selatan, Banten, 15314, Indonesia
| | - Nihayatul Karimah
- Centre for Vaccine and Drug Research, National Research and Innovation Agency Republic of Indonesia, LAPTIAB 1, Gedung 611, Kawasan Puspiptek Serpong, Tangerang Selatan, Banten, 15314, Indonesia
| | - Astutiati Nurhasanah
- Centre for Vaccine and Drug Research, National Research and Innovation Agency Republic of Indonesia, LAPTIAB 1, Gedung 611, Kawasan Puspiptek Serpong, Tangerang Selatan, Banten, 15314, Indonesia.
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23
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Biernacki MA, Lok J, Black RG, Foster KA, Cummings C, Woodward KB, Monahan T, Oehler VG, Stirewalt DL, Wu D, Rongvaux A, Deeg HJ, Bleakley M. Discovery of U2AF1 neoantigens in myeloid neoplasms. J Immunother Cancer 2023; 11:e007490. [PMID: 38164756 PMCID: PMC10729103 DOI: 10.1136/jitc-2023-007490] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/19/2023] [Indexed: 01/03/2024] Open
Abstract
BACKGROUND Myelodysplastic syndromes (MDS) arise from somatic mutations acquired in hematopoietic stem and progenitor cells, causing cytopenias and predisposing to transformation into secondary acute myeloid leukemia (sAML). Recurrent mutations in spliceosome genes, including U2AF1, are attractive therapeutic targets as they are prevalent in MDS and sAML, arise early in neoplastic cells, and are generally absent from normal cells, including normal hematopoietic cells. MDS and sAML are susceptible to T cell-mediated killing, and thus engineered T-cell immunotherapies hold promise for their treatment. We hypothesized that targeting spliceosome mutation-derived neoantigens with transgenic T-cell receptor (TCR) T cells would selectively eradicate malignant cells in MDS and sAML. METHODS We identified candidate neoantigen epitopes from recurrent protein-coding mutations in the spliceosome genes SRSF2 and U2AF1 using a multistep in silico process. Candidate epitopes predicted to bind human leukocyte antigen (HLA) class I, be processed and presented from the parent protein, and not to be subject to tolerance then underwent in vitro immunogenicity screening. CD8+ T cells recognizing immunogenic neoantigen epitopes were evaluated in in vitro assays to assess functional avidity, confirm the predicted HLA restriction, the potential for recognition of similar peptides, and the ability to kill neoplastic cells in an antigen-specific manner. Neoantigen-specific TCR were sequenced, cloned into lentiviral vectors, and transduced into third-party T cells after knock-out of endogenous TCR, then tested in vitro for specificity and ability to kill neoplastic myeloid cells presenting the neoantigen. The efficacy of neoantigen-specific T cells was evaluated in vivo in a murine cell line-derived xenograft model. RESULTS We identified two neoantigens created from a recurrent mutation in U2AF1, isolated CD8+ T cells specific for the neoantigens, and demonstrated that transferring their TCR to third-party CD8+ T cells is feasible and confers specificity for the U2AF1 neoantigens. Finally, we showed that these neoantigen-specific TCR-T cells do not recognize normal hematopoietic cells but efficiently kill malignant myeloid cells bearing the specific U2AF1 mutation, including primary cells, in vitro and in vivo. CONCLUSIONS These data serve as proof-of-concept for developing precision medicine approaches that use neoantigen-directed T-cell receptor-transduced T cells to treat MDS and sAML.
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MESH Headings
- Humans
- Mice
- Animals
- CD8-Positive T-Lymphocytes
- Splicing Factor U2AF/genetics
- Splicing Factor U2AF/metabolism
- Antigens, Neoplasm
- Receptors, Antigen, T-Cell/genetics
- Receptors, Antigen, T-Cell/metabolism
- Myelodysplastic Syndromes/genetics
- Myelodysplastic Syndromes/therapy
- Leukemia, Myeloid, Acute/genetics
- Leukemia, Myeloid, Acute/therapy
- Leukemia, Myeloid, Acute/metabolism
- Epitopes/metabolism
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Affiliation(s)
- Melinda Ann Biernacki
- Translational Sciences and Therapeutics Division, Fred Hutchinson Cancer Center, Seattle, Washington, USA
- Department of Medicine, University of Washington, Seattle, Washington, USA
| | - Jessica Lok
- Translational Sciences and Therapeutics Division, Fred Hutchinson Cancer Center, Seattle, Washington, USA
| | - Ralph Graeme Black
- Translational Sciences and Therapeutics Division, Fred Hutchinson Cancer Center, Seattle, Washington, USA
| | - Kimberly A Foster
- Department of Immunology, University of Washington, Seattle, Washington, USA
| | - Carrie Cummings
- Translational Sciences and Therapeutics Division, Fred Hutchinson Cancer Center, Seattle, Washington, USA
| | - Kyle B Woodward
- Translational Sciences and Therapeutics Division, Fred Hutchinson Cancer Center, Seattle, Washington, USA
| | - Tim Monahan
- Translational Sciences and Therapeutics Division, Fred Hutchinson Cancer Center, Seattle, Washington, USA
| | - Vivian G Oehler
- Translational Sciences and Therapeutics Division, Fred Hutchinson Cancer Center, Seattle, Washington, USA
- Department of Medicine, University of Washington, Seattle, Washington, USA
| | - Derek L Stirewalt
- Translational Sciences and Therapeutics Division, Fred Hutchinson Cancer Center, Seattle, Washington, USA
- Department of Medicine, University of Washington, Seattle, Washington, USA
| | - David Wu
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, Washington, USA
| | - Anthony Rongvaux
- Translational Sciences and Therapeutics Division, Fred Hutchinson Cancer Center, Seattle, Washington, USA
| | - Hans Joachim Deeg
- Translational Sciences and Therapeutics Division, Fred Hutchinson Cancer Center, Seattle, Washington, USA
- Department of Medicine, University of Washington, Seattle, Washington, USA
| | - Marie Bleakley
- Translational Sciences and Therapeutics Division, Fred Hutchinson Cancer Center, Seattle, Washington, USA
- Department of Pediatrics, University of Washington, Seattle, Washington, USA
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24
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Shirasawa M, Yoshida T, Shiraishi K, Goto N, Yagishita S, Imabayashi T, Matsumoto Y, Masuda K, Shinno Y, Okuma Y, Goto Y, Horinouchi H, Yotsukura M, Yoshida Y, Nakagawa K, Naoki K, Tsuchida T, Hamamoto R, Yamamoto N, Motoi N, Kohno T, Watanabe SI, Ohe Y. Tumor microenvironment-mediated immune profiles and efficacy of anti-PD-L1 antibody plus chemotherapy stratified by DLL3 expression in small-cell lung cancer. Br J Cancer 2023; 129:2003-2013. [PMID: 37731022 PMCID: PMC10703835 DOI: 10.1038/s41416-023-02427-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Revised: 08/26/2023] [Accepted: 09/05/2023] [Indexed: 09/22/2023] Open
Abstract
BACKGROUND Delta-like ligand 3 (DLL3) is a therapeutic target in small-cell lung cancer (SCLC). However, how DLL3 expression status affects the tumor microenvironment (TME) and clinical outcomes in SCLC remains unclear. METHODS This retrospective study included patients with postoperative limited-stage (LS)-SCLC and extensive-stage (ES)-SCLC treated with platinum and etoposide (PE) plus anti-programmed cell death ligand 1 (PD-L1) antibody. We investigated the relationship of DLL3 expression with TME, mutation status, tumor neoantigens, and immunochemotherapy. RESULTS In the LS-SCLC cohort (n = 59), whole-exome sequencing revealed that DLL3High cases had significantly more neoantigens (P = 0.004) and a significantly higher rate of the signature SBS4 associated with smoking (P = 0.02) than DLL3Low cases. Transcriptome analysis in the LS-SCLC cohort revealed that DLL3High cases had significantly suppressed immune-related pathways and dendritic cell (DC) function. SCLC with DLL3High had significantly lower proportions of T cells, macrophages, and DCs than those with DLL3Low. In the ES-SCLC cohort (n = 30), the progression-free survival associated with PE plus anti-PD-L1 antibody was significantly worse in DLL3High cases than in DLL3Low cases (4.7 vs. 7.4 months, P = 0.01). CONCLUSIONS Although SCLC with DLL3High had a higher neoantigen load, these tumors were resistant to immunochemotherapy due to suppressed tumor immunity by inhibiting antigen-presenting functions.
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Affiliation(s)
- Masayuki Shirasawa
- Department of Thoracic Oncology, National Cancer Center Hospital, 5-1-1 Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan
- Division of Genome Biology, National Cancer Center Research Institute, 5-1-1, Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan
- Department of Respiratory Medicine, Kitasato University School of Medicine, 1-15-1, Kitasato, Minami-ku, Sagamihara city, Kanagawa, 252-0375, Japan
| | - Tatsuya Yoshida
- Department of Thoracic Oncology, National Cancer Center Hospital, 5-1-1 Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan.
- Division of Molecular Pharmacology, National Cancer Center Research Institute, 5-1-1, Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan.
| | - Kouya Shiraishi
- Division of Genome Biology, National Cancer Center Research Institute, 5-1-1, Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan
| | - Naoko Goto
- Department of Thoracic Oncology, National Cancer Center Hospital, 5-1-1 Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan
| | - Shigehiro Yagishita
- Division of Molecular Pharmacology, National Cancer Center Research Institute, 5-1-1, Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan
| | - Tatsuya Imabayashi
- Department of Endoscopy, Respiratory Endoscopy Division, National Cancer Center Hospital, Tokyo, 104-0045, Japan
| | - Yuji Matsumoto
- Department of Thoracic Oncology, National Cancer Center Hospital, 5-1-1 Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan
- Department of Endoscopy, Respiratory Endoscopy Division, National Cancer Center Hospital, Tokyo, 104-0045, Japan
| | - Ken Masuda
- Department of Thoracic Oncology, National Cancer Center Hospital, 5-1-1 Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan
| | - Yuki Shinno
- Department of Thoracic Oncology, National Cancer Center Hospital, 5-1-1 Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan
| | - Yusuke Okuma
- Department of Thoracic Oncology, National Cancer Center Hospital, 5-1-1 Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan
| | - Yasushi Goto
- Department of Thoracic Oncology, National Cancer Center Hospital, 5-1-1 Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan
| | - Hidehito Horinouchi
- Department of Thoracic Oncology, National Cancer Center Hospital, 5-1-1 Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan
| | - Masaya Yotsukura
- Department of Thoracic Surgery, National Cancer Center Hospital, 5-1-1, Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan
| | - Yukihiro Yoshida
- Department of Thoracic Surgery, National Cancer Center Hospital, 5-1-1, Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan
| | - Kazuo Nakagawa
- Department of Thoracic Surgery, National Cancer Center Hospital, 5-1-1, Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan
| | - Katsuhiko Naoki
- Department of Respiratory Medicine, Kitasato University School of Medicine, 1-15-1, Kitasato, Minami-ku, Sagamihara city, Kanagawa, 252-0375, Japan
| | - Takaaki Tsuchida
- Department of Endoscopy, Respiratory Endoscopy Division, National Cancer Center Hospital, Tokyo, 104-0045, Japan
| | - Ryuji Hamamoto
- Division of Medical AI Research and Development, National Cancer Center Research Institute, Tokyo, 104-0045, Japan
| | - Noboru Yamamoto
- Department of Thoracic Oncology, National Cancer Center Hospital, 5-1-1 Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan
- Division of Molecular Pharmacology, National Cancer Center Research Institute, 5-1-1, Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan
| | - Noriko Motoi
- Division of Genome Biology, National Cancer Center Research Institute, 5-1-1, Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan
- Department of Diagnostic Pathology, National Cancer Center Hospital, 5-1-1, Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan
- Department of Pathology, Saitama Cancer Center, Saitama, 362-0806, Japan
| | - Takashi Kohno
- Division of Genome Biology, National Cancer Center Research Institute, 5-1-1, Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan
| | - Shun-Ichi Watanabe
- Department of Thoracic Surgery, National Cancer Center Hospital, 5-1-1, Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan
| | - Yuichiro Ohe
- Department of Thoracic Oncology, National Cancer Center Hospital, 5-1-1 Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan
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25
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Nilsson JB, Kaabinejadian S, Yari H, Kester MG, van Balen P, Hildebrand WH, Nielsen M. Accurate prediction of HLA class II antigen presentation across all loci using tailored data acquisition and refined machine learning. SCIENCE ADVANCES 2023; 9:eadj6367. [PMID: 38000035 PMCID: PMC10672173 DOI: 10.1126/sciadv.adj6367] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Accepted: 10/25/2023] [Indexed: 11/26/2023]
Abstract
Accurate prediction of antigen presentation by human leukocyte antigen (HLA) class II molecules is crucial for rational development of immunotherapies and vaccines targeting CD4+ T cell activation. So far, most prediction methods for HLA class II antigen presentation have focused on HLA-DR because of limited availability of immunopeptidomics data for HLA-DQ and HLA-DP while not taking into account alternative peptide binding modes. We present an update to the NetMHCIIpan prediction method, which closes the performance gap between all three HLA class II loci. We accomplish this by first integrating large immunopeptidomics datasets describing the HLA class II specificity space across all loci using a refined machine learning framework that accommodates inverted peptide binders. Next, we apply targeted immunopeptidomics assays to generate data that covers additional HLA-DP specificities. The final method, NetMHCIIpan-4.3, achieves high accuracy and molecular coverage across all HLA class II allotypes.
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Affiliation(s)
- Jonas B. Nilsson
- Department of Health Technology, Technical University of Denmark, DK-2800 Lyngby, Denmark
| | - Saghar Kaabinejadian
- Pure MHC LLC, Oklahoma City, OK, USA
- Department of Microbiology and Immunology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Hooman Yari
- Department of Microbiology and Immunology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Michel G. D. Kester
- Department of Hematology, Leiden University Medical Center, Leiden, Netherlands
| | - Peter van Balen
- Department of Hematology, Leiden University Medical Center, Leiden, Netherlands
| | - William H. Hildebrand
- Department of Microbiology and Immunology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Morten Nielsen
- Department of Health Technology, Technical University of Denmark, DK-2800 Lyngby, Denmark
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26
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Wu M, Zhou S. Harnessing tumor immunogenomics: Tumor neoantigens in ovarian cancer and beyond. Biochim Biophys Acta Rev Cancer 2023; 1878:189017. [PMID: 37935309 DOI: 10.1016/j.bbcan.2023.189017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2023] [Revised: 10/30/2023] [Accepted: 11/01/2023] [Indexed: 11/09/2023]
Abstract
Ovarian cancer is a major cause of death among gynecological cancers due to its highly aggressive nature. Immunotherapy has emerged as a promising avenue for ovarian cancer treatment, offering targeted approaches with reduced off-target effects. With the advent of next-generation sequencing, it has become possible to identify genomic alterations that can serve as potential targets for immunotherapy. Furthermore, immunogenomics research has revealed the importance of genetic alterations in shaping the cancer immune responses. However, the heterogeneity of immunogenicity and the low tumor mutation burden pose challenges for neoantigen-based immunotherapies. Further research is needed to identify neoantigen-specific tumor-infiltrating lymphocytes (TIL) and establish guidelines for patient inclusion criteria in TIL-based therapy. The study of neoantigens and their implications in ovarian cancer immunotherapy holds great promise, and efforts focused on personalized treatment strategies, refined neoantigen selection, and optimized therapeutic combinations will contribute to improving patient outcomes in the future.
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Affiliation(s)
- Mengrui Wu
- Department of Obstetrics and Gynecology, Key Laboratory of Birth Defects and Related Diseases of Women and Children of MOE, State Key Laboratory of Biotherapy, West China Second Hospital, Sichuan University and Collaborative Innovation Center, Chengdu, PR China
| | - Shengtao Zhou
- Department of Obstetrics and Gynecology, Key Laboratory of Birth Defects and Related Diseases of Women and Children of MOE, State Key Laboratory of Biotherapy, West China Second Hospital, Sichuan University and Collaborative Innovation Center, Chengdu, PR China.
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27
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Nelde A, Schuster H, Heitmann JS, Bauer J, Maringer Y, Zwick M, Volkmer JP, Chen JY, Stanger AMP, Lehmann A, Appiah B, Märklin M, Rücker-Braun E, Salih HR, Roerden M, Schroeder SM, Häring MF, Schlosser A, Schetelig J, Schmitz M, Boerries M, Köhler N, Lengerke C, Majeti R, Weissman IL, Rammensee HG, Walz JS. Immune Surveillance of Acute Myeloid Leukemia Is Mediated by HLA-Presented Antigens on Leukemia Progenitor Cells. Blood Cancer Discov 2023; 4:468-489. [PMID: 37847741 PMCID: PMC10618727 DOI: 10.1158/2643-3230.bcd-23-0020] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Revised: 06/13/2023] [Accepted: 09/28/2023] [Indexed: 10/19/2023] Open
Abstract
Therapy-resistant leukemia stem and progenitor cells (LSC) are a main cause of acute myeloid leukemia (AML) relapse. LSC-targeting therapies may thus improve outcome of patients with AML. Here we demonstrate that LSCs present HLA-restricted antigens that induce T-cell responses allowing for immune surveillance of AML. Using a mass spectrometry-based immunopeptidomics approach, we characterized the antigenic landscape of patient LSCs and identified AML- and AML/LSC-associated HLA-presented antigens absent from normal tissues comprising nonmutated peptides, cryptic neoepitopes, and neoepitopes of common AML driver mutations of NPM1 and IDH2. Functional relevance of shared AML/LSC antigens is illustrated by presence of their cognizant memory T cells in patients. Antigen-specific T-cell recognition and HLA class II immunopeptidome diversity correlated with clinical outcome. Together, these antigens shared among AML and LSCs represent prime targets for T cell-based therapies with potential of eliminating residual LSCs in patients with AML. SIGNIFICANCE The elimination of therapy-resistant leukemia stem and progenitor cells (LSC) remains a major challenge in the treatment of AML. This study identifies and functionally validates LSC-associated HLA class I and HLA class II-presented antigens, paving the way to the development of LSC-directed T cell-based immunotherapeutic approaches for patients with AML. See related commentary by Ritz, p. 430 . This article is featured in Selected Articles from This Issue, p. 419.
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Affiliation(s)
- Annika Nelde
- Department of Peptide-Based Immunotherapy, University and University Hospital Tübingen, Tübingen, Germany
- Institute for Cell Biology, Department of Immunology, University of Tübingen, Tübingen, Germany
- Cluster of Excellence iFIT (EXC2180) “Image-Guided and Functionally Instructed Tumor Therapies”, University of Tübingen, Tübingen, Germany
| | - Heiko Schuster
- Institute for Cell Biology, Department of Immunology, University of Tübingen, Tübingen, Germany
| | - Jonas S. Heitmann
- Cluster of Excellence iFIT (EXC2180) “Image-Guided and Functionally Instructed Tumor Therapies”, University of Tübingen, Tübingen, Germany
- Clinical Collaboration Unit Translational Immunology, German Cancer Consortium (DKTK), Department of Internal Medicine, University Hospital Tübingen, Tübingen, Germany
| | - Jens Bauer
- Department of Peptide-Based Immunotherapy, University and University Hospital Tübingen, Tübingen, Germany
- Institute for Cell Biology, Department of Immunology, University of Tübingen, Tübingen, Germany
- Cluster of Excellence iFIT (EXC2180) “Image-Guided and Functionally Instructed Tumor Therapies”, University of Tübingen, Tübingen, Germany
| | - Yacine Maringer
- Department of Peptide-Based Immunotherapy, University and University Hospital Tübingen, Tübingen, Germany
- Institute for Cell Biology, Department of Immunology, University of Tübingen, Tübingen, Germany
- Cluster of Excellence iFIT (EXC2180) “Image-Guided and Functionally Instructed Tumor Therapies”, University of Tübingen, Tübingen, Germany
| | - Melissa Zwick
- Department of Medicine I, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Jens-Peter Volkmer
- Institute for Stem Cell Biology and Regenerative Medicine and the Ludwig Cancer Center, Stanford University School of Medicine, Stanford, California
| | - James Y. Chen
- Institute for Stem Cell Biology and Regenerative Medicine and the Ludwig Cancer Center, Stanford University School of Medicine, Stanford, California
| | - Anna M. Paczulla Stanger
- Department of Hematology, Oncology, Clinical Immunology and Rheumatology, University Hospital Tübingen, Tübingen, Germany
- Department of Biomedicine, University of Basel and University Hospital Basel, Basel, Switzerland
| | - Ariane Lehmann
- Faculty of Medicine, Medical Center, Institute of Medical Bioinformatics and Systems Medicine (IBSM), University of Freiburg, Germany
| | - Bismark Appiah
- Faculty of Medicine, Medical Center, Institute of Medical Bioinformatics and Systems Medicine (IBSM), University of Freiburg, Germany
| | - Melanie Märklin
- Cluster of Excellence iFIT (EXC2180) “Image-Guided and Functionally Instructed Tumor Therapies”, University of Tübingen, Tübingen, Germany
- Clinical Collaboration Unit Translational Immunology, German Cancer Consortium (DKTK), Department of Internal Medicine, University Hospital Tübingen, Tübingen, Germany
| | - Elke Rücker-Braun
- Department of Medicine I, University Hospital of Dresden, Dresden, Germany
- Center for Regenerative Therapies Dresden, Technische Universität Dresden, Dresden, Germany
| | - Helmut R. Salih
- Cluster of Excellence iFIT (EXC2180) “Image-Guided and Functionally Instructed Tumor Therapies”, University of Tübingen, Tübingen, Germany
- Clinical Collaboration Unit Translational Immunology, German Cancer Consortium (DKTK), Department of Internal Medicine, University Hospital Tübingen, Tübingen, Germany
| | - Malte Roerden
- Department of Peptide-Based Immunotherapy, University and University Hospital Tübingen, Tübingen, Germany
- Institute for Cell Biology, Department of Immunology, University of Tübingen, Tübingen, Germany
- Department of Hematology, Oncology, Clinical Immunology and Rheumatology, University Hospital Tübingen, Tübingen, Germany
| | - Sarah M. Schroeder
- Department of Peptide-Based Immunotherapy, University and University Hospital Tübingen, Tübingen, Germany
- Institute for Cell Biology, Department of Immunology, University of Tübingen, Tübingen, Germany
- Department of Otorhinolaryngology, Head and Neck Surgery, University of Tübingen, Tübingen, Germany
| | - Max-Felix Häring
- Department of Peptide-Based Immunotherapy, University and University Hospital Tübingen, Tübingen, Germany
- Institute for Cell Biology, Department of Immunology, University of Tübingen, Tübingen, Germany
- Department of Hematology, Oncology, Clinical Immunology and Rheumatology, University Hospital Tübingen, Tübingen, Germany
| | | | - Johannes Schetelig
- Department of Medicine I, University Hospital of Dresden, Dresden, Germany
- German Bone Marrow Donor Center (DKMS), Clinical Trials Unit, Dresden, Germany
| | - Marc Schmitz
- Institute of Immunology, Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
- National Center for Tumor Diseases (NCT), University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
- German Cancer Consortium (DKTK), partner site Dresden, and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Melanie Boerries
- Faculty of Medicine, Medical Center, Institute of Medical Bioinformatics and Systems Medicine (IBSM), University of Freiburg, Germany
- Comprehensive Cancer Center Freiburg (CCCF), Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany
- German Cancer Consortium (DKTK), Partner Site, Freiburg, and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Natalie Köhler
- Department of Medicine I, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany
- Centre for Integrative Biological Signalling Studies (CIBSS), University of Freiburg, Freiburg, Germany
| | - Claudia Lengerke
- Department of Hematology, Oncology, Clinical Immunology and Rheumatology, University Hospital Tübingen, Tübingen, Germany
- Department of Biomedicine, University of Basel and University Hospital Basel, Basel, Switzerland
- Clinic for Hematology, University of Basel and University Hospital Basel, Basel, Switzerland
- German Cancer Consortium (DKTK), DKFZ partner site Tübingen, Germany
| | - Ravindra Majeti
- Institute for Stem Cell Biology and Regenerative Medicine and the Ludwig Cancer Center, Stanford University School of Medicine, Stanford, California
- Division of Hematology, Department of Medicine, Stanford University School of Medicine, Stanford, California
| | - Irving L. Weissman
- Institute for Stem Cell Biology and Regenerative Medicine and the Ludwig Cancer Center, Stanford University School of Medicine, Stanford, California
| | - Hans-Georg Rammensee
- Institute for Cell Biology, Department of Immunology, University of Tübingen, Tübingen, Germany
- Cluster of Excellence iFIT (EXC2180) “Image-Guided and Functionally Instructed Tumor Therapies”, University of Tübingen, Tübingen, Germany
- German Cancer Consortium (DKTK), DKFZ partner site Tübingen, Germany
| | - Juliane S. Walz
- Department of Peptide-Based Immunotherapy, University and University Hospital Tübingen, Tübingen, Germany
- Institute for Cell Biology, Department of Immunology, University of Tübingen, Tübingen, Germany
- Cluster of Excellence iFIT (EXC2180) “Image-Guided and Functionally Instructed Tumor Therapies”, University of Tübingen, Tübingen, Germany
- Clinical Collaboration Unit Translational Immunology, German Cancer Consortium (DKTK), Department of Internal Medicine, University Hospital Tübingen, Tübingen, Germany
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Lv Z, Ji F, Song J, Li P, Chen M, Chang J. Predicting the spatial structure of membrane protein and B-cell epitopes of the MPXV_VEROE6 strain of monkeypox virus. Heliyon 2023; 9:e20386. [PMID: 37767496 PMCID: PMC10520823 DOI: 10.1016/j.heliyon.2023.e20386] [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] [Received: 10/25/2022] [Revised: 08/31/2023] [Accepted: 09/20/2023] [Indexed: 09/29/2023] Open
Abstract
By targeting the membrane (M) proteins of monkeypox virus (MPXV) strain VEROE6, we analyzed its evolutionary hierarchy and predicted its dominant antigenic B-cell epitope to provide a theoretical basis for the development of MPXV epitope vaccines and related monoclonal antibodies. In this study, phylogenetic trees were constructed based on the nucleic acid sequences of MPXV and the amino acid sequences of M proteins. The 3D structure of the MPXV_VEROE6 M proteins was predicted with AlphaFold v2.0 and the dominant antigenic B-cell epitopes were comprehensively predicted by analyzing parameters such as flexible segments, the hydrophilic index, the antigenic index, and the protein surface probability. The results showed that the M protein of MPXV_VEROE6 contained 377 amino acids, and their spatial configuration was relatively regular with a turning and random coil structure. The results of a comprehensive multiparameter analysis indicated that possible B-cell epitopes were located in the 23-28, 57-63, 67-78, 80-93, 98-105, 125-131, 143-149, 201-206, 231-237, 261-270, 291-303, and 346-362 amino acid segments. This study elucidated the structural and evolutionary characteristics of MPXV membrane proteins with the aim of providing theoretical information for the development of epitope vaccines, rapid diagnostic reagents, and monoclonal antibodies for monkeypox virus.
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Affiliation(s)
- Zhiyuan Lv
- The Xinjiang Key Laboratory of Natural Medicine Active Components and Drug Release Technology, College of Pharmacy, Xinjiang Medical University, Urumqi Xinjiang 830011, China
| | - Feng Ji
- Zhongda Hospital, Medical School, Southeast University, Nanjing 210009, China
| | - Jianzhong Song
- The Xinjiang Key Laboratory of Natural Medicine Active Components and Drug Release Technology, College of Pharmacy, Xinjiang Medical University, Urumqi Xinjiang 830011, China
- Department of Pharmacy, Affiliated Tumor Hospital of Xinjiang Medical University, Urumqi 830011,China
| | - Panpan Li
- The Xinjiang Key Laboratory of Natural Medicine Active Components and Drug Release Technology, College of Pharmacy, Xinjiang Medical University, Urumqi Xinjiang 830011, China
| | - Ming Chen
- Zhongda Hospital, Medical School, Southeast University, Nanjing 210009, China
| | - Junmin Chang
- The Xinjiang Key Laboratory of Natural Medicine Active Components and Drug Release Technology, College of Pharmacy, Xinjiang Medical University, Urumqi Xinjiang 830011, China
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29
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Pu T, Peddle A, Zhu J, Tejpar S, Verbandt S. Neoantigen identification: Technological advances and challenges. Methods Cell Biol 2023; 183:265-302. [PMID: 38548414 DOI: 10.1016/bs.mcb.2023.06.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/02/2024]
Abstract
Neoantigens have emerged as promising targets for cutting-edge immunotherapies, such as cancer vaccines and adoptive cell therapy. These neoantigens are unique to tumors and arise exclusively from somatic mutations or non-genomic aberrations in tumor proteins. They encompass a wide range of alterations, including genomic mutations, post-transcriptomic variants, and viral oncoproteins. With the advancements in technology, the identification of immunogenic neoantigens has seen rapid progress, raising new opportunities for enhancing their clinical significance. Prediction of neoantigens necessitates the acquisition of high-quality samples and sequencing data, followed by mutation calling. Subsequently, the pipeline involves integrating various tools that can predict the expression, processing, binding, and recognition potential of neoantigens. However, the continuous improvement of computational tools is constrained by the availability of datasets which contain validated immunogenic neoantigens. This review article aims to provide a comprehensive summary of the current knowledge as well as limitations in neoantigen prediction and validation. Additionally, it delves into the origin and biological role of neoantigens, offering a deeper understanding of their significance in the field of cancer immunotherapy. This article thus seeks to contribute to the ongoing efforts to harness neoantigens as powerful weapons in the fight against cancer.
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Affiliation(s)
- Ting Pu
- Digestive Oncology Unit, KULeuven, Leuven, Belgium
| | | | - Jingjing Zhu
- de Duve Institute, Université catholique de Louvain, Brussels, Belgium
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30
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Balz K, Kaushik A, Cemic F, Sampath V, Heger V, Renz H, Nadeau K, Skevaki C. Cross-reactive MHC class I T cell epitopes may dictate heterologous immune responses between respiratory viruses and food allergens. Sci Rep 2023; 13:14874. [PMID: 37684288 PMCID: PMC10491592 DOI: 10.1038/s41598-023-41187-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Accepted: 08/23/2023] [Indexed: 09/10/2023] Open
Abstract
Respiratory virus infections play a major role in asthma, while there is a close correlation between asthma and food allergy. We hypothesized that T cell-mediated heterologous immunity may induce asthma symptoms among sensitized individuals and used two independent in silico pipelines for the identification of cross-reactive virus- and food allergen- derived T cell epitopes, considering individual peptide sequence similarity, MHC binding affinity and immunogenicity. We assessed the proteomes of human rhinovirus (RV1b), respiratory syncytial virus (RSVA2) and influenza-strains contained in the seasonal quadrivalent influenza vaccine 2019/2020 (QIV 2019/2020), as well as SARS-CoV-2 for human HLA alleles, in addition to more than 200 most common food allergen protein sequences. All resulting allergen-derived peptide candidates were subjected to an elaborate scoring system considering multiple criteria, including clinical relevance. In both bioinformatics approaches, we found that shortlisted peptide pairs that are potentially binding to MHC class II molecules scored up to 10 × lower compared to MHC class I candidate epitopes. For MHC class I food allergen epitopes, several potentially cross-reactive peptides from shrimp, kiwi, apple, soybean and chicken were identified. The shortlisted set of peptide pairs may be implicated in heterologous immune responses and translated to peptide immunization strategies with immunomodulatory properties.
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Affiliation(s)
- Kathrin Balz
- Institute of Laboratory Medicine, Universities of Giessen and Marburg Lung Center (UGMLC), Philipps University Marburg, German Center for Lung Research (DZL), 35043, Marburg, Germany
| | - Abhinav Kaushik
- Division of Pulmonary, Allergy and Critical Care Medicine, Sean N. Parker Center for Allergy and Asthma Research at Stanford University, Stanford, CA, 94040, USA
- Departmental of Environmental Health, Harvard T. H. Chan School of Public Health, Boston, MA, 02115, USA
| | - Franz Cemic
- Department of Computer Science, TH Mittelhessen, University of Applied Sciences Gießen, 35390, Giessen, Germany
| | - Vanitha Sampath
- Division of Pulmonary, Allergy and Critical Care Medicine, Sean N. Parker Center for Allergy and Asthma Research at Stanford University, Stanford, CA, 94040, USA
| | - Vanessa Heger
- Department of Computer Science, TH Mittelhessen, University of Applied Sciences Gießen, 35390, Giessen, Germany
| | - Harald Renz
- Institute of Laboratory Medicine, Universities of Giessen and Marburg Lung Center (UGMLC), Philipps University Marburg, German Center for Lung Research (DZL), 35043, Marburg, Germany
| | - Kari Nadeau
- Departmental of Environmental Health, Harvard T. H. Chan School of Public Health, Boston, MA, 02115, USA
| | - Chrysanthi Skevaki
- Institute of Laboratory Medicine, Universities of Giessen and Marburg Lung Center (UGMLC), Philipps University Marburg, German Center for Lung Research (DZL), 35043, Marburg, Germany.
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31
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Srivastava S, Kolbe M. Novel "GaEl Antigenic Patches" Identified by a "Reverse Epitomics" Approach to Design Multipatch Vaccines against NIPAH Infection, a Silent Threat to Global Human Health. ACS OMEGA 2023; 8:31698-31713. [PMID: 37692250 PMCID: PMC10483669 DOI: 10.1021/acsomega.3c01909] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Accepted: 08/01/2023] [Indexed: 09/12/2023]
Abstract
Nipah virus (NiV) is a zoonotic virus that causes lethal encephalitis and respiratory disease with the symptom of endothelial cell-cell fusion. Several NiV outbreaks have been reported since 1999 with nearly annual occurrences in Bangladesh. The outbreaks had high mortality rates ranging from 40 to 90%. No specific vaccine has yet been reported against NiV. Recently, several vaccine candidates and different designs of vaccines composed of epitopes against NiV were proposed. Most of the vaccines target single protein or protein complex subunits of the pathogen. The multiepitope vaccines proposed also cover a largely limited number of epitopes, and hence, their efficiency is still uncertain. To address the urgent need for a specific and effective vaccine against NiV infection, in the present study, we have utilized the "reverse epitomics" approach ("overlapping-epitope-clusters-to-patches" method) to identify "antigenic patches" (Ag-Patches) and utilize them as immunogenic composition for multipatch vaccine (MPV) design. The designed MPVs were analyzed for immunologically crucial parameters, physiochemical properties, and interaction with Toll-like receptor 3 ectodomain. In total, 30 CTL (cytotoxic T lymphocyte) and 27 HTL (helper T lymphocyte) antigenic patches were identified from the entire NiV proteome based on the clusters of overlapping epitopes. These identified Ag-Patches cover a total of discrete 362 CTL and 414 HTL epitopes from the entire proteome of NiV. The antigenic patches were utilized as immunogenic composition for the design of two CTL and two HTL multipatch vaccines. The 57 antigenic patches utilized here cover 776 overlapping epitopes targeting 52 different HLA class I and II alleles, providing a global ethnically distributed human population coverage of 99.71%. Such large number of epitope coverage resulting in large human population coverage cannot be reached with single-protein/subunit or multiepitope based vaccines. The reported antigenic patches also provide potential immunogenic composition for early detection diagnostic kits for NiV infection. Further, all the MPVs and Toll-like receptor ectodomain complexes show a stable nature of molecular interaction with numerous hydrogen bonds, salt bridges, and nonbounded contact formation and acceptable root mean square deviation and fluctuation. The cDNA analysis shows a favorable large-scale expression of the MPV constructs in a human cell line. By utilizing the novel "reverse epitomics" approach, highly immunogenic novel "GaEl antigenic patches" (GaEl Ag-Patches), a synonym term for "antigenic patches", were identified and utilized as immunogenic composition to design four MPVs against NiV. We conclude that the novel multipatch vaccines are potential candidates to combat NiV, with greater effectiveness, high specificity, and large human population coverage worldwide.
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Affiliation(s)
- Sukrit Srivastava
- Infection
Biology Group, Indian Foundation for Fundamental
Research Trust, Raebareli, Uttar Pradesh 229316, India
- Department
for Structural Infection Biology, Centre
for Structural Systems Biology (CSSB) & Helmholtz-Centre for Infection
Research, Notkestraße 85, 22607 Hamburg, Germany
| | - Michael Kolbe
- Department
for Structural Infection Biology, Centre
for Structural Systems Biology (CSSB) & Helmholtz-Centre for Infection
Research, Notkestraße 85, 22607 Hamburg, Germany
- Faculty
of Mathematics, Informatics and Natural Sciences, University of Hamburg, Rothenbaumchaussee 19, 20148 Hamburg, Germany
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32
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Saravanakumar S, Chatterjee J. The Use of In Silico Methods to Identify and Assess Antigenic Regions Suitable for the Development of Peptide-based Pan-viral Vaccines. Altern Lab Anim 2023; 51:313-322. [PMID: 37548284 DOI: 10.1177/02611929231193416] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
The constant evolution of pathogenic viral variants and the emergence of new viruses have reinforced the need for broad-spectrum vaccines to combat such threats. The spread of new viral variants leading to epidemic and pandemic infection can be effectively contained, if broad-spectrum vaccines effective against the newer viral variants are readily available. The development of broad-spectrum, pan-neutralising antibodies against viruses which, in general terms, are very antigenically different - such as HIV, influenza virus and paramyxoviruses - has been reported in the literature. The amino acid sequences used to generate a range of approved recombinant anti-viral vaccines were analysed by using in silico methods, with the aim of identifying highly antigenic peptide regions that may be suitable for the development of broad-spectrum peptide-based anti-viral vaccines. This was achieved through the use of open-source data, an algorithm-driven probability matrix, and published in silico prediction tools (SVMTriP, IEDB-AR, VaxiJen 2.0, AllergenFP v. 1.0, AllerTOP v. 2.0, ToxinPred and ProtParam) to evaluate antigenicity, MHC-I and MHC-II binding potential, immunogenicity, allergenicity, toxicity and physicochemical properties. We report a pan-antigenic peptide region with strong affinity for MHC-I and MHC-II, and good immunogenic potential. According to the output from the relevant in silico tools, the peptide was predicted to be non-toxic, non-allergic and to possess the desired physicochemical properties for potentially successful vaccine production. With further investigation and optimisation, this peptide could be considered for use in the development of a broad-spectrum anti-viral vaccine that may protect against emerging new viruses. Our approach of using in silico methods to identify candidate antigenic peptides with the desired physicochemical properties could potentially circumvent the use of some animal studies for peptide vaccine candidate evaluation.
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Bodas-Pinedo A, Lafuente EM, Pelaez-Prestel HF, Ras-Carmona A, Subiza JL, Reche PA. Combining different bacteria in vaccine formulations enhances the chance for antiviral cross-reactive immunity: a detailed in silico analysis for influenza A virus. Front Immunol 2023; 14:1235053. [PMID: 37675108 PMCID: PMC10477994 DOI: 10.3389/fimmu.2023.1235053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Accepted: 08/02/2023] [Indexed: 09/08/2023] Open
Abstract
Bacteria are well known to provide heterologous immunity against viral infections through various mechanisms including the induction of innate trained immunity and adaptive cross-reactive immunity. Cross-reactive immunity from bacteria to viruses is responsible for long-term protection and yet its role has been downplayed due the difficulty of determining antigen-specific responses. Here, we carried out a systematic evaluation of the potential cross-reactive immunity from selected bacteria known to induce heterologous immunity against various viruses causing recurrent respiratory infections. The bacteria selected in this work were Bacillus Calmette Guerin and those included in the poly-bacterial preparation MV130: Streptococcus pneumoniae, Staphylococcus aureus, Staphylococcus epidermidis, Klebisella pneumoniae, Branhamella catarrhalis and Haemophilus influenzae. The virus included influenza A and B viruses, human rhinovirus A, B and C, respiratory syncytial virus A and B and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Through BLAST searches, we first identified the shared peptidome space (identity ≥ 80%, in at least 8 residues) between bacteria and viruses, and subsequently predicted T and B cell epitopes within shared peptides. Interestingly, the potential epitope spaces shared between bacteria in MV130 and viruses are non-overlapping. Hence, combining diverse bacteria can enhance cross-reactive immunity. We next analyzed in detail the cross-reactive T and B cell epitopes between MV130 and influenza A virus. We found that MV130 contains numerous cross-reactive T cell epitopes with high population protection coverage and potentially neutralizing B cell epitopes recognizing hemagglutinin and matrix protein 2. These results contribute to explain the immune enhancing properties of MV130 observed in the clinic against respiratory viral infections.
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Affiliation(s)
- Andrés Bodas-Pinedo
- Children’s Digestive Unit, Institute for Children and Adolescents, Hospital Clinico San Carlos, Madrid, Spain
| | - Esther M. Lafuente
- Department of Immunology & O2, Faculty of Medicine, University Complutense of Madrid, Ciudad Universitaria, Pza. Ramón y Cajal, Madrid, Spain
| | - Hector F. Pelaez-Prestel
- Department of Immunology & O2, Faculty of Medicine, University Complutense of Madrid, Ciudad Universitaria, Pza. Ramón y Cajal, Madrid, Spain
| | - Alvaro Ras-Carmona
- Department of Immunology & O2, Faculty of Medicine, University Complutense of Madrid, Ciudad Universitaria, Pza. Ramón y Cajal, Madrid, Spain
| | | | - Pedro A. Reche
- Department of Immunology & O2, Faculty of Medicine, University Complutense of Madrid, Ciudad Universitaria, Pza. Ramón y Cajal, Madrid, Spain
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34
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Albert BA, Yang Y, Shao XM, Singh D, Smit KN, Anagnostou V, Karchin R. Deep neural networks predict class I major histocompatibility complex epitope presentation and transfer learn neoepitope immunogenicity. NAT MACH INTELL 2023; 5:861-872. [PMID: 37829001 PMCID: PMC10569228 DOI: 10.1038/s42256-023-00694-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Accepted: 06/23/2023] [Indexed: 10/14/2023]
Abstract
Identifying neoepitopes that elicit an adaptive immune response is a major bottleneck to developing personalized cancer vaccines. Experimental validation of candidate neoepitopes is extremely resource intensive and the vast majority of candidates are non-immunogenic, creating a needle-in-a-haystack problem. Here we address this challenge, presenting computational methods for predicting class I major histocompatibility complex (MHC-I) epitopes and identifying immunogenic neoepitopes with improved precision. The BigMHC method comprises an ensemble of seven pan-allelic deep neural networks trained on peptide-MHC eluted ligand data from mass spectrometry assays and transfer learned on data from assays of antigen-specific immune response. Compared with four state-of-the-art classifiers, BigMHC significantly improves the prediction of epitope presentation on a test set of 45,409 MHC ligands among 900,592 random negatives (area under the receiver operating characteristic = 0.9733; area under the precision-recall curve = 0.8779). After transfer learning on immunogenicity data, BigMHC yields significantly higher precision than seven state-of-the-art models in identifying immunogenic neoepitopes, making BigMHC effective in clinical settings.
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Affiliation(s)
- Benjamin Alexander Albert
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Yunxiao Yang
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Xiaoshan M. Shao
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Dipika Singh
- The Sidney Kimmel Comprehensive Cancer Center, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
- Bloomberg~Kimmel Institute for Cancer Immunotherapy, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Kellie N. Smit
- The Sidney Kimmel Comprehensive Cancer Center, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
- Bloomberg~Kimmel Institute for Cancer Immunotherapy, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Valsamo Anagnostou
- The Sidney Kimmel Comprehensive Cancer Center, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
- Bloomberg~Kimmel Institute for Cancer Immunotherapy, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Rachel Karchin
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
- The Sidney Kimmel Comprehensive Cancer Center, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
- Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD, USA
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35
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Brito Baleeiro R, Liu P, Chard Dunmall LS, Di Gioia C, Nagano A, Cutmore L, Wang J, Chelala C, Nyambura LW, Walden P, Lemoine N, Wang Y. Personalized neoantigen viro-immunotherapy platform for triple-negative breast cancer. J Immunother Cancer 2023; 11:e007336. [PMID: 37586771 PMCID: PMC10432671 DOI: 10.1136/jitc-2023-007336] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/21/2023] [Indexed: 08/18/2023] Open
Abstract
BACKGROUND Triple-negative breast cancer (TNBC) corresponds to approximately 20% of all breast tumors, with a high propensity for metastasis and a poor prognosis. Because TNBC displays a high mutational load compared with other breast cancer types, a neoantigen-based immunotherapy strategy could be effective. One major bottleneck in the development of a neoantigen-based vaccine for TNBC is the selection of the best targets, that is, tumor-specific neoantigens which are presented at the surface of tumor cells and capable of eliciting robust immune responses. In this study, we aimed to set up a platform for identification and delivery of immunogenic neoantigens in a vaccine regimen for TNBC using oncolytic vaccinia virus (VV). METHODS We used bioinformatic tools and cell-based assays to identify immunogenic neoantigens in TNBC patients' samples, human and murine cell lines. Immunogenicity of the neoantigens was tested in vitro (human) and ex vivo (murine) in T-cell assays. To assess the efficacy of our regimen, we used a preclinical model of TNBC where we treated tumor-bearing mice with neoantigens together with oncolytic VV and evaluated the effect on induction of neoantigen-specific CD8+T cells, tumor growth and survival. RESULTS We successfully identified immunogenic neoantigens and generated neoantigen-specific CD8+T cells capable of recognizing a human TNBC cell line expressing the mutated gene. Using a preclinical model of TNBC, we showed that our tumor-specific oncolytic VV was able to change the tumor microenvironment, attracting and maintaining mature cross-presenting CD8α+dendritic cells and effector T-cells. Moreover, when delivered in a prime/boost regimen together with oncolytic VV, long peptides encompassing neoantigens were able to induce neoantigen-specific CD8+T cells, slow tumor growth and increase survival. CONCLUSIONS Our study provides a promising approach for the development of neoantigen-based immunotherapies for TNBC. By identifying immunogenic neoantigens and developing a delivery system through tumor-specific oncolytic VV, we have demonstrated that neoantigen-based vaccines could be effective in inducing neoantigen-specific CD8+T cells response with significant impact on tumor growth. Further studies are needed to determine the safety and efficacy of this approach in clinical trials.
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Affiliation(s)
- Renato Brito Baleeiro
- Centre for Cancer Biomarkers and Biotherapeutics, Queen Mary University of London, London, UK
| | - Peng Liu
- Centre for Cancer Biomarkers and Biotherapeutics, Queen Mary University of London, London, UK
| | - Louisa S Chard Dunmall
- Centre for Cancer Biomarkers and Biotherapeutics, Queen Mary University of London, London, UK
| | - Carmela Di Gioia
- Centre for Cancer Biomarkers and Biotherapeutics, Queen Mary University of London, London, UK
| | - Ai Nagano
- Centre for Cancer Biomarkers and Biotherapeutics, Queen Mary University of London, London, UK
| | - Lauren Cutmore
- Centre for Cancer Biomarkers and Biotherapeutics, Queen Mary University of London, London, UK
| | - Jun Wang
- Centre for Cancer Biomarkers and Biotherapeutics, Queen Mary University of London, London, UK
| | - Claude Chelala
- Centre for Cancer Biomarkers and Biotherapeutics, Queen Mary University of London, London, UK
| | - Lydon Wainaina Nyambura
- Department of Dermatology, Venerology and Allergology, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Peter Walden
- Department of Dermatology, Venerology and Allergology, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Nicholas Lemoine
- Centre for Cancer Biomarkers and Biotherapeutics, Queen Mary University of London, London, UK
- Zhengzhou University, Zhengzhou, Henan, China
| | - Yaohe Wang
- Centre for Cancer Biomarkers and Biotherapeutics, Queen Mary University of London, London, UK
- Zhengzhou University, Zhengzhou, Henan, China
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36
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Medici G, Freudenmann LK, Velz J, Wang SSY, Kapolou K, Paramasivam N, Mühlenbruch L, Kowalewski DJ, Vasella F, Bilich T, Frey BM, Dubbelaar ML, Patterson AB, Zeitlberger AM, Silginer M, Roth P, Weiss T, Wirsching HG, Krayenbühl N, Bozinov O, Regli L, Rammensee HG, Rushing EJ, Sahm F, Walz JS, Weller M, Neidert MC. A T-cell antigen atlas for meningioma: novel options for immunotherapy. Acta Neuropathol 2023; 146:173-190. [PMID: 37368072 PMCID: PMC10329067 DOI: 10.1007/s00401-023-02605-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Revised: 06/16/2023] [Accepted: 06/17/2023] [Indexed: 06/28/2023]
Abstract
Meningiomas are the most common primary intracranial tumors. Although most symptomatic cases can be managed by surgery and/or radiotherapy, a relevant number of patients experience an unfavorable clinical course and additional treatment options are needed. As meningiomas are often perfused by dural branches of the external carotid artery, which is located outside the blood-brain barrier, they might be an accessible target for immunotherapy. However, the landscape of naturally presented tumor antigens in meningioma is unknown. We here provide a T-cell antigen atlas for meningioma by in-depth profiling of the naturally presented immunopeptidome using LC-MS/MS. Candidate target antigens were selected based on a comparative approach using an extensive immunopeptidome data set of normal tissues. Meningioma-exclusive antigens for HLA class I and II are described here for the first time. Top-ranking targets were further functionally characterized by showing their immunogenicity through in vitro T-cell priming assays. Thus, we provide an atlas of meningioma T-cell antigens which will be publicly available for further research. In addition, we have identified novel actionable targets that warrant further investigation as an immunotherapy option for meningioma.
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Affiliation(s)
- Gioele Medici
- Laboratory of Molecular Neuro-Oncology, Department of Neurology, Clinical Neuroscience Center, University Hospital and University of Zurich, Frauenklinikstrasse 26, 8091, Zurich, Switzerland.
- Department of Neurosurgery, Clinical Neuroscience Center, University Hospital and University of Zurich, Frauenklinikstrasse 10, 8091, Zurich, Switzerland.
| | - Lena K Freudenmann
- Institute for Cell Biology, Department of Immunology, University of Tübingen, Tübingen, Germany
- DKFZ Partner Site Tübingen, German Cancer Consortium (DKTK), Tübingen, Germany
- Cluster of Excellence iFIT (EXC2180) "Image-Guided and Functionally Instructed Tumor Therapies", University of Tübingen, Tübingen, Germany
| | - Julia Velz
- Laboratory of Molecular Neuro-Oncology, Department of Neurology, Clinical Neuroscience Center, University Hospital and University of Zurich, Frauenklinikstrasse 26, 8091, Zurich, Switzerland
- Department of Neurosurgery, Clinical Neuroscience Center, University Hospital and University of Zurich, Frauenklinikstrasse 10, 8091, Zurich, Switzerland
| | - Sophie Shih-Yüng Wang
- Laboratory of Molecular Neuro-Oncology, Department of Neurology, Clinical Neuroscience Center, University Hospital and University of Zurich, Frauenklinikstrasse 26, 8091, Zurich, Switzerland
- Department of Neurosurgery and Neurotechnology, Eberhard Karls University Tübingen, Tübingen, Germany
| | - Konstantina Kapolou
- Laboratory of Molecular Neuro-Oncology, Department of Neurology, Clinical Neuroscience Center, University Hospital and University of Zurich, Frauenklinikstrasse 26, 8091, Zurich, Switzerland
- Roche Diagnostics International Ltd, Rotkreuz, Switzerland
| | - Nagarajan Paramasivam
- Computational Oncology Group, Molecular Precision Oncology Program, NCT Heidelberg and DKFZ, Heidelberg, Germany
| | - Lena Mühlenbruch
- Institute for Cell Biology, Department of Immunology, University of Tübingen, Tübingen, Germany
- Cluster of Excellence iFIT (EXC2180) "Image-Guided and Functionally Instructed Tumor Therapies", University of Tübingen, Tübingen, Germany
- Department of Peptide-Based Immunotherapy, University and University Hospital Tübingen, Tübingen, Germany
| | - Daniel J Kowalewski
- Institute for Cell Biology, Department of Immunology, University of Tübingen, Tübingen, Germany
- DKFZ Partner Site Tübingen, German Cancer Consortium (DKTK), Tübingen, Germany
| | - Flavio Vasella
- Laboratory of Molecular Neuro-Oncology, Department of Neurology, Clinical Neuroscience Center, University Hospital and University of Zurich, Frauenklinikstrasse 26, 8091, Zurich, Switzerland
- Department of Neurosurgery, Clinical Neuroscience Center, University Hospital and University of Zurich, Frauenklinikstrasse 10, 8091, Zurich, Switzerland
| | - Tatjana Bilich
- Institute for Cell Biology, Department of Immunology, University of Tübingen, Tübingen, Germany
- Cluster of Excellence iFIT (EXC2180) "Image-Guided and Functionally Instructed Tumor Therapies", University of Tübingen, Tübingen, Germany
- Clinical Collaboration Unit Translational Immunology, German Cancer Consortium (DKTK), Department of Internal Medicine, University Hospital Tübingen, Tübingen, Germany
- Institute for Immunity, Transplantation and Infection, Stanford University School of Medicine, Stanford, CA, USA
| | - Beat M Frey
- Blood Transfusion Service, Swiss Red Cross, Schlieren, Switzerland
| | - Marissa L Dubbelaar
- Institute for Cell Biology, Department of Immunology, University of Tübingen, Tübingen, Germany
- Cluster of Excellence iFIT (EXC2180) "Image-Guided and Functionally Instructed Tumor Therapies", University of Tübingen, Tübingen, Germany
- Department of Peptide-Based Immunotherapy, University and University Hospital Tübingen, Tübingen, Germany
- Quantitative Biology Center (QBiC), Eberhard Karls University Tübingen, 72076, Tübingen, Baden-Württemberg, Germany
| | | | - Anna Maria Zeitlberger
- Department of Neurosurgery, Cantonal Hospital St. Gallen, Rorschacher Strasse 95, 9007, St. Gallen, Switzerland
| | - Manuela Silginer
- Laboratory of Molecular Neuro-Oncology, Department of Neurology, Clinical Neuroscience Center, University Hospital and University of Zurich, Frauenklinikstrasse 26, 8091, Zurich, Switzerland
| | - Patrick Roth
- Laboratory of Molecular Neuro-Oncology, Department of Neurology, Clinical Neuroscience Center, University Hospital and University of Zurich, Frauenklinikstrasse 26, 8091, Zurich, Switzerland
| | - Tobias Weiss
- Laboratory of Molecular Neuro-Oncology, Department of Neurology, Clinical Neuroscience Center, University Hospital and University of Zurich, Frauenklinikstrasse 26, 8091, Zurich, Switzerland
| | - Hans-Georg Wirsching
- Laboratory of Molecular Neuro-Oncology, Department of Neurology, Clinical Neuroscience Center, University Hospital and University of Zurich, Frauenklinikstrasse 26, 8091, Zurich, Switzerland
| | - Niklaus Krayenbühl
- Department of Neurosurgery, Clinical Neuroscience Center, University Hospital and University of Zurich, Frauenklinikstrasse 10, 8091, Zurich, Switzerland
| | - Oliver Bozinov
- Department of Neurosurgery, Cantonal Hospital St. Gallen, Rorschacher Strasse 95, 9007, St. Gallen, Switzerland
| | - Luca Regli
- Department of Neurosurgery, Clinical Neuroscience Center, University Hospital and University of Zurich, Frauenklinikstrasse 10, 8091, Zurich, Switzerland
| | - Hans-Georg Rammensee
- Institute for Cell Biology, Department of Immunology, University of Tübingen, Tübingen, Germany
- DKFZ Partner Site Tübingen, German Cancer Consortium (DKTK), Tübingen, Germany
| | - Elisabeth Jane Rushing
- Department of Neuropathology, University Hospital and University of Zurich, Schmelzbergstrasse 12, 8091, Zurich, Switzerland
| | - Felix Sahm
- Department of Neuropathology, Heidelberg University Hospital, Heidelberg, Germany
- CCU Neuropathology, German Consortium for Translational Cancer Research (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Juliane S Walz
- Institute for Cell Biology, Department of Immunology, University of Tübingen, Tübingen, Germany
- Cluster of Excellence iFIT (EXC2180) "Image-Guided and Functionally Instructed Tumor Therapies", University of Tübingen, Tübingen, Germany
- Department of Peptide-Based Immunotherapy, University and University Hospital Tübingen, Tübingen, Germany
- Clinical Collaboration Unit Translational Immunology, German Cancer Consortium (DKTK), Department of Internal Medicine, University Hospital Tübingen, Tübingen, Germany
| | - Michael Weller
- Laboratory of Molecular Neuro-Oncology, Department of Neurology, Clinical Neuroscience Center, University Hospital and University of Zurich, Frauenklinikstrasse 26, 8091, Zurich, Switzerland
| | - Marian C Neidert
- Laboratory of Molecular Neuro-Oncology, Department of Neurology, Clinical Neuroscience Center, University Hospital and University of Zurich, Frauenklinikstrasse 26, 8091, Zurich, Switzerland
- Department of Neurosurgery, Clinical Neuroscience Center, University Hospital and University of Zurich, Frauenklinikstrasse 10, 8091, Zurich, Switzerland
- Department of Neurosurgery, Cantonal Hospital St. Gallen, Rorschacher Strasse 95, 9007, St. Gallen, Switzerland
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He J, Li J, Leung K. Dynamic structural analysis-based epitope prediction of Exendin-4 in aqueous solution. Phys Rev E 2023; 108:024403. [PMID: 37723773 DOI: 10.1103/physreve.108.024403] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Accepted: 07/22/2023] [Indexed: 09/20/2023]
Abstract
The study of epitopes has a broad range of applications in drug discovery, vaccine design, and immunotherapy. In this study, an epitope prediction method was developed based on the dynamic structure of protein antigens. Solvent accessible surface area, charge, and root mean square fluctuation were introduced as the key residue property parameters. The epitope prediction algorithm was established by constructing a three-parameter complex metrics of seven-peptide groups. The method was applied to predict the epitopes of Exendin-4, an effective antidiabetic drug. The epitopes of both the natural and C-terminal amidated forms of Exendin-4 were predicted and compared in their folded and intermediate states. In the folded state, the epitopes of natural Exendin-4 (His1-Phe6 and Asp9-Val19) were found to be nearly identical to the epitopes of C-terminal aminated Exendin-4 (His1-Thr7 and Asp9-Val19). In the intermediate state, however, the epitopes of natural Exendin-4 (His1-Gly4, Phe6 and Lys12-Arg20) covered fewer amino acids than the epitopes of C-terminal aminated Exendin-4 (His1-Gly4, Phe6, Asp9-Val19 and Trp25-Lys27). The comparison with the results from other prediction tools demonstrates the reliability of our predicted epitopes of Exendin-4.
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Affiliation(s)
- Jianfeng He
- School of Physics, Beijing Institute of Technology, Beijing 100081, People's Republic of China
| | - Jing Li
- Research and Development Center, Beijing Genetech Pharmaceutical Co., Ltd., Beijing 102200, People's Republic of China
| | - Kingsley Leung
- Uni-Bioscience Pharm Company Limited, Hong Kong, People's Republic of China
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Zhuang L, Ye Z, Li L, Yang L, Gong W. Next-Generation TB Vaccines: Progress, Challenges, and Prospects. Vaccines (Basel) 2023; 11:1304. [PMID: 37631874 PMCID: PMC10457792 DOI: 10.3390/vaccines11081304] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2023] [Revised: 07/28/2023] [Accepted: 07/28/2023] [Indexed: 08/27/2023] Open
Abstract
Tuberculosis (TB), caused by Mycobacterium tuberculosis (MTB), is a prevalent global infectious disease and a leading cause of mortality worldwide. Currently, the only available vaccine for TB prevention is Bacillus Calmette-Guérin (BCG). However, BCG demonstrates limited efficacy, particularly in adults. Efforts to develop effective TB vaccines have been ongoing for nearly a century. In this review, we have examined the current obstacles in TB vaccine research and emphasized the significance of understanding the interaction mechanism between MTB and hosts in order to provide new avenues for research and establish a solid foundation for the development of novel vaccines. We have also assessed various TB vaccine candidates, including inactivated vaccines, attenuated live vaccines, subunit vaccines, viral vector vaccines, DNA vaccines, and the emerging mRNA vaccines as well as virus-like particle (VLP)-based vaccines, which are currently in preclinical stages or clinical trials. Furthermore, we have discussed the challenges and opportunities associated with developing different types of TB vaccines and outlined future directions for TB vaccine research, aiming to expedite the development of effective vaccines. This comprehensive review offers a summary of the progress made in the field of novel TB vaccines.
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Affiliation(s)
- Li Zhuang
- Beijing Key Laboratory of New Techniques of Tuberculosis Diagnosis and Treatment, Senior Department of Tuberculosis, Eighth Medical Center of Chinese PLA General Hospital, Beijing 100091, China
- Hebei North University, Zhangjiakou 075000, China
| | - Zhaoyang Ye
- Hebei North University, Zhangjiakou 075000, China
| | - Linsheng Li
- Hebei North University, Zhangjiakou 075000, China
| | - Ling Yang
- Hebei North University, Zhangjiakou 075000, China
| | - Wenping Gong
- Beijing Key Laboratory of New Techniques of Tuberculosis Diagnosis and Treatment, Senior Department of Tuberculosis, Eighth Medical Center of Chinese PLA General Hospital, Beijing 100091, China
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39
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Lau Q, Igawa T, Kosch TA, Dharmayanthi AB, Berger L, Skerratt LF, Satta Y. Conserved Evolution of MHC Supertypes among Japanese Frogs Suggests Selection for Bd Resistance. Animals (Basel) 2023; 13:2121. [PMID: 37443920 DOI: 10.3390/ani13132121] [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: 05/17/2023] [Revised: 06/16/2023] [Accepted: 06/20/2023] [Indexed: 07/15/2023] Open
Abstract
The chytrid fungus Batrachochytrium dendrobatidis (Bd) is a major threat to amphibians, yet there are no reports of major disease impacts in East Asian frogs. Genetic variation of the major histocompatibility complex (MHC) has been associated with resistance to Bd in frogs from East Asia and worldwide. Using transcriptomic data collated from 11 Japanese frog species (one individual per species), we isolated MHC class I and IIb sequences and validated using molecular cloning. We then compared MHC from Japanese frogs and other species worldwide, with varying Bd susceptibility. Supertyping analysis, which groups MHC alleles based on physicochemical properties of peptide binding sites, identified that all examined East Asian frogs contained at least one MHC-IIb allele belonging to supertype ST-1. This indicates that, despite the large divergence times between some Japanese frogs (up to 145 million years), particular functional properties in the peptide binding sites of MHC-II are conserved among East Asian frogs. Furthermore, preliminary analysis using NetMHCIIpan-4.0, which predicts potential Bd-peptide binding ability, suggests that MHC-IIb ST-1 and ST-2 have higher overall peptide binding ability than other supertypes, irrespective of whether the peptides are derived from Bd, other fungi, or bacteria. Our findings suggest that MHC-IIb among East Asian frogs may have co-evolved under the same selective pressure. Given that Bd originated in this region, it may be a major driver of MHC evolution in East Asian frogs.
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Affiliation(s)
- Quintin Lau
- Research Center for Integrative Evolutionary Science, Sokendai (The Graduate University for Advanced Studies), Hayama 240-0115, Japan
| | - Takeshi Igawa
- Amphibian Research Center, Hiroshima University, Higashi-Hiroshima 739-8526, Japan
| | - Tiffany A Kosch
- One Health Research Group, Faculty of Science, University of Melbourne, Parkville 3010, Australia
| | - Anik B Dharmayanthi
- Research Center for Biosystematics and Evolution, National Research and Innovation Agency (BRIN), Bogor 16911, Indonesia
| | - Lee Berger
- One Health Research Group, Faculty of Science, University of Melbourne, Parkville 3010, Australia
| | - Lee F Skerratt
- One Health Research Group, Faculty of Science, University of Melbourne, Parkville 3010, Australia
| | - Yoko Satta
- Research Center for Integrative Evolutionary Science, Sokendai (The Graduate University for Advanced Studies), Hayama 240-0115, Japan
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40
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Jesus-Oliveira P, Silva-Couto L, Pinho N, Da Silva-Ferreira AT, Saboia-Vahia L, Cuervo P, Da-Cruz AM, Gomes-Silva A, Pinto EF. Identification of Immunodominant Proteins of the Leishmania (Viannia) naiffi SubProteome as Pan-Specific Vaccine Targets against Leishmaniasis. Vaccines (Basel) 2023; 11:1129. [PMID: 37514945 PMCID: PMC10386316 DOI: 10.3390/vaccines11071129] [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: 02/28/2023] [Revised: 03/22/2023] [Accepted: 04/10/2023] [Indexed: 07/30/2023] Open
Abstract
Leishmaniasis is a wide-spectrum disease caused by parasites from Leishmania genus. A well-modulated immune response that is established after the long-lasting clinical cure of leishmaniasis can represent a standard requirement for a vaccine. Previous studies demonstrated that Leishmania (Viannia) naiffi causes benign disease and its antigens induce well-modulated immune responses in vitro. In this work we aimed to identify the immunodominant proteins present in the soluble extract of L. naiffi (sLnAg) as candidates for composing a pan-specific anti-leishmaniasis vaccine. After immunoblotting using cured patients of cutaneous leishmaniasis sera and proteomics approaches, we identified a group of antigenic proteins from the sLnAg. In silico analyses allowed us to select mildly similar proteins to the host; in addition, we evaluated the binding potential and degree of promiscuity of the protein epitopes to HLA molecules and to B-cell receptors. We selected 24 immunodominant proteins from a sub-proteome with 328 proteins. Homology analysis allowed the identification of 13 proteins with the most orthologues among seven Leishmania species. This work demonstrated the potential of these proteins as promising vaccine targets capable of inducing humoral and cellular pan-specific immune responses in humans, which may in the future contribute to the control of leishmaniasis.
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Affiliation(s)
- Prisciliana Jesus-Oliveira
- Laboratório Interdisciplinar de Pesquisas Médicas, Instituto Oswaldo Cruz, Fundação Oswaldo Cruz, Rio de Janeiro 21040-360, Brazil
| | - Luzinei Silva-Couto
- Laboratório Interdisciplinar de Pesquisas Médicas, Instituto Oswaldo Cruz, Fundação Oswaldo Cruz, Rio de Janeiro 21040-360, Brazil
| | - Nathalia Pinho
- Laboratório de Pesquisa em Leishmanioses, Instituto Oswaldo Cruz, Fundação Oswaldo Cruz, Rio de Janeiro 21040-360, Brazil
- Rede de Pesquisas de Neuroinflamação do Rio de Janeiro, Instituto Oswaldo Cruz, Fundação Oswaldo Cruz, Rio de Janeiro 21040-360, Brazil
| | | | - Leonardo Saboia-Vahia
- Laboratório de Vírus Respiratórios e Sarampo, Laboratório de Referência para COVID-19 (World Health Organization), Instituto Oswaldo Cruz, Fundação Oswaldo Cruz, Rio de Janeiro 21040-360, Brazil
| | - Patricia Cuervo
- Laboratório de Pesquisa em Leishmanioses, Instituto Oswaldo Cruz, Fundação Oswaldo Cruz, Rio de Janeiro 21040-360, Brazil
- Rede de Pesquisas de Neuroinflamação do Rio de Janeiro, Instituto Oswaldo Cruz, Fundação Oswaldo Cruz, Rio de Janeiro 21040-360, Brazil
| | - Alda Maria Da-Cruz
- Laboratório Interdisciplinar de Pesquisas Médicas, Instituto Oswaldo Cruz, Fundação Oswaldo Cruz, Rio de Janeiro 21040-360, Brazil
- Rede de Pesquisas em Saúde, Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro, Rio de Janeiro 20020-000, Brazil
- Disciplina de Parasitologia, Departamento de Microbiologia, Imunologia e Parasitologia, Faculdade de Ciências Médicas, Universidade Estadual do Rio de Janeiro, Rio de Janeiro 20550-170, Brazil
- Instituto Nacional de Ciência e Tecnologia em Neuroimunomodulação (INCT-NIM), Rio de Janeiro 21040-900, Brazil
| | - Adriano Gomes-Silva
- Laboratório Interdisciplinar de Pesquisas Médicas, Instituto Oswaldo Cruz, Fundação Oswaldo Cruz, Rio de Janeiro 21040-360, Brazil
- Laboratório de Pesquisa Clínica em Micobacterioses, Instituto Nacional de Infectologia Evandro Chagas, Fundação Oswaldo Cruz, Rio de Janeiro 21040-360, Brazil
| | - Eduardo Fonseca Pinto
- Laboratório Interdisciplinar de Pesquisas Médicas, Instituto Oswaldo Cruz, Fundação Oswaldo Cruz, Rio de Janeiro 21040-360, Brazil
- Rede de Pesquisas em Saúde, Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro, Rio de Janeiro 20020-000, Brazil
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41
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Ravi A, Hellmann MD, Arniella MB, Holton M, Freeman SS, Naranbhai V, Stewart C, Leshchiner I, Kim J, Akiyama Y, Griffin AT, Vokes NI, Sakhi M, Kamesan V, Rizvi H, Ricciuti B, Forde PM, Anagnostou V, Riess JW, Gibbons DL, Pennell NA, Velcheti V, Digumarthy SR, Mino-Kenudson M, Califano A, Heymach JV, Herbst RS, Brahmer JR, Schalper KA, Velculescu VE, Henick BS, Rizvi N, Jänne PA, Awad MM, Chow A, Greenbaum BD, Luksza M, Shaw AT, Wolchok J, Hacohen N, Getz G, Gainor JF. Genomic and transcriptomic analysis of checkpoint blockade response in advanced non-small cell lung cancer. Nat Genet 2023; 55:807-819. [PMID: 37024582 PMCID: PMC10181943 DOI: 10.1038/s41588-023-01355-5] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Accepted: 02/24/2023] [Indexed: 04/08/2023]
Abstract
Anti-PD-1/PD-L1 agents have transformed the treatment landscape of advanced non-small cell lung cancer (NSCLC). To expand our understanding of the molecular features underlying response to checkpoint inhibitors in NSCLC, we describe here the first joint analysis of the Stand Up To Cancer-Mark Foundation cohort, a resource of whole exome and/or RNA sequencing from 393 patients with NSCLC treated with anti-PD-(L)1 therapy, along with matched clinical response annotation. We identify a number of associations between molecular features and outcome, including (1) favorable (for example, ATM altered) and unfavorable (for example, TERT amplified) genomic subgroups, (2) a prominent association between expression of inducible components of the immunoproteasome and response and (3) a dedifferentiated tumor-intrinsic subtype with enhanced response to checkpoint blockade. Taken together, results from this cohort demonstrate the complexity of biological determinants underlying immunotherapy outcomes and reinforce the discovery potential of integrative analysis within large, well-curated, cancer-specific cohorts.
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Affiliation(s)
- Arvind Ravi
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA
- Lank Center for Genitourinary Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | | | - Monica B Arniella
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA
| | - Mark Holton
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA
| | - Samuel S Freeman
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA
| | - Vivek Naranbhai
- Massachusetts General Hospital Cancer Center, Massachusetts General Hospital, Boston, MA, USA
- Dana-Farber Cancer Institute, Boston, MA, USA
- Center for the AIDS Programme for Research in South Africa, Durban, South Africa
- Center for Thoracic Cancers, Massachusetts General Hospital, Boston, MA, USA
| | - Chip Stewart
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA
| | - Ignaty Leshchiner
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA
| | | | - Yo Akiyama
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA
| | - Aaron T Griffin
- Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY, USA
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY, USA
| | - Natalie I Vokes
- Department of Thoracic and Head and Neck Oncology, MD Anderson Cancer Center, Houston, TX, USA
- Department of Genomic Medicine, MD Anderson Cancer Center, Houston, TX, USA
| | - Mustafa Sakhi
- Center for Thoracic Cancers, Massachusetts General Hospital, Boston, MA, USA
| | - Vashine Kamesan
- Center for Thoracic Cancers, Massachusetts General Hospital, Boston, MA, USA
| | - Hira Rizvi
- Druckenmiller Center for Lung Cancer Research, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Biagio Ricciuti
- Lowe Center for Thoracic Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Patrick M Forde
- Bloomberg-Kimmel Institute for Cancer Immunotherapy, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Valsamo Anagnostou
- Bloomberg-Kimmel Institute for Cancer Immunotherapy, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | | | - Don L Gibbons
- Department of Thoracic and Head and Neck Oncology, MD Anderson Cancer Center, Houston, TX, USA
| | - Nathan A Pennell
- Department of Hematology and Medical Oncology, Cleveland Clinic, Cleveland, OH, USA
| | - Vamsidhar Velcheti
- Department of Hematology and Oncology, NYU Langone Health, New York, NY, USA
| | - Subba R Digumarthy
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Massachusetts General Hospital, Boston, MA, USA
| | - Mari Mino-Kenudson
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Department of Pathology, Massachusetts General Hospital, Boston, MA, USA
| | - Andrea Califano
- Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY, USA
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY, USA
- Department of Biomedical Informatics, Columbia University, New York, NY, USA
- Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY, USA
- Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA
- J.P. Sulzberger Columbia Genome Center, New York, NY, USA
| | - John V Heymach
- Department of Thoracic and Head and Neck Oncology, MD Anderson Cancer Center, Houston, TX, USA
| | - Roy S Herbst
- Yale Cancer Center, Yale School of Medicine, New Haven, CT, USA
| | - Julie R Brahmer
- Bloomberg-Kimmel Institute for Cancer Immunotherapy, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Kurt A Schalper
- Yale Cancer Center, Yale School of Medicine, New Haven, CT, USA
- Department of Pathology, Yale School of Medicine, New Haven, CT, USA
| | - Victor E Velculescu
- Bloomberg-Kimmel Institute for Cancer Immunotherapy, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Brian S Henick
- Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY, USA
| | | | - Pasi A Jänne
- Lowe Center for Thoracic Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Mark M Awad
- Lowe Center for Thoracic Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Andrew Chow
- Druckenmiller Center for Lung Cancer Research, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Benjamin D Greenbaum
- Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Physiology, Biophysics & Systems Biology, Weill Cornell Medicine, Weill Cornell Medical College, New York, NY, USA
| | - Marta Luksza
- Department of Oncological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Alice T Shaw
- Center for Thoracic Cancers, Massachusetts General Hospital, Boston, MA, USA
| | | | - Nir Hacohen
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA.
- Massachusetts General Hospital Cancer Center, Massachusetts General Hospital, Boston, MA, USA.
- Center for Cancer Research, Massachusetts General Hospital, Boston, MA, USA.
| | - Gad Getz
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA.
- Massachusetts General Hospital Cancer Center, Massachusetts General Hospital, Boston, MA, USA.
- Department of Pathology, Massachusetts General Hospital, Boston, MA, USA.
- Center for Cancer Research, Massachusetts General Hospital, Boston, MA, USA.
| | - Justin F Gainor
- Massachusetts General Hospital Cancer Center, Massachusetts General Hospital, Boston, MA, USA.
- Center for Thoracic Cancers, Massachusetts General Hospital, Boston, MA, USA.
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42
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Ye Z, Li S, Mi X, Shao B, Dai Z, Ding B, Feng S, Sun B, Shen Y, Xiao Z. STMHCpan, an accurate Star-Transformer-based extensible framework for predicting MHC I allele binding peptides. Brief Bioinform 2023; 24:7147024. [PMID: 37122066 DOI: 10.1093/bib/bbad164] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Revised: 03/22/2023] [Accepted: 04/06/2023] [Indexed: 05/02/2023] Open
Abstract
Peptide-major histocompatibility complex I (MHC I) binding affinity prediction is crucial for vaccine development, but existing methods face limitations such as small datasets, model overfitting due to excessive parameters and suboptimal performance. Here, we present STMHCPan (STAR-MHCPan), an open-source package based on the Star-Transformer model, for MHC I binding peptide prediction. Our approach introduces an attention mechanism to improve the deep learning network architecture and performance in antigen prediction. Compared with classical deep learning algorithms, STMHCPan exhibits improved performance with fewer parameters in receptor affinity training. Furthermore, STMHCPan outperforms existing ligand benchmark datasets identified by mass spectrometry. It can also handle peptides of arbitrary length and is highly scalable for predicting T-cell responses. Our software is freely available for use, training and extension through Github (https://github.com/Luckysoutheast/STMHCPan.git).
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Affiliation(s)
- Zheng Ye
- State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing, Jiangsu 210096, China
| | - Shaohao Li
- State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing, Jiangsu 210096, China
| | - Xue Mi
- State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing, Jiangsu 210096, China
| | - Baoyi Shao
- State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing, Jiangsu 210096, China
| | - Zhu Dai
- State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing, Jiangsu 210096, China
| | - Bo Ding
- Department of Obstetrics and Gynecoloty, Zhongda Hospital, School of Medicine, Southeast University, Nanjing 210009, China
| | - Songwei Feng
- Department of Obstetrics and Gynecoloty, Zhongda Hospital, School of Medicine, Southeast University, Nanjing 210009, China
| | - Bo Sun
- State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing, Jiangsu 210096, China
| | - Yang Shen
- Department of Obstetrics and Gynecoloty, Zhongda Hospital, School of Medicine, Southeast University, Nanjing 210009, China
| | - Zhongdang Xiao
- State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing, Jiangsu 210096, China
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43
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Nilsson JB, Kaabinejadian S, Yari H, Peters B, Barra C, Gragert L, Hildebrand W, Nielsen M. Machine learning reveals limited contribution of trans-only encoded variants to the HLA-DQ immunopeptidome. Commun Biol 2023; 6:442. [PMID: 37085710 PMCID: PMC10121683 DOI: 10.1038/s42003-023-04749-7] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2022] [Accepted: 03/23/2023] [Indexed: 04/23/2023] Open
Abstract
Human leukocyte antigen (HLA) class II antigen presentation is key for controlling and triggering T cell immune responses. HLA-DQ molecules, which are believed to play a major role in autoimmune diseases, are heterodimers that can be formed as both cis and trans variants depending on whether the α- and β-chains are encoded on the same (cis) or opposite (trans) chromosomes. So far, limited progress has been made for predicting HLA-DQ antigen presentation. In addition, the contribution of trans-only variants (i.e. variants not observed in the population as cis) in shaping the HLA-DQ immunopeptidome remains largely unresolved. Here, we seek to address these issues by integrating state-of-the-art immunoinformatics data mining models with large volumes of high-quality HLA-DQ specific mass spectrometry immunopeptidomics data. The analysis demonstrates highly improved predictive power and molecular coverage for models trained including these novel HLA-DQ data. More importantly, investigating the role of trans-only HLA-DQ variants reveals a limited to no contribution to the overall HLA-DQ immunopeptidome. In conclusion, this study furthers our understanding of HLA-DQ specificities and casts light on the relative role of cis versus trans-only HLA-DQ variants in the HLA class II antigen presentation space. The developed method, NetMHCIIpan-4.2, is available at https://services.healthtech.dtu.dk/services/NetMHCIIpan-4.2 .
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Affiliation(s)
| | - Saghar Kaabinejadian
- Pure MHC, LLC, Oklahoma City, OK, USA
- Department of Microbiology and Immunology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Hooman Yari
- Department of Microbiology and Immunology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Bjoern Peters
- Center for Infectious Disease and Vaccine Research, La Jolla Institute for Immunology, La Jolla, CA, 92037, California, USA
| | - Carolina Barra
- Department of Health Technology, Technical University of Denmark, DK-2800, Lyngby, Denmark
| | - Loren Gragert
- Department of Pathology and Laboratory Medicine, Tulane University School of Medicine, New Orleans, LA, 70112, USA
| | - William Hildebrand
- Department of Microbiology and Immunology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Morten Nielsen
- Department of Health Technology, Technical University of Denmark, DK-2800, Lyngby, Denmark.
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44
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Huang R, Zhao B, Hu S, Zhang Q, Su X, Zhang W. Adoptive neoantigen-reactive T cell therapy: improvement strategies and current clinical researches. Biomark Res 2023; 11:41. [PMID: 37062844 PMCID: PMC10108522 DOI: 10.1186/s40364-023-00478-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Accepted: 03/21/2023] [Indexed: 04/18/2023] Open
Abstract
Neoantigens generated by non-synonymous mutations of tumor genes can induce activation of neoantigen-reactive T (NRT) cells which have the ability to resist the growth of tumors expressing specific neoantigens. Immunotherapy based on NRT cells has made preeminent achievements in melanoma and other solid tumors. The process of manufacturing NRT cells includes identification of neoantigens, preparation of neoantigen expression vectors or peptides, induction and activation of NRT cells, and analysis of functions and phenotypes. Numerous improvement strategies have been proposed to enhance the potency of NRT cells by engineering TCR, promoting infiltration of T cells and overcoming immunosuppressive factors in the tumor microenvironment. In this review, we outline the improvement of the preparation and the function assessment of NRT cells, and discuss the current status of clinical trials related to NRT cell immunotherapy.
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Affiliation(s)
- Ruichen Huang
- Department of Respiratory and Critical Care Medicine, the First Affiliated Hospital of Second Military Medical University, Shanghai, 200433, People's Republic of China
| | - Bi Zhao
- Department of Respiratory and Critical Care Medicine, the First Affiliated Hospital of Second Military Medical University, Shanghai, 200433, People's Republic of China
| | - Shi Hu
- Department of Biophysics, College of Basic Medical Sciences, Second Military Medical University, 800 Xiangyin Road, Shanghai, 200433, People's Republic of China
| | - Qian Zhang
- National Key Laboratory of Medical Immunology, Institute of Immunology, Second Military Medical University, 800 Xiangyin Road, Shanghai, 200433, People's Republic of China
| | - Xiaoping Su
- School of Basic Medicine, Wenzhou Medical University, Wenzhou, 325000, People's Republic of China.
| | - Wei Zhang
- Department of Respiratory and Critical Care Medicine, the First Affiliated Hospital of Second Military Medical University, Shanghai, 200433, People's Republic of China.
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45
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Frank ML, Lu K, Erdogan C, Han Y, Hu J, Wang T, Heymach JV, Zhang J, Reuben A. T-Cell Receptor Repertoire Sequencing in the Era of Cancer Immunotherapy. Clin Cancer Res 2023; 29:994-1008. [PMID: 36413126 PMCID: PMC10011887 DOI: 10.1158/1078-0432.ccr-22-2469] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Revised: 10/07/2022] [Accepted: 11/14/2022] [Indexed: 11/23/2022]
Abstract
T cells are integral components of the adaptive immune system, and their responses are mediated by unique T-cell receptors (TCR) that recognize specific antigens from a variety of biological contexts. As a result, analyzing the T-cell repertoire offers a better understanding of immune responses and of diseases like cancer. Next-generation sequencing technologies have greatly enabled the high-throughput analysis of the TCR repertoire. On the basis of our extensive experience in the field from the past decade, we provide an overview of TCR sequencing, from the initial library preparation steps to sequencing and analysis methods and finally to functional validation techniques. With regards to data analysis, we detail important TCR repertoire metrics and present several computational tools for predicting antigen specificity. Finally, we highlight important applications of TCR sequencing and repertoire analysis to understanding tumor biology and developing cancer immunotherapies.
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Affiliation(s)
- Meredith L Frank
- Department of Thoracic/Head and Neck Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas.,The University of Texas MD Anderson Cancer Center UT Health Houston Graduate School of Biomedical Sciences, Houston, Texas
| | - Kaylene Lu
- Department of Thoracic/Head and Neck Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas.,The University of Texas MD Anderson Cancer Center UT Health Houston Graduate School of Biomedical Sciences, Houston, Texas.,Department of Cancer Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Can Erdogan
- Department of Thoracic/Head and Neck Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas.,Rice University, Houston, Texas
| | - Yi Han
- Quantitative Biomedical Research Center, Peter O'Donnell Jr. School of Public Health, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Jian Hu
- The University of Texas MD Anderson Cancer Center UT Health Houston Graduate School of Biomedical Sciences, Houston, Texas.,Department of Cancer Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Tao Wang
- Quantitative Biomedical Research Center, Peter O'Donnell Jr. School of Public Health, University of Texas Southwestern Medical Center, Dallas, Texas.,Center for the Genetics of Host Defense, University of Texas Southwestern Medical Center, Dallas, Texas
| | - John V Heymach
- Department of Thoracic/Head and Neck Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas.,The University of Texas MD Anderson Cancer Center UT Health Houston Graduate School of Biomedical Sciences, Houston, Texas
| | - Jianjun Zhang
- Department of Thoracic/Head and Neck Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas.,The University of Texas MD Anderson Cancer Center UT Health Houston Graduate School of Biomedical Sciences, Houston, Texas.,Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Alexandre Reuben
- Department of Thoracic/Head and Neck Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas.,The University of Texas MD Anderson Cancer Center UT Health Houston Graduate School of Biomedical Sciences, Houston, Texas
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46
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Song Y, Hu H, Xiao K, Huang X, Guo H, Shi Y, Zhao J, Zhu S, Ji T, Xia B, Jiang J, Cao L, Zhang Y, Zhang Y, Xu W. A Synthetic SARS-CoV-2-Derived T-Cell and B-Cell Peptide Cocktail Elicits Full Protection against Lethal Omicron BA.1 Infection in H11-K18-hACE2 Mice. Microbiol Spectr 2023; 11:e0419422. [PMID: 36912685 PMCID: PMC10100915 DOI: 10.1128/spectrum.04194-22] [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: 10/14/2022] [Accepted: 02/19/2023] [Indexed: 03/14/2023] Open
Abstract
Emerging variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been developing the capacity for immune evasion and resistance to existing vaccines and drugs. To address this, development of vaccines against coronavirus disease 2019 (COVID-19) has focused on universality, strong T cell immunity, and rapid production. Synthetic peptide vaccines, which are inexpensive and quick to produce, show low toxicity, and can be selected from the conserved SARS-CoV-2 proteome, are promising candidates. In this study, we evaluated the effectiveness of a synthetic peptide cocktail containing three murine CD4+ T-cell epitopes from the SARS-CoV-2 nonspike proteome and one B-cell epitope from the Omicron BA.1 receptor-binding domain (RBD), along with aluminum phosphate (Al) adjuvant and 5' cytosine-phosphate-guanine 3' oligodeoxynucleotide (CpG-ODN) adjuvant in mice. The peptide cocktail induced good Th1-biased T-cell responses and effective neutralizing-antibody titers against the Omicron BA.1 variant. Additionally, H11-K18-hACE2 transgenic mice were fully protected against lethal challenge with the BA.1 strain, with a 100% survival rate and reduced pulmonary viral load and pathological lesions. Subcutaneous administration was found to be the superior route for synthetic peptide vaccine delivery. Our findings demonstrate the effectiveness of the peptide cocktail in mice, suggesting the feasibility of synthetic peptide vaccines for humans. IMPORTANCE Current vaccines based on production of neutralizing antibodies fail to prevent the infection and transmission of SARS-CoV-2 Omicron and its subvariants. Understanding the critical factors and avoiding the disadvantages of vaccine strategies are essential for developing a safe and effective COVID-19 vaccine, which would include a more effective and durable cellular response, minimal effects of viral mutations, rapid production against emerging variants, and good safety. Peptide-based vaccines are an excellent alternative because they are inexpensive, quick to produce, and very safe. In addition, human leukocyte antigen T-cell epitopes could be targeted at robust T-cell immunity and selected in the conserved region of the SARS-CoV-2 variants. Our study showed that a synthetic SARS-CoV-2-derived peptide cocktail induced full protection against lethal infection with Omicron BA.1 in H11-K18-hACE2 mice for the first time. This could have implications for the development of effective COVID-19 peptide vaccines for humans.
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Affiliation(s)
- Yang Song
- NHC Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Hongqiao Hu
- NHC Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Kang Xiao
- NHC Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Xinghu Huang
- NHC Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Hong Guo
- NHC Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yuqing Shi
- NHC Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Jiannan Zhao
- NHC Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Shuangli Zhu
- NHC Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Tianjiao Ji
- NHC Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Baicheng Xia
- NHC Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Jie Jiang
- NHC Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Lei Cao
- NHC Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yong Zhang
- NHC Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yan Zhang
- NHC Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Wenbo Xu
- NHC Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
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47
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Contemplating immunopeptidomes to better predict them. Semin Immunol 2023; 66:101708. [PMID: 36621290 DOI: 10.1016/j.smim.2022.101708] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Revised: 12/16/2022] [Accepted: 12/20/2022] [Indexed: 01/09/2023]
Abstract
The identification of T-cell epitopes is key for a complete molecular understanding of immune recognition mechanisms in infectious diseases, autoimmunity and cancer. T-cell epitopes further provide targets for personalized vaccines and T-cell therapy, with several therapeutic applications in cancer immunotherapy and elsewhere. T-cell epitopes consist of short peptides displayed on Major Histocompatibility Complex (MHC) molecules. The recent advances in mass spectrometry (MS) based technologies to profile the ensemble of peptides displayed on MHC molecules - the so-called immunopeptidome - had a major impact on our understanding of antigen presentation and MHC ligands. On the one hand, these techniques enabled researchers to directly identify hundreds of thousands of peptides presented on MHC molecules, including some that elicited T-cell recognition. On the other hand, the data collected in these experiments revealed fundamental properties of antigen presentation pathways and significantly improved our ability to predict naturally presented MHC ligands and T-cell epitopes across the wide spectrum of MHC alleles found in human and other organisms. Here we review recent computational developments to analyze experimentally determined immunopeptidomes and harness these data to improve our understanding of antigen presentation and MHC binding specificities, as well as our ability to predict MHC ligands. We further discuss the strengths and limitations of the latest approaches to move beyond predictions of antigen presentation and tackle the challenges of predicting TCR recognition and immunogenicity.
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48
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Abdulhameed Odhar H, Hashim AF, Humadi SS, Ahjel SW. Design and construction of multi epitope- peptide vaccine candidate for rabies virus. Bioinformation 2023; 19:167-177. [PMID: 37814687 PMCID: PMC10560302 DOI: 10.6026/97320630019167] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Revised: 02/28/2023] [Accepted: 02/28/2023] [Indexed: 09/01/2023] Open
Abstract
Rabies virus is a zoonotic pathogen that causes lethal encephalitis with a case fatality rate of almost 100% in unvaccinated individuals. The currently available vaccines against rabies are composed of inactivated viral particles that only confer a short-term immune response. It is well-known that the entry of rabies virus into host cells is mediated by a trimeric glycoprotein presents on the surface of viral envelope. As the sole viral surface protein, this trimeric glycoprotein represents a promising molecular target to design new vaccines and neutralizing antibodies against rabies virus. Epitope mapping studies had identified several antigenic sites on the surface of trimeric pre-fusion glycoprotein of rabies virus. Therefore, it is of interest to screen the rabies virus glycoprotein by different web-based immuno-informatics tools to identify potential B-cells and T-cells linear epitopes. Here, we present a construct of peptide vaccine that consists of these predicted linear epitopes of rabies virus glycoprotein together with appropriate linkers and adjuvant. Various online prediction tools, molecular docking and dynamics simulation assume that the vaccine construct may be stable, safe and effective. However, validation of these in-silico results is necessary both in vitro and in vivo setting.
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Affiliation(s)
| | | | - Suhad Sami Humadi
- Department of pharmacy, Al-Zahrawi University College, Karbala, Iraq
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49
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Bunkofske ME, Perumal N, White B, Strauch EM, Tarleton R. Epitopes in the Glycosylphosphatidylinositol Attachment Signal Peptide of Trypanosoma cruzi Mucin Proteins Generate Robust but Delayed and Nonprotective CD8+ T Cell Responses. JOURNAL OF IMMUNOLOGY (BALTIMORE, MD. : 1950) 2023; 210:420-430. [PMID: 36603035 PMCID: PMC9898211 DOI: 10.4049/jimmunol.2200723] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/03/2022] [Accepted: 12/05/2022] [Indexed: 01/06/2023]
Abstract
Infection with the protozoan parasite Trypanosoma cruzi elicits substantial CD8+ T cell responses that disproportionately target epitopes encoded in the large trans-sialidase (TS) gene family. Within the C57BL/6 infection model, a significant proportion (30-40%) of the T. cruzi-specific CD8+ T cell response targets two immunodominant TS epitopes, TSKb18 and TSKb20. However, both TS-specific CD8+ T cell responses are dispensable for immune control, and TS-based vaccines have no demonstrable impact on parasite persistence, a determinant of disease. Besides TS, the specificity and protective capacity of CD8+ T cells that mediate immune control of T. cruzi infection are unknown. With the goal of identifying alternative CD8+ T cell targets, we designed and screened a representative set of genome-wide, in silico-predicted epitopes. Our screen identified a previously uncharacterized, to our knowledge, T cell epitope MUCKb25, found within mucin family proteins, the third most expanded large gene family in T. cruzi. The MUCKb25-specific response was characterized by delayed kinetics, relative to TS-specific responses, and extensive cross-reactivity with a large number of endogenous epitope variants. Similar to TS-specific responses, the MUCKb25 response was dispensable for control of the infection, and vaccination to generate MUCK-specific CD8+ T cells failed to confer protection. The lack of protection by MUCK vaccination was partly attributed to the fact that MUCKb25-specific T cells exhibit limited recognition of T. cruzi-infected host cells. Overall, these results indicate that the CD8+ T cell compartment in many T. cruzi-infected mice is occupied by cells with minimal apparent effector potential.
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Affiliation(s)
- Molly E. Bunkofske
- Department of Microbiology, University of Georgia, Athens, GA 30602, USA
- Center for Tropical and Emerging Global Diseases, University of Georgia, Athens, GA 30602, USA
| | - Natasha Perumal
- Center for Tropical and Emerging Global Diseases, University of Georgia, Athens, GA 30602, USA
- Department of Cellular Biology, University of Georgia, Athens, GA 30602, USA
| | - Brooke White
- Center for Tropical and Emerging Global Diseases, University of Georgia, Athens, GA 30602, USA
| | - Eva-Maria Strauch
- Department of Pharmaceutical and Biomedical Sciences, University of Georgia, Athens, GA 30602, USA
| | - Rick Tarleton
- Center for Tropical and Emerging Global Diseases, University of Georgia, Athens, GA 30602, USA
- Department of Cellular Biology, University of Georgia, Athens, GA 30602, USA
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50
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Sun H, Zhang Y, Wang G, Yang W, Xu Y. mRNA-Based Therapeutics in Cancer Treatment. Pharmaceutics 2023; 15:pharmaceutics15020622. [PMID: 36839944 PMCID: PMC9964383 DOI: 10.3390/pharmaceutics15020622] [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: 01/08/2023] [Revised: 01/28/2023] [Accepted: 01/28/2023] [Indexed: 02/15/2023] Open
Abstract
Over the past two decades, significant technological innovations have led to messenger RNA (mRNA) becoming a promising option for developing prophylactic and therapeutic vaccines, protein replacement therapies, and genome engineering. The success of the two COVID-19 mRNA vaccines has sparked new enthusiasm for other medical applications, particularly in cancer treatment. In vitro-transcribed (IVT) mRNAs are structurally designed to resemble naturally occurring mature mRNA. Delivery of IVT mRNA via delivery platforms such as lipid nanoparticles allows host cells to produce many copies of encoded proteins, which can serve as antigens to stimulate immune responses or as additional beneficial proteins for supplements. mRNA-based cancer therapeutics include mRNA cancer vaccines, mRNA encoding cytokines, chimeric antigen receptors, tumor suppressors, and other combination therapies. To better understand the current development and research status of mRNA therapies for cancer treatment, this review focused on the molecular design, delivery systems, and clinical indications of mRNA therapies in cancer.
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Affiliation(s)
- Han Sun
- Department of Biochemistry and Molecular Cell Biology, Shanghai Key Laboratory for Tumor Microenvironment and Inflammation, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Yu Zhang
- Department of Biochemistry and Molecular Cell Biology, Shanghai Key Laboratory for Tumor Microenvironment and Inflammation, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Ge Wang
- Department of Oral Maxillofacial & Head and Neck Oncology, National Center of Stomatology, National Clinical Research Center for Oral Disease, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200011, China
| | - Wen Yang
- Department of Biochemistry and Molecular Cell Biology, Shanghai Key Laboratory for Tumor Microenvironment and Inflammation, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Yingjie Xu
- Department of Biochemistry and Molecular Cell Biology, Shanghai Key Laboratory for Tumor Microenvironment and Inflammation, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
- Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
- Correspondence:
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