Identification and Validation of T-Cell Epitopes Using the IFN-γ EliSpot Assay

Wulf, Markus; Hoehn, Petra; Trinder, P. K. E.

doi:10.1007/978-1-59745-450-6_32

Cited by 10 publications

(6 citation statements)

References 3 publications

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“…Secondary antibodies are then used to probe for the presence of the captured cytokine, followed by color development steps, resulting in the occurrence of distinct spots in the well. Each of these spots corresponds to a single cytokineproducing cell when employing an appropriate dilution of cells (162). ELISPOT based on IFN-gamma secretion is a mainstay method for the identification of novel epitopes (163)(164)(165) and ensuing T cell functional studies (86, 165).…”

Section: Diversity Of Immunotechnologiesmentioning

confidence: 99%

Sources of diversity in T cell epitope discovery

Chang

Dai²,

Tan³

et al. 2011

Front Biosci

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CD8-positive T cells respond to small antigenic peptide fragments presented on class I major histocompatibility complexes (MHCs). Those specific T cell epitopes capable of precipitating a cellular immune response are either derived from (altered) self (i.e. they are autoimmune- or cancer-associated) or come from foreign sources (i.e. they are pathogen-associated). Identification of T cell epitopes provides elementary information that can be employed in technologies that monitor and predict the likely outcome of an immune response, as well as in therapeutic and vaccine development efforts. The coexistence between host and pathogen has largely driven the diversification of both their systems of immune surveillance and their antigenic determinants, respectively. In this review, we discuss the multitude of factors that introduce diversity to the T cell response from both sides of the host-pathogen interaction. Furthermore, we provide an overview of a variety of commonly employed methods and tools to characterize class I MHC restricted antigen presentation and recent endeavors towards the harmonization of reporting data concerning T cell responses.

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Section: Diversity Of Immunotechnologiesmentioning

confidence: 99%

Sources of diversity in T cell epitope discovery

Chang

Dai²,

Tan³

et al. 2011

Front Biosci

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“…HLA binding studies validated computational predictions with 79% accuracy for a panel of six HLA Class II alleles, representing >90% of the global human population [15]. Here, we report functional studies testing the human T cell responses to each of these 90 peptides by interferon-γ ELISpot assay, since this is a widely used screening method to measure effector functions of low-frequency antigen-specific T cell populations to class II epitopes in human PBMCs [16] including to a putative H. pylori vaccine candidate. [17] …”

Section: Introductionmentioning

confidence: 96%

Human Immune Responses to H. pylori HLA Class II Epitopes Identified by Immunoinformatic Methods

et al. 2014

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H. pylori persists in the human stomach over decades and promotes several adverse clinical sequelae including gastritis, peptic ulcers and gastric cancer that are linked to the induction and subsequent evasion of chronic gastric inflammation. Emerging evidence indicates that H. pylori infection may also protect against asthma and some other immune-mediated conditions through regulatory T cell effects outside the stomach. To characterize the complexity of the CD4+ T cell response generated during H. pylori infection, computational methods were previously used to generate a panel of 90 predicted epitopes conserved among H. pylori genomes that broadly cover HLA Class II diversity for maximum population coverage. Here, these sequences were tested individually for their ability to induce in vitro responses in peripheral blood mononuclear cells by interferon-γ ELISpot assay. The average number of spot-forming cells/million PBMCs was significantly elevated in H. pylori-infected subjects over uninfected persons. Ten of the 90 peptides stimulated IFN-γ secretion in the H. pylori-infected group only, whereas two out of the 90 peptides elicited a detectable IFN-γ response in the H. pylori-uninfected subjects but no response in the H. pylori-infected group. Cytokine ELISA measurements performed using in vitro PBMC culture supernatants demonstrated significantly higher levels of TNF-α, IL-2, IL-4, IL-6, IL-10, and TGF-β1 in the H. pylori-infected subjects, whereas IL-17A expression was not related to the subjects H. pylori-infection status. Our results indicate that the human T cell responses to these 90 peptides are generally increased in actively H. pylori-infected, compared with H. pylori-naïve, subjects. This information will improve understanding of the complex immune response to H. pylori, aiding rational epitope-driven vaccine design as well as helping identify other H. pylori epitopes with potentially immunoregulatory effects.

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“…Several methods have been developed to identify and to predict T-cell epitopes from a given source protein. Based on in vitro assays, such as competitive binding assays and ELISpot assays, MHC-binding affinity and immunogenicity of peptides can be experimentally assessed (2,3). However, given the large variety of antigens and MHC allotypes, in vitro testing of all possible candidates is not feasible (4).…”

Section: Introductionmentioning

confidence: 99%

Performance Evaluation of MHC Class-I Binding Prediction Tools Based on an Experimentally Validated MHC–Peptide Binding Data Set

Bonsack

Hoppe

Winter

et al. 2019

Cancer Immunology Research

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Knowing whether a protein can be processed and the resulting peptides presented by major histocompatibility complex (MHC) is highly important for immunotherapy design. MHC ligands can be predicted by in silico peptide-MHC class-I binding prediction algorithms. However, prediction performance differs considerably, depending on the selected algorithm, MHC class-I type, and peptide length. We evaluated the prediction performance of 13 algorithms based on binding affinity data of 8-to 11-mer peptides derived from the HPV16 E6 and E7 proteins to the most prevalent human leukocyte antigen (HLA) types. Peptides from high to low predicted binding likelihood were synthesized, and their HLA binding was experimentally verified by in vitro competitive binding assays. Based on the actual binding capacity of the peptides, the performance of prediction algorithms was analyzed by calculating receiver operating characteristics (ROC) and the area under the curve (A ROC). No algorithm outperformed others, but different algorithms predicted best for particular HLA types and peptide lengths. The sensitivity, specificity, and accuracy of decision thresholds were calculated. Commonly used decision thresholds yielded only 40% sensitivity. To increase sensitivity, optimal thresholds were calculated, validated, and compared. In order to make maximal use of prediction algorithms available online, we developed MHCcombine, a web application that allows simultaneous querying and output combination of up to 13 prediction algorithms. Taken together, we provide here an evaluation of peptide-MHC class-I binding prediction tools and recommendations to increase prediction sensitivity to extend the number of potential epitopes applicable as targets for immunotherapy.

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Identification and Validation of T-Cell Epitopes Using the IFN-γ EliSpot Assay

Cited by 10 publications

References 3 publications

Sources of diversity in T cell epitope discovery

Sources of diversity in T cell epitope discovery

Human Immune Responses to H. pylori HLA Class II Epitopes Identified by Immunoinformatic Methods

Performance Evaluation of MHC Class-I Binding Prediction Tools Based on an Experimentally Validated MHC–Peptide Binding Data Set

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