Poor correlation between T-cell activation assays and HLA-DR binding prediction algorithms in an immunogenic fragment of Pseudomonas exotoxin A

Mazor, Ronit; Tai, Chin‐Hsien; Lee, Byung Kook; Pastan, Ira

doi:10.1016/j.jim.2015.06.003

Cited by 22 publications

(18 citation statements)

References 56 publications

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“…It should be noted, however, that analysis of the predictive power of in silico T-cell epitope prediction has questioned its accuracy. This potential inaccuracy may be due to the observation that current prediction software is accurate at predicting the dominant DRdisplayed peptides, but lacks accuracy in predicting DP and/or DQ alleles (52). These findings further support the rationale to drive the full v-domain sequence (inclusive of CDRs) as close as possible to human germ line, due to our inability to fully avoid false negatives in in silico epitope screening.…”

Section: Discussionmentioning

confidence: 71%

“…These findings further support the rationale to drive the full v-domain sequence (inclusive of CDRs) as close as possible to human germ line, due to our inability to fully avoid false negatives in in silico epitope screening. Predictive power of immunogenicity analyses post-ABS could also be improved by performing in vitro antigen stimulation assays (52).…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Augmented Binary Substitution: Single-pass CDR germ-lining and stabilization of therapeutic antibodies

Townsend

Fennell

Apgar

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

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Although humanized antibodies have been highly successful in the clinic, all current humanization techniques have potential limitations, such as: reliance on rodent hosts, immunogenicity due to high non-germ-line amino acid content, v-domain destabilization, expression and formulation issues. This study presents a technology that generates stable, soluble, ultrahumanized antibodies via single-step complementarity-determining region (CDR) germ-lining. For three antibodies from three separate key immune host species, binary substitution CDR cassettes were inserted into preferred human frameworks to form libraries in which only the parental or human germ-line destination residue was encoded at each position. The CDR-H3 in each case was also augmented with 1 ± 1 random substitution per clone. Each library was then screened for clones with restored antigen binding capacity. Lead ultrahumanized clones demonstrated high stability, with affinity and specificity equivalent to, or better than, the parental IgG. Critically, this was mainly achieved on germ-line frameworks by simultaneously subtracting up to 19 redundant non-germ-line residues in the CDRs. This process significantly lowered non-germ-line sequence content, minimized immunogenicity risk in the final molecules and provided a heat map for the essential non-germ-line CDR residue content of each antibody. The ABS technology therefore fully optimizes the clinical potential of antibodies from rodents and alternative immune hosts, rendering them indistinguishable from fully human in a simple, single-pass process.antibody | paratope | plasticity | humanization | immunogenicity

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Section: Discussionmentioning

confidence: 71%

Section: Discussionmentioning

confidence: 99%

Augmented Binary Substitution: Single-pass CDR germ-lining and stabilization of therapeutic antibodies

Townsend

Fennell

Apgar

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

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show abstract

“…Correlations between the immunogenicity of a peptide, its MHC-binding affinity and pMHC complex stability tend to be poor. [82][83][84][85] Each method has its advantages and shortcomings and depending on needs and means, different strategies for TA T cell epitope discovery are indicated. Bioinformatics sequencing data analysis, identification of mutated and overexpressed genes, and prediction of MHC ligands constitute a crucial initial part.…”

Section: Discussionmentioning

confidence: 99%

Current tools for predicting cancer-specific T cell immunity

Gfeller¹,

Bassani-Sternberg²,

Schmidt³

et al. 2016

OncoImmunology

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Tumor exome and RNA sequencing data provide a systematic and unbiased view on cancer-specific expression, over-expression, and mutations of genes, which can be mined for personalized cancer vaccines and other immunotherapies. Of key interest are tumor-specific mutations, because T cells recognizing neoepitopes have the potential to be highly tumoricidal. Here, we review recent developments and technical advances in identifying MHC class I and class II-restricted tumor antigens, especially neoantigen derived MHC ligands, including in silico predictions, immune-peptidome analysis by mass spectrometry, and MHC ligand validation by biochemical methods on T cells.

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“…These two thresholds were choisen on the basis of rates of experimental epitope discovery, which ranged from 8% to 19% of tested peptides corresponding to proteins that were mapped (see below). The same threshold has been used in recent work evaluating the 5 correlation between MHC-binding and T-cell activation assays [39]. We note that in general it is difficult to choose the “correct” threshold that best balances true and false positive rates; it is for this reason that we also use the AUC metric to evaluate performance on single-allele and human datasets.…”

Section: Methodsmentioning

confidence: 99%

CD4+ T-cell epitope prediction using antigen processing constraints

Mettu

Charles

Landry

2016

Journal of Immunological Methods

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T-cell CD4+ epitopes are important targets of immunity against infectious diseases and cancer. State-of-the-art methods for MHC class II epitope prediction rely on supervised learning methods in which an implicit or explicit model of sequence specificity is constructed using a training set of peptides with experimentally tested MHC class II binding affinity. In this paper we present a novel method for CD4+ T-cell eptitope prediction based on modeling antigen-processing constraints. Previous work indicates that dominant CD4+ T-cell epitopes tend to occur adjacent to sites of initial proteolytic cleavage. Given an antigen with known three-dimensional structure, our algorithm first aggregates four types of conformational stability data in order to construct a profile of stability that allows us to identify regions of the protein that are most accessible to proteolysis. Using this profile, we then construct a profile of epitope likelihood based on the pattern of transitions from unstable to stable regions. We validate our method using 35 datasets of experimentally measured CD4+ T cell responses of mice bearing I-Ab or HLA-DR4 alleles as well as of human subjects. Overall, our results show that antigen processing constraints provide a significant source of predictive power. For epitope prediction in single-allele systems, our approach can be combined with sequence-based methods, or used in instances where little or no training data is available. In multiple-allele systems, sequence-based methods can only be used if the allele distribution of a population is known. In contrast, our approach does not make use of MHC binding prediction, and is thus agnostic to MHC class II genotypes.

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Poor correlation between T-cell activation assays and HLA-DR binding prediction algorithms in an immunogenic fragment of Pseudomonas exotoxin A

Cited by 22 publications

References 56 publications

Augmented Binary Substitution: Single-pass CDR germ-lining and stabilization of therapeutic antibodies

Augmented Binary Substitution: Single-pass CDR germ-lining and stabilization of therapeutic antibodies

Current tools for predicting cancer-specific T cell immunity

CD4+ T-cell epitope prediction using antigen processing constraints

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