Robust prediction of HLA class II epitopes by deep motif deconvolution of immunopeptidomes

Racle, Julien; Michaux, Justine; Rockinger, Georg Alexander; Arnaud, Marion; Bobisse, Sara; Chong, Chloé; Guillaume, Philippe; Coukos, George; Harari, Alexandre; Jandus, Camilla; Bassani-Sternberg, Michal; Gfeller, David

doi:10.1038/s41587-019-0289-6

Cited by 224 publications

(279 citation statements)

References 45 publications

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“…The results of this analysis have been recently published (15) and show that training in both ligand and binding datasets is the most effective and that the optimal output is the prediction of eluted ligands. These results have been confirmed by three independent studies (27)(28)(29). Although a formal benchmarking for HLA class II molecules in a controlled experimental system is to date lacking, these results are in strong agreement with the results of the murine class I study of Tscharke in the VACV system (19).…”

Section: What Is the Relative Value Of Binding Vs Elution Predictionsupporting

confidence: 75%

Major Histocompatibility Complex Binding, Eluted Ligands, and Immunogenicity: Benchmark Testing and Predictions

et al. 2020

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Antidrug antibody (ADA) responses impact drug safety, potency, and efficacy. It is generally assumed that ADA responses are associated with human leukocyte antigen (HLA) class II-restricted CD4+ T-cell reactivity. Although this review does not address ADA responses per se, the analysis presented here is relevant to the topic, because measuring or predicting CD4+ T-cell reactivity is a common strategy to address ADA and immunogenicity concerns. Because human CD4+ T-cell reactivity relies on the recognition of peptides bound to HLA class II, prediction, or measurement of the capacity of different peptides to bind or be natural ligands of HLA class II is used as a predictor of CD4+ T-cell reactivity and ADA development. Thus, three different interconnected variables are commonly utilized in predicting T-cell reactivity: major histocompatibility complex (MHC) binding, capacity to be generated as natural HLA ligands, and T-cell immunogenicity. To provide the scientific community with guidance in the relative merit of different approaches, it is necessary to clearly define what outcomes are being considered. Thus, the accuracy of HLA binding predictions varies as a function of what the outcome predicted is, whether it is binding itself, natural processing, or T-cell immunogenicity. Furthermore, it is necessary that the accuracy of prediction is based on rigorous benchmarking, grounded by fair, objective, transparent, and experimental criteria. In this review, we provide our perspective on how different variables and methodologies predict each of the various outcomes and point out knowledge gaps and areas to be addressed by further experimental work.

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Section: What Is the Relative Value Of Binding Vs Elution Predictionsupporting

confidence: 75%

Major Histocompatibility Complex Binding, Eluted Ligands, and Immunogenicity: Benchmark Testing and Predictions

et al. 2020

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“…Thus, FucoID opens a new door to study primary antigen specific CD4 + T cells not only in tumors but also in autoimmune diseases. CD4 + T cells are challenging targets to study using conventional approaches partially due to the diversity and length variation (11 to 30 amino acids) of MHC-II binding epitopes and their weak interactions with MHC-II (Editorial, 2017;Racle et al, 2019). Likewise, one can envisage applying FucoID to separate T cells possessing high affinity TCRs from those with weaker ones for studying their functions in tumor and related infection models.…”

Section: Discussionmentioning

confidence: 99%

Detecting Tumor Specific Antigen-Reactive T cells from Tumor Infiltrating Lymphocytes via Interaction Dependent Fucosyl-biotinylation

Liu

Chen

et al. 2020

Preprint

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HighlightsInteraction dependent fucosylation enables the detection and isolation of bona fide intratumoral tumor specific antigen-reactive T cells Tumor specific antigen-reactive CD8 + T cells possess capabilities to be expanded and adoptively transferred for tumor control Tumor specific antigen-reactive CD8 + T cells feature oligoclonal expansion and upregulate genes for the steroid biosynthesis and metabolic process Intratumoral bystander CD8 + T cells can be separated into two groups based on PD-1 expression that feature distinct gene modules SummaryRe-activation and clonal expansion of tumor specific antigen (TSA)-reactive T cells are critical to the success of checkpoint blockade and adoptive transfer of tumor-infiltrating lymphocyte (TIL) based therapies. There are no reliable markers to specifically identify the repertoire of TSA-reactive T cells due to their heterogeneous composition. Here we introduce FucoID as a general platform to detect endogenous antigen-specific T cells and study their biology. Through this interaction dependent labeling approach, TSA-reactive T cells can be detected and separated from bystander T cells in primary tumor digests based on their cell-surface enzymatic fucosylbiotinylation. Compared to bystander TILs, TSA-reactive TILs possess a distinct TCR repertoire and unique gene features. Though exhibiting a dysfunctional phenotype, this subset of TILs possesses substantial capabilities of proliferation and tumor specific killing. FucoID features genetic manipulation-free procedures and a quick turnover cycle, and therefore should have the potential of accelerating the pace of personalized cancer treatment.

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“…This approach, however, is not feasible when patient samples are used, which will almost always be multi-allelic. To overcome this, there are currently significant efforts to develop computational methods that can accurately annotate multi-allelic ligands to their respective MHC (49,50). However, such methods will still rely on the identification of shared motifs of the eluted peptides.…”

Section: Discussionmentioning

confidence: 99%

Comparison of HLA ligand elution data and binding predictions reveals varying prediction performance for the multiple motifs recognized by HLA-DQ2.5

Yalcin

Sidney

Chronister

et al. 2020

Preprint

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Binding prediction tools are commonly used to identify peptides presented on MHC class II molecules. Recently, a wealth of data in the form of naturally eluted ligands has become available and discrepancies between ligand elution data and binding predictions have been reported. Quantitative metrics for such comparisons are currently lacking. In this study, we assessed how efficiently MHC class II binding predictions can identify naturally eluted peptides, and investigated instances with discrepancies between the two methods in detail. We found that, in general, MHC class II eluted ligands are predicted to bind to their reported restriction element with high affinity. But, for several studies reporting an increased number of ligands that were not predicted to bind, we found that the reported MHC restriction was ambiguous. Additional analyses determined that most of the ligands predicted to not bind are either weak binders or predicted to bind other co-expressed MHC class II molecules. For selected alleles, we addressed discrepancies between elution data and binding predictions by experimental measurements, and found that predicted and measured affinities correlate well. For DQA1*05:01/DQB1*02:01 (DQ2.5) however, binding predictions did miss several peptides that were determined experimentally to be binders. For these peptides and several known DQ2.5 binders we determined key residues for conferring DQ2.5 binding capacity, which revealed that DQ2.5 utilizes two different binding motifs, of which only one is predicted effectively. These findings have important implications for the interpretation of ligand elution data and for the improvement of MHC class II binding predictions.

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Robust prediction of HLA class II epitopes by deep motif deconvolution of immunopeptidomes

Cited by 224 publications

References 45 publications

Major Histocompatibility Complex Binding, Eluted Ligands, and Immunogenicity: Benchmark Testing and Predictions

Major Histocompatibility Complex Binding, Eluted Ligands, and Immunogenicity: Benchmark Testing and Predictions

Detecting Tumor Specific Antigen-Reactive T cells from Tumor Infiltrating Lymphocytes via Interaction Dependent Fucosyl-biotinylation

Comparison of HLA ligand elution data and binding predictions reveals varying prediction performance for the multiple motifs recognized by HLA-DQ2.5

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