Major Histocompatibility Complex Anchor Research Articles

Computational prediction of MHC anchor locations guides neoantigen identification and prioritization.

Neoantigens are tumor-specific peptide sequences resulting from sources such as somatic DNA mutations. Upon loading onto major histocompatibility complex (MHC) molecules, they can trigger recognition by T cells. Accurate neoantigen identification is thus critical for both designing cancer vaccines and predicting response to immunotherapies. Neoantigen identification and prioritization relies on correctly predicting whether the presenting peptide sequence can successfully induce an immune response. Because most somatic mutations are single-nucleotide variants, changes between wild-type and mutated peptides are typically subtle and require cautious interpretation. A potentially underappreciated variable in neoantigen prediction pipelines is the mutation position within the peptide relative to its anchor positions for the patient's specific MHC molecules. Whereas a subset of peptide positions are presented to the T cell receptor for recognition, others are responsible for anchoring to the MHC, making these positional considerations critical for predicting T cell responses. We computationally predicted anchor positions for different peptide lengths for 328 common HLA alleles and identified unique anchoring patterns among them. Analysis of 923 tumor samples shows that 6 to 38% of neoantigen candidates are potentially misclassified and can be rescued using allele-specific knowledge of anchor positions. A subset of anchor results were orthogonally validated using protein crystallography structures. Representative anchor trends were experimentally validated using peptide-MHC stability assays and competition binding assays. By incorporating our anchor prediction results into neoantigen prediction pipelines, we hope to formalize, streamline, and improve the identification process for relevant clinical studies.

Abstract 5639: Computational prediction of MHC anchor locations guide neoantigen prediction and prioritization

Abstract Neoantigens are novel peptide sequences resulting from somatic mutations in tumors that upon loading onto major histocompatibility complex (MHC) molecules allow recognition by T cells. Accurate neoantigen identification is thus critical for designing cancer vaccines and predicting response to immunotherapies. Neoantigen identification and prioritization relies on correctly inferring whether the presenting peptide sequence can successfully induce an immune response. As the majority of somatic mutations are SNVs, changes between wildtype and mutant peptide are subtle and require cautious interpretation. An important, yet underappreciated, variable in neoantigen-prediction pipelines is the mutation position within the peptide relative to its anchor positions for the patient’s specific HLA alleles. While a subset of peptide positions are presented to the T-cell receptor for recognition, others are responsible for anchoring to the MHC, making these positional considerations critical for predicting T-cell responses. However, a systematic method for determining anchor locations for the wide range of HLA alleles present in the population and application of these to evaluate MT/WT peptide pairs arising in tumors has not been reported. As a result, many neoantigen studies have either failed to adequately consider this crucial factor or have used conventional assumptions to guide their neoantigen identification process. Here, we provide a computational workflow for predicting anchor locations for a wide range of HLA alleles, using a reference dataset generated from clinical and The Cancer Genome Atlas (TCGA) patient samples. We calculated high probability anchor positions for different peptide lengths for over 300 common HLA alleles. Analysis of these results showed clusters of different anchor trends among the HLA alleles analyzed. A subset of these HLA anchor results were orthogonally validated using protein crystallography structures. Analysis of 923 tumor samples showed that 7-41% of neoantigen candidates were potentially misclassified in the neoantigen selection process and can be rescued using allele-specific knowledge of anchor positions. These anchor predictions are currently undergoing experimental validation using both peptide-MHC stability assays as well as fluorescence-based competition binding assays. By incorporating our anchor prediction results into neoantigen prediction pipelines, such as pVACtools, we hope to formalize and streamline the identification process for relevant clinical studies. Citation Format: Huiming Xia, Joshua McMichael, Michelle Becker-Hapak, Onyinyechi C. Onyeador, Rico Buchli, Ethan McClain, Patrick Pence, Suangson Supabphol, Megan M. Richters, Anamika Basu, Cody A. Ramirez, Cristina Puig-Saus, Kelsy C. Cotto, Jasreet Hundal, Susanna Kiwala, S. Peter Goedegebuure, Tanner M. Johanns, Gavin P. Dunn, Antoni Ribas, Christopher A. Miller, William Gillanders, Todd A. Fehniger, Obi L. Griffith, Malachi Griffith. Computational prediction of MHC anchor locations guide neoantigen prediction and prioritization [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5639.

Abstract 4413: Accurate neoantigen prediction depends on mutation position relative to patient-specific MHC anchor location

Abstract Neoantigens (neoAgs) are short peptide sequences resulting from somatic mutations specifically found in tumor populations. They can be loaded onto major histocompatibility complex (MHC) class I or II molecules to allow recognition by cytotoxic T cells. Accurate neoAg prediction is critical for the design of personalized vaccines and may improve prediction of response to immune checkpoint blockade therapy. The effectiveness of a neoAg-based vaccine relies in part on whether the sequence presented to T cells has previously been exposed to the immune system. Incorrectly selecting for wildtype (WT) peptides will result in susceptibility to central tolerance and potentially induce auto-immunity. As the vast majority of somatic mutations found are single nucleotide variants, changes between the WT and mutant (MT) peptide are subtle and must be interpreted cautiously. An important yet currently overlooked factor in neoAg predicting pipelines is the position of the mutation within the peptide relative to its anchor positions for the patient's human leukocyte antigen (HLA) alleles. Current pipelines consider simple filtering strategies (e.g. MT peptide IC50 < 500 nM and WT/MT binding affinity fold change (agretopicity) > 1); however, only a subset of positions on the loaded peptide sequence are presented to the T cell receptor for recognition, while other positions are responsible for anchoring to the MHC, making these positional considerations critical for predicting T cell responses. We have collected peptide data, through clinical collaborations and The Cancer Genome Atlas (TCGA), for over 200 commonly observed HLA alleles and computationally predicted high probability anchor positions with respect to different peptide lengths (8-11mers). We observed unique anchoring patterns among different HLA alleles, varying in sequence positions and number of anchoring locations within the binding groove. To demonstrate the importance of positional information on prioritization of neoAgs, we are additionally analyzing 1000 TCGA patient samples where potential neoAgs are filtered according to different criteria including: A) MT IC50 < 500 nM, B) MT IC50 < 500 nM and agretopicity > 1, C) MT IC50 < 500 nM with data-driven filtering based on peptide mutation position, MHC anchor position and WT IC50 value. The number of potentially misclassified neoAg candidates will be accessed using experimentally validated neoAg datasets. Currently, prediction pipelines have relatively low accuracy when prioritizing neoAgs for T cell response in patients. By accounting for additional positional information, we hope to significantly reduce the number of false positive neoAgs and increase prediction accuracy. Our anchor results will be implemented as a visualization guide for tumor immunogenomics boards for clinical trials and incorporated into our existing neoAg prioritization pipeline, pVACtools. Citation Format: Huiming Xia, Megan M. Richters, Cody A. Ramirez, Cristina Puig-Saus, Kelsy C. Cotto, Gavin P. Dunn, Todd Fehniger, Antoni Ribas, William E. Gillanders, Obi L. Griffith, Malachi Griffith. Accurate neoantigen prediction depends on mutation position relative to patient-specific MHC anchor location [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 4413.

Functional Recognition by CD8+ T Cells of Epitopes with Amino Acid Variations Outside Known MHC Anchor or T Cell Receptor Recognition Residues.

Peptide-based vaccines can be safer and more cost effective than whole organism vaccines. Previous studies have shown that inorganic polystyrene nanoparticles (PSNPs) covalently conjugated to the minimal immunodominant peptide epitope from murine liver stage malaria (SYIPSAEKI) induced potent CD8+ T cell responses. Many pathogens, including malaria, have polymorphic T cell epitope regions. Amino acid changes in positions that are contact residues for the T cell receptor (TCR) often alter the specific cross-reactivity induced by the peptide antigen, and it is largely assumed that changes outside of these residues have little impact. Herein, each amino acid residue (except major histocompatibility complex (MHC) anchors) was systematically changed to an alanine. Peptide epitopes with altered amino acids outside T cell contact residues were still recognized by T cells induced by PSNPs-SYIPSAEKI (KI) vaccines, albeit at lower levels, except for the variant SYIPSAAKI (A7). PSNPs-SYIPSAAKI vaccines further elicited high responses to the index KI peptide. None of the epitopes displayed altered peptide ligand (APL) antagonism in vitro, and re-stimulating SYIPSAEKI and SYIPSAAKI together synergistically enhanced IFN-γ production by the T cells. These results show epitope variation in non-TCR recognition residues can have effects on T cell reactivity, suggesting that such natural variation may also be driven by immune pressure. Additionally, when re-modelling peptides to enhance the cross-reactivity of vaccines, both TCR recognition and non-recognition residues should be considered.

Identification of an altered peptide ligand based on the endogenously presented, rheumatoid arthritis-associated, human cartilage glycoprotein-39(263–275) epitope: an MHC anchor variant peptide for immune modulation

We sought to identify an altered peptide ligand (APL) based on the endogenously expressed synovial auto-epitope of human cartilage glycoprotein-39 (HC gp-39) for modulation of cognate, HLA-DR4-restricted T cells. For this purpose we employed a panel of well-characterized T cell hybridomas generated from HC gp-39-immunized HLA-DR4 transgenic mice. The hybridomas all respond to the HC gp-39(263–275) epitope when bound to HLA-DR4(B1*0401) but differ in their fine specificities. First, the major histocompatibility complex (MHC) and T-cell receptor (TCR) contact residues were identified by analysis of single site substituted analogue peptides for HLA-DR4 binding and cognate T cell recognition using both T hybridomas and polyclonal T cells from peptide-immunized HLA-DR4 transgenic mice. Analysis of single site substituted APL by cognate T cells led to identification of Phe265 as the dominant MHC anchor. The amino acids Ala268, Ser269, Glu271 and Thr272 constituted the major TCR contact residues, as substitution at these positions did not affect HLA-DR4(B1*0401) binding but abrogated T cell responses. A structural model for visualisation of TCR recognition was derived. Second, a set of non-classical APLs, modified at the MHC key anchor position but with unaltered TCR contacts, was developed. When these APLs were analysed, a partial TCR agonist was identified and found to modulate the HC gp-39(263–275)-specific, pro-inflammatory response in HLA-DR4 transgenic mice. We identified a non-classical APL by modification of the p1 MHC anchor in a synovial auto-epitope. This APL may qualify for rheumatoid arthritis immunotherapy.

Enhanced major histocompatibility complex class I binding and immune responses through anchor modification of the non‐canonical tumour‐associated mucin 1‐8 peptide

Designing peptide-based vaccines for therapeutic applications in cancer immunotherapy requires detailed knowledge of the interactions between the antigenic peptide and major histocompatibility complex (MHC) in addition to that between the peptide-MHC complex and the T-cell receptor. Past efforts to immunize with high-affinity tumour-associated antigenic peptides have not been very immunogenic, which may be attributed to the lack of T cells to these peptides, having been deleted during thymic development. For this reason, low-to-medium affinity non-canonical peptides represent more suitable candidates. However, in addition to the difficulty in identifying such antigens, peptide binding to MHC, and hence its ability to induce a strong immune response, is limited. Therefore, to enhance binding to MHC and improve immune responses, anchor modifications of non-canonical tumour-associated peptides would be advantageous. In this study, the non-canonical tumour-associated peptide from MUC1, MUC1-8 (SAPDTRPA), was modified at the MHC anchor residues to SAPDFRPL (MUC1-8-5F8L) and showed enhanced binding to H-2Kb and improved immune responses. Furthermore, the crystal structure of MUC1-8-5F8L in complex with H-2Kb was determined and it revealed that binding of the peptide to MHC is similar to that of the canonical peptide OVA8 (SIINFEKL).

Structural analysis of two HLA-DR-presented autoantigenic epitopes: crucial role of peripheral but not central peptide residues for T-cell receptor recognition

Specific and major histocompatibility complex (MHC)-restricted T-cell recognition of antigenic peptides is based on interactions of the T-cell receptor (TCR) with the MHC alpha helices and solvent exposed peptide residues termed TCR contacts. In the case of MHC class II-presented peptides, the latter are located in the positions p2/3, p5 and p7/8 between MHC anchor residues. For numerous epitopes, peptide substitution studies have identified the central residue p5 as primary TCR contact characterized by very low permissiveness for peptide substitution, while the more peripheral positions generally represent auxiliary TCR contacts. In structural studies of TCR/peptide/MHC complexes, this has been shown to be due to intimate contact between the TCR complementarity determining region (CDR) three loops and the central peptide residue. We asked whether this model also applied to two HLA-DR presented epitopes derived from an antigen targeted in type 1 diabetes. Large panels of epitope variants with mainly conservative single substitutions were tested for human leukocyte antigen (HLA) class II binding affinity and T cell stimulation. Both epitopes bind with high affinity to the presenting HLA-DR molecules. However, in striking contrast to the standard distribution of TCR contacts, recognition of the central p5 residue displayed high permissiveness even for non-conservative substitutions, while the more peripheral p2 and p8 TCR contacts showed very low permissiveness for substitution. This suggests that intimate TCR interaction with the central peptide residue is not always required for specific antigen recognition and can be compensated by interactions with positions normally acting as auxiliary contacts.

Use of combinatorial peptide libraries to construct functional mimics of tumor epitopes recognized by MHC class I-restricted cytolytic T lymphocytes.

Identification of cytolytic T lymphocyte (CTL) epitopes presented by major histocompatibility complex (MHC) class I molecules on tumor cells is critical for the design of active immunotherapy. We describe the use of combinatorial peptide libraries with defined amino acids in two MHC anchor positions to search for epitopes that are recognized by H-2Db- and Kb-restricted CTL specific for the mouse lymphoma EL4. An iterative strategy was used for screening libraries in which 16 amino acids were divided into 3 groups and 3 subgroups: alpha (AL, VT, FY); beta (GS, P, DE); gamma (KR, H, NQ). The proportions of each group and subgroup at individual peptide positions were changed in the library synthesis, and the effect of these changes on CTL activity was measured in a sensitive RMA-S cell assay. A single H-2Db epitope mimic was deduced from the original library that contained > 2 x 10(8) potential peptides and was at least 9 logs more potent than the original library. Immunization of syngeneic mice with this peptide elicited CTL that lysed EL4 cells as well as RMA-S cells pulsed with peptides isolated from Db molecules of EL4 cells, indicating functional similarity between the mimicking peptide and the naturally processed CTL epitope. Furthermore, adoptive transfer of such a CTL line had a therapeutic effect in mice with EL4 established as an ascites tumor. Two H-2Kb-restricted epitope mimics of the same tumor were also identified. Our method represents a novel approach for the construction of MHC class I-restricted targets that can serve as immunogens for active immunotherapy of cancer.

Presentation of a horse cytochrome c peptide by multiple H-2b class I major histocompatibility complex (MHC) molecules to C57BL/6- and bm1-derived cytotoxic T lymphocytes: presence of a single MHC anchor residue may confer efficient peptide-specific CTL recognition.

In this study the immunogenic tryptic fragment from a horse cytochrome c (cyt c) digest recognized by cytotoxic T lymphocytes (CTL) induced by in vitro peptide stimulation from C57BL/6 (B6) and mutant B6.C-H-2bm1 (bm1) mice is identified. An identical sequence, p40-53, is recognized by CTL from both B6 and bm1 mice. In addition, both B6 bm1 cloned CTL lines display unusual major histocompatibility complex (MHC) class I-restricted recognition of this peptide in that they respond to it in the context of H-2Kb, H-2Db, and H-2Kbm1 class I molecules, although the sequence lacks the usual structural Kb and Db peptide-binding motifs. Truncated analogues which resemble the lengths of naturally processed MHC class I-presented peptides, confer reactivity for B6 and bm1 CTL against EL4 (H-2b) targets as well as the L cell transfectants, L+Kb, L+Db, and L+Kbm1. The antigenic peptide with the greatest potency is p41-49, which appears to be generated by angiotensin converting enzyme cleavage of the full-length p40-53 tryptic peptide. The minimum antigenic peptide recognized by both B6 and bm1 CTL, and which targets lysis on each of the transfectants, is the hexamer p43-48 peptide from horse cyt c. Residues Pro44 and Thr47, which occupy polymorphic positions with respect to other species-variant cyt c molecules, influence recognition of these peptides differently for the B6 and bm1 CTL. The ability of H-2Kb, H-2Db, and mutant H-2Kbm1 class I molecules to present the same peptide to a single cloned CTL is discussed in the context of current knowledge of peptide anchor residues and side chain-specific binding pockets in the MHC class I peptide-binding site.

Dissection of major histocompatibility complex (MHC) and T cell receptor contact residues in a Kb-restricted ovalbumin peptide and an assessment of the predictive power of MHC-binding motifs.

The effect of alanine substitution on the major histocompatibility complex (MHC) binding and T cell receptor recognition of the Kb-restricted ovalbumin 257-264 peptide was investigated. Positions 3, 5 and 8 of the octamer were important for Kb binding, as predicted from the motifs found in Kb-associated peptides, while mutations at positions 4, 6 and 7 affected cytotoxic T lymphocyte recognition. Substitutions at positions 1 and 2 had very minor effects on T cell recognition. In addition, we tested the capacity of sequence motifs to predict MHC binding by analysis of a series of peptides which all bear the minimal Kb motif. We found that possession of good motifs was not always sufficient to give strong MHC binding, indicating secondary effects of the residues flanking the "MHC anchor" positions.