T cell receptor (TCR) restriction by highly polymorphic major histocompatibility complex (MHC) proteins is a foundation of cellular immunity. Although the effects of MHC polymorphisms on peptide binding and selection are well established, how micropolymorphisms within MHC supertypes impact immune recognition is poorly understood. Here, we identified a mechanism through which the micropolymorphisms in two closely related HLA-A3 superfamily members govern TCR specificity. We previously showed that TCRs specific for a public neoantigen arising from a PIK3CA oncogenic hotspot mutation restricted by HLA-A*03:01 were unable to recognize the same epitope in the context of HLA-A*03:02 despite equivalent processing and presentation by both alleles. We found here that the two micropolymorphisms distinguishing A*03:02 from A*03:01 prevent TCR binding not by altering peptide binding or static structures, but by altering the conformational ensemble of the neoantigen, preventing it from adopting a binding-permissive state. The effect is rooted in how the two polymorphic sites interact with other covarying, evolutionarily coupled polymorphisms, reflecting a cross-groove network of interactions that controls the conformational adaptability of the peptide/HLA complex. We suggest polymorphism-dependent adaptability reflects an evolved feature of class I MHC proteins, further diversifying epitopes and contributing to how TCRs and other immunoreceptors differentiate between antigens. Beyond this mechanistic insight, our findings emphasize the need for high-resolution HLA typing in efforts across immunology, including antigen-specific immunotherapy.

T cell receptor (TCR) recognition of peptide/MHC complexes is fundamental for adaptive immunity. Many studies have described the importance of peptide/MHC motion or dynamics in TCR recognition. A role for dynamics in recognition intersects with the concept of dynamic allostery, which describes how alterations to a protein's energy landscape and thus motions influence function, often in the absence of conformational changes. Tuning of MHC protein energy landscapes by different peptides has clearly been shown. Evidence is mounting, however, that MHC polymorphisms also alter the protein's energy landscape. Here, we address this concept, summarizing findings that suggest that, in addition to dictating peptide binding and selection, naturally occurring variations within MHC proteins promote differential peptide and protein dynamics, altering TCR recognition in an MHC allele-dependent manner. We hypothesize that MHC polymorphisms have been selected evolutionarily in part to tune the protein's dynamic response, altering immune specificity and further diversifying immune responses across populations.

Abstract Neoantigens (NeoAgs) are a critical class of human cancer rejection antigens. The vast majority arise from random passenger mutations unique to a single individual, which limits the systematic study of the molecular basis of NeoAg immunogenicity in patients. In contrast, “public” NeoAg are clonally conserved epitopes derived from recurrently mutated driver genes that are shared among patients. In this study, we developed of a unique research platform to perform a comprehensive structural, biophysical, genetic, and immunogenic analysis of a family of shared NeoAgs derived from mutant NRAS Q61, the second most prevalent RAS mutation. We combined a mass-spectrometry screen, x-ray crystallography, dextramer-based T cell detection, single cell TCRa/b-sequencing, and functional immune validation assays to determine the immunogenicity of NRAS(Q61) epitopes. From our mass-spectrometry screen, we discovered that neoepitopes derived from the three most common NRAS(Q61) hotspot substitutions (R, K, and L) are naturally processed and presented in HLA-A*01, thereby generating a family of public NeoAgs. By resolving the x-ray structures of the mutant pep/HLA complexes and their wild-type counterpart, we established that each hotspot substitution “untethers” a TCR contact residue from the side wall of HLA, increasing solvent exposure of the mutated residue and facilitating immune recognition. We subsequently performed immune monitoring of peripheral blood and tumor samples from n=47 HLA-A*01+ patients with an NRAS(Q61) mutated cancer, the largest biorepository from patients who express an identical NeoAg ever assembled. Detectable NRAS public NeoAg-specific T cell responses were observed across all hotspot substitutions; however, the proportion of patients who developed a response correlated with the relative hydrophobicity of the mutant sidechains (L>R>K). In addition, we found that exposure to immune checkpoint blockade, but not tumor mutational burden, was significantly correlated with the detection and clonal dynamics of CD8+ T cells reactive to NRAS NeoAgs. Using single-cell sequencing, we retrieved, functionally validated, and characterized a panel of n=30 TCRs from patient samples that specifically confer recognition to cancer cells expressing NRAS Q61 public NeoAgs. Each of these TCRs display high functional-avidity and function in a CD8 co-receptor independent manner. Moreover, a subset of TCRs demonstrate therapeutic “cross-protection” in vitro and in vivo towards multiple NRAS Q61 mutated variants, allowing a single receptor to provide therapeutic coverage for >90% of NRAS mutations. Importantly, cross-protective TCRs were not more likely to be cross-reactive to normal human proteins compared with TCRs that recognize a single NRAS hotspot substitution. Together, these findings reveal that NRAS mutations give rise to immunogenic public NeoAgs that can be studied across patients. Further, our data helps establish generalizable principles regarding NeoAg immunogenicity while also providing a therapeutically actionable target for a TCR-based approach. Citation Format: Inaki Etxeberria, Gihan Perera, Olga Lyudovyk, Smita Chandran, Lauren Banks, Michael Gormally, Michael Postow, Taha Merghoub, Jedd Wolchok, Benjamin Greenbaum, Brian Baker, Christopher Klebanoff. Immunogenic landscape and therapeutic targeting of mutant NRAS ”public” neoantigens [abstract]. In: Proceedings of the AACR IO Conference: Discovery and Innovation in Cancer Immunology: Revolutionizing Treatment through Immunotherapy; 2025 Feb 23-26; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Immunol Res 2025;13(2 Suppl):Abstract nr PR011.

The inherent antigen cross-reactivity of the T cell receptor (TCR) is balanced by high specificity. Surprisingly, TCR specificity often manifests in ways not easily interpreted from static structures. Here we show that TCR discrimination between an HLA-A*03:01 (HLA-A3)-restricted public neoantigen and its wild-type (WT) counterpart emerges from distinct motions within the HLA-A3 peptide binding groove that vary with the identity of the peptide’s first primary anchor. These motions create a dynamic gate that, in the presence of the WT peptide, impedes a large conformational change required for TCR binding. The neoantigen is insusceptible to this limiting dynamic, and, with the gate open, upon TCR binding the central tryptophan can transit underneath the peptide backbone to the opposing side of the HLA-A3 peptide binding groove. Our findings thus reveal a novel mechanism driving TCR specificity for a cancer neoantigen that is rooted in the dynamic and allosteric nature of peptide/MHC-I binding grooves, with implications for resolving long-standing and often confounding questions about T cell specificity. While static structures can provide insight into T cell receptor (TCR) antigen specificity, this often fails and auxiliary information is needed. Here the authors show, by focusing on an HLA-A3-bound neoantigen and its WT counterpart, the allosteric formation of a peptide-dependent dynamic gate that permits selective TCR recognition of a neoantigen.

Insertion or deletion of one or two base pairs within a coding region causes a frameshift, which has the potential to generate neoepitopes (InDel-generated neoepitopes) that lack a self-counterpart and are entirely novel. Despite the obvious appeal of InDel-generated neoepitopes, and the demonstration of such candidate neoepitopes that can elicit a CD8 T-cell response, no InDel-generated neoepitopes that actually control tumors in vivo have been reported thus far. Here, in a mouse colon carcinoma line, we identify 11 InDels, only one of which generates a neoepitope that elicits tumor control in vivo in models of prophylaxis as well as therapy. Although this neoepitope has no self-counterpart, it has a low affinity (IC50 33,937.60 nM) for its MHC I allele. Despite its low affinity for MHC I, this neoepitope elicits antitumor activity in vivo through CD8 T cells. Furthermore, CD8 T cells elicited by this InDel-generated neoepitope, like the neoepitopes created by point mutations, show notably less exhaustion than classical immunogenic epitopes. Ironically, this InDel-generated neoepitope follows the same rules as noted for most of the tumor control–mediating neoepitopes generated by point mutations that have a poor affinity for MHC I alleles.

Background Challenges in predicting which neoantigens mediate tumor rejection limit the efficacy of neoantigen vaccines to treat cancers, especially for cancers with a high mutational burden like cutaneous squamous cell carcinoma (cSCC). Only a small portion of neoantigens prioritized by current methods elicit effective T cell responses, demonstrating the critical need for improved criteria for the prediction of tumor-rejecting neoantigens.Methods Publicly available human cSCC datasets were used to assess the frequency of shared mutations between patients. A transplantable ultraviolet light-induced mouse model of cSCC was generated. The mutational signature and driver mutations in the mouse model were compared with human tumors. Neoantigens were prioritized in the mouse model, and tumor-rejecting neoantigens were identified through (enzyme-linked immunosorbent spot (ELISpot) and in vivo prophylactic vaccination. Binding of the neoantigens and corresponding wild-type peptides to major histocompatibility complex (MHC) class I was determined. Structural modeling of peptide:MHC complexes was performed to assess for changes in structural characteristics of the neoantigens relative to the wild-type peptides.Results A minority of human cSCC tumors shared neoantigens. The mouse cSCC model recapitulated the mutational signature and driver mutations found in human disease and was constrained by CD8 T cells. Two MHC class I neoantigens were identified in the mouse model that constrained cSCC growth. One tumor-rejecting neoantigen exhibited improved MHC binding, and the other had increased solvent accessibility of the mutated residue, compared with wild-type. Across known neoantigens that do not impact MHC binding, increased exposure of the mutated residue distinguished tumor-rejecting from non-immunogenic neoantigens.Conclusions Given the paucity of shared mutations, this work supports the need for personalized neoantigen vaccines in cSCC. To facilitate further discovery, we provide a clinically relevant mouse cSCC model with two defined neoantigens that mediate tumor rejection. Structural changes in the exposure of features that promote T cell receptor recognition defined tumor-rejecting neoantigens. Incorporation of structural modeling to predict changes in T cell receptor accessibility is anticipated to improve the selection of neoantigens for inclusion in personalized cancer vaccines.

A healthy immune system is tolerant to self-antigens while maintaining responsiveness to foreign threats. Co-expression of the inhibitory receptors PD-1 and CD73 regulates tolerance by restricting the expansion of auto-reactive CD4+ T cells independently of thymic selection.

CD8+ T cells are crucial for viral elimination and recovery from viral infection. Nonetheless, the current understanding of the T cell response to SARS-CoV-2 at the antigen level remains limited. The Spike protein is an external structural protein that is prone to mutations, threatening the efficacy of current vaccines. Therefore, we have characterised the immune response towards the immunogenic Spike-derived peptide (S976-984, VLNDILSRL), restricted to the HLA-A*02:01 molecule, which is mutated in both Alpha (S982A) and Omicron BA.1 (L981F) variants of concern. We determined that the mutation in the Alpha variant (S982A) impacted both the stability and conformation of the peptide, bound to HLA-A*02:01, in comparison to the original S976-984. We identified a longer and overlapping immunogenic peptide (S975-984, SVLNDILSRL) that could be presented by HLA-A*02:01, HLA-A*11:01 and HLA-B*13:01 allomorphs. We showed that S975-specific CD8+ T cells were weakly cross-reactive to the mutant peptides despite their similar conformations when presented by HLA-A*11:01. Altogether, our results show that the impact of SARS-CoV-2 mutations on peptide presentation is HLA allomorph-specific, and that post vaccination there are T cells able to react and cross-react towards the variant of concern peptides.

Major histocompatibility complex (MHC) proteins present peptides on the cell surface for T cell surveillance. Reliable in silico prediction of which peptides would be presented and which T cell receptors would recognize them is an important problem in structural immunology. Here, we introduce an AlphaFold-based pipeline for predicting the three-dimensional structures of peptide-MHC complexes for class I and class II MHC molecules. Our method demonstrates high accuracy, outperforming existing tools in class I modeling accuracy and class II peptide register prediction. We validate its performance and utility with new experimental data on a recently described cancer neoantigen/wild-type peptide pair and explore applications toward improving peptide-MHC binding prediction.

Editorial: Quantification and prediction of T-cell cross-reactivity through experimental and computational methods

SARS-CoV-2 infection can induce multisystem inflammatory syndrome in children, which resembles superantigen-induced toxic shock syndrome. Recent work has suggested that the SARS-CoV-2 spike (S) protein could act as a superantigen by binding T cell receptors (TCRs) and inducing broad antigen-independent T cell responses. Structure-based computational modeling identified potential TCR-binding sites near the S receptor-binding domain, in addition to a site with homology to known neurotoxins. We experimentally examined the mechanism underpinning this theory—the direct interaction between the TCR and S protein. Surface plasmon resonance of recombinantly expressed S protein and TCR revealed no detectable binding. Orthogonally, we pseudotyped lentiviruses with SARS-CoV-2 S in both wild-type and prefusion-stabilized forms, demonstrated their functionality in a cell line assay, and observed no transduction, activation, or stimulation of proliferation of CD8 + T cells. We conclude that it is unlikely that the SARS-CoV-2 spike protein engages nonspecifically with TCRs or has superantigenic character.

Development of T cell receptors (TCRs) as immunotherapeutics is hindered by inherent TCR cross-reactivity. Engineering more specific TCRs has proven challenging, as unlike antibodies, improving TCR affinity does not usually improve specificity. Although various protein design approaches have been explored to surmount this, mutations in TCR binding interfaces risk broadening specificity or introducing new reactivities. Here we explored if TCR specificity could alternatively be tuned through framework mutations distant from the interface. Studying the 868 TCR specific for the HIV SL9 epitope presented by HLA-A2, we used deep mutational scanning to identify a framework mutation above the mobile CDR3β loop. This glycine to proline mutation had no discernable impact on binding affinity or functional avidity towards the SL9 epitope but weakened recognition of SL9 escape variants and led to fewer responses in a SL9-derived positional scanning library. In contrast, an interfacial mutation near the tip of CDR3α that also did not impact affinity or functional avidity towards SL9 weakened specificity. Simulations indicated that the specificity-enhancing mutation functions by reducing the range of loop motions, limiting the ability of the TCR to adjust to different ligands. Although our results are likely to be TCR dependent, using framework engineering to control TCR loop motions may be a viable strategy for improving the specificity of TCR-based immunotherapies.

Recognition of antigens by T cell receptors (TCRs) is a key component of adaptive immunity. Understanding the structures of these TCR interactions provides major insights into immune protection and diseases, and enables design of therapeutics, vaccines and predictive modeling algorithms. Previously, we released TCR3d, a database and resource for structures of TCRs and their recognition. Due to the growth of available structures and categories of complexes, the content of TCR3d has expanded substantially in the past 5 years. This expansion includes new tables dedicated to TCR mimic antibody complex structures, TCR-CD3 complexes and annotated Class I and II peptide-MHC complexes. Additionally, tools are available for users to calculate docking geometries for input TCR and TCR mimic complex structures. The core tables of TCR-peptide-MHC complexes have grown by 50%, and include binding affinity data for experimentally determined structures. These major content and feature updates enhance TCR3d as a resource for immunology, therapeutics and structural biology research, and enable advanced approaches for predictive TCR modeling and design. TCR3d is available at: https://tcr3d.ibbr.umd.edu. Graphical Abstract

Challenges in identifying tumor-rejecting neoantigens limit the efficacy of neoantigen vaccines to treat cancers, including cutaneous squamous cell carcinoma (cSCC). A minority of human cSCC tumors shared neoantigens, supporting the need for personalized vaccines. Using a UV-induced mouse cSCC model which recapitulated the mutational signature and driver mutations found in human disease, we found that CD8 T cells constrain cSCC. Two MHC class I neoantigens were identified that constrained cSCC growth. Compared to the wild-type peptides, one tumor-rejecting neoantigen exhibited improved MHC binding and the other had increased solvent accessibility of the mutated residue. Across known neoantigens that do not impact MHC binding, structural modeling of the peptide/MHC complexes indicated that increased solvent accessibility, which will facilitate TCR recognition of the neoantigen, distinguished tumor-rejecting from non-immunogenic neoantigens. This work reveals characteristics of tumor-rejecting neoantigens that may be of considerable importance in identifying optimal vaccine candidates in cSCC and other cancers.

Identification of neoepitopes that can control tumor growth in vivo remains a challenge even 10 y after the first genomics-defined cancer neoepitopes were identified. In this study, we identify a neoepitope, resulting from a mutation in the junction plakoglobin (Jup) gene (chromosome 11), from the mouse colon cancer line MC38-FABF (C57BL/6). This neoepitope, Jup mutant (JupMUT), was detected during mass spectrometry of MHC class I-eluted peptides from the tumor. JupMUT has a predicted binding affinity of 564 nM for the Kb molecule and a higher predicted affinity of 82 nM for Db. However, whereas structural modeling of JupMUT and its unmutated counterpart Jup wild-type indicates that there are little conformational differences between the two epitopes bound to Db, large structural divergences are predicted between the two epitopes bound to Kb. Together with in vitro binding data with RMA-S cells, these data suggest that Kb rather than Db is the relevant MHC class I molecule of JupMUT. Immunization of naive C57BL/6 mice with JupMUT elicits CD8-dependent tumor control of a MC38-FABF challenge. Despite the CD8 dependence of JupMUT-mediated tumor control in vivo, CD8+ T cells from JupMUT-immunized mice do not produce higher levels of IFN-γ than do naive mice. The structural and immunological characteristics of JupMUT are substantially different from those of many other neoepitopes that have been shown to mediate tumor control.

Neoepitopes arising from amino acid substitutions due to single nucleotide polymorphisms are targets of T cell immune responses to cancer and are of significant interest in the development of cancer vaccines. However, understanding the characteristics of rare protective neoepitopes that truly control tumor growth has been a challenge, due to their scarcity as well as the challenge of verifying true, neoepitope-dependent tumor control in humans. Taking advantage of recent work in mouse models that circumvented these challenges, here, we compared the structural and physical properties of neoepitopes that range from fully protective to immunologically inactive. As neoepitopes are derived from self-peptides that can induce immune tolerance, we studied not only how the various neoepitopes differ from each other but also from their wild-type counterparts. We identified multiple features associated with protection, including features that describe how neoepitopes differ from self as well as features associated with recognition by diverse T cell receptor repertoires. We demonstrate both the promise and limitations of neoepitope structural analysis and predictive modeling and illustrate important aspects that can be incorporated into neoepitope prediction pipelines.

IntroductionSignificant evidence suggests a connection between transplant rejection and the presence of high levels of pre-existing memory T cells. Viral infection can elicit viral-specific memory T cells that cross-react with allo-MHC capable of driving allograft rejection in mice. Despite these advances, and despite their critical role in transplant rejection, a systematic study of allo-reactive memory T cells, their specificities, and the role of cross-reactivity with viral antigens has not been performed.MethodsHere, we established a model to identify, isolate, and characterize cross-reactive T cells using Nur77 reporter mice (C57BL/6 background), which transiently express GFP exclusively upon TCR engagement. We infected Nur77 mice with lymphocytic choriomeningitis virus (LCMV-Armstrong) to generate a robust memory compartment, where quiescent LCMV-specific memory CD8+ T cells could be readily tracked with MHC tetramer staining. Then, we transplanted LCMV immune mice with allogeneic hearts and monitored expression of GFP within MHC-tetramer defined viral-specific T cells as an indicator of their ability to cross-react with alloantigens.ResultsStrikingly, prior LCMV infection significantly increased the kinetics and magnitude of rejection as well as CD8+ T cell recruitment into allogeneic, but not syngeneic, transplanted hearts, relative to non-infected controls. Interestingly, as early as day 1 after allogeneic heart transplant an average of ~8% of MHC-tetramer+ CD8+ T cells expressed GFP, in contrast to syngeneic heart transplants, where the frequency of viral-specific CD8+ T cells that were GFP+ was <1%. These data show that a significant percentage of viral-specific memory CD8+ T cells expressed T cell receptors that also recognized alloantigens in vivo. Notably, the frequency of cross-reactive CD8+ T cells differed depending upon the viral epitope. Further, TCR sequences derived from cross-reactive T cells harbored distinctive motifs that may provide insight into cross-reactivity and allo-specificity.DiscussionIn sum, we have established a mouse model to track viral-specific, allo-specific, and cross-reactive T cells; revealing that prior infection elicits substantial numbers of viral-specific T cells that cross-react to alloantigen, respond very early after transplant, and may promote rapid rejection.