The development of immunological therapies that incorporate peptide antigens presented to T cells by MHC proteins is a long sought-after goal, particularly for cancer, where mutated neoantigens are being explored as personalized cancer vaccines. Although neoantigens can be identified through sequencing, bioinformatics and mass spectrometry, identifying those which are immunogenic and able to promote tumor rejection remains a significant challenge. Here we examined the potential of high-resolution structural modeling followed by energetic scoring of structural features for predicting neoantigen immunogenicity. After developing a strategy to rapidly and accurately model nonameric peptides bound to the common class I MHC protein HLA-A2, we trained a neural network on structural features that influence T cell receptor (TCR) and peptide binding energies. The resulting structurally-parameterized neural network outperformed methods that do not incorporate explicit structural or energetic properties in predicting CD8 + T cell responses of HLA-A2 presented nonameric peptides, while also providing insight into the underlying structural and biophysical mechanisms governing immunogenicity. Our proof-of-concept study demonstrates the potential for structure-based immunogenicity predictions in the development of personalized peptide-based vaccines.

Neoepitopes are the only truly tumor-specific antigens. Although potential neoepitopes can be readily identified using genomics, the neoepitopes that mediate tumor rejection constitute a small minority, and there is little consensus on how to identify them. Here, for the first time to our knowledge, we use a combination of genomics, unbiased discovery mass spectrometry (MS) immunopeptidomics, and targeted MS to directly identify neoepitopes that elicit actual tumor rejection in mice. We report that MS-identified neoepitopes are an astonishingly rich source of tumor rejection-mediating neoepitopes (TRMNs). MS has also demonstrated unambiguously the presentation by MHC I, of confirmed tumor rejection neoepitopes that bind weakly to MHC I; this was done using DCs exogenously loaded with long peptides containing the weakly binding neoepitopes. Such weakly MHC I–binding neoepitopes are routinely excluded from analysis, and our demonstration of their presentation, and their activity in tumor rejection, reveals a broader universe of tumor-rejection neoepitopes than presently imagined. Modeling studies show that a mutation in the active neoepitope alters its conformation such that its T cell receptor–facing surface is substantially altered, increasing its exposed hydrophobicity. No such changes are observed in the inactive neoepitope. These results broaden our understanding of antigen presentation and help prioritize neoepitopes for personalized cancer immunotherapy.

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T cell receptors (TCRs) have emerged as a new class of immunological therapeutics. However, though antigen specificity is a hallmark of adaptive immunity, TCRs themselves do not possess the high specificity of monoclonal antibodies. Although a necessary function of T cell biology, the resulting cross-reactivity presents a significant challenge for TCR-based therapeutic development, as it creates the potential for off-target recognition and immune toxicity. Efforts to enhance TCR specificity by mimicking the antibody maturation process and enhancing affinity can inadvertently exacerbate TCR cross-reactivity. Here we demonstrate this concern by showing that even peptide-targeted mutations in the TCR can introduce new reactivities against peptides that bear similarity to the original target. To counteract this, we explored a novel structure-guided approach for enhancing TCR specificity independent of affinity. Tested with the MART-1-specific TCR DMF5, our approach had a small but discernible impact on cross-reactivity toward MART-1 homologs yet was able to eliminate DMF5 cross-recognition of more divergent, unrelated epitopes. Our study provides a proof of principle for the use of advanced structure-guided design techniques for improving TCR specificity, and it suggests new ways forward for enhancing TCRs for therapeutic use.

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