Mass spectrometry-based thermostability profiling of virus-derived MHC peptide complexes serves as an effective predictor of immunogenicity

The major histocompatibility complex (MHC) encodes molecules that present peptides on the surface of cells to stimulate T-cell-mediated immune responses. The stability of peptide-MHC class I complexes (pMHCI) has been postulated to influence the immunogenicity of virus-derived epitopes and cancer neoepitopes. Here, we sought to investigate this further by conducting thermostability profiling of thousands of individual pMHCI, including a panel of 110 vaccinia virus (VACV) derived peptides with known CD8 ⁺ T cell response profiles. The denaturation profiles of these peptides spanned thermostability (T _m ) ranges of 41.2°C to 65.1°C, and we found that thermostability correlated with immunogenicity in VACV-infected mice. We developed two machine learning-based models from these thermostability data to predict peptide immunogenicity and demonstrate the ability of this model to distinguish immunogenic epitopes derived from an unrelated infectious pathogen, influenza A virus in mice. Using such models, we provide evidence that the thermostability of pMHCI allows for improved prediction of immunogenic CD8 ⁺ T cell epitopes and conclude that this information is a valuable measurement for selecting optimal targets for T cell-mediated therapies and vaccine design.