{
  "abstract": "Background Cytotoxic T cell responses are critical in the control of cancer and viral infections and are targets of next generation therapeutic and prophylactic vaccines. Inducing robust and varied responses is challenging due to the diversity of MHC Class I molecules within a species and across species. We have used computational modeling and orthogonal in vivo studies in mice to demonstrate the unique potency and mechanism of action of mRNA/lipid nanoparticle vaccines to establish rules for the design of polyepitope vaccines targeting cytotoxic T cell.Methods Computational software suites were developed to condense MHC diversity and optimize vaccine design to allow for a better understanding of the impact of MHC polymorphisms on mRNA vaccine immunogenicity. Studies in both inbred and outbred mice were used to test the predictions of the computational models. Polyepitope mRNA/lipid nanoparticle vaccine formulations provided the platform to compare neoantigen responses to those against viral and xenogeneic antigens.Results Innovac’s computational modeling revealed that Human Leukocyte Antigen diversity could be reduced to less than 100 HLA-A and -B types to cover 99.9% of the population such that vaccines could be designed to be universal by increasing the number of predicted HLA binding epitopes in the vaccine. Using polyepitope vaccines containing 50 different predicted epitopes and encoding an artificial protein of ~150 KD the models predictions were tested using both inbred and outbred mice. The models predicted that with mRNA vaccine constructs of this size the average number of unique T cell responses would be ~40% or 20 positive epitopes per individual regardless of HLA type. Testing these hypotheses in mice confirmed the computational predictions despite the fact that they were not designed or optimized to overcome murine MHC diversity.Conclusions The results demonstrate that the MHC Class I system is highly conserved across species and the number and diversity of amino acids encoded in a polyepitope vaccine determine the number and diversity of T cell responses in predictable ways. Xenogeneic and viral responses were more robust than those for neoantigens (usually characterized by a single amino acid change from self) but the frequencies of neoantigen T cell responses were strikingly similar to those for viral/xenogeneic antigens when computational software is used to triage neoantigens for the MHC type of the mouse. These findings provide a generalizable framework for optimizing personalized cancer vaccine design and predicting frequencies of T cell responses expected for each patient.",
  "authors": [
    {
      "affiliations": [
        "Innovac Therapeutics, Somerville, MA, USA"
      ],
      "name": "Monia Draghi"
    },
    {
      "affiliations": [
        "Innovac Therapeutics, Somerville, MA, USA"
      ],
      "name": "Benjamin Breton"
    },
    {
      "affiliations": [
        "Innovac Therapeutics, Somerville, MA, USA"
      ],
      "name": "Vincent Luczkow"
    },
    {
      "affiliations": [
        "Innovac Therapeutics, Somerville, MA, USA"
      ],
      "name": "Rose J Lewis"
    },
    {
      "affiliations": [
        "Innovac Therapeutics, Hangzhou, Zhejiang, China"
      ],
      "name": "Xinrui Zhou"
    },
    {
      "affiliations": [
        "Innovac Therapeutics, Hangzhou, Zhejiang, China"
      ],
      "name": "Ying Tang"
    },
    {
      "affiliations": [
        "Innovac Therapeutics, Hangzhou, Zhejiang, China"
      ],
      "name": "Hongjun Chen"
    },
    {
      "affiliations": [
        "Innovac Therapeutics, Hangzhou, Zhejiang, China"
      ],
      "name": "Yue Ouyang"
    },
    {
      "affiliations": [
        "Innovac Therapeutics, Hangzhou, Zhejiang, China"
      ],
      "name": "Bing Zhao"
    },
    {
      "affiliations": [
        "Innovac Therapeutics, Hangzhou, Zhejiang, China"
      ],
      "name": "Hang Yuan"
    },
    {
      "affiliations": [
        "Innovac Therapeutics, Hangzhou, Zhejiang, China"
      ],
      "name": "Chi Zhang"
    },
    {
      "affiliations": [
        "Innovac Therapeutics, Somerville, MA, USA"
      ],
      "name": "Nicholas M Valiante"
    }
  ],
  "title": "822 Computational modeling to overcome MHC diversity and drive potent and diverse neoantigen and viral antigen specific killer T cell responses",
  "uid": "19815b4c-c0ba-5055-a87b-95ba134dd6d6"
}