Structural modeling of neoantigen presentation for rational design of heteroclitic neoepitope vaccines

项目总结

Project Summary Pancreatic ductal adenocarcinoma cancer (PDAC) is highly resistant to frontline surgical resection and chemotherapy treatments. Many treatment-resistant cancer types have benefited from immunotherapies that activate cytotoxic anti-tumor T cells against the somatic mutations, or neoantigens, expressed in cancer cells. One major challenge to the development of neoantigen-targeted immunotherapy for PDAC has been the low number and weakly immunogenic profile of identified neoantigens. Efficient activation of neoantigen-specific T cells is dependent on the recognition of 8- to 11-mer neoepitopes displayed on human leukocyte antigen (HLA) class I molecules. This recognition is the culmination of the biophysical and stereochemical contacts between the peptide, HLA, and T cell receptor (TCR) molecules. One mechanism to improve neoepitope immunogenicity is by modifying the peptide amino acid residues to enhance HLA binding or TCR recognition, thereby enhancing cognate T cell activation, while conserving reactivity to the parental epitope. These modified epitopes are termed heteroclitic epitopes. However, the stereochemical features of heteroclitic epitopes that enhance HLA binding or TCR recognition are understudied. Additionally, heteroclitic epitopes have been explored in the context of a limited number of HLA subtypes, restricting their development and application across patients. We hypothesize that rational design of heteroclitic neoepitope vaccines through structural modelling will improve T cell responses against PDAC neoantigens. To address this hypothesis, we will define the structural binding and spatial display dynamics of both shared and private PDAC heteroclitic neoepitopes in diverse HLAs. Among shared neoantigens expressed in PDAC, activating mutations in KRAS at codon 12 are present in up to 80% of PDAC tumors. In Specific Aim 1, we will interrogate the structural mechanics and immunogenic profile of heteroclitic KRAS G12D/V/C epitopes in a panel of 18, globally representative HLA subtypes. In Specific Aim 2, we will develop a computational pipeline to identify, prioritize and optimize patient- specific heteroclitic neoantigen vaccine candidates based on structural epitope features. We will use HLA binding measurements and T cell reactivity assays to validate immunogenic features of our computationally modelled heteroclitic epitopes. Together, these aims will define the structural features of immunogenic neoantigens in diverse HLAs, generate heteroclitic epitope vaccine candidates for shared and private PDAC antigens, and improve the therapeutic potential of cancer vaccines for hard-to-treat cancers such as PDAC.