VLP-mediated delivery of structure-selected neoantigens demonstrates immunogenicity and antitumoral activity in mice

Abstract

BackgroundNeoantigens are patient- and tumor-specific peptides that arise from somatic mutations. They stand as promising targets for personalized therapeutic cancer vaccines. The identification process for neoantigens has evolved with the use of next-generation sequencing technologies and bioinformatic tools in tumor genomics. However, in silico strategies for selecting immunogenic neoantigens still have very low accuracy rates, since they mainly focus on predicting peptide binding to Major Histocompatibility Complex (MHC) molecules, which is key but not the sole determinant for immunogenicity. MethodsWe developed a novel neoantigen selection pipeline based on existing software combined with a novel prediction method, the Neoantigen Optimization Algorithm (NOAH), which takes into account structural features of the peptide/MHC-I interaction in its prediction strategy. Moreover, to maximize neoantigens therapeutic potential, neoantigen-based vaccines should be manufactured in an optimal delivery platform that elicits robust de novo immune responses and bypasses central and peripheral tolerance. ResultsWe generated a highly immunogenic vaccine platform based on engineered HIV-1 Gag-based Virus-Like Particles (VLPs) expressing a high copy number of each in silico selected neoantigen. We tested different neoantigen-loaded VLPs (neoVLPs) in a B16-F10 melanoma mouse model to evaluate their capability to generate new immunogenic specificities. NeoVLPs were used in in vivo immunogenicity and tumor challenge experiments. ConclusionsNeoVLPs can promote the generation of de novo antitumor-specific immune responses, resulting in a delay in tumor growth. Vaccination with the neoVLP platform is a robust alternative to current therapeutic vaccine approaches and a promising candidate for future personalized immunotherapy. WHAT IS ALREADY KNOWN ON THIS TOPICIdentification of highly immunogenic neoantigens is still challenging, currently available pipelines base their prediction on MHC-I binding affinity. Moreover, neoantigen-based vaccine delivery needs to be improved to increase the potency of anti-tumor immune response. WHAT THIS STUDY ADDSNOAH is a novel pipeline for the identification and selection of neoantigens that combines binding affinity and structural features of the peptide/MHC-I interaction. Preclinical studies show highly immunogenic vaccine platform based on HIV-1 Gag based VLPs (neoVLPs) generates antitumor-specific immune responses, delaying tumor growth. HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICYThe combination of NOAH and neoVLP platform represents an alternative to current therapeutic vaccine approaches and a promising candidate for future personalized immunotherapy.