VLPs generated by the fusion of RSV-F or hMPV-F glycoprotein to HIV-Gag show improved immunogenicity and neutralizing response in mice.

Respiratory syncytial virus (RSV) and human metapneumovirus (hMPV) vaccines have been long overdue. Structure-based vaccine design created a new momentum in the last decade, and the first RSV vaccines have finally been approved in older adults and pregnant individuals. These vaccines are based on recombinant stabilized pre-fusion F glycoproteins administered as soluble proteins. Multimeric antigenic display could markedly improve immunogenicity and should be evaluated in the next generations of vaccines. Here we tested a new virus like particles-based vaccine platform which utilizes the direct fusion of an immunogen of interest to the structural human immunodeficient virus (HIV) protein Gag to increase its surface density and immunogenicity. We compared, in mice, the immunogenicity of RSV-F or hMPV-F based immunogens delivered either as soluble proteins or displayed on the surface of our VLPs. VLP associated F-proteins showed better immunogenicity and induced superior neutralizing responses. Moreover, when combining both VLP associated and soluble immunogens in a heterologous regimen, VLP-associated immunogens provided added benefits when administered as the prime immunization.

Virus-like particle-mediated delivery of structure-selected neoantigens demonstrates immunogenicity and antitumoral activity in mice.

BACKGROUND: Neoantigens 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. Moreover, the therapeutic potential of neoantigen-based vaccines may be enhanced using an optimal delivery platform that elicits robust de novo immune responses. METHODS: We 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, as well as the interaction between the peptide/MHC-I complex and the TCR, 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. RESULTS: We 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. CONCLUSIONS: Our results indicate the relevance of incorporating other immunogenic determinants beyond the binding of neoantigens to MHC-I. Thus, neoVLPs loaded with neoantigens enhancing the interaction with the TCR 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.

Exploring FeLV-Gag-Based VLPs as a New Vaccine Platform-Analysis of Production and Immunogenicity.

Feline leukemia virus (FeLV) is one of the most prevalent infectious diseases in domestic cats. Although different commercial vaccines are available, none of them provides full protection. Thus, efforts to design a more efficient vaccine are needed. Our group has successfully engineered HIV-1 Gag-based VLPs that induce a potent and functional immune response against the HIV-1 transmembrane protein gp41. Here, we propose to use this concept to generate FeLV-Gag-based VLPs as a novel vaccine strategy against this retrovirus. By analogy to our HIV-1 platform, a fragment of the FeLV transmembrane p15E protein was exposed on FeLV-Gag-based VLPs. After optimization of Gag sequences, the immunogenicity of the selected candidates was evaluated in C57BL/6 and BALB/c mice, showing strong cellular and humoral responses to Gag but failing to generate anti-p15E antibodies. Altogether, this study not only tests the versatility of the enveloped VLP-based vaccine platform but also sheds light on FeLV vaccine research.

An engineered HIV-1 Gag-based VLP displaying high antigen density induces strong antibody-dependent functional immune responses.

Antigen display on the surface of Virus-Like Particles (VLPs) improves immunogenicity compared to soluble proteins. We hypothesised that immune responses can be further improved by increasing the antigen density on the surface of VLPs. In this work, we report an HIV-1 Gag-based VLP platform engineered to maximise the presence of antigen on the VLP surface. An HIV-1 gp41-derived protein (Min), including the C-terminal part of gp41 and the transmembrane domain, was fused to HIV-1 Gag. This resulted in high-density MinGag-VLPs. These VLPs demonstrated to be highly immunogenic in animal models using either a homologous (VLP) or heterologous (DNA/VLP) vaccination regimen, with the latter yielding 10-fold higher anti-Gag and anti-Min antibody titres. Despite these strong humoral responses, immunisation with MinGag-VLPs did not induce neutralising antibodies. Nevertheless, antibodies were predominantly of an IgG2b/IgG2c profile and could efficiently bind CD16-2. Furthermore, we demonstrated that MinGag-VLP vaccination could mediate a functional effect and halt the progression of a Min-expressing tumour cell line in an in vivo mouse model.