MuSyC dosing of adjuvanted cancer vaccines optimizes antitumor responses

A Cancer Nanovaccine for Co-Delivery of Peptide Neoantigens and Optimized Combinations of STING and TLR4 Agonists

Immune checkpoint blockade (ICB) has revolutionized cancer treatment and led to complete and durable responses, but only for a minority of patients. Resistance to ICB can largely be attributed to insufficient number and/or function of antitumor CD8+ T cells in the tumor microenvironment. Neoantigen targeted cancer vaccines can activate and expand the antitumor T cell repertoire, but historically, clinical responses have been poor because immunity against peptide antigens is typically weak, resulting in insufficient activation of CD8+ cytotoxic T cells. Herein, we describe a nanoparticle vaccine platform that can overcome these barriers in several ways. First, the vaccine can be reproducibly formulated using a scalable confined impingement jet mixing method to coload a variety of physicochemically diverse peptide antigens and multiple vaccine adjuvants into pH-responsive, vesicular nanoparticles that are monodisperse and less than 100 nm in diameter. Using this approach, we encapsulated synergistically acting adjuvants, cGAMP and monophosphoryl lipid A (MPLA), into the nanocarrier to induce a robust and tailored innate immune response that increased peptide antigen immunogenicity. We found that incorporating both adjuvants into the nanovaccine synergistically enhanced expression of dendritic cell costimulatory markers, pro-inflammatory cytokine secretion, and peptide antigen cross-presentation. Additionally, the nanoparticle delivery increased lymph node accumulation and uptake of peptide antigen by dendritic cells in the draining lymph node. Consequently, nanoparticle codelivery of peptide antigen, cGAMP, and MPLA enhanced the antigen-specific CD8+ T cell response and delayed tumor growth in several mouse models. Finally, the nanoparticle platform improved the efficacy of ICB immunotherapy in a murine colon carcinoma model. This work establishes a versatile nanoparticle vaccine platform for codelivery of peptide neoantigens and synergistic adjuvants to enhance responses to cancer vaccines.

Dose optimization of an adjuvanted peptide-based personalized neoantigen melanoma vaccine

The advancements in next-generation sequencing have made it possible to effectively detect somatic mutations, which has led to the development of personalized neoantigen cancer vaccines that are tailored to the unique variants found in a patient's cancer. These vaccines can provide significant clinical benefit by leveraging the patient's immune response to eliminate malignant cells. However, determining the optimal vaccine dose for each patient is a challenge due to the heterogeneity of tumors. To address this challenge, we formulate a mathematical dose optimization problem based on a previous mathematical model that encompasses the immune response cascade produced by the vaccine in a patient. We propose an optimization approach to identify the optimal personalized vaccine doses, considering a fixed vaccination schedule, while simultaneously minimizing the overall number of tumor and activated T cells. To validate our approach, we perform in silico experiments on six real-world clinical trial patients with advanced melanoma. We compare the results of applying an optimal vaccine dose to those of a suboptimal dose (the dose used in the clinical trial and its deviations). Our simulations reveal that an optimal vaccine regimen of higher initial doses and lower final doses may lead to a reduction in tumor size for certain patients. Our mathematical dose optimization offers a promising approach to determining an optimal vaccine dose for each patient and improving clinical outcomes.