Discovery of New States of Immunomodulation for Vaccine Adjuvants via High Throughput Screening: Expanding Innate Responses to PRRs

Identification of CDK4/6 Inhibitors as Small Molecule NLRP3 Inflammasome Activators that Facilitate IL-1β Secretion and T Cell Adjuvanticity

Several FDA-approved adjuvants signal through the NLRP3 inflammasome and IL-1β release. Identifying small molecules that induce IL-1β release could allow targeted delivery and structure-function optimization, thereby improving safety and efficacy of next-generation adjuvants. In this work, we leverage our existing high throughput data set to identify small molecules that induce IL-1β release. We find that ribociclib induces IL-1β release when coadministered with a TLR4 agonist in an NLRP3- and caspase-dependent fashion. Ribociclib was formulated with a TLR4 agonist into liposomes, which were used as an adjuvant in an ovalbumin prophylactic vaccine model. The liposomes induced antigen-specific immunity in an IL-1 receptor-dependent fashion. Furthermore, the liposomes were coadministered with a tumor antigen and used in a therapeutic cancer vaccine, where they facilitated rejection of E.G7-OVA tumors. While further chemical optimization of the ribociclib scaffold is needed, this study provides proof-of-concept for its use as an IL-1 producing adjuvant in various immunotherapeutic contexts.

High-throughput screen identifies non inflammatory small molecule inducers of trained immunity

Trained immunity is characterized by epigenetic and metabolic reprogramming in response to specific stimuli. This rewiring can result in increased cytokine and effector responses to pathogenic challenges, providing nonspecific protection against disease. It may also improve immune responses to established immunotherapeutics and vaccines. Despite its promise for next-generation therapeutic design, most current understanding and experimentation is conducted with complex and heterogeneous biologically derived molecules, such as β-glucan or the Bacillus Calmette-Guérin (BCG) vaccine. This limited collection of training compounds also limits the study of the genes most involved in training responses as each molecule has both training and nontraining effects. Small molecules with tunable pharmacokinetics and delivery modalities would both assist in the study of trained immunity and its future applications. To identify small molecule inducers of trained immunity, we screened a library of 2,000 drugs and drug-like compounds. Identification of well-defined compounds can improve our understanding of innate immune memory and broaden the scope of its clinical applications. We identified over two dozen small molecules in several chemical classes that induce a training phenotype in the absence of initial immune activation-a current limitation of reported inducers of training. A surprising result was the identification of glucocorticoids, traditionally considered immunosuppressive, providing an unprecedented link between glucocorticoids and trained innate immunity. We chose seven of these top candidates to characterize and establish training activity in vivo. In this work, we expand the number of compounds known to induce trained immunity, creating alternative avenues for studying and applying innate immune training.

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.

High-throughput screening identification of novel immunomodulatory combinations for the generation of tolerogenic dendritic cells

Introduction

Tolerogenic Dendritic Cells (tolDCs) have an exceptional promise as a potential therapy for autoimmune disease and transplantation rejection. TolDCs are a unique phenotype of antigen presenting cells (APCs) that can influence naïve T cells into antigen specific T regulatory cells (Tregs), which can re-establish tolerance against auto/allo-antigens in the long term. Despite their promise, tolDCs have not found clinical success. Most strategies seek to generate tolDCs ex vivo by differentiating naïve dendritic cells (DCs) with immunosuppressive agents. Recently, we developed a tolDC generation strategy, which we call Push/Pull Immunomodulation (PPI). In PPI, DCs are treated with combinations of toll-like-receptor (TLR) agonists and immunomodulatory agents, which generate more robust, Treg-inducing tolDCs than previous strategies. Here, we seek to identify more potent and clinically viable PPI formulations using data from a high-throughput screening project.

Methods

Over 40,000 combinations of pathogen-associated molecular patterns (PAMPs) and immunomodulatory small molecules were screened using a modified murine macrophage line, RAW dual cells, to observe the effect of these combinations on two major immune regulatory transcription factors, NF-κB and IRF. Combinations were further screened for inflammatory cytokine activity using a human monocyte cell line, THP-1, then on murine DCs. Leading candidates were co-cultured with T cells to assess antigen specific T cell responses.

Results

From this data, we identified 355 combinations that showed low or moderate IRF activity, low NF-κB activity, low inflammatory cytokine generation and good viability: all hallmarks of tolerogenic potential. We further screened these 355 combinations using bone marrow derived DCs (BMDCs) and identified 10 combinations that demonstrated high IL-10 (tolerogenic) and low TNF-α (inflammatory) secretion. After further optimizing these combinations, we identified two combinations that generate robust tolDCs from BMDCs ex vivo. We further show that these PPI-tolDCs can also generate antigen specific Tregs but do not increase overall Treg populations.

Discussion

These second-generation PPI formulations have significant potential to generate robust tolDCs and strong antigen specific Tregs.

Data-driven discovery of innate immunomodulators via machine learning-guided high throughput screening

The innate immune response is vital for the success of prophylactic vaccines and immunotherapies. Control of signaling in innate immune pathways can improve prophylactic vaccines by inhibiting unfavorable systemic inflammation and immunotherapies by enhancing immune stimulation. In this work, we developed a machine learning-enabled active learning pipeline to guide in vitro experimental screening and discovery of small molecule immunomodulators that improve immune responses by altering the signaling activity of innate immune responses stimulated by traditional pattern recognition receptor agonists. Molecules were tested by in vitro high throughput screening (HTS) where we measured modulation of the nuclear factor κ-light-chain-enhancer of activated B-cells (NF-κB) and the interferon regulatory factors (IRF) pathways. These data were used to train data-driven predictive models linking molecular structure to modulation of the NF-κB and IRF responses using deep representational learning, Gaussian process regression, and Bayesian optimization. By interleaving successive rounds of model training and in vitro HTS, we performed an active learning-guided traversal of a 139 998 molecule library. After sampling only ∼2% of the library, we discovered viable molecules with unprecedented immunomodulatory capacity, including those capable of suppressing NF-κB activity by up to 15-fold, elevating NF-κB activity by up to 5-fold, and elevating IRF activity by up to 6-fold. We extracted chemical design rules identifying particular chemical fragments as principal drivers of specific immunomodulation behaviors. We validated the immunomodulatory effect of a subset of our top candidates by measuring cytokine release profiles. Of these, one molecule induced a 3-fold enhancement in IFN-β production when delivered with a cyclic di-nucleotide stimulator of interferon genes (STING) agonist. In sum, our machine learning-enabled screening approach presents an efficient immunomodulator discovery pipeline that has furnished a library of novel small molecules with a strong capacity to enhance or suppress innate immune signaling pathways to shape and improve prophylactic vaccination and immunotherapies.