Improving Vaccine Adjuvants via New Signal Processing
To respond to an infection, the immune system identifies chemical motifs that distinguish pathogens (“non-self”) from self. These pathogen-associated molecular patterns bind pattern recognition receptors (PRRs) with a precise spatiotemporal code to activate the innate immune system and initiate a response. Early vaccines included weakened or heat-killed pathogens which retain the spatiotemporal information needed for the pathogens to activate the innate immune system. Newer technologies, such as subunit protein or mRNA vaccines, while safer for patients, lack such endogenous pathogen information—as a result, these vaccines must be co-administered with PRR agonists or other helper molecules, called adjuvants, to provide immune support.
In the Esser-Kahn lab, we seek to design adjuvants which better mimic the spatiotemporal pattern of immune activation induced by natural pathogens to create safer, more effective vaccines. We are doing so by (1) studying multi-adjuvant synergies, (2) developing molecules that can target new PRRs, and (3) modulating the pathways by which adjuvants signal.
Immunotherapeutic nanoparticles comprised of a TLR7 and NLRP3 heterodimeric polymer, immune checkpoint blockade (ICB) antibodies, and neoantigen peptides were administered to mice with established CT26 tumors and induced complete tumor remission in 7/10 mice.
1. Studying multi-adjuvant synergies
To study multi-adjuvant synergies, we have designed covalently linked PRR agonists, polymers decorated with PRR agonists, and controlled release mechanisms (such as light-activated adjuvants or slow-release adjuvant-loaded nanoparticles). We have used our trimer platform to better understand how different PRR agonists can induce immune synergies, and our top-performing trimers have been used in effective pre-clinical subunit vaccines against Coxiella burnetii and SARS-CoV-2 (https://doi.org/10.4049/jimmunol.1900991). Our polymers comprised of TLR2/6 agonists and TLR7 agonists, meanwhile, have shown high efficacy as adjuvant immunotherapies in a variety of cancer models (https://doi.org/10.1021/acscentsci.0c01001).
2. Developing molecules that can target new PRRs
In targeting new PRRs, we are currently interested in designing new adjuvants that target the NLRP3 inflammasome to induce IL-1β production. While IL-1β production is critical in the Shingrix, Mosquirix, and COVID-19 vaccines, current adjuvants are limited by significant toxic side effects and limited production capabilities. We are therefore interested in identifying peptides, polymers, and small molecules which can induce IL-1β production with fewer toxic side effects for use in vaccines and cancer immunotherapies. We have already identified a series of peptides and polymers which robustly activate the inflammasome and can be formulated into nanoparticles for use in vaccines and immunotherapies (https://doi.org/10.1021/acscentsci.8b00218). We are now interested in understanding what properties of polymers can modulate inflammasome activation to better inform the design of new materials for a breadth of applications.
3. Modulating the pathways by which adjuvants signal
We also are searching for ways to modulate the immune response towards existing adjuvants using immunomodulatory compounds. We hypothesize we can selectively tailor innate pathway signaling through NF-κB and IRF after binding of PRR agonists. We showed preliminary success in decoupling negative side effects like systemic inflammation from protective benefits like antigen presentation using a peptide modulator, SN50 (https://doi.org/10.1126/sciadv.aaz8700). To build off these results, we launched a high-throughput screening workflow studying tens of thousands of combinations of small molecule immunomodulators and PRR agonists. Our workflow consists of a variety of immunoassays studying transcription factor activity, cytokine production, and cell surface marker expression. Our top candidates are now being further validated in vaccination models. Additionally, we use the results from these wet-lab experiments to inform a machine learning model that predicts additional molecules for future study.
High throughput screening of immune modulator compounds identified compounds that can enhance antibody titers while reducing inflammatory cytokine production during vaccination.
Learn more about our other immunoengineering projects below!
