The Next Generation of Pattern Recognition Receptor Agonists: Improving Response Rates in Cancer Immunotherapy

Small molecule modulators of immune pattern recognition receptors

Pattern recognition receptors (PRRs) represent a re-emerging class of therapeutic targets for vaccine adjuvants, inflammatory diseases and cancer. In this review article, we summarize exciting developments in discovery and characterization of small molecule PRR modulators, focusing on Toll-like receptors (TLRs), NOD-like receptors (NLRs) and the cGAS-STING pathway. We also highlight PRRs that are currently lacking small molecule modulators and opportunities for chemical biology and therapeutic discovery.

Discovery and characterisation of quinazolines and 8-Azaquinazolines as NLRP3 agonists with oral bioavailability in mice

The NLRP3 inflammasome is a multiprotein complex that plays a critical role in activating the immune system in response to danger signals. Small molecule agonists of NLRP3 may offer clinical benefits in cancer immunology either as a monotherapy or in combination with checkpoint blockade, where it is hypothesised that their application can help to initiate an antitumor immune response. In this study, we report the discovery of quinazolines and 8-azaquinazolines as NLRP3 agonists and their chemical optimization to afford compounds with oral bioavailability in mice. We confirm that these compounds engage the NLRP3 inflammasome by verifying their dependence upon lipopolysaccharide (LPS) priming for cytokine release and the activation of Caspase-1. We further demonstrate pathway engagement through loss of activity in an NLRP3-knockout THP1 cell line. Based on their pharmacokinetic profile and biological activity, these compounds represent valuable tools to evaluate the therapeutic potential of NLRP3 activation in a pre-clinical setting.

PRR-HyPred: A two-layer hybrid framework to predict pattern recognition receptors and their families by employing sequence encoded optimal features

Pattern recognition receptors (PRRs) recognize distinct features on the surface of pathogens or damaged cells and play key roles in the innate immune system. PRRs are divided into various families, including Toll-like receptors, retinoic acid-inducible gene-I-like receptors, nucleotide oligomerization domain-like receptors, and C-type lectin receptors. As these are implicated in host health and several diseases, their accurate identification is indispensable for their functional characterization and targeted therapeutic approaches. Here, we construct PRR-HyPred, a novel two-layer hybrid framework in which the first layer predicts whether a given sequence is PRR or non-PRR using a support vector machine, and in the second, the predicted PRR sequence is assigned to a specific family using a random forest-based classifier. Based on a 10-fold cross-validation test, PRR-HyPred achieved 83.4 % accuracy in the first layer and 95 % in the second, with Matthew's correlation coefficient values of 0.639 and 0.816, respectively. This is the first study that can simultaneously predict and classify PRRs into specific families. PRR-HyPred is available as a web portal at https://procarb.org/PRRHyPred/. We hope that it could be a valuable tool for the large-scale prediction and classification of PRRs and subsequently facilitate future studies.

Identification and immunological evaluation of novel TLR2 agonists through structural optimization of Diprovocim

As an important family member of Toll-like receptors (TLRs), TLR2 can recognize various pathogen-associated molecular patterns (PAMPs) such as bacteria and viral components. Accumulating evidence demonstrates that TLR2 agonists play a critical role in cancer immunotherapy and infectious diseases. Diprovocim is the most potent small molecule TLR2 agonist known, showing remarkably immune adjuvant activity in mice. However, the further clinical research and development of Diprovocim was hampered because of its structural complexity as well as high molecular weight. Here, we designed and synthesized 21 structurally simplified derivatives of Diprovocim, performed their TLR2 agonistic activities by HEK-Blue hTLR2 SEAP assay, and evaluated the toxicity in two human normal cell lines. Compounds B3-B4 and B9-B12 with excellent TLR2 agonistic activity were found through the structure-activity relationship study. Among them, diastereomer B10 and B12 substituted (S)-2-phenylcyclopropylamide side chain of Diprovocim with simple (R)- and (S)-n-butyl groups exhibited comparable TLR2 agonistic activities with EC₅₀ values of 35 nM and 39 nM, respectively. ELISA and western blot experiments on THP-1 cells showed that B10 and B12 displayed remarkable immunostimulatory activity in the release of various inflammatory cytokines through activating MyD88-dependent NF-κB and MAPK signaling pathways. Importantly, B10 and B12 have less structural complexity and better safety compared to Diprovocim, and the chiral center of right pyrrolidine ring has negligible influence on TLR2 activition. Our study provides simplified Diprovocim derivatives with high agonistic activity, providing a clue to further optimize Diprovocim.

Antibody-Pattern Recognition Receptor Agonist Conjugates: A Promising Therapeutic Strategy for Cancer

Antibody-drug conjugates (ADCs) are composed of monoclonal antibodies linked to cytotoxic payload drugs, each of which can be diversely designed in accordance with pharmacological and clinical requirements. The use of ADCs is effective for the treatment of different diseases, including cancers, and is gaining widespread attention. To date, 12 ADCs have been approved by the U.S. Food and Drug Administration for treating cancer and improving the quality of life of patients. To expand the application of ADCs and improve their treatment efficiency, various formats have recently been manufactured, including pattern recognition receptor (PRR) agonist-based ADCs. The antibody has a unique structure that enables the specific delivery of PRR agonists to the tumor area, and this improves the therapeutic efficacy while minimizing systemic toxicity. This review briefly discusses the current landscape and future perspectives of antibody-PRR agonist conjugates for cancer therapy.

Targeting innate immune system by nanoparticles for cancer immunotherapy

Various cancer therapies have advanced remarkably over the past decade. Unlike the direct therapeutic targeting of tumor cells, cancer immunotherapy is a new strategy that boosts the host's immune system...

Immune Regulatory Processes of the Tumor Microenvironment under Malignant Conditions

The tumor microenvironment (TME) is a critical regulator of tumor growth, progression, and metastasis. Since immune cells represent a large fraction of the TME, they play a key role in mediating pro- and anti-tumor immune responses. Immune escape, which suppresses anti-tumor immunity, enables tumor cells to maintain their proliferation and growth. Numerous mechanisms, which have been intensively studied in recent years, are involved in this process and based on these findings, novel immunotherapies have been successfully developed. Here, we review the composition of the TME and the mechanisms by which immune evasive processes are regulated. In detail, we describe membrane-bound and soluble factors, their regulation, and their impact on immune cell activation in the TME. Furthermore, we give an overview of the tumor/antigen presentation and how it is influenced under malignant conditions. Finally, we summarize novel TME-targeting agents, which are already in clinical trials for different tumor entities.

NLRC5 promotes cell migration and invasion by activating the PI3K/AKT signaling pathway in endometrial cancer

Objective

NOD-like receptor family caspase recruitment domain family domain-containing 5 (NLRC5) is involved in the development of cancer. Our objective was to explore the role of NLRC5 in the progression of endometrial cancer (EC).

Methods

The roles of NLRC5 in migration and invasion of AN3CA EC cells were examined by cell wound-healing assay, Transwell migration, and invasion analysis. Overexpression of NLRC5 was achieved with NLRC5 plasmid, and knockdown of NLRC5 was achieved using small interfering (si)RNA-NLRC5 in AN3CA cells. The expression of NLRC5 was detected by immunohistochemical, western blot, and quantitative real-time PCR. LY294002 was used to inhibit the phosphatidylinositol 3-kinase (PI3K)/AKT signaling pathway.

Results

NLRC5 was downregulated in EC tissue compared with normal endometrium. Overexpression of NLRC5 led to upregulation of cell migration and invasion in AN3CA cells and expression of matrix metallopeptidase (MMP)-9. Inhibition of NLRC5 restricted migration and invasion of AN3CA cells and expression of MMP9. Overexpression of NLRC5 promoted the activation of PI3K/AKT signaling pathway. Inhibiting PI3K/AKT signaling pathway by using LY294002 blocked the positive role of NLRC5 in migration and invasion of AN3CA cells and expression of MMP9.

Conclusions

These results demonstrate that NLRC5 promotes EC progression by activating the PI3K/AKT signaling pathway.

The anti-tumor effects of cetuximab in combination with VTX-2337 are T cell dependent

The Toll-like receptor 8 (TLR8) agonist VTX-2337 (motolimod) is an anti-cancer immunotherapeutic agent that is believed to augment natural killer (NK) and dendritic cell (DC) activity. The goal of this work is to examine the role of TLR8 expression/activity in head and neck squamous cell carcinoma (HNSCC) to facilitate the prediction of responders to VTX-2337-based therapy. The prognostic role of TLR8 expression in HNSCC patients was assessed by TCGA and tissue microarray analyses. The anti-tumor effect of VTX-2337 was determined in SCCVII/C3H, mEERL/C57Bl/6 and TUBO-human EGFR/BALB/c syngeneic mouse models. The effect of combined VTX-2337 and cetuximab treatment on tumor growth, survival and immune cell recruitment was assessed. TLR8 expression was associated with CD8+ T cell infiltration and favorable survival outcomes. VTX-2337 delayed tumor growth in all 3 syngeneic mouse models and significantly increased the survival of cetuximab-treated mice. The anti-tumor effects of VTX-2337+ cetuximab were accompanied by increased splenic lymphoid DCs and IFNγ+ CD4+ and tumor-specific CD8+ T cells. Depletion of CD4+ T cells, CD8+ T cells and NK cells were all able to abolish the anti-tumor effect of VTX-2337+ cetuximab. Altogether, VTX-2337 remains promising as an adjuvant for cetuximab-based therapy however patients with high TLR8 expression may be more likely to derive benefit from this drug combination compared to patients with low TLR8 expression.

Small molecules targeting the innate immune cGAS‒STING‒TBK1 signaling pathway

Multiple cancer immunotherapies including chimeric antigen receptor T cell and immune checkpoint inhibitors (ICIs) have been successfully developed to treat various cancers by motivating the adaptive anti-tumor immunity. Particularly, the checkpoint blockade approach has achieved great clinic success as evidenced by several U.S. Food and Drug Administration (FDA)-approved anti-programmed death receptor 1/ligand 1 or anti-cytotoxic T lymphocyte associated protein 4 antibodies. However, the majority of cancers have low clinical response rates to these ICIs due to poor tumor immunogenicity. Indeed, the cyclic guanosine monophosphate-adenosine monophosphate synthase‒stimulator of interferon genes‒TANK-binding kinase 1 (cGAS‒STING‒TBK1) axis is now appreciated as the major signaling pathway in innate immune response across different species. Aberrant signaling of this pathway has been closely linked to multiple diseases, including auto-inflammation, virus infection and cancers. In this perspective, we provide an updated review on the latest progress on the development of small molecule modulators targeting the cGAS‒STING‒TBK1 signaling pathway and their preclinical and clinical use as a new immune stimulatory therapy. Meanwhile, highlights on the clinical candidates, limitations and challenges, as well as future directions in this field are also discussed. Further, small molecule inhibitors targeting this signaling axis and their potential therapeutic use for various indications are discussed as well.

New horizons in adjuvants for vaccine development

Adjuvant molecules, particularly toll like receptor (TLR) agonists have been in development for decades, though until now only a natural TLR 4 ligand (mono-phosphoryl lipid A, MPL) has been incorporated into licensed vaccine products, in formulations than enhance and complement the MPL activity. The inclusion of MPL-based formulations into vaccines has been based on enhancing antibody responses to subunit antigens, and has provided important proof-of-concept for enhancing desired immune responses to defined molecular targets. Challenges remain in adjuvant development, particularly for those that stimulated effective T cell responses for both preventative and therapeutic vaccines. The discovery of molecules, many based on RNA, that stimulate innate and adaptive immune responses and have the ability to stimulate potent CD8 T cell responses, has opened the door for development of a new generation of vaccines.

A Hybrid Model for Predicting Pattern Recognition Receptors Using Evolutionary Information

This study describes a method developed for predicting pattern recognition receptors (PRRs), which are an integral part of the immune system. The models developed here were trained and evaluated on the largest possible non-redundant PRRs, obtained from PRRDB 2.0, and non-pattern recognition receptors (Non-PRRs), obtained from Swiss-Prot. Firstly, a similarity-based approach using BLAST was used to predict PRRs and got limited success due to a large number of no-hits. Secondly, machine learning-based models were developed using sequence composition and achieved a maximum MCC of 0.63. In addition to this, models were developed using evolutionary information in the form of PSSM composition and achieved maximum MCC value of 0.66. Finally, we developed hybrid models that combined a similarity-based approach using BLAST and machine learning-based models. Our best model, which combined BLAST and PSSM based model, achieved a maximum MCC value of 0.82 with an AUROC value of 0.95, utilizing the potential of both similarity-based search and machine learning techniques. In order to facilitate the scientific community, we also developed a web server "PRRpred" based on the best model developed in this study (http://webs.iiitd.edu.in/raghava/prrpred/).