A Mathematical Modelling of Initiation of Dendritic Cells-Induced T Cell Immune Response

Single dual-specific anti-PD-L1/TGF-β antibody synergizes with chemotherapy as neoadjuvant treatment for pancreatic ductal adenocarcinoma: a preclinical experimental study

AIMS

Chemotherapy resistance is an important cause of neoadjuvant therapy failure in pancreatic ductal adenocarcinoma (PDAC). BiTP (anti-PD-L1/TGF-β bispecific antibody) is a single antibody that can simultaneously and dually target transforming growth factor-beta (TGF-β) and programmed cell death ligand 1 (PD-L1). We attempted in this study to investigate the efficacy of BiTP in combination with first-line chemotherapy in PDAC.

METHODS

Preclinical assessments of BiTP plus gemcitabine and nab-paclitaxel were completed through a resectable KPC mouse model (C57BL/6J). Spectral flow cytometry, tissue section staining, enzyme-linked immunosorbent assays, Counting Kit-8, transwell, and Western blot assays were used to investigate the synergistic effects.

RESULTS

BiTP combinatorial chemotherapy in neoadjuvant settings significantly downstaged PDAC tumors, enhanced survival, and had a higher resectability for mice with PDAC. BiTP was high affinity binding to targets and reverse chemotherapy resistance of PDAC cells. The combination overcame immune evasion through reprogramming tumor microenvironment via increasing penetration and function of T cells, natural killer cells, and dendritic cells and decreasing the function of immunosuppression-related cells as regulatory T cells, M2 macrophages, myeloid-derived suppressor cells, and cancer-associated fibroblasts.

CONCLUSION

Our results suggest that the BiTP combinatorial chemotherapy is a promising neoadjuvant therapy for PDAC.

Engineering Hydrogels for Modulation of Dendritic Cell Function

Dendritic cells (DCs), the most potent antigen-presenting cells, are necessary for the effective activation of naïve T cells. DCs encounter numerous microenvironments with different biophysical properties, such as stiffness and viscoelasticity. Considering the emerging importance of mechanical cues for DC function, it is essential to understand the impacts of these cues on DC function in a physiological or pathological context. Engineered hydrogels have gained interest for the exploration of the impacts of biophysical matrix cues on DC functions, owing to their extracellular-matrix-mimetic properties, such as high water content, a sponge-like pore structure, and tunable mechanical properties. In this review, the introduction of gelation mechanisms of hydrogels is first summarized. Then, recent advances in the substantial effects of developing hydrogels on DC function are highlighted, and the potential molecular mechanisms are subsequently discussed. Finally, persisting questions and future perspectives are presented.

TAFA4-IL-10 axis potentiate immunotherapy for airway allergy by induction of specific regulatory T cells

Allergen-specific immunotherapy (AIT) is the main treatment for allergic diseases. The therapeutic efficacy of AIT has to be improved. Neuropeptides, such as TAFA4, have immune-regulating features. The objective of this study is to promote the efficacy of AIT in experimental allergic rhinitis (AR) by the concurrent use of TAFA chemokine as a family member 4 (TAFA4). In this study, an AR mouse model was developed using ovalbumin (OVA) as the specific antigen. The AR response was assessed in mice after treatment with AIT or/and TAFA4. We found that exposure to TAFA4 activated dendritic cells (DCs) in the airway tissues. Activation of DC by TAFA4 resulted in the expression of IL-10. TAFA4 also promoted the activities of c-Maf inducing protein. The FPR1-MyD88-AKT signal pathway was associated with the TAFA4-induced Il10 expression in the DCs. Co-administration of AIT/TAFA4 attenuated the AR response in mice by inducing antigen-specific Tr1 cells. In conclusion, TAFA4 induces the expression of IL-10 in DCs. Acting as an adjuvant, TAFA4 significantly improves AIT’s therapeutic efficacy against AR by inducing antigen-specific Tr1 cells.

A model-informed approach to assess the risk of immune checkpoint inhibitor-induced autoimmune myocarditis

Immune checkpoint inhibitors (ICIs), as a novel immunotherapy, are designed to modulate the immune system to attack malignancies. Despite their promising benefits, immune-related adverse events (IRAEs) may occur, and incidences are bound to increase with surging demand of this class of drugs in treating cancer. Myocarditis, although rare compared to other IRAEs, has a significantly higher fatal frequency. Due to the overwhelming complexity of the immune system, this condition is not well understood, despite the significant research efforts devoted to it. To better understand the development and progression of autoimmune myocarditis and the roles of ICIs therein, we suggest a new approach: mathematical modelling. Mathematical modelling of myocarditis has enormous potential to determine which parts of the immune system are critical to the development and progression of the disease, and therefore warrant further investigation. We provide the immunological background needed to develop a mathematical model of this disease and review relevant existing models of immunology that serve as the mathematical inspiration needed to develop this field.

Integrative lymph node-mimicking models created with biomaterials and computational tools to study the immune system

The lymph node (LN) is a vital organ of the lymphatic and immune system that enables timely detection, response, and clearance of harmful substances from the body. Each LN comprises of distinct substructures, which host a plethora of immune cell types working in tandem to coordinate complex innate and adaptive immune responses. An improved understanding of LN biology could facilitate treatment in LN-associated pathologies and immunotherapeutic interventions, yet at present, animal models, which often have poor physiological relevance, are the most popular experimental platforms. Emerging biomaterial engineering offers powerful alternatives, with the potential to circumvent limitations of animal models, for in-depth characterization and engineering of the lymphatic and adaptive immune system. In addition, mathematical and computational approaches, particularly in the current age of big data research, are reliable tools to verify and complement biomaterial works. In this review, we first discuss the importance of lymph node in immunity protection followed by recent advances using biomaterials to create in vitro/vivo LN-mimicking models to recreate the lymphoid tissue microstructure and microenvironment, as well as to describe the related immuno-functionality for biological investigation. We also explore the great potential of mathematical and computational models to serve as in silico supports. Furthermore, we suggest how both in vitro/vivo and in silico approaches can be integrated to strengthen basic patho-biological research, translational drug screening and clinical personalized therapies. We hope that this review will promote synergistic collaborations to accelerate progress of LN-mimicking systems to enhance understanding of immuno-complexity.