Co-inhibitory Receptor Signaling in T-Cell-Mediated Autoimmune Glomerulonephritis

A mechanistic quantitative systems pharmacology model platform for translational efficacy evaluation and checkpoint combination design of bispecific immuno-modulatory antibodies

Over the past 2 decades, tumor immunotherapies have witnessed remarkable advancements, especially with the emergence of immune checkpoint-targeting bispecific antibodies. However, a quantitative understanding of the dynamic cross-talking mechanisms underlying different immune checkpoints as well as the optimal dosing and target design of checkpoint-targeting bispecific antibodies still remain challenging to researchers. To address this challenge, we have here developed a multi-scale quantitative systems pharmacology (QSP) model platform that integrates a diverse array of immune checkpoints and their interactive functions. The model has been calibrated and validated against an extensive collection of multiscale experimental datasets covering 20+ different monoclonal and bispecific antibody treatments at over 60 administered dose levels. Based on high-throughput simulations, the QSP model platform comprehensively screened and characterized the potential efficacy of different bispecific antibody target combination designs, and model-based preclinical population-level simulations revealed target-specific dose-response relationships as well as alternative dosing strategies that can maintain anti-tumor treatment efficacy while reducing dosing frequencies. Model simulations also pointed out that combining checkpoint-targeting bispecific antibodies with monoclonal antibodies can lead to significantly enhanced anti-tumor efficacy. Our mechanistic QSP model can serve as an integrated precision medicine simulation platform to guide the translational research and clinical development of checkpoint-targeting immuno-modulatory bispecific antibodies.

PD-1 immunology in the kidneys: a growing relationship

In recent years, knowledge regarding immune regulation has expanded rapidly, and major advancements have been made in immunotherapy for immune-associated disorders, particularly cancer. The programmed cell death 1 (PD-1) pathway is a cornerstone in immune regulation. It comprises PD-1 and its ligands mediating immune tolerance mechanisms and immune homeostasis. Accumulating evidence demonstrates that the PD-1 axis has a crucial immunosuppressive role in the tumor microenvironment and autoimmune diseases. PD-1 receptors and ligands on immune cells and renal parenchymal cells aid in maintaining immunological homeostasis in the kidneys. Here, we present a comprehensive review of PD-1 immunology in various kidney disorders, including renal cell carcinoma, glomerulonephritis, kidney transplantation, renal aging, and renal immune-related adverse events secondary to PD-1 immunotherapy.

Review of the potential value of serum interleukin levels as prognostic biomarkers of liver failure

Liver failure (LF) is prevalent in China and is characterized by complex pathogenesis, challenging clinical management, poor prognosis, and rising incidence and mortality rates. The immune status is an important factor affecting LF prognosis. Interleukins (Ils) are a type of cytokine that act and interact with multiple cells, including immune cells. These signaling molecules play important roles in intercellular information transmission, including the regulation of immune cells; mediation of the activation, proliferation, and differentiation of T and B cells; and orchestration of the inflammatory response. To date, many studies have explored the correlation between IL expression and liver disease prognosis, but few studies have evaluated Ils as the prognostic biomarkers of LF. This article reviews the potential use of Ils as the prognostic biomarkers of LF. Particularly, it evaluates the predictive values of IL-21, IL-22, and IL-31, the three often overlooked yet promising prognostic biomarkers, in predicting susceptibility to LF. Harnessing biomarkers for early prognostic insights can facilitate tailored treatment strategies and enhance patient survival. Thus, this article focuses on the identification of IL-21, IL-22, and IL-33 as biomarkers in preclinical and clinical studies on LF and reviews their role as biomarkers in the pathogenesis and diagnosis of LF.

PANoptosis-like death in acute-on-chronic liver failure injury

The pathogenesis of Acute-on-chronic liver failure (ACLF) involves several forms of cell death, such as pyroptosis, apoptosis, and necroptosis, which consist of PANoptosis. To explore PANoptosis as a regulated cell death pathway in ACLF. Firstly, a bioinformatic strategy was used to observe the role of the PANoptosis pathway in ACLF and identify differentially expressed genes related to PANoptosis. Enrichment analysis showed that PANoptosis-related pathways were up-regulated in ACLF. We screened out BAX from the intersection of pyroptosis, apoptosis, necroptosis, and DEGs. Secondly, we screened articles from literature databases related to PANoptosis and liver failure, and specific forms of PANoptosis were reported in different experimental models in vitro and in vivo. Secondly, we established a model of ACLF using carbon tetrachloride-induced liver fibrosis, followed by D-galactosamine and lipopolysaccharide joint acute attacks. A substantial release of inflammatory factors(IL-6, IL-18, TNFα, and IFNγ) and the key proteins of PANoptosis (NLRP3, CASP1, GSDMD, BAX, CASP8, CASP3, CASP7, and MLKL) were detected independently in the ACLF rats. Finally, we found that combining TNF-α/INF-γ inflammatory cytokines could induce L02 cells PANoptosis. Our study highlighted the potential role of ACLF and helps drug discovery targeting PANoptosis in the future.

Targeting immune checkpoints in anti-neutrophil cytoplasmic antibodies associated vasculitis: the potential therapeutic targets in the future

Anti-neutrophil cytoplasmic autoantibodies (ANCA) associated vasculitis (AAV) is a necrotizing vasculitis mainly involving small blood vessels. It is demonstrated that T cells are important in the pathogenesis of AAV, including regulatory T cells (Treg) and helper T cells (Th), especially Th2, Th17, and follicular Th cells (Tfh). In addition, the exhaustion of T cells predicted the favorable prognosis of AAV. The immune checkpoints (ICs) consist of a group of co-stimulatory and co-inhibitory molecules expressed on the surface of T cells, which maintains a balance between the activation and exhaustion of T cells. CD28, inducible T-cell co-stimulator (ICOS), OX40, CD40L, glucocorticoid induced tumor necrosis factor receptor (GITR), and CD137 are the common co-stimulatory molecules, while the programmed cell death 1 (PD-1), cytotoxic T lymphocyte-associated molecule 4 (CTLA-4), T cell immunoglobulin (Ig) and mucin domain-containing protein 3 (TIM-3), B and T lymphocyte attenuator (BTLA), V-domain Ig suppressor of T cell activation (VISTA), T-cell Ig and ITIM domain (TIGIT), CD200, and lymphocyte activation gene 3 (LAG-3) belong to co-inhibitory molecules. If this balance was disrupted and the activation of T cells was increased, autoimmune diseases (AIDs) might be induced. Even in the treatment of malignant tumors, activation of T cells by immune checkpoint inhibitors (ICIs) may result in AIDs known as rheumatic immune-related adverse events (Rh-irAEs), suggesting the importance of ICs in AIDs. In this review, we summarized the features of AAV induced by immunotherapy using ICIs in patients with malignant tumors, and then reviewed the biological characteristics of different ICs. Our aim was to explore potential targets in ICs for future treatment of AAV.

Exploring the Underlying Mechanism of Shenyankangfu Tablet in the Treatment of Glomerulonephritis Through Network Pharmacology, Machine Learning, Molecular Docking, and Experimental Validation

Purpose

This study aimed to explore the underlying mechanisms of Shenyankangfu tablet (SYKFT) in the treatment of glomerulonephritis (GN) based on network pharmacology, machine learning, molecular docking, and experimental validation.

Methods

The active ingredients and potential targets of SYKFT were obtained through the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform, the targets of GN were obtained through GeneCards, etc. Perl and Cytoscape were used to construct an herb-active ingredient–target network. Then, the clusterProfiler package of R was used for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. We also used the STRING platform and Cytoscape to construct a protein–protein interaction (PPI) network, as well as the SwissTargetPrediction server to predict the target protein of the core active ingredient based on machine-learning model. Molecular-docking analysis was further performed using AutoDock Vina and Pymol. Finally, we verified the effect of SYKFT on GN in vivo.

Results

A total of 154 active ingredients and 255 targets in SYKFT were screened, and 135 targets were identified to be related to GN. GO enrichment analysis indicated that biological processes were primarily associated with oxidative stress and cell proliferation. KEGG pathway analysis showed that these targets were involved mostly in infection-related and GN-related pathways. PPI network analysis identified 13 core targets of SYKFT. Results of machine-learning model suggested that STAT3 and AKT1 may be the key target. Results of molecular docking suggested that the main active components of SYKFT can be combined with various target proteins. In vivo experiments confirmed that SYKFT may alleviate renal pathological injury by regulating core genes, thereby reducing urinary protein.

Conclusion

This study demonstrated for the first time the multicomponent, multitarget, and multipathway characteristics of SYKFT for GN treatment.