Immunologic Research最新文献

The cyclic GMP-AMP synthase (cGAS)-stimulator of interferon genes (STING) signaling pathway has been identified as a significant modulator of inflammation in various clinical contexts, including infection, cellular stress, and tissue injury. The extensive participation of the cGAS-STING pathway can be attributed to its ability to detect and control the cellular reaction to DNAs originating from both microorganisms and hosts. These DNAs are well recognized as molecules linked with potential risks. At physiological levels, the STING signaling system exhibits protective effects. However, prolonged stimulation of this pathway contributes to autoimmune disorder pathogenesis. The present paper provides an overview of the activation mechanism of the cGAS-STING signaling pathways and their associated significant functions, as well as therapeutic interventions in the context of systemic lupus erythematosus (SLE). The primary objective is to enhance our comprehension of SLE and facilitate more effective diagnosis and treatment strategies for this condition.

Diabetes mellitus (DM) is a major risk factor for tuberculosis (TB), though the underlying mechanisms linking DM and TB remain ambiguous. Macrophages are a key player in the innate immune response and their phagocytic ability is enhanced in response to microbial infections. Upon infection or inflammation, they also repel invading pathogens by generating; reactive oxygen species (ROS), reactive nitrogen species (RNS), pro-inflammatory cytokines (IL-1β and IL-6), and anti-inflammatory cytokines (IL-10). However, the robustness of these innate defensive capabilities of macrophages when exposed to hyperglycemia remains unclear. In our current work, we explored the production of these host defense molecules in response to challenge with Mycobacterium tuberculosis (Mtb) infection and lipopolysaccharide (LPS) stimulation. Utilizing peritoneal macrophages from high-fat diet + streptozotocin induced diabetic mice and hyperglycemic THP-1-derived macrophages as model systems; we found that LPS stimulation and Mtb infection were ineffective in stimulating the production of ROS, RNS, and pro-inflammatory cytokines in cells exposed to hyperglycemia. On the contrary, an increase in production of anti-inflammatory cytokines was observed. To confirm the mechanism of decreased anti-bacterial activity of the diabetic macrophage, we explored activation status of these compromised macrophages and found decreased surface expression of activation (TLR-4) and differentiation markers (CD11b and CD11c). We postulate that this could be the cause for higher susceptibility for Mtb infection among diabetic individuals.

Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by synovial hyperplasia, pannus formation, and cartilage and bone destruction. Lysine-specific demethylase 1 (LSD1), an enzyme involved in transcriptional regulation, has an unclear role in synovial inflammation, fibroblast-like synoviocytes migration, and invasion during RA pathogenesis. In this study, we observed increased LSD1 expression in RA synovial tissues and in TNF-α-stimulated MH7A cells. SP2509, an LSD1 antagonist, directly reduced LSD1 expression and reversed the elevated levels of proteins associated with inflammation, apoptosis, proliferation, and autophagy induced by TNF-α. Furthermore, SP2509 inhibited the migratory capacity of MH7A cells, which was enhanced by TNF-α. In CIA models, SP2509 treatment ameliorated RA development, reducing the expression of pro-inflammatory cytokines and alleviating joint pathological symptoms. These findings underscore the significance of LSD1 in RA and propose the therapeutic potential of SP2509.

Multiple sclerosis (MS) is a chronic inflammatory disease that leads to demyelination and damage to the central nervous system. It is well known, the significance of the involvement and influence of the immune system in the development and course of MS. Nowadays, more and more studies are demonstrating that an important factor that affects the action of the immune system is the gut microbiota. Changes in the composition and interrelationships in the gut microbiota have a significant impact on the course of MS. Dysbiosis affects the disease course mainly by influencing the immune system directly but also by modifying the secreted metabolites and increasing mucosal permeability. The essential metabolites affecting the course of MS are short-chain fatty acids, which alter pro- and anti-inflammatory responses in the immune system but also increase the permeability of the intestinal wall and the blood-brain barrier. Dietary modification alone can have a significant impact on MS. Based on these interactions, new treatments for MS are being developed, including probiotics administration, supplementation of bacterial metabolites, fecal microbiota transplantation, and dietary changes. Further studies may serve to develop new drugs and therapeutic approaches for MS.

This study aimed to develop and validate a nomogram based on immune checkpoint genes (ICGs) for predicting prognosis and immune checkpoint blockade (ICB) efficacy in lung adenocarcinoma (LUAD) patients. A total of 385 LUAD patients from the TCGA database and 269 LUAD patients in the combined dataset (GSE41272 + GSE50081) were divided into training and validation cohorts, respectively. Three different machine learning algorithms including random forest (RF), least absolute shrinkage and selection operator (LASSO) logistic regression analysis, and support vector machine (SVM) were employed to select the predictive markers from 82 ICGs to construct the prognostic nomogram. The X-tile software was used to stratify patients into high- and low-risk subgroups based on the nomogram-derived risk scores. Differences in functional enrichment and immune infiltration between the two subgroups were assessed using gene set variation analysis (GSVA) and various algorithms. Additionally, three lung cancer cohorts receiving ICB therapy were utilized to evaluate the ability of the model to predict ICB efficacy in the real world. Five ICGs were identified as predictive markers across all three machine learning algorithms, leading to the construction of a nomogram with strong potential for prognosis prediction in both the training and validation cohorts (all AUC values close to 0.800). The patients were divided into high- (risk score ≥ 185.0) and low-risk subgroups (risk score < 185.0). Compared to the high-risk subgroup, the low-risk subgroup exhibited enrichment in immune activation pathways and increased infiltration of activated immune cells, such as CD8 + T cells and M1 macrophages (P < 0.05). Furthermore, the low-risk subgroup had a greater likelihood of benefiting from ICB therapy and longer progression-free survival (PFS) than did the high-risk subgroup (P < 0.05) in the two cohorts receiving ICB therapy. A nomogram based on ICGs was constructed and validated to aid in predicting prognosis and ICB treatment efficacy in LUAD patients.

Allergic diseases affect nearly 30% of people worldwide. There is a wide range of allergen sources, such as animal dander, food, venom, dust mites, and pollen. The skin prick test is the predominant technique used to identify allergenic sensitivity in vivo; the main problem is that it can be imprecise as many of the allergen extracts are made of mixtures of allergic and nonallergic components, making it difficult to identify the disease-eliciting allergen. An alternative to solve this problem is employing cellular models in vitro that may allow allergen identification, allergy diagnosis, and testing of novel potential compounds that can be used in immunotherapeutics. For example, rat basophilic leukemia (RBL) cells are a well-suited model for studying allergies. Unfortunately, cells generated from RBL cells are not commercially available. Therefore, we developed an RBL model with a degranulation gene reporter capable of recognizing human IgE involved in allergenic sensitivity using commercial plasmids. Employing this model, we successfully evaluated the capacity of union between IgE from allergic patients to allergenic proteins from Oleaceae tree pollen. This RBL cell model can be used as a diagnostic method for sensitivity to any allergens from different sources in vitro.

Prompt disease control of flares in patients with systemic lupus erythematosus (SLE) is a priority in treatment strategy planning. However, the long-term dosage-related collateral effects of glucocorticoids (GCs) have pushed researchers towards the identification and utilization of novel biological agents that could both induce and maintain low disease activity and remission, especially in the context of lupus nephritis (LN). This scoping review aims at assessing the current evidence of the potential steroid-sparing effect of biologic therapies by reviewing phase II and phase III randomized, placebo-controlled trials involving SLE/LN patients. A scoping review of the literature was carried out in accordance with PRISMA-ScR recommendations. Risk of bias was assessed through the utilization of the Cochrane Collaboration's tool for randomized controlled trials (RCTs). Eight RCTs met the inclusion criteria and were included in this analysis (treatment drug, 7 belimumab; 1 anifrolumab). Four studies showed a definite steroid-sparing effect (treatment drug, 3 belimumab; 1 anifrolumab), while in the remaining four RCTs, the steroid-sparing effect was not observed. When focusing on phase III trials, the overall quality of the studies resulted fair or good considering the risk of bias. However, a degree of heterogeneity of steroid regimen protocol (considering initial dosage, tapering and rescue treatment allowance) was observed. While a growing body of evidence is supporting the safety and efficacy of biological treatment in SLE, the evidence on their steroid-sparing effect remains scattered. Future research needs to pursue the identification of precise SLE clusters of patients who would benefit most from a specific treatment protocol with a definite steroid-sparing effect.