Absent in melanoma 2 (AIM2) in rheumatoid arthritis: novel molecular insights and implications

Luteolin as a potential therapeutic candidate for lung cancer: Emerging preclinical evidence

Lung cancer is a prevalent malignant tumor and a leading cause of cancer-related fatalities globally. However, current treatments all have limitations. Therefore, there is an urgent need to identify a readily available therapeutic agent to counteract lung cancer development and progression. Luteolin is a flavonoid derived from vegetables and herbs that possesses preventive and therapeutic effects on various cancers. With the goal of providing new directions for the treatment of lung cancer, we review here the recent findings on luteolin so as to provide new ideas for the development of new anti-lung cancer drugs. The search focused on studies published between January 1995 and January 2024 that explored the use of luteolin in lung cancer. A comprehensive literature search was conducted in the SCOPUS, Google Scholar, PubMed, and Web of Science databases using the keywords "luteolin" and "lung cancer." By collecting previous literature, we found that luteolin has multiple mechanisms of therapeutic effects, including promotion of apoptosis in lung cancer cells; inhibition of tumor cell proliferation, invasion and metastasis; and modulation of immune responses. In addition, it can be used as an adjuvant to radio-chemotherapy and helps to ameliorate cancer complications. This review summarizes the structure, natural sources, physicochemical properties and pharmacokinetics of luteolin, and focuses on the anti-lung cancer mechanism of luteolin, so as to provide new ideas for the development of new anti-lung cancer drugs.

Identification of clinical characteristics biomarkers for rheumatoid arthritis through targeted DNA methylation sequencing

OBJECTIVES

Rheumatoid arthritis (RA) is a complex disease with a challenging diagnosis, especially in seronegative patients. The aim of this study is to investigate whether the methylation sites associated with the overall immune response in RA can assist in clinical diagnosis, using targeted methylation sequencing technology on peripheral venous blood samples.

METHODS

The study enrolled 241 RA patients, 30 osteoarthritis patients (OA), and 30 healthy volunteers control (HC). Fifty significant cytosine guanine (CG) sites between undifferentiated arthritis and RA were selected and analyzed using targeted DNA methylation sequencing. Logistic regression models were used to establish diagnostic models for different clinical features of RA, and six machine learning methods (logit model, random forest, support vector machine, adaboost, naive bayes, and learning vector quantization) were used to construct clinical diagnostic models for different subtypes of RA. Least absolute shrinkage and selection operator regression and detrended correspondence analysis were utilized to screen for important CGs. Spearman correlation was used to calculate the correlation coefficient.

RESULTS

The study identified 16 important CG sites, including tumor necrosis factort receptor associated factor 5 (TRAF5) (chr1:211500151), mothers against decapentaplegic homolog 3 (SMAD3) (chr15:67357339), tumor endothelial marker 1 (CD248) (chr11:66083766), lysosomal trafficking regulator (LYST) (chr1:235998714), PR domain zinc finger protein 16 (PRDM16) (chr1:3307069), A-kinase anchoring protein 10 (AKAP10) (chr17:19850460), G protein subunit gamma 7 (GNG7) (chr19:2546620), yes1 associated transcriptional regulator (YAP1) (chr11:101980632), PRDM16 (chr1:3163969), histone deacetylase complex subunit sin3a (SIN3A) (chr15:75747445), prenylated rab acceptor protein 2 (ARL6IP5) (chr3:69134502), mitogen-activated protein kinase kinase kinase 4 (MAP3K4) (chr6:161412392), wnt family member 7A (WNT7A) (chr3:13895991), inhibin subunit beta B (INHBB) (chr2:121107018), deoxyribonucleic acid replication helicase/nuclease 2 (DNA2) (chr10:70231628) and chromosome 14 open reading frame 180 (C14orf180) (chr14:105055171). Seven CG sites showed abnormal changes between the three groups (P < 0.05), and 16 CG sites were significantly correlated with common clinical indicators (P < 0.05). Diagnostic models constructed using different CG sites had an area under the receiver operating characteristic curve (AUC) range of 0.64-0.78 for high-level clinical indicators of high clinical value, with specificity ranging from 0.42 to 0.77 and sensitivity ranging from 0.57 to 0.88. The AUC range for low-level clinical indicators of high clinical value was 0.63-0.72, with specificity ranging from 0.48 to 0.74 and sensitivity ranging from 0.72 to 0.88. Diagnostic models constructed using different CG sites showed good overall diagnostic accuracy for the four subtypes of RA, with an accuracy range of 0.61-0.96, a balanced accuracy range of 0.46-0.94, and an AUC range of 0.46-0.94.

CONCLUSIONS

This study identified potential clinical diagnostic biomarkers for RA and provided novel insights into the diagnosis and subtyping of RA. The use of targeted deoxyribonucleic acid (DNA) methylation sequencing and machine learning methods for establishing diagnostic models for different clinical features and subtypes of RA is innovative and can improve the accuracy and efficiency of RA diagnosis.

Metabolite itaconate in host immunoregulation and defense

Metabolic states greatly influence functioning and differentiation of immune cells. Regulating the metabolism of immune cells can effectively modulate the host immune response. Itaconate, an intermediate metabolite derived from the tricarboxylic acid (TCA) cycle of immune cells, is produced through the decarboxylation of cis-aconitate by cis-aconitate decarboxylase in the mitochondria. The gene encoding cis-aconitate decarboxylase is known as immune response gene 1 (IRG1). In response to external proinflammatory stimulation, macrophages exhibit high IRG1 expression. IRG1/itaconate inhibits succinate dehydrogenase activity, thus influencing the metabolic status of macrophages. Therefore, itaconate serves as a link between macrophage metabolism, oxidative stress, and immune response, ultimately regulating macrophage function. Studies have demonstrated that itaconate acts on various signaling pathways, including Keap1-nuclear factor E2-related factor 2-ARE pathways, ATF3-IκBζ axis, and the stimulator of interferon genes (STING) pathway to exert antiinflammatory and antioxidant effects. Furthermore, several studies have reported that itaconate affects cancer occurrence and development through diverse signaling pathways. In this paper, we provide a comprehensive review of the role IRG1/itaconate and its derivatives in the regulation of macrophage metabolism and functions. By furthering our understanding of itaconate, we intend to shed light on its potential for treating inflammatory diseases and offer new insights in this field.

Identification of immunological characterization and Anoikis-related molecular clusters in rheumatoid arthritis

Objective: To investigate the potential association between Anoikis-related genes, which are responsible for preventing abnormal cellular proliferation, and rheumatoid arthritis (RA). Methods: Datasets GSE89408, GSE198520, and GSE97165 were obtained from the GEO with 282 RA patients and 28 healthy controls. We performed differential analysis of all genes and HLA genes. We performed a protein-protein interaction network analysis and identified hub genes based on STRING and cytoscape. Consistent clustering was performed with subgrouping of the disease. SsGSEA were used to calculate immune cell infiltration. Spearman's correlation analysis was employed to identify correlations. Enrichment scores of the GO and KEGG were calculated with the ssGSEA algorithm. The WGCNA and the DGIdb database were used to mine hub genes' interactions with drugs. Results: There were 26 differentially expressed Anoikis-related genes (FDR = 0.05, log2FC = 1) and HLA genes exhibited differential expression (P < 0.05) between the disease and control groups. Protein-protein interaction was observed among differentially expressed genes, and the correlation between PIM2 and RAC2 was found to be the highest; There were significant differences in the degree of immune cell infiltration between most of the immune cell types in the disease group and normal controls (P < 0.05). Anoikis-related genes were highly correlated with HLA genes. Based on the expression of Anoikis-related genes, RA patients were divided into two disease subtypes (cluster1 and cluster2). There were 59 differentially expressed Anoikis-related genes found, which exhibited significant differences in functional enrichment, immune cell infiltration degree, and HLA gene expression (P < 0.05). Cluster2 had significantly higher levels in all aspects than cluster1 did. The co-expression network analysis showed that cluster1 had 51 hub differentially expressed genes and cluster2 had 72 hub differentially expressed genes. Among them, three hub genes of cluster1 were interconnected with 187 drugs, and five hub genes of cluster2 were interconnected with 57 drugs. Conclusion: Our study identified a link between Anoikis-related genes and RA, and two distinct subtypes of RA were determined based on Anoikis-related gene expression. Notably, cluster2 may represent a more severe state of RA.

PANoptosis: Emerging mechanisms and disease implications

PANoptosis, a unique new form of programmed cell death (PCD), is characterized by pyroptosis, apoptosis, and necroptosis, but it cannot be explained by pyroptosis, apoptosis or necroptosis alone. Assembly of the PANoptosome complex is a key feature of PANoptosis. To date, four kinds of PANoptosomes with distinct sensors and regulators have been defined, namely Z-DNA binding protein 1 (ZBP1) PANoptosome, absent in melanoma 2 (AIM2) PANoptosome, receptor-interacting protein kinase 1 (RIPK1) PANoptosome, and nucleotide-binding leucine-rich repeat-containing receptor 12 (NLRP12). Each PANoptosome contains three components: sensors for pathogen-associated molecular patterns (PAMPs) or damage-associated molecular patterns (DAMPs), adaptors as connected bridges, and catalytic effectors or executioners. Mechanistically, different PAMPs or DAMPs are recognized by the sensors in a context-dependent manner, which initiates PANoptosome assembly through adaptors, and ultimately engages synchronous activation of pyroptosis, apoptosis, and necroptosis via different catalytic effectors. Resultantly, PANoptosis is emerged as a prospective and promising therapeutic target for various diseases. This review covers the accumulating evidence about the roles and mechanisms of PANoptosis in innate immunity and discusses the attractive prospect of manipulating PANoptosis as a new treatment for diseases.

Can pyroptosis be a new target in rheumatoid arthritis treatment?

Rheumatoid arthritis (RA) is a chronic systemic autoimmune disease of undefined etiology, with persistent synovial inflammation and destruction of articular cartilage and bone. Current clinical drugs for RA mainly include non-steroidal anti-inflammatory drugs (NSAIDs), glucocorticoids, disease modifying anti-rheumatic drugs (DMARDs) and so on, which can relieve patients' joint symptoms. If we want to have a complete cure for RA, there are still some limitations of these drugs. Therefore, we need to explore new mechanisms of RA to prevent and treat RA radically. Pyroptosis is a newly discovered programmed cell death (PCD) in recent years, which is characterized by the appearance of holes in cell membranes, cell swelling and rupture, and the release of intracellular pro-inflammatory factors into the extracellular space, resulting in a strong inflammatory response. The nature of pyroptosis is pro-inflammatory, and whether it is participating in the development of RA has attracted a wide interest among scholars. This review describes the discovery and mechanism of pyroptosis, the main therapeutic strategies for RA, and the role of pyroptosis in the mechanism of RA development. From the perspective of pyroptosis, the study of new mechanisms of RA may provide a potential target for the treatment of RA and the development of new drugs in the clinics.

Apelin-13, a regulator of autophagy, apoptosis and inflammation in multifaceted bone protection

Apelin/APJ is widely distributed in various tissues in the body and participates in the regulation of physiological and pathological mechanisms such as autophagy, apoptosis, inflammation, and oxidative stress. Apelin-13 is an adipokine family member with multiple biological roles and has been shown to be involved in the development and progression of bone diseases. In the process of osteoporosis and fracture healing, Apelin-13 plays an osteoprotective role by regulating the autophagy and apoptosis of BMSCs, and promotes the osteogenic differentiation of BMSCs. In addition, Apelin-13 also attenuates the progression of arthritis by regulating the inflammatory response of macrophages. In conclusion, Apelin-13 has an important connection with bone protection, which provides a new strategy for the clinical treatment of bone-related diseases.

Role of the granzyme family in rheumatoid arthritis: Current Insights and future perspectives

Rheumatoid arthritis (RA) is a complex autoimmune disease characterized by chronic inflammation that affects synovial tissues of multiple joints. Granzymes (Gzms) are serine proteases that are released into the immune synapse between cytotoxic lymphocytes and target cells. They enter target cells with the help of perforin to induce programmed cell death in inflammatory and tumor cells. Gzms may have a connection with RA. First, increased levels of Gzms have been found in the serum (GzmB), plasma (GzmA, GzmB), synovial fluid (GzmB, GzmM), and synovial tissue (GzmK) of patients with RA. Moreover, Gzms may contribute to inflammation by degrading the extracellular matrix and promoting cytokine release. They are thought to be involved in RA pathogenesis and have the potential to be used as biomarkers for RA diagnosis, although their exact role is yet to be fully elucidated. The purpose of this review was to summarize the current knowledge regarding the possible role of the granzyme family in RA, with the aim of providing a reference for future research on the mechanisms of RA and the development of new therapies.