1
|
Zhang J, Ma Y. Luteolin as a potential therapeutic candidate for lung cancer: Emerging preclinical evidence. Biomed Pharmacother 2024; 176:116909. [PMID: 38852513 DOI: 10.1016/j.biopha.2024.116909] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2024] [Revised: 06/04/2024] [Accepted: 06/06/2024] [Indexed: 06/11/2024] Open
Abstract
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.
Collapse
Affiliation(s)
- Jin Zhang
- Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, 36 Sanhao Street, Heping District, Shenyang, Liaoning 110004, PR China
| | - Yue Ma
- Department of Pulmonary and Critical Care Medicine, Shengjing Hospital of China Medical University, 36 Sanhao Street, Heping District, Shenyang, Liaoning 110004, PR China.
| |
Collapse
|
2
|
Zhao J, Xu L, Wei K, Jiang P, Chang C, Xu L, Shi Y, Zheng Y, Shan Y, Zheng Y, Shen Y, Liu J, Guo S, Wang R, He D. Identification of clinical characteristics biomarkers for rheumatoid arthritis through targeted DNA methylation sequencing. Int Immunopharmacol 2024; 131:111860. [PMID: 38508093 DOI: 10.1016/j.intimp.2024.111860] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2024] [Revised: 02/24/2024] [Accepted: 03/11/2024] [Indexed: 03/22/2024]
Abstract
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.
Collapse
Affiliation(s)
- Jianan Zhao
- Department of Rheumatology, Shanghai Guanghua Hospital of Integrative Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China; Guanghua Clinical Medical College, Shanghai University of Traditional Chinese Medicine, Shanghai, China; Institute of Arthritis Research in Integrative Medicine, Shanghai Academy of Traditional Chinese Medicine, Shanghai, China
| | - Lingxia Xu
- Department of Rheumatology, Shanghai Guanghua Hospital of Integrative Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China; Guanghua Clinical Medical College, Shanghai University of Traditional Chinese Medicine, Shanghai, China; Institute of Arthritis Research in Integrative Medicine, Shanghai Academy of Traditional Chinese Medicine, Shanghai, China
| | - Kai Wei
- Department of Rheumatology, Shanghai Guanghua Hospital of Integrative Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China; Guanghua Clinical Medical College, Shanghai University of Traditional Chinese Medicine, Shanghai, China; Institute of Arthritis Research in Integrative Medicine, Shanghai Academy of Traditional Chinese Medicine, Shanghai, China
| | - Ping Jiang
- Department of Rheumatology, Shanghai Guanghua Hospital of Integrative Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China; Guanghua Clinical Medical College, Shanghai University of Traditional Chinese Medicine, Shanghai, China; Institute of Arthritis Research in Integrative Medicine, Shanghai Academy of Traditional Chinese Medicine, Shanghai, China
| | - Cen Chang
- Department of Rheumatology, Shanghai Guanghua Hospital of Integrative Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China; Guanghua Clinical Medical College, Shanghai University of Traditional Chinese Medicine, Shanghai, China; Institute of Arthritis Research in Integrative Medicine, Shanghai Academy of Traditional Chinese Medicine, Shanghai, China
| | - Linshuai Xu
- Department of Rheumatology, Shanghai Guanghua Hospital of Integrative Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China; Guanghua Clinical Medical College, Shanghai University of Traditional Chinese Medicine, Shanghai, China; Institute of Arthritis Research in Integrative Medicine, Shanghai Academy of Traditional Chinese Medicine, Shanghai, China
| | - Yiming Shi
- Department of Rheumatology, Shanghai Guanghua Hospital of Integrative Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China; Guanghua Clinical Medical College, Shanghai University of Traditional Chinese Medicine, Shanghai, China; Institute of Arthritis Research in Integrative Medicine, Shanghai Academy of Traditional Chinese Medicine, Shanghai, China
| | - Yixin Zheng
- Department of Rheumatology, Shanghai Guanghua Hospital of Integrative Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China; Guanghua Clinical Medical College, Shanghai University of Traditional Chinese Medicine, Shanghai, China; Institute of Arthritis Research in Integrative Medicine, Shanghai Academy of Traditional Chinese Medicine, Shanghai, China
| | - Yu Shan
- Department of Rheumatology, Shanghai Guanghua Hospital of Integrative Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China; Guanghua Clinical Medical College, Shanghai University of Traditional Chinese Medicine, Shanghai, China; Institute of Arthritis Research in Integrative Medicine, Shanghai Academy of Traditional Chinese Medicine, Shanghai, China
| | - Yuejuan Zheng
- The Research Center for Traditional Chinese Medicine, Shanghai Institute of Infectious Diseases and Biosecurity, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Yi Shen
- Department of Rheumatology, Shanghai Guanghua Hospital of Integrative Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China; Guanghua Clinical Medical College, Shanghai University of Traditional Chinese Medicine, Shanghai, China; Institute of Arthritis Research in Integrative Medicine, Shanghai Academy of Traditional Chinese Medicine, Shanghai, China
| | - Jia Liu
- Department of Rheumatology, Shanghai Guanghua Hospital of Integrative Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China; Guanghua Clinical Medical College, Shanghai University of Traditional Chinese Medicine, Shanghai, China; Institute of Arthritis Research in Integrative Medicine, Shanghai Academy of Traditional Chinese Medicine, Shanghai, China
| | - Shicheng Guo
- Department of Rheumatology, Shanghai Guanghua Hospital of Integrative Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Rongsheng Wang
- Department of Rheumatology, Shanghai Guanghua Hospital of Integrative Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China; Guanghua Clinical Medical College, Shanghai University of Traditional Chinese Medicine, Shanghai, China; Institute of Arthritis Research in Integrative Medicine, Shanghai Academy of Traditional Chinese Medicine, Shanghai, China
| | - Dongyi He
- Department of Rheumatology, Shanghai Guanghua Hospital of Integrative Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China; Guanghua Clinical Medical College, Shanghai University of Traditional Chinese Medicine, Shanghai, China; Institute of Arthritis Research in Integrative Medicine, Shanghai Academy of Traditional Chinese Medicine, Shanghai, China.
| |
Collapse
|
3
|
Yang W, Wang Y, Tao K, Li R. Metabolite itaconate in host immunoregulation and defense. Cell Mol Biol Lett 2023; 28:100. [PMID: 38042791 PMCID: PMC10693715 DOI: 10.1186/s11658-023-00503-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2023] [Accepted: 10/20/2023] [Indexed: 12/04/2023] Open
Abstract
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.
Collapse
Affiliation(s)
- Wenchang Yang
- Department of Gastrointestinal Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1277 Jiefang Avenue, Wuhan, 430022, Hubei, China
- Department of Gastrointestinal Surgery, Affiliated Hospital of Qingdao University, Qingdao, China
| | - Yaxin Wang
- Department of Critical Care Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China
| | - Kaixiong Tao
- Department of Gastrointestinal Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1277 Jiefang Avenue, Wuhan, 430022, Hubei, China
| | - Ruidong Li
- Department of Gastrointestinal Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1277 Jiefang Avenue, Wuhan, 430022, Hubei, China.
| |
Collapse
|
4
|
Zhao J, Wei K, Shi Y, Jiang P, Xu L, Chang C, Xu L, Zheng Y, Shan Y, Liu J, Li L, Guo S, Schrodi SJ, Wang R, He D. Identification of immunological characterization and Anoikis-related molecular clusters in rheumatoid arthritis. Front Mol Biosci 2023; 10:1202371. [PMID: 38046810 PMCID: PMC10691379 DOI: 10.3389/fmolb.2023.1202371] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2023] [Accepted: 11/07/2023] [Indexed: 12/05/2023] Open
Abstract
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.
Collapse
Affiliation(s)
- Jianan Zhao
- 1Department of Rheumatology, Shanghai Guanghua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Guanghua Clinical Medical College, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Institute of Arthritis Research in Integrative Medicine, Shanghai Academy of Traditional Chinese Medicine, Shanghai, China
| | - Kai Wei
- 1Department of Rheumatology, Shanghai Guanghua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Guanghua Clinical Medical College, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Institute of Arthritis Research in Integrative Medicine, Shanghai Academy of Traditional Chinese Medicine, Shanghai, China
| | - Yiming Shi
- 1Department of Rheumatology, Shanghai Guanghua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Guanghua Clinical Medical College, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Institute of Arthritis Research in Integrative Medicine, Shanghai Academy of Traditional Chinese Medicine, Shanghai, China
| | - Ping Jiang
- 1Department of Rheumatology, Shanghai Guanghua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Guanghua Clinical Medical College, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Institute of Arthritis Research in Integrative Medicine, Shanghai Academy of Traditional Chinese Medicine, Shanghai, China
| | - Lingxia Xu
- 1Department of Rheumatology, Shanghai Guanghua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Guanghua Clinical Medical College, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Institute of Arthritis Research in Integrative Medicine, Shanghai Academy of Traditional Chinese Medicine, Shanghai, China
| | - Cen Chang
- 1Department of Rheumatology, Shanghai Guanghua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Guanghua Clinical Medical College, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Institute of Arthritis Research in Integrative Medicine, Shanghai Academy of Traditional Chinese Medicine, Shanghai, China
| | - Linshuai Xu
- 1Department of Rheumatology, Shanghai Guanghua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Guanghua Clinical Medical College, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Institute of Arthritis Research in Integrative Medicine, Shanghai Academy of Traditional Chinese Medicine, Shanghai, China
| | - Yixin Zheng
- 1Department of Rheumatology, Shanghai Guanghua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Guanghua Clinical Medical College, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Institute of Arthritis Research in Integrative Medicine, Shanghai Academy of Traditional Chinese Medicine, Shanghai, China
| | - Yu Shan
- 1Department of Rheumatology, Shanghai Guanghua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Guanghua Clinical Medical College, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Institute of Arthritis Research in Integrative Medicine, Shanghai Academy of Traditional Chinese Medicine, Shanghai, China
| | - Jia Liu
- 1Department of Rheumatology, Shanghai Guanghua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Institute of Arthritis Research in Integrative Medicine, Shanghai Academy of Traditional Chinese Medicine, Shanghai, China
- Arthritis Institute of Integrated Traditional and Western Medicine, Shanghai Chinese Medicine Research Institute, Shanghai, China
| | - Li Li
- 1Department of Rheumatology, Shanghai Guanghua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Institute of Arthritis Research in Integrative Medicine, Shanghai Academy of Traditional Chinese Medicine, Shanghai, China
- Arthritis Institute of Integrated Traditional and Western Medicine, Shanghai Chinese Medicine Research Institute, Shanghai, China
| | - Shicheng Guo
- Computation and Informatics in Biology and Medicine, University of Wisconsin-Madison, Madison, WIUnited States
- Department of Medical Genetics, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, United States
| | - Steven J. Schrodi
- Computation and Informatics in Biology and Medicine, University of Wisconsin-Madison, Madison, WIUnited States
- Department of Medical Genetics, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, United States
| | - Rongsheng Wang
- 1Department of Rheumatology, Shanghai Guanghua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Guanghua Clinical Medical College, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Institute of Arthritis Research in Integrative Medicine, Shanghai Academy of Traditional Chinese Medicine, Shanghai, China
| | - Dongyi He
- 1Department of Rheumatology, Shanghai Guanghua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Guanghua Clinical Medical College, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Institute of Arthritis Research in Integrative Medicine, Shanghai Academy of Traditional Chinese Medicine, Shanghai, China
- Arthritis Institute of Integrated Traditional and Western Medicine, Shanghai Chinese Medicine Research Institute, Shanghai, China
| |
Collapse
|
5
|
Qi Z, Zhu L, Wang K, Wang N. PANoptosis: Emerging mechanisms and disease implications. Life Sci 2023; 333:122158. [PMID: 37806654 DOI: 10.1016/j.lfs.2023.122158] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Revised: 09/26/2023] [Accepted: 10/05/2023] [Indexed: 10/10/2023]
Abstract
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.
Collapse
Affiliation(s)
- Zehong Qi
- Department of Pathophysiology, Key Laboratory of Sepsis Translational Medicine of Hunan, School of Basic Medical Science, Central South University, 410008 Changsha, Hunan, China
| | - Lili Zhu
- Department of Pathophysiology, Key Laboratory of Sepsis Translational Medicine of Hunan, School of Basic Medical Science, Central South University, 410008 Changsha, Hunan, China
| | - Kangkai Wang
- Department of Pathophysiology, Key Laboratory of Sepsis Translational Medicine of Hunan, School of Basic Medical Science, Central South University, 410008 Changsha, Hunan, China.
| | - Nian Wang
- Department of Pathophysiology, Key Laboratory of Sepsis Translational Medicine of Hunan, School of Basic Medical Science, Central South University, 410008 Changsha, Hunan, China.
| |
Collapse
|
6
|
Wu D, Li Y, Xu R. Can pyroptosis be a new target in rheumatoid arthritis treatment? Front Immunol 2023; 14:1155606. [PMID: 37426634 PMCID: PMC10324035 DOI: 10.3389/fimmu.2023.1155606] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Accepted: 06/07/2023] [Indexed: 07/11/2023] Open
Abstract
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.
Collapse
Affiliation(s)
- Dengqiang Wu
- Department of Clinical Laboratory, Ningbo No.6 Hospital, Ningbo, China
| | - Yujie Li
- Department of Clinical Laboratory, Ningbo Medical Center Lihuili Hospital, Ningbo, China
| | - Ranxing Xu
- Department of Clinical Laboratory, Ningbo No.6 Hospital, Ningbo, China
| |
Collapse
|
7
|
Gong G, Wan W, Liu X, Yin J. Apelin-13, a regulator of autophagy, apoptosis and inflammation in multifaceted bone protection. Int Immunopharmacol 2023; 117:109991. [PMID: 37012875 DOI: 10.1016/j.intimp.2023.109991] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2023] [Revised: 03/01/2023] [Accepted: 03/02/2023] [Indexed: 03/12/2023]
Abstract
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.
Collapse
Affiliation(s)
- Ge Gong
- Department of Geriatrics, Jinling Hospital, Medical School of Nanjing University, Nanjing 211002, China
| | - Wenhui Wan
- Department of Geriatrics, Jinling Hospital, Medical School of Nanjing University, Nanjing 211002, China
| | - Xinhui Liu
- Department of Orthopedics, the Affiliated Jiangning Hospital with Nanjing Medical University, Nanjing 211100, China.
| | - Jian Yin
- Department of Orthopedics, the Affiliated Jiangning Hospital with Nanjing Medical University, Nanjing 211100, China.
| |
Collapse
|
8
|
Zheng Y, Zhao J, Shan Y, Guo S, Schrodi SJ, He D. Role of the granzyme family in rheumatoid arthritis: Current Insights and future perspectives. Front Immunol 2023; 14:1137918. [PMID: 36875082 PMCID: PMC9977805 DOI: 10.3389/fimmu.2023.1137918] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Accepted: 02/03/2023] [Indexed: 02/18/2023] Open
Abstract
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.
Collapse
Affiliation(s)
- Yixin Zheng
- Department of Rheumatology, Shanghai Guanghua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China.,Guanghua Clinical Medical College, Shanghai University of Traditional Chinese Medicine, Shanghai, China.,Institute of Arthritis Research in Integrative Medicine, Shanghai Academy of Traditional Chinese Medicine, Shanghai, China
| | - Jianan Zhao
- Department of Rheumatology, Shanghai Guanghua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China.,Guanghua Clinical Medical College, Shanghai University of Traditional Chinese Medicine, Shanghai, China.,Institute of Arthritis Research in Integrative Medicine, Shanghai Academy of Traditional Chinese Medicine, Shanghai, China
| | - Yu Shan
- Department of Rheumatology, Shanghai Guanghua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China.,Guanghua Clinical Medical College, Shanghai University of Traditional Chinese Medicine, Shanghai, China.,Institute of Arthritis Research in Integrative Medicine, Shanghai Academy of Traditional Chinese Medicine, Shanghai, China
| | - Shicheng Guo
- Center for Human Genomics and Precision Medicine, University of Wisconsin-Madison, Madison, WI, United States.,Department of Medical Genetics, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, United States
| | - Steven J Schrodi
- Center for Human Genomics and Precision Medicine, University of Wisconsin-Madison, Madison, WI, United States.,Department of Medical Genetics, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, United States
| | - Dongyi He
- Department of Rheumatology, Shanghai Guanghua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China.,Guanghua Clinical Medical College, Shanghai University of Traditional Chinese Medicine, Shanghai, China.,Institute of Arthritis Research in Integrative Medicine, Shanghai Academy of Traditional Chinese Medicine, Shanghai, China.,Arthritis Institute of Integrated Traditional and Western medicine, Shanghai Chinese Medicine Research Institute, Shanghai, China
| |
Collapse
|