Identification of New, Functionally Relevant Mutations in the Coding Regions of the Human Fos and Jun Proto-Oncogenes in Rheumatoid Arthritis Synovial Tissue

Huber, René; Augsten, Sandra; Kirsten, Holger; Zell, Roland; Stelzner, A.; Thude, Hansjörg; Eidner, Thorsten; Stuhlmüller, Bruno; Ahnert, Peter; Kinne, Raimund W.

doi:10.3390/life11010005

Cited by 10 publications

(8 citation statements)

References 76 publications

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“…JUN is a major component of AP-1, which determines the expression of many pro-inflammatory proteins in RA. [36] MAPK protein kinase is involved in the signaling process from the cell membrane to nucleus and regulates cell growth, differentiation, stress, inflammation, and other cell pathological and physiological processes. [37] Therefore, melittin may inhibit the activation of JUN and ERK1/2 (MAPK3, MAPK1) pathways, thereby effectively blocking inflammatory responses, which was confirmed in this study.…”

Section: Discussionmentioning

confidence: 99%

Exploring potential network pharmacology-and molecular docking-based mechanism of melittin in treating rheumatoid arthritis

Wei

Gong

et al. 2023

Medicine

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Background: Rheumatoid arthritis (RA) is a type of difficult-to-cure arthralgia with a worldwide prevalence. It severely affects people’s living standards. For a long time, bee venom has been used to treat RA and has shown good results. Melittin is the main active component of bee venom used for RA treatment, but the molecular mechanism of melittin in RA treatments remains unclear. Methods: Potential melittin and RA targets were obtained from relevant databases, and common targets of melittin and RA were screened. The STRING database was used to build the PPI network and screen the core targets after visualization. The core targets were enriched by Gene Ontology functional annotation and Kyoto Encyclopedia of Genes and Genomes pathway. Finally, the binding of melittin to target proteins was evaluated through simulated molecular docking, which verified the reliability of the prediction results of network pharmacology. Results: In total, 138 melittin targets and 5795 RA targets were obtained from relevant databases, and 90 common targets were obtained through intersection. Eighteen core targets, such as STAT3, AKT1, tumor necrosis factor, and JUN, were screened out. Enrichment analysis results suggested that melittin plays an anti-RA role mainly through tumor necrosis factor, interleukin-17, toll-like receptors, and advanced glycation end products–RAGE signaling pathways, and pathogenic bacterial infection. Molecular docking results suggested that melittin has good docking activity with core target proteins. Conclusion: RA treatment with melittin is the result of a multi-target and multi-pathway interaction. This study offers a theoretical basis and scientific evidence for further exploring melittin in RA therapy.

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Section: Discussionmentioning

confidence: 99%

Exploring potential network pharmacology-and molecular docking-based mechanism of melittin in treating rheumatoid arthritis

Wei

Gong

et al. 2023

Medicine

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“…CAV1 [626], TFAP2A [842], TP53 [843] and NFKB1 [844] have been identified as a new potential therapeutic target against systemic sclerosis. CAV1 [767], hsa-mir-19b-3p [845], JUN (Jun proto-oncogene, AP-1 transcription factor subunit) [846], STAT1 [847], TP53 [848] and NFKB1 [849] are reported to promote rheumatoid arthritis. The role of CAV1 [797] in the growth and progression of scleroderma.…”

Section: Discussionmentioning

confidence: 99%

Study on potential differentially expressed genes in idiopathic pulmonary fibrosis by bioinformatics and next generation sequencing data analysis

Vastrad,

Vastrad

2023

Preprint

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Idiopathic pulmonary fibrosis (IPF) is a chronic progressive lung disease with reduced quality of life and earlier mortality, but its pathogenesis and key genes are still unclear. In this investigation, bioinformatics was used to deeply analyze the pathogenesis of IPF and related key genes, so as to investigate the potential molecular pathogenesis of IPF and provide guidance for clinical treatment. Next generation sequencing dataset GSE213001 was obtained from Gene Expression Omnibus (GEO), the differentially expressed genes (DEGs) were identified between IPF and normal control group. The DEGs between IPF and normal control group were screened with the DESeq2 package of R language. The Gene Ontology (GO) and REACTOME pathway enrichment analyses of the DEGs were performed. Using the g:Profiler, the function and pathway enrichment analysis of DEGs were performed. Then, a protein protein interaction (PPI) network was constructed via the Integrated Interactions Database (IID) database. Cytoscape with Network Analyzer was used to identify the hub genes. miRNet and NetworkAnalyst database was used to construct the targeted microRNAs (miRNAs) and transcription factors (TFs) of the hub genes. Finally receiver operating characteristic (ROC) curve analysis was used to validates the hub genes. A total of 958 DEGs were screened out in this study, including 479 up regulated genes and 479 down regulated genes. Most of the DEGs were significantly enriched in response to stimulus, GPCR ligand binding, microtubule-based process and defective GALNT3 causes HFTC. In combination with the results of the PPI network, miRNA-hub gene regulatory network and TF-hub gene regulatory network, hub genes including LRRK2, BMI1, EBP, MNDA, KBTBD7, KRT15, OTX1, TEKT4, SPAG8 and EFHC2 were selected. Our findings will contribute to identification of potential biomarkers and novel strategies for the treatment of IPF, and provide a novel strategy for clinical therapy.

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“… 32 , 33 , 34 TNFAIP3 had the biological function of deubiquitinase, which could block the interaction between ubiquitin ligase and conjugation enzyme, thereby inhibiting the activation of NF‐κB signaling 35 ; A complex formed by FOS and JUN in the nucleus could bind to the AP‐1 site of the target gene, which would not only activate matrix metalloproteinase (MMP) to destroy cartilage matrix, promote NF‐κB signal to induce osteoclast differentiation and damage bone, but also promote the secretion of inflammatory factors and exacerbate joint inflammation. 36 , 37 , 38 Therefore, the author believes that by acting on the above targets and pathways, the inflammatory factors in the blood can be effectively regulated to inhibit the body's inflammatory response as well as the proliferation, differentiation, and apoptosis of chondrocytes and osteoclasts, thereby alleviating the destruction of articular cartilage to treat gout and its complications (Detailed information is shown in Figure 7 ).…”

Section: Discussionmentioning

confidence: 99%

“…When NF‐κB protein was stimulated by blood uric acid, it would be transported to the nucleus, bind with PTGS2 (Cyclooxygenase‐2, COX‐2) promoter region (including NF‐kB site), activate the oxidative stress response, release IL‐1β and other inflammatory factors, and further stimulate the expression of IL‐17 pathway 32‐34 35 ; A complex formed by FOS and JUN in the nucleus could bind to the AP‐1 site of the target gene, which would not only activate matrix metalloproteinase (MMP) to destroy cartilage matrix, promote NF‐κB signal to induce osteoclast differentiation and damage bone, but also promote the secretion of inflammatory factors and exacerbate joint inflammation 36‐38 7).…”

Section: Discussionmentioning

confidence: 99%

Construction of lncRNA‐miRNA‐mRNA network based on ceRNA mechanism reveals the function of lncRNA in the pathogenesis of gout

Chen

Zhang

Chai

et al. 2022

Clinical Laboratory Analysis

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Objective To identify differentially expressed lncRNA, miRNA, and mRNA during the pathogenesis of gout, explore the ceRNA network regulatory mechanism of gout, and seek potential therapeutic targets. Method First, gout‐related chips were retrieved by GEO database. Then, the analysis of differentially expressed lncRNAs and mRNAs was conducted by R language and other software. Besides, miRNA and its regulated mRNA were predicted based on public databases, the intersection of differentially expressed mRNA and predicated mRNA was taken, and the lncRNA‐miRNA‐mRNA regulatory relationships were obtained to construct the ceRNA regulatory network. Subsequently, hub genes were screened by the STRING database and Cytoscape software. Then the DAVID database was used to illustrate the gene functions and related pathways of hub genes and to mine key ceRNA networks. Results Three hundred and eighty‐eight lncRNAs and 758 mRNAs were identified with significant differential expression in gout patient, which regulates hub genes in the ceRNA network, such as JUN, FOS, PTGS2, NR4A2, and TNFAIP3. In the ceRNA network, lncRNA competes with mRNA for miRNA, thus affecting the IL‐17 signaling pathway, TNF signaling pathway, Oxytocin signaling pathway, and NF‐κB signaling pathway through regulating the cell's response to chemical stress. The research indicates that five miRNAs (miR‐429, miR‐137, miR‐139‐5p, miR‐217, miR‐23b‐3p) and five lncRNAs (SNHG1, FAM182A, SPAG5‐AS1, HNF1A‐AS1, UCA1) play an important role in the formation and development of gout. Conclusion The interaction in the ceRNA network can affect the formation and development of gout by regulating the body's inflammatory response as well as proliferation, differentiation, and apoptosis of chondrocytes and osteoclasts. The identification of potential therapeutic targets and signaling pathways through ceRNA network can provide a reference for further research on the pathogenesis of gout.

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Identification of New, Functionally Relevant Mutations in the Coding Regions of the Human Fos and Jun Proto-Oncogenes in Rheumatoid Arthritis Synovial Tissue

Cited by 10 publications

References 76 publications

Exploring potential network pharmacology-and molecular docking-based mechanism of melittin in treating rheumatoid arthritis

Exploring potential network pharmacology-and molecular docking-based mechanism of melittin in treating rheumatoid arthritis

Study on potential differentially expressed genes in idiopathic pulmonary fibrosis by bioinformatics and next generation sequencing data analysis

Construction of lncRNA‐miRNA‐mRNA network based on ceRNA mechanism reveals the function of lncRNA in the pathogenesis of gout

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