OP0184 PHENOTYPING OF MOLECULAR SIGNATURES IN THE SYNOVIAL TISSUE OF RHEUMATOID ARTHRITIS BY INTEGRATIVE SYSTEMS ANALYSIS

Background:Rheumatoid arthritis (RA) is an aggressive immune-mediated joint disease characterized by synovial proliferation and inflammation, cartilage destruction, and joint destruction1. Despite efforts to characterize the disease subsets and to predict the differential prognosis in RA patients, disease heterogeneity is not adequately translated into the current clinical subclassification2.Objectives:To develop and validate an integrative system approach for stratifying patients with RA according to disease status and whole-genome gene expression data.Methods:An RNA sequencing dataset of synovial tissues from 124 RA patients (including 57 patients with early RA, 95 with established RA) and 15 healthy controls (HC) was imported from the Gene Expression Omnibus (GEO) database (GSE89408) by software package R (version 4.0.3). After filtrating of differentially expressed genes (DEGs) between RA and HC, non-negative matrix factorization, functional enrichment, and immune cell infiltration were applied to illustrate the landscapes of these patients for classification. Clinical features (age, gender, and auto-antibodies) were also compared to discover the signatures of these classifications.Results:A matrix of 576 DEGs from RA samples was classified into 5 subtypes (early/C1–C3, established/C4-C5) with distinct molecular and cellular signatures and two sub-groups (S1 and S2) (Figure 1A-1D). New-onset patients (early C2) and established C4 patients were named as S1, they shared similar gene signatures mainly characterized by prominent immune cells and proinflammatory signatures, and enriched in the chemokine-mediated signaling pathway, lymphocyte activation, response to bacterium and Primary immunodeficiency. S2(C1, C3 and C5) were more occupied by synovial fibroblasts of destructive phenotype. They were mainly enriched in the response to external factors and PPAR signaling pathway (Figure 1E-1H). Interestingly, combined with clinical information, S1 and S2 had no significance in age and gender (P > 0.05). But patients in S1 had a stronger association with the presence of anti-citrullinated protein antibodies (ACPA) (P < 0.05) (Figure 1I-1J).Conclusion:We successfully deconvoluted RA synovial tissues into pathobiological discrete subsets using an unsupervised machine learning method and described their distinct molecular and cellular characteristics. These results provide important insights into divergent and shared mechanistic features of RA and serve as a template for future studies to guide drug tar-get discovery by synovial molecular signatures and de-sign stratified approaches for patients with RA.References:[1]Smolen JS, Aletaha D, McInnes IB. Rheumatoid arthritis. Lancet 2016;388(10055):2023-38. doi: 10.1016/S0140-6736(16)30173-8 [published Online First: 2016/10/30][2]Jung SM, Park KS, Kim KJ. Deep phenotyping of synovial molecular signatures by integrative systems analysis in rheumatoid arthritis. Rheumatology (Oxford) 2020 doi: 10.1093/rheumatology/keaa751 [published Online First: 2020/11/25]Acknowledgements:This project was supported by National Science Foundation of China (82001740), Open Fund from the Key Laboratory of Cellular Physiology (Shanxi Medical University) (KLCP2019) and Innovation Plan for Postgraduate Education in Shanxi Province (2020BY078).Disclosure of Interests:None declared

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Identification and validation of hub genes of synovial tissue for patients with osteoarthritis and rheumatoid arthritis

Hereditas ◽

10.1186/s41065-021-00201-0 ◽

2021 ◽

Vol 158 (1) ◽

Author(s):

Yanzhi Ge ◽

Zuxiang Chen ◽

Yanbin Fu ◽

Xiujuan Xiao ◽

Haipeng Xu ◽

...

Keyword(s):

Rheumatoid Arthritis ◽

Gene Expression ◽

Signaling Pathway ◽

Quantitative Polymerase Chain Reaction ◽

Functional Enrichment ◽

Proximal Promoter ◽

Integrated Analysis ◽

Data Sets ◽

Hub Genes ◽

Multiple Gene

Abstract Background Osteoarthritis (OA) and rheumatoid arthritis (RA) were two major joint diseases with similar clinical phenotypes. This study aimed to determine the mechanistic similarities and differences between OA and RA by integrated analysis of multiple gene expression data sets. Methods Microarray data sets of OA and RA were obtained from the Gene Expression Omnibus (GEO). By integrating multiple gene data sets, specific differentially expressed genes (DEGs) were identified. The Gene Ontology (GO) functional annotation, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways and protein–protein interaction (PPI) network analysis of DEGs were conducted to determine hub genes and pathways. The “Cell Type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT)” algorithm was employed to evaluate the immune infiltration cells (IICs) profiles in OA and RA. Moreover, mouse models of RA and OA were established, and selected hub genes were verified in synovial tissues with quantitative polymerase chain reaction (qPCR). Results A total of 1116 DEGs were identified between OA and RA. GO functional enrichment analysis showed that DEGs were enriched in regulation of cell morphogenesis involved in differentiation, positive regulation of neuron differentiation, nuclear speck, RNA polymerase II transcription factor complex, protein serine/threonine kinase activity and proximal promoter sequence-specific DNA binding. KEGG pathway analysis showed that DEGs were enriched in EGFR tyrosine kinase inhibitor resistance, ubiquitin mediated proteolysis, FoxO signaling pathway and TGF-beta signaling pathway. Immune cell infiltration analysis identified 9 IICs with significantly different distributions between OA and RA samples. qPCR results showed that the expression levels of the hub genes (RPS6, RPS14, RPS25, RPL11, RPL27, SNRPE, EEF2 and RPL19) were significantly increased in OA samples compared to their counterparts in RA samples (P < 0.05). Conclusion This large-scale gene analyses provided new insights for disease-associated genes, molecular mechanisms as well as IICs profiles in OA and RA, which may offer a new direction for distinguishing diagnosis and treatment between OA and RA.

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POS0458 IDENTIFICATION OF HUB GENES AND MOLECULAR PATHWAYS IN PATIENTS WITH RHEUMATOID ARTHRITIS BY BIOINFORMATICS ANALYSIS

Annals of the Rheumatic Diseases ◽

10.1136/annrheumdis-2021-eular.1938 ◽

2021 ◽

Vol 80 (Suppl 1) ◽

pp. 460.1-460

Author(s):

L. Cheng ◽

S. X. Zhang ◽

S. Song ◽

C. Zheng ◽

X. Sun ◽

...

Keyword(s):

Rheumatoid Arthritis ◽

Signaling Pathway ◽

Synovial Tissue ◽

Bioinformatics Analysis ◽

Metabolic Process ◽

Shanxi Province ◽

Molecular Pathways ◽

Biological Processes ◽

Hub Genes ◽

Tissue Samples

Background:Rheumatoid arthritis (RA) is a chronic, inflammatory synovitis based systemic disease of unknown etiology1. The genes and pathways in the inflamed synovium of RA patients are poorly understood.Objectives:This study aims to identify differentially expressed genes (DEGs) associated with the progression of synovitis in RA using bioinformatics analysis and explore its pathogenesis2.Methods:RA expression profile microarray data GSE89408 were acquired from the public gene chip database (GEO), including 152 synovial tissue samples from RA and 28 healthy synovial tissue samples. The DEGs of RA synovial tissues were screened by adopting the R software. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed. Protein-protein interaction (PPI) networks were assembled with Cytoscape software.Results:A total of 654 DEGs (268 up-regulated genes and 386 down-regulated genes) were obtained by the differential analysis. The GO enrichment results showed that the up-regulated genes were significantly enriched in the biological processes of myeloid leukocyte activation, cellular response to interferon-gamma and immune response-regulating signaling pathway, and the down-regulated genes were significantly enriched in the biological processes of extracellular matrix, retinoid metabolic process and regulation of lipid metabolic process. The KEGG annotation showed the up-regulated genes mainly participated in the staphylococcus aureus infection, chemokine signaling pathway, lysosome signaling pathway and the down-regulated genes mainly participated in the PPAR signaling pathway, AMPK signaling pathway, ECM-receptor interaction and so on. The 9 hub genes (PTPRC, TLR2, tyrobp, CTSS, CCL2, CCR5, B2M, fcgr1a and PPBP) were obtained based on the String database model by using the Cytoscape software and cytoHubba plugin3.Conclusion:The findings identified the molecular mechanisms and the key hub genes of pathogenesis and progression of RA.References:[1]Xiong Y, Mi BB, Liu MF, et al. Bioinformatics Analysis and Identification of Genes and Molecular Pathways Involved in Synovial Inflammation in Rheumatoid Arthritis. Med Sci Monit 2019;25:2246-56. doi: 10.12659/MSM.915451 [published Online First: 2019/03/28][2]Mun S, Lee J, Park A, et al. Proteomics Approach for the Discovery of Rheumatoid Arthritis Biomarkers Using Mass Spectrometry. Int J Mol Sci 2019;20(18) doi: 10.3390/ijms20184368 [published Online First: 2019/09/08][3]Zhu N, Hou J, Wu Y, et al. Identification of key genes in rheumatoid arthritis and osteoarthritis based on bioinformatics analysis. Medicine (Baltimore) 2018;97(22):e10997. doi: 10.1097/MD.0000000000010997 [published Online First: 2018/06/01]Acknowledgements:This project was supported by National Science Foundation of China (82001740), Open Fund from the Key Laboratory of Cellular Physiology (Shanxi Medical University) (KLCP2019) and Innovation Plan for Postgraduate Education in Shanxi Province (2020BY078).Disclosure of Interests:None declared

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Differential gene expression in articular cartilage between rheumatoid arthritis and endemic Kashin–Beck disease

Bioscience Reports ◽

10.1042/bsr20190188 ◽

2019 ◽

Vol 39 (6) ◽

Cited By ~ 1

Author(s):

Zongqiang Gao ◽

Chen Duan ◽

Fang-fang Yu ◽

Xiong Guo

Keyword(s):

Rheumatoid Arthritis ◽

Gene Expression ◽

Articular Cartilage ◽

Signaling Pathway ◽

Differential Gene Expression ◽

Mapk Signaling ◽

Janus Kinase ◽

Ppi Network ◽

Differential Gene ◽

Beck Disease

AbstractKashin–beck disease (KBD) is endemic chronic osteoarthrosis and its pathogenesis is still unclear. The present study aimed to explore differential gene expression in articular cartilage between patients with rheumatoid arthritis (RA) and KBD. Articular cartilages were collected from KBD and RA patients, and differentially expressed genes (DEGs) were analyzed by RNA-seq. The signaling pathway and biological process (BP) of the DEGs were identified by enrichment analysis. The protein–protein interaction (PPI) network of DEGs and the key genes of KBD were identified by network analysis with STRING and cytoscape software. We identified 167 immune-related DEGs in articular cartilage samples from KBD patients compared with RA. The up-regulation of MAPK signaling pathway and the down-regulation of signaling pathways such as toll-like receptor, janus kinase-signal transducers and activators of transcription, leukocyte migration, T-cell receptor and chemokine, and antigen processing and presentation were involved in KBD. We identified 137 genes nodes related with immune and mapped the PPI network diagram. BP analysis revealed that immune response, calcium ion homeostasis, blood vessel morphogenesis, inflammatory response, lymphocyte proliferation, and MAPK activation were involved in KBD. In conclusion, gene expression profiling can be used to identify the different mechanism of pathogenesis between KBD and RA.

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Network analysis uncovers putative genes affecting resistance to tick infestation in Braford cattle skin

BMC Genomics ◽

10.1186/s12864-019-6360-3 ◽

2019 ◽

Vol 20 (1) ◽

Cited By ~ 4

Author(s):

Daniela D. Moré ◽

Fernando F. Cardoso ◽

Maurício A. Mudadu ◽

Wilson Malagó-Jr ◽

Claudia C. Gulias-Gomes ◽

...

Keyword(s):

Gene Expression ◽

Network Analysis ◽

Wnt Signaling ◽

Signaling Pathway ◽

Tick Infestation ◽

Wnt Signaling Pathway ◽

Functional Enrichment ◽

A Genome ◽

Genetic Mechanisms ◽

Different Levels

Abstract Background Genetic resistance in cattle is considered a suitable way to control tick burden and its consequent losses for livestock production. Exploring tick-resistant (R) and tick-susceptible (S) hosts, we investigated the genetic mechanisms underlying the variation of Braford resistance to tick infestation. Skin biopsies from four-times-artificially infested R (n = 20) and S (n = 19) hosts, obtained before the first and 24 h after the fourth tick infestation were submitted to RNA-Sequencing. Differential gene expression, functional enrichment, and network analysis were performed to identify genetic pathways and transcription factors (TFs) affecting host resistance. Results Intergroup comparisons of hosts before (Rpre vs. Spre) and after (Rpost vs. Spost) tick infestation found 51 differentially expressed genes (DEGs), of which almost all presented high variation (TopDEGs), and 38 were redundant genes. Gene expression was consistently different between R and S hosts, suggesting the existence of specific anti-tick mechanisms. In the intragroup comparisons, Rpost vs. Rpre and Spost vs. Spre, we found more than two thousand DEGs in response to tick infestation in both resistance groups. Redundant and non-redundant TopDEGs with potential anti-tick functions suggested a role in the development of different levels of resistance within the same breed. Leukocyte chemotaxis was over-represented in both hosts, whereas skin degradation and remodeling were only found in TopDEGs from R hosts. Also, these genes indicated the participation of cytokines, such as IL6 and IL22, and the activation of Wingless (WNT)-signaling pathway. A central gene of this pathway, WNT7A, was consistently modulated when hosts were compared. Moreover, the findings based on a genome-wide association study (GWAS) corroborate the prediction of the WNT-signaling pathway as a candidate mechanism of resistance. The regulation of immune response was the most relevant pathway predicted for S hosts. Members of Ap1 and NF-kB families were the most relevant TFs predicted for R and S, respectively. Conclusion This work provides indications of genetic mechanisms presented by Braford cattle with different levels of resistance in response to tick infestation, contributing to the search of candidate genes for tick resistance in bovine.

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Single Cell RNA-Seq Analysis Identifies Differentially Expressed Genes of Treg Cell in Early Treatment-Naive Rheumatoid Arthritis By Arsenic Trioxide

Frontiers in Pharmacology ◽

10.3389/fphar.2021.656124 ◽

2021 ◽

Vol 12 ◽

Author(s):

Chunling Li ◽

Tianshu Chu ◽

Zhiyi Zhang ◽

Yue Zhang

Keyword(s):

Rheumatoid Arthritis ◽

Gene Expression ◽

Amino Acids ◽

Single Cell ◽

Signaling Pathway ◽

Early Treatment ◽

Cell Apoptosis ◽

Treg Cells ◽

Rna Seq ◽

Treatment Naïve

Objective: Early treatment-naïve rheumatoid arthritis (RA) has defective regulatory T (Treg) cells and increased inflammation response. In this study, we aim to illustrate the regulation of Treg cells in pathogenesis of early rheumatoid arthritis by arsenic trioxide (As2O3).Methods: We studied the effects of As2O3 on gene expression in early treatment-naïve RA Treg cells with single cell RNA-seq (scRNA-seq). Treg cells were sorted from peripheral blood mononuclear cells (PBMCs) and purified by fluorescence-activated cell sorting (FACS) and cultured with or without As2O3 (at 0.1 µM) for 24 h. Total RNA was isolated and sequenced, and functional analysis was performed against the Gene Ontology (GO) database. Results for selected genes were confirmed with RT-qPCR.Results: As2O3 exerts no significant effect on CD4+ T-cell apoptosis under physical condition, and selectively modulate CD4+ T cells toward Treg cells not Th17 cells under special polarizing stimulators. As2O3 increased the expression of 200 and reduced that of 272 genes with fold change (FC) 2.0 or greater. Several genes associated with inflammation, Treg-cell activation and differentiation as well as glucose and amino acids metabolism were among the most strongly affected genes. GO function analysis identified top ten ranked significant biological process (BPs), molecular functions (MFs), and cell components (CCs) in treatment and nontreatment Treg cells. In GO analysis, genes involved in the immunoregulation, cell apoptosis and cycle, inflammation, and cellular metabolism were enriched among the significantly affected genes. The KEGG pathway enrichment analysis identified the forkhead box O (FoxO) signal pathway, apoptosis, cytokine–cytokine receptor interaction, cell cycle, nuclear factor-kappa B (NF-κB) signaling pathway, tumor necrosis factor α (TNF-α), p53 signaling pathway, and phosphatidylinositol 3′-kinase (PI3K)-Akt signaling pathway were involved in the pathogenesis of early treatment-naïve RA.Conclusion: This is the first study investigating the genome-wide effects of As2O3 on the gene expression of treatment-naïve Treg cells. In addition to clear anti-inflammatory and immunoregulation effects, As2O3 affect amino acids and glucose metabolism in Treg cells, an observation that might be particularly important in the metabolic phenotype of treatment-naïve RA.

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Identification of Potential Biomarkers in Synovial Tissue of Rheumatoid Arthritis via Integrated Microarray Analysis. Identification of Biomarkers of Rheumatoid Arthritis

10.21203/rs.3.rs-700226/v1 ◽

2021 ◽

Author(s):

Li Tao ◽

ChaoLiang Xiong ◽

Li Xue

Keyword(s):

Rheumatoid Arthritis ◽

Gene Expression ◽

Pathway Analysis ◽

Expression Profiles ◽

Diagnostic Value ◽

Functional Enrichment ◽

Venn Diagram ◽

Ppi Network ◽

Hub Genes ◽

Gene Markers

Abstract Background: Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by synovitis and subsequent destruction of cartilage and bone. This study aimed to explore RA-related gene markers and the underlying molecular mechanism.Material and Methods: The expression profiles of GSE77298, GSE55235 and GSE12021 were obtained from the Gene Expression Omnibus database. Then, the differential gene expression analysis was conducted between GSE77298 and GSE55235 datasets. Limma package and a Venn diagram were utilized to screen the overlapping differentially expressed genes (DEGs), and Functional enrichment and pathway analysis were performed by using DAVID database. Subsequently, a protein-protein interaction (PPI) network was established, and candidate hub genes were recognized by using STRING and Cytoscape software. Finally, another dataset (GSE12021) was used for the validation of diagnostic value of the candidate hub genes and to identify real hub genes by using receiver operating characteristic (ROC) curves.Results: A total of 385 DEGs were detected, which include 19 downregulated genes and 366 upregulated genes. GO and KEGG pathway analysis showed that DEGs was mainly enriched in various immune and inflammatory response-related functions and pathways. The PPI network was composed of 374 nodes and 767 edges. A total of 8 real hub genes (HLA-DRA, HLA-DRB1, LCK, VAV1, HLA-DPA1, HLA-DPB1, C3AR1 and CD3D) which displayed an excellent diagnostic value for RA were identified.Conclusion: these findings may provide novel and reliable biomarkers for RA, which have some interesting implications for early diagnosis, prognosis and targeted therapy.

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The Function and Molecular Mechanism of MicroRNA-429 in Rheumatoid Arthritis

Journal of Biomaterials and Tissue Engineering ◽

10.1166/jbt.2020.2352 ◽

2020 ◽

Vol 10 (7) ◽

pp. 945-950

Author(s):

Pengdong Zhang ◽

Bailong Yu ◽

Bin Lei ◽

Changlin Li ◽

Xiaoqiang Yuan

Keyword(s):

Rheumatoid Arthritis ◽

Gene Expression ◽

Molecular Mechanism ◽

Synovial Tissue ◽

Luciferase Assay ◽

Rt Pcr ◽

Tnf Α ◽

Tlr4 Gene ◽

Synovial Tissues ◽

D Model

Objective: To explain the function and molecular mechanism of miRNA-429 in Rheumatoid Arthritis development. Methods: Collecting synovial tissue of 36 RA patients and 36 traumatic amputation patients, the miRNA-429 and TLR4 gene expressions were measured by RT-PCR. The SD rats were divided into NC, 14 d Model and 28 d Model groups. The IL-1β and TNF-α concentrations of serum were measured by Elisa assay in difference rats groups; The synovial tissue pathology was evaluated by HE staining; the miRNA-429 gene expression of rats groups were measured by RT-PCR, the TLR4 and NF-κB proteins expressions of rats groups were evaluated by IHC staining; the correlation between miRNA-429 and TLR4 were evaluated by Double luciferase assay. Results: Compared with normal synovial tissues, the miRNA-429 and TLR4 gene expression of synovial tissues were significantly difference in RA patients. In rats vivo study, we found that IL-1 and TNF-α concentrations were significantly up-regulation with time increasing (P < 0 05, respectively); inflammation degree was serious by HE staining and miRNA-429 gene expression was significantly reduced (P < 0.05, respectively); TLR4 and NF-κB proteins expressions were significantly up-regulation (P < 0.05, respectively) with time increasing; TLR4 was the target gene of miRNA-429 by Double luciferase assay. Conclusion: miRNA-429 over-expression stimulated RA development.

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Synovial cellular and molecular signatures stratify clinical response to csDMARD therapy and predict radiographic progression in early rheumatoid arthritis patients

Annals of the Rheumatic Diseases ◽

10.1136/annrheumdis-2018-214539 ◽

2019 ◽

Vol 78 (6) ◽

pp. 761-772 ◽

Cited By ~ 47

Author(s):

Frances Humby ◽

Myles Lewis ◽

Nandhini Ramamoorthi ◽

Jason A Hackney ◽

Michael R Barnes ◽

...

Keyword(s):

Rheumatoid Arthritis ◽

Gene Expression ◽

B Cells ◽

Disease Activity ◽

Treatment Response ◽

Radiographic Progression ◽

Joint Damage ◽

Molecular Signatures ◽

Early Ra ◽

Treatment Naïve

ObjectivesTo unravel the hierarchy of cellular/molecular pathways in the disease tissue of early, treatment-naïve rheumatoid arthritis (RA) patients and determine their relationship with clinical phenotypes and treatment response/outcomes longitudinally.Methods144 consecutive treatment-naïve early RA patients (<12 months symptoms duration) underwent ultrasound-guided synovial biopsy before and 6 months after disease-modifying antirheumatic drug (DMARD) initiation. Synovial biopsies were analysed for cellular (immunohistology) and molecular (NanoString) characteristics and results compared with clinical and imaging outcomes. Differential gene expression analysis and logistic regression were applied to define variables correlating with treatment response and predicting radiographic progression.ResultsCellular and molecular analyses of synovial tissue demonstrated for the first time in early RA the presence of three pathology groups: (1) lympho-myeloid dominated by the presence of B cells in addition to myeloid cells; (2) diffuse-myeloid with myeloid lineage predominance but poor in B cells nd (3) pauci-immune characterised by scanty immune cells and prevalent stromal cells. Longitudinal correlation of molecular signatures demonstrated that elevation of myeloid- and lymphoid-associated gene expression strongly correlated with disease activity, acute phase reactants and DMARD response at 6 months. Furthermore, elevation of synovial lymphoid-associated genes correlated with autoantibody positivity and elevation of osteoclast-targeting genes predicting radiographic joint damage progression at 12 months. Patients with predominant pauci-immune pathology showed less severe disease activity and radiographic progression.ConclusionsWe demonstrate at disease presentation, prior to pathology modulation by therapy, the presence of specific cellular/molecular synovial signatures that delineate disease severity/progression and therapeutic response and may pave the way to more precise definition of RA taxonomy, therapeutic targeting and improved outcomes.

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Linc02381 Exacerbates Rheumatoid Arthritis Through Adsorbing miR-590-5p and Activating the Mitogen-Activated Protein Kinase Signaling Pathway in Rheumatoid arthritis-fibroblast-like synoviocytes

Cell Transplantation ◽

10.1177/0963689720938023 ◽

2020 ◽

Vol 29 ◽

pp. 096368972093802

Author(s):

Jing Wang ◽

Qing Zhao

Keyword(s):

Rheumatoid Arthritis ◽

Cell Proliferation ◽

Protein Kinase ◽

Signaling Pathway ◽

Mapk Signaling ◽

Mitogen Activated Protein Kinase ◽

Mitogen Activated Protein ◽

Synovial Tissues ◽

Proliferation And Invasion ◽

Fibroblast Like Synoviocytes

Rheumatoid arthritis (RA) is a chronic systemic autoimmune disease. New evidence suggested that linc02381 suppressed colorectal cancer progression by regulating PI3 K signaling pathway, but the role of linc02381 in other diseases, such as RA, remains unclear. This study aimed to reveal the mechanism of linc02381 in RA progression. In vivo and in vitro, we found that linc02381 was upregulated in RA synovial tissues or RA fibroblast-like synoviocytes (RA-FLSs, P < 0.01), which were detected by quantitative real-time polymerase chain reaction. Cell Counting Kit-8, EDU, and Transwell assays revealed that linc02381 overexpression enhanced cell proliferation and invasion, and linc02381 knockdown inhibited cell proliferation and invasion in FLSs. Moreover, the results of bioinformatics analysis, luciferase reporter gene assay, and pull-down assay verified that linc02381 could directly bind with miR-590-5p. MiR-590-5p was downregulated in RA-FLSs, and overexpression of linc02381 suppressed expression of miR-590-5p that post-transcriptionally suppressed the expression of mitogen-activated protein kinase kinase 3 (MAP2K3), and overexpression of miR-590-5p reversed the effect of linc02381 overexpression on MAP2K3 expression. MiR-590-5p inhibitor reversed the inhibition effect of linc02381 knockdown on proliferation and invasion of FLSs, which enhanced expression of MAP2K3, and activation of p38 and AP-1 in the MAPK signaling pathway. In summary, linc02381 was upregulated in RA synovial tissues and RA-FLSs, and it exacerbated RA by adsorbing miR-590-5p to activate the MAPK signaling pathway.

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