Exploration and validation of therapeutic molecules for rheumatoid arthritis based on ferroptosis-related genes.

AIMS: This study aimed to identify hub ferroptosis-related genes (FRGs) and investigate potential therapy for RA based on FRGs. MAIN METHODS: The differentially expressed FRGs in synovial tissue of RA patients were obtained from the dataset GSE12021 (GPL96). Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses were conducted to investigate the potential signaling pathways associated with FRGs. Hub genes were identified through topological analysis. The expression levels of these hub genes as well as their diagnostic accuracies were further evaluated. Connectivity Map (CMap) database was utilized to analyze the top 10 FRGs-guided potential drugs for RA. In vitro and in vivo experiments were carried out for further validation. KEY FINDINGS: 2 hub genes among 58 FRGs were identified (EGR1 and CDKN1A), and both were down regulated in RA synovial tissue. GPx4 expression was also decreased in the RA synovial tissue. The natural compound withaferin-a exhibited the highest negative CMap score. In-vitro and in-vivo experiments demonstrated anti-arthritic effects of withaferin-a. SIGNIFICANCE: Ferroptosis participates in pathogenesis of RA, ferroptosis-related genes EGR1 and CDKN1A can be used as diagnostic and therapeutic targets for RA. Withaferin-a can be used as potential anti-arthritic treatment.

M2 Macrophage-Derived Extracellular Vesicles Encapsulated in Hyaluronic Acid Alleviate Osteoarthritis by Modulating Macrophage Polarization.

An imbalance between M1 and M2 macrophage polarization is critical in osteoarthritis (OA) development. We investigated the effect of M2 macrophage-derived extracellular vesicles (M2-EVs) to reprogramme macrophages from the M1 to M2 phenotype for OA treatment. M1 macrophages and mouse OA models were treated with M2-EVs. Proteomic analysis was performed to evaluate macrophage polarization in vitro. The OA models were as follows: destabilization of the medial meniscus (DMM) surgery-induced OA and collagenase-induced OA (CIOA). Hyaluronic acid (HA) was used to deliver M2-EVs. M2-EVs decreased macrophage accumulation, repolarized macrophages from the M1 to M2 phenotype, mitigated synovitis, reduced cartilage degradation, alleviated subchondral bone damage, and improved gait abnormalities in the CIOA and DMM models. Moreover, HA increased the retention time of M2-EVs and enhanced the efficiency of M2-EVs in OA treatment. Furthermore, proteomic analysis demonstrated that M2-EVs exhibited a macrophage reprogramming ability similar to IL-4, and the pathways might be the NOD-like receptor (NLR), TNF, NF-κB, and Toll-like receptor (TLR) signaling pathways. M2-EVs reprogrammed macrophages from the M1 to M2 phenotype, which resulted in beneficial effects on cartilage and attenuation of OA severity. In summary, our study indicated that M2-EV-guided reprogramming of macrophages is a promising treatment strategy for OA.

Novel pyroptosis-related lncRNAs and ceRNAs predict osteosarcoma prognosis and indicate immune microenvironment signatures.

Objective: To study pyroptosis-related biomarkers that are associated with the prognosis and immune microenvironment characteristics of osteosarcoma (OS). The goal is to establish a foundation for the prognosis and treatment of OS. Methods: We retrieved transcriptome and clinical data from The Cancer Genome Atlas (TCGA) database for 88 OS patients. Using this data, we constructed a prognostic model to identify pyroptosis-related genes (PRGs) associated with OS prognosis. To further explore the biological function of these PRGs, we performed enrichment analysis. To identify pyroptosis-related long non-coding RNAs (PRLncs) associated with the prognosis of OS, we performed co-expression analysis. Subsequently, a risk prognostic model was constructed using these PRLncs to generate a risk score, termed as PRLncs-score, thereby obtaining PRLncs associated with the prognosis of OS. The accuracy of the prognostic model was verified through survival analysis, risk curve, independent prognostic analysis, receiver operating characteristic (ROC) curve, difference analysis between high- and low-risk groups, and clinical correlation analysis. And to determine whether PRLncs-score is independent prognostic factor for OS. In addition, we further conducted external and internal validation for the risk prognosis model. Further analyses of immune cell infiltration and tumor microenvironment were performed. A pyroptosis-related competitive endogenous RNA (PRceRNA) network was constructed to obtain PRceRNAs associated with the prognosis of OS and performed gene set enrichment analysis (GSEA) on PRceRNA genes. Results: We obtained five PRGs (CHMP4C, BAK1, GSDMA, CASP1, and CASP6) that predicted OS prognosis and seven PRLncs (AC090559.1, AP003119.2, CARD8-AS1, AL390728.4, SATB2-AS1, AL133215.2, and AC009495.3) and one PRceRNA (CARD8-AS1-hsa-miR-21-5p-IL1B) that predicted OS prognosis and indicated characteristics of the OS immune microenvironment. The PRLncs-score, in combination with other clinical features, was established as an independent prognostic factor for OS patients. Subsequent scrutiny of the tumor microenvironment and immune infiltration indicated that patients with low-PRLncs-scores were associated with reduced metastatic risk, improved survival rates, heightened levels of immune cells and stroma, and increased immune activity compared to those with high-PRLncs-scores. Conclusion: The study's findings offer insight into the prognosis of OS and its immune microenvironment, and hold promise for improving early diagnosis and immunotherapy.

The m6A/m1A/m5C-Related Methylation Modification Patterns and Immune Landscapes in Rheumatoid Arthritis and Osteoarthritis Revealed by Microarray and Single-Cell Transcriptome.

Purpose: The goal of this study was to explore the expression characteristics of RNA modification-related genes, reveal immune landscapes and identify novel potential diagnostic biomarkers in osteoarthritis (OA) and rheumatoid arthritis (RA) patients. Patients and Methods: RNA microarray and single-cell sequencing (scRNA-seq) data were downloaded from gene expression omnibus (GEO) database. Differentially expressed RNA modification-related genes were identified and then functionally annotated. Univariate logistic regression and lasso regression analysis were used to identify primary disease genes for OA and RA. Validation was done using scRNA-seq analysis and immunohistochemistry (IHC) in human knee synovial tissues and a murine destabilization of the medial meniscus (DMM) model. Through WGCNA analysis, genes associated with cell pyroptosis or autophagy in OA and RA were identified, which were then combined with differentially expressed RNA modification-related genes to construct a PPI interaction network. Furthermore, hub genes were selected for ceRNA interaction network analysis, correlation analysis with OA and RA molecular subtypes, as well as correlation analysis with 22 immune cells. Results: Six RNA modification-related genes (ADAMDEC1, IGHM, OGN, TNFRSF11B, SCARA3 and PTN) were identified as potential OA and RA pathogenesis biomarkers. Their expression was validated in human knee synovial tissues and a murine DMM model. Functional enrichment of differentially expressed RNA modification-related genes between RA and OA was analyzed using GO, KEGG, GSEA, and GSVA. Based on WGCNA and PPI analysis, the six hub genes related to pyroptosis and RNA modification (CXCL10, CXCL9, CCR7, CCL5, CXCL1, and CCR2) were identified as central nodes for ceRNA interaction, correlation with OA and RA molecular subtypes, and association with 22 immune cells. Conclusion: Our research revealed the significance of RNA modification-related genes in the development of OA and RA pathogenesis, thereby providing a novel research direction for understanding the mechanisms, diagnosis, and treatment of OA and RA.

Ferroptosis-related lncRNAs guiding osteosarcoma prognosis and immune microenvironment.

OBJECTIVE: To investigate the ferroptosis-related long non-coding RNAs (FRLncs) implicated in influencing the prognostic and immune microenvironment in osteosarcoma (OS), and to establish a foundational framework for informing clinical decision making pertaining to OS management. METHODS: Transcriptome data and clinical data pertaining to 86 cases of OS, the GSE19276, GSE16088 and GSE33382 datasets, and a list of ferroptosis-related genes (FRGs) were used to establish a risk prognostic model through comprehensive analysis. The identification of OS-related differentially expressed FRGs was achieved through an integrated analysis encompassing the aforementioned 86 OS transcriptome data and the GSE19276, GSE16088 and GSE33382 datasets. Concurrently, OS-related FRLncs were ascertained via co-expression analysis. To establish a risk prognostic model for OS, Univariate Cox regression analysis and Lasso Cox regression analysis were employed. Subsequently, a comprehensive evaluation was conducted, comprising risk curve analysis, survival analysis, receiver operating characteristic curve analysis and independent prognosis analysis. Model validation with distinct clinical subgroups was performed to assess the applicability of the risk prognostic model to diverse patient categories. Moreover, single sample gene set enrichment analysis (ssGSEA) was conducted to investigate variations in immune cell populations and immune functions within the context of the risk prognostic model. Furthermore, an analysis of immune checkpoint differentials yielded insights into immune checkpoint-related genes linked to OS prognosis. Finally, the risk prognosis model was verified by dividing the samples into train group and test group. RESULTS: We identified a set of seven FRLncs that exhibit potential as prognostic markers and influence factors of the immune microenvironment in the context of OS. This ensemble encompasses three high-risk FRLncs, denoted as APTR, AC105914.2 and AL139246.5, alongside four low-risk FRLncs, designated as DSCR8, LOH12CR2, AC027307.2 and AC025048.2. Furthermore, our analysis revealed notable down-regulation in the high-risk group across four distinct immune cell types, namely neutrophils, natural killer cells, plasmacytoid dendritic cells and tumor-infiltrating lymphocytes. This down-regulation was also reflected in four key immune functions, antigen-presenting cell (APC)-co-stimulation, checkpoint, cytolytic activity and T cell co-inhibition. Additionally, we identified seven immune checkpoint-associated genes with significant implications for OS prognosis, including CD200R1, HAVCR2, LGALS9, CD27, LAIR1, LAG3 and TNFSF4. CONCLUSION: The findings of this study have identified FRLncs capable of influencing OS prognosis and immune microenvironment, as well as immune checkpoint-related genes that are linked to OS prognosis. These discoveries establish a substantive foundation for further investigations into OS survival and offer valuable insights for informing clinical decision making in this context.

Identification of the potential regulatory interactions in rheumatoid arthritis through a comprehensive analysis of lncRNA-related ceRNA networks.

OBJECTIVE: This study aimed at constructing a network of competing endogenous RNA (ceRNA) in the synovial tissues of rheumatoid arthritis (RA). It seeks to discern potential biomarkers and explore the long non-coding RNA (lncRNA)-microRNA (miRNA)-messenger RNA (mRNA) axes that are intricately linked to the pathophysiological mechanisms underpinning RA, and providing a scientific basis for the pathogenesis and treatment of RA. METHODS: Microarray data pertaining to RA synovial tissue, GSE103578, GSE128813, and GSE83147, were acquired from the Gene Expression Omnibus (GEO) database ( http://www.ncbi.nlm.nih.gov/geo ). Conducted to discern both differentially expressed lncRNAs (DELncRNAs) and differentially expressed genes (DEGs). A ceRNA network was obtained through key lncRNAs, key miRNAs, and key genes. Further investigations involved co-expression analyses to uncover the lncRNA-miRNA-mRNA axes contributing to the pathogenesis of RA. To delineate the immune-relevant facets of this axis, we conducted an assessment of key genes, emphasizing those with the most substantial immunological correlations, employing the GeneCards database. Finally, gene set enrichment analysis (GSEA) was executed on the identified key lncRNAs to elucidate their functional implications in RA. RESULTS: The 2 key lncRNAs, 7 key miRNAs and 6 key genes related to the pathogenesis of RA were obtained, as well as 2 key lncRNA-miRNA-mRNA axes (KRTAP5-AS1-hsa-miR-30b-5p-PNN, XIST-hsa-miR-511-3p/hsa-miR-1277-5p-F2RL1). GSEA of two key lncRNAs obtained biological processes and signaling pathways related to RA synovial lesions. CONCLUSION: The findings of this investigation hold promise in furnishing a foundational framework and guiding future research endeavors aimed at comprehending the etiology and therapeutic interventions for RA.

Lycium ruthenicum Murr. anthocyanins inhibit hyperproliferation of synovial fibroblasts from rheumatoid patients and the mechanism study powered by network pharmacology.

BACKGROUND: Rheumatoid arthritis (RA), is a typical autoimmune disease affecting nearly 1% of the world's population. The dysfunctional hyperproliferation of synovial fibroblast (SF) in articular cartilage of RA patients is considered as the essential etiology. Traditional chemotherapeutic agents for RA treatment are imperfect for their high cost and unpredictable side-effects. L. ruthenicum anthocyanins (LRAC) is a natural product that of potential for therapeutic application against RA. METHODS: LRAC was characterized by UPLC-MS/MS. Bioinformatics analyses based on network pharmacology were applied to predict the potential targets of LRAC, and to select DEGs (differentially expressed genes) caused by RA pathogenesis from GSE77298. Interactions between LRAC and the predicted targets were evaluated by molecular docking. Effects of LRAC on SFs from RA patients were examined by in vitro assays, which were analyzed by flow cytometry and western blotting (WB). RESULTS: LRAC was able to inhibit the abnormal proliferation and aggressive invasion of SFs from RA patients. LRAC was mainly constituted by petunidin (82.7%), with small amount of delphinidin (12.9%) and malvidin (4.4%) in terms of anthocyanidin. Bioinformatics analyses showed that in 3738 RA-related DEGs, 58 of them were collectively targeted by delphinidin, malvidin and delphinidin. AR, CDK2, CHEK1, HIF1A, CXCR4, MMP2 and MMP9, the seven hub genes constructed a central network mediating the signal transduction. Molecular docking confirmed the high affinities between the LRAC ligands and the protein receptors encoded by the hub genes. The in vitro assays validated that LRAC repressed the growth of RASF by cell cycle arresting and cell invasion paralyzing (c-Myc/p21/CDK2), initiating cell apoptosis (HIF-1α/CXCR4/Bax/Bcl-2), and inducing pyroptosis via ROS-dependent pathway (NOX4/ROS/NLRP3/IL-1ß/Caspase-1). CONCLUSION: LRAC can selectively inhibit the proliferation of RASFs, without side-effecting immunosuppression that usually occurred for RA treatment using MTX (methotrexate). These findings demonstrate the potential application of LRAC as a phytomedicine for RA treatment, and provide a valid approach for exploring natural remedies against autoimmune diseases.

No evidence of a genetic causal relationship between ankylosing spondylitis and iron homeostasis: A two-sample Mendelian randomization study.

Background: Ankylosing spondylitis (AS) is an immune-mediated chronic inflammatory disease that leads to bone hyperplasia and spinal ankylosis. Iron homeostasis plays a very important role in the inflammatory response and is closely related to the pathogenesis of AS. This study aimed to use large-scale genome-wide association study (GWAS) summary data to study the genetic causal relationship between AS and iron homeostasis using Mendelian randomization (MR). Methods: Genome-wide association study summary data of AS and iron homeostasis-related indicators were obtained from the FinnGen consortium and the DeCODE genetics database, respectively. We used four iron homeostasis-related indicators: ferritin, serum iron, total iron binding capacity (TIBC), and transferrin saturation (TSAT) for two-sample MR analyses to test for genetic causal association with AS using the "TwoSampleMR" package of the R software (version 4.1.2). The random-effects inverse variance weighted (IVW) method was the main analysis method used for MR. We examined the MR analysis results for heterogeneity, horizontal pleiotropy, and possible outliers. In addition, we confirmed the robustness of the MR analysis by testing whether the results were affected by a single SNP and whether they followed a normal distribution. Results: The random-effects IVW results showed that ferritin [p = 0.225, OR 95% confidence interval (CI) = 0.836 (0.627-1.116)], serum iron [p = 0.714, OR 95% CI = 0.948 (0.714-1.260)], TIBC [p = 0.380, OR 95% CI = 0.917 (0.755-1.113)], and TSAT [p = 0.674, OR 95% CI = 0.942 (0.713-1.244)] have no genetic causal relationship with AS. We detected no heterogeneity，horizontal pleiotropy and possible outliers in our MR analysis (p > 0.05). In addition, our MR analysis results were not affected by a single SNP, and were normally distributed. Conclusion: Our study did not detect a genetic causal relationship between AS and iron homeostasis. Nonetheless, this does not rule out a relationship between the two at other mechanistic levels.

No Evidence of a Genetic Causal Relationship between Ankylosing Spondylitis and Gut Microbiota: A Two-Sample Mendelian Randomization Study.

Objective: Ankylosing spondylitis (AS) is associated with a variety of gut microbiotas. We aim to analyze the causal relationship between the two at the genetic level. Methods: Mendelian randomization (MR) is a type of instrumental variables (IVs) analysis; MR follows the Mendelian genetic rule of "parental alleles are randomly assigned to offspring" and takes genetic variation as IVs to infer the causal association between exposure factors and study outcome in observational studies. Genome-wide association study (GWAS) summary data of AS were from the FinnGen consortium, and the gut microbiota (Bacteroides, Streptococcus, Proteobacteria, Lachnospiraceae) were from the MiBioGen consortium. The TwoSampleMR and MRPRESSO packages of the R were used to perform a two-sample MR study. Random-effects inverse variance weighted (IVW) was the main analysis method, and MR Egger, weighted median, simple mode, and weighted mode were used as supplementary methods. We examined heterogeneity and horizontal pleiotropy, and examined whether the analysis results were influenced by a single SNP. We applied radial variants of the IVW and MR-Egger model for the improved visualization of the causal estimate. We further examined the causal relationship between AS and gut microbiota, and the robustness of the analysis results. Finally, we performed maximum likelihood, penalized weighted median, and IVW (fixed effects) to further identify the potential causal association. Results: The random-effects IVW results showed that Bacteroides (p = 0.965, OR 95% confidence interval [CI] = 0.990 [0.621-1.579]), Streptococcus (p = 0.591, OR 95% CI = 1.120 [0.741-1.692]), Proteobacteria (p = 0.522, OR 95% CI = 1.160 [0.737-1.826]), and Lachnospiraceae (p = 0.717, OR 95% CI = 1.073 [0.732-1.574]) have no genetic causal relationship with AS. There was no heterogeneity, horizontal pleiotropy or outliers, and results were normally distributed. The MR analysis results were not driven by a single SNP. Conclusions: This study showed that Bacteroides, Streptococcus, Proteobacteria and Lachnospiraceae, four common gut microbiotas associated with AS, had no causal relationship with AS at the genetic level. This study makes a positive contribution to the genetics of AS, but the insufficient number of gut microbiota included is a limitation.

Total hip arthroplasty for posttraumatic osteoarthritis secondary to acetabular fracture: An evidence based on 1,284 patients from 1970 to 2018.

Background: Posttraumatic osteoarthritis (PTOA) can be a crippling sequela of acetabular fracture (AF), and total hip arthroplasty (THA) is often necessary to alleviate the clinical progression of symptoms. The purpose of this study was to summarize the existing clinical evidence concerning the surgical management of AF with THA through meta-analyses. Methods: Databases were searched for articles published between 1995 and January 2022 that contained the keywords "acetabular," "fracture," "arthroplasty," and "osteoarthritis." Our study was registered in PROSPERO under number CRD42022314997. Results: We screened 3,125 studies and included data from 31 studies with 1,284 patients. The median patient age at the time of THA was 52 years and ranged from 19 to 94 years. The pooled overall survival rate was 88% [86%-90%, 95% confidence interval (CI)] and could reach 83% at ≥15-year follow-up. For the Harris Hip Score, we pooled 22 studies with an overall mean difference of 43.25 (40.40-46.10, 95% CI; P < 0.001), indicating a large clinical effect. The pooled complications (incidence rates) across studies were: heterotopic ossification (22.53%), implant dislocation (4.66%), implant infection (3.44%), and iatrogenic nerve injury (1.07%). Conclusion: THA in patients with PTOA following AF leads to significant improvement in symptoms and function at ≥15-year follow-up. Survival rates of implants free from re-operation or revision after THA decreased with follow-up time and could still reach 83% at ≥15-year follow-up. THA might be an effective therapeutic method for patients with PTOA due to AF.

A novel signature to guide osteosarcoma prognosis and immune microenvironment: Cuproptosis-related lncRNA.

Objective: Osteosarcoma (OS) is a common bone malignancy with poor prognosis. We aimed to investigate the relationship between cuproptosis-related lncRNAs (CRLncs) and the survival outcomes of patients with OS. Methods: Transcriptome and clinical data of 86 patients with OS were downloaded from The Cancer Genome Atlas (TCGA). The GSE16088 dataset was downloaded from the Gene Expression Omnibus (GEO) database. The 10 cuproptosis-related genes (CRGs) were obtained from a recently published article on cuproptosis in Science. Combined analysis of OS transcriptome data and the GSE16088 dataset identified differentially expressed CRGs related to OS. Next, pathway enrichment analysis was performed. Co-expression analysis obtained CRLncs related to OS. Univariate COX regression analysis and least absolute shrinkage and selection operator (LASSO) regression analysis were used to construct the risk prognostic model of CRLncs. The samples were divided evenly into training and test groups to verify the accuracy of the model. Risk curve, survival, receiver operating characteristic (ROC) curve, and independent prognostic analyses were performed. Next, principal component analysis (PCA) and t-distributed stochastic neighbor embedding (t-SNE) analysis were performed. Single-sample gene set enrichment analysis (ssGSEA) was used to explore the correlation between the risk prognostic models and OS immune microenvironment. Drug sensitivity analysis identified drugs with potential efficacy in OS. Real-time quantitative PCR, Western blotting, and immunohistochemistry analyses verified the expression of CRGs in OS. Real-time quantitative PCR was used to verify the expression of CRLncs in OS. Results: Six CRLncs that can guide OS prognosis and immune microenvironment were obtained, including three high-risk CRLncs (AL645608.6, AL591767.1, and UNC5B-AS1) and three low-risk CRLncs (CARD8-AS1, AC098487.1, and AC005041.3). Immune cells such as B cells, macrophages, T-helper type 2 (Th2) cells, regulatory T cells (Treg), and immune functions such as APC co-inhibition, checkpoint, and T-cell co-inhibition were significantly downregulated in high-risk groups. In addition, we obtained four drugs with potential efficacy for OS: AUY922, bortezomib, lenalidomide, and Z.LLNle.CHO. The expression of LIPT1, DLAT, and FDX1 at both mRNA and protein levels was significantly elevated in OS cell lines compared with normal osteoblast hFOB1.19. The mRNA expression level of AL591767.1 was decreased in OS, and that of AL645608.6, CARD8-AS1, AC005041.3, AC098487.1, and UNC5B-AS1 was upregulated in OS. Conclusion: CRLncs that can guide OS prognosis and the immune microenvironment and drugs that may have a potential curative effect on OS obtained in this study provide a theoretical basis for OS survival research and clinical decision-making.

Metformin Ameliorates Senescence of Adipose-Derived Mesenchymal Stem Cells and Attenuates Osteoarthritis Progression via the AMPK-Dependent Autophagy Pathway.

Osteoarthritis (OA) is one of the most serious age-related diseases worldwide that drastically affects the quality of life of patients. Despite advancements in the treatment of arthritis, especially with adipose-derived mesenchymal stem cells (ADSCs), senescence-induced alterations in ADSCs negatively affect the treatment outcomes. This study was aimed at mechanistically exploring whether metformin could ameliorate the senescence of ADSCs and at exploring the effect of metformin-preconditioned ADSCs in an experimental OA mouse model. In this study, an H2O2-induced mouse ADSC senescent model was established. Cell proliferation, senescence, and autophagy were investigated in vitro. Moreover, the effects of intra-articular injection of metformin-preconditioned ADSCs were investigated in vivo. Metformin could promote autophagy and activate the AMPK/mTOR pathway in ADSCs. The metformin-enhanced autophagy could improve the survival and reduce the senescence of ADSCs. The protective effects of metformin against senescence were partially blocked by 3-methyladenine and compound C. Injection of metformin-preconditioned ADSCs slowed OA progression and reduced OA pain in mice. The results suggest that metformin activates the AMPK/mTOR-dependent autophagy pathway in ADSCs against H2O2-induced senescence, while metformin-preconditioned ADSCs can potentially inhibit OA progression.

Bioinformatics Analysis Identified the Hub Genes, mRNA-miRNA-lncRNA Axis, and Signaling Pathways Involved in Rheumatoid Arthritis Pathogenesis.

Objective: Rheumatoid arthritis (RA) is a nonspecific, chronic, systemic autoimmune disease characterized by symmetric polyarticular synovitis. Bioinformatics analysis of potential biomarkers, mRNA-miRNA-lncRNA axes, and signaling pathways in the pathogenesis of RA provides potential targets and theoretical basis for further research on RA. Methods: The GSE1919 and GSE77298 datasets were downloaded from the Gene Expression Omnibus database (http://www.ncbi.nlm.nih.gov/geo). Perl was used to perform data merging, and R was used to perform batch correction. The "limma" package of R was used to screen differentially expressed genes, and the "clusterProfiler" package was used to perform enrichment analysis of the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes. Search Tool for the Retrieval of Interacting Genes/Proteins was used to construct the protein-protein interaction network, Cytoscape was used for module analysis, and R was used to screen for hub genes. GraphPad Prism was used to plot the receiver operating characteristic curve of the hub genes. Gene set enrichment analysis and competitive endogenous RNA network analysis were performed on hub genes with the greatest diagnostic values. The hub gene with the greatest diagnostic value was verified using immunohistochemical staining. Results: We obtained nine hub genes (ITGB2, VAMP8, HLA-A, PTAFR, SYK, FCER1G, HLA-DPB1, LCP2, and ACTR2) and four mRNA-miRNA-lncRNA axes (ITGB2-hsa-miR-486-3p-SNHG3, ITGB2-hsa-miR-338-5p-XIST, ITGB2-hsa-miR-5581-3p-XIST, and ITGB2-hsa-miR-1226-5p-XIST) related to the pathogenesis of RA. The nine hub genes were highly expressed, and ITGB2 had the highest diagnostic value for RA. We also identified signaling pathways related to the pathogenesis of RA: Fc epsilon Rl and chemokine signaling pathways. The immunohistochemical results showed that ITGB2 expression was significantly upregulated in RA. Conclusion: The hub genes, mRNA-miRNA-lncRNA axes, and signaling pathways related to RA pathogenesis identified in this study provide a new research direction for the mechanism, diagnosis, and treatment of RA.

Peroxiredoxin 4 regulates tumor-cell-like characteristics of fibroblast-like synoviocytes in rheumatoid arthritis through PI3k/Akt signaling pathway.

Peroxiredoxin-4 (PRDX4), a member of PRDX family, which played an important role in scavenging reactive oxygen species (ROS). The up-regulation of PRDX4 in synovial tissue and synovial fluid from rheumatoid arthritis (RA) patients has been reported. However, the biological functions of PRDX4 in fibroblast-like synoviocytes (RA-FLS) remains unclear. In this research, we reveal that expression of PRDX4 was notably increased in RA synovial tissue, especially in hyperplastic synovial tissue. PRDX4 silencing significantly inhibited the tumor cell-like behaviors and mRNA expression of matrix metalloproteinases (MMPs) in RA-FLS. Furthermore, overexpression of PRDX4 markedly activated PI3K/Akt signaling pathway, which can be reverted by Akt inhibitor MK-2206. These observations identified elevated PRDX4 may regulates the tumor cell-like biological characteristic of RA-FLS via Pi3k/Akt pathway. Targeting PRDX4 and its downstream signaling pathway might provide a potential diagnostic markers and therapeutic target for RA.

A Pan-Cancer Analysis of the Role of Selenoprotein P mRNA in Tumorigenesis.

BACKGROUND: Selenium (Se) exhibits its anti-carcinogenic properties by regulating the redox system. However, the relationship between selenoprotein P (SeP), mRNA (SELENOP mRNA) and tumorigenesis remains unclear. Plasma SeP transports Se to various target tissues and has antioxidant characteristics. The present study aimed to explore the multifaceted pan-cancer properties of SELENOP in terms of its tissue-specific expression, prognostic value, immune function, and signaling pathway enrichment. PATIENTS AND METHODS: The expression profile of SELENOP was determined in 33 tumor types and survival, pathway enrichment, and correlation analyses were conducted based on TCGA database. The relationship between SELENOP expression and immune infiltration and macrophage subtype gene markers was investigated using the TIMER and GEPIA. RESULTS: SELENOP gene expression was decreased in many cancer tissues, but was upregulated in brain lower grade glioma (LGG). Furthermore, SELENOP expression was associated with a better prognosis in most cancers, but a poorer prognosis in LGG and uterine corpus endometrioid carcinoma (UCEC). Our results showed that SELENOP was correlated with infiltration level of six immune cell types, where SELENOP also showed a strong correlation with macrophages in some cancer types. However, we failed to determine macrophage polarization in 33 tumor types. SELENOP negatively regulated vascular endothelial cell proliferation in LGG and UCEC and epidermal cell differentiation in six tumor types. In contrast, upregulation was related to immune function, including T cell activation, B cell-mediated immunity, adaptive immune response and immune response regulation cell surface receptor signaling pathways in another six tumor types. CONCLUSION: These findings highlighted the tissue-specific expression, prognostic value and immune characteristics of SELENOP in pan-cancer, and provided insights for illustrating the role of SELENOP in tumorigenesis.

Derlin-1, as a Potential Early Predictive Biomarker for Nonresponse to Infliximab Treatment in Rheumatoid Arthritis, Is Related to Autophagy.

Background: The goal of this study was to identify potential predictive biomarkers for the therapeutic effect of infliximab (IFX) in Rheumatoid arthritis (RA) and explore the potential molecular mechanism of nonresponse to IFX treatment to achieve individualized treatment of RA. Methods: Differential gene expression between IFX responders and nonresponders in the GSE58795 and GSE78068 datasets was identified. Coexpression analysis was used to identify the modules associated with nonresponse to IFX therapy for RA, and enrichment analysis was conducted on module genes. Least absolute shrink and selection operator (LASSO) regression was used to develop a gene signature for predicting the therapeutic effect of IFX in RA, and the area under the receiver operating characteristic curve (AUC) was used to evaluate the predictive value of the signature. Correlation analysis and single-sample gene set enrichment analysis (ssGSEA) were used to explore the potential role of the hub genes. Experimental validation was conducted in synovial tissue and RA fibroblast-like synoviocytes (RA-FLSs). Results: A total of 46 common genes were obtained among the two datasets. The yellow-green module was identified as the key module associated with nonresponse to IFX therapy for RA. We identified a 25-gene signature in GSE78068, and the AUC for the signature was 0.831 in the internal validation set and 0.924 in the GSE58795 dataset(external validation set). Derlin-1 (DERL1) was identified as the hub gene and demonstrated to be involved in the immune response and autophagy regulation. DERL1 expression was increased in RA synovial tissue compared with OA synovial tissue, and DERL1-siRNA partially inhibited autophagosome formation in RA-FLSs. Conclusion: The 25-gene signature may have potential predictive value for the therapeutic effect of IFX in RA at the beginning of IFX treatment, and autophagy may be involved in nonresponse to IFX treatment. In particular, DERL1 may be associated with the regulation of autophagy.

Puerarin for OVX-Induced Postmenopausal Osteoporosis in Murine Model: Systematic Review and Meta-Analysis.

AIMS/BACKGROUND: Ovariectomy (OVX)-induced murine model is widely used for postmenopausal osteoporosis study. Our current study was conducted to systematically review and essentially quantified the bone mass enhancing effect of puerarin on treating OVX-induced postmenopausal osteoporosis in murine model. METHODS: Literatures from PUBMED, EMBASE, and CNKI were involved in our searching strategy by limited the inception date to January 9th, 2019. Moreover, the enhancing effect of puerarin on bone mass compared to OVX-induced rats is evaluated by four independent reviewers. Finally, all the data were extracted, quantified and analyzed via RevMan, besides that in our current review study, we assessed the methodological quality for each involved study. RESULTS: Based on the searching strategy, eight randomization studies were finally included in current meta-analysis and systematic review. According to the data analysis by RevMan, puerarin could improve bone mineral density (BMD); (eight studies, n=203; weighted mean difference, 0.05; 95% CI, 0.03-0.07; P<0.0001) using a random-effects model. There is no significant difference between puerarin and estrogen (seven studies, n=184; weighted mean difference, 0.00; 95% CI, -0.01 to 0.00; P=0.30). CONCLUSION: Puerarin showed upregulating effects on bone mass in OVX-induced postmenopausal osteoporosis in murine model. More studies of the effect of puerarin on bone density in OVX animals are needed.

Natural Occurring Compounds Inhibit Osteoclastogenesis via Targeting NFATc1-related Signaling Pathways.

Osteoclasts are originated from monocytic precursors of the hematopoietic lineage. Regulation of gene expression by transcription factors is one of the major mechanisms for controlling cellular functions. This is particularly important in the process of osteoclast production. As a main regulatory transcriptional factor, nuclear factor of activated T-cells cytoplasmic 1 (NFATc1) plays a significant role in osteoclast differentiation. Although current studies focus on the regulatory effects of treatment in the process of osteoclastogenesis, many of these drugs possess cytotoxicity which is harmful to bone formation. Naturally occurring compounds with less or no side effects are most required in present clinical and fundamental study. In this paper, we summarize several plant-derived compounds in inhibiting osteoclastogenesis.