Proteomics in Rheumatoid Arthritis Research

Metabolomic Profiling of Blood Plasma in Females with Hyperplasia and Endometrial Cancer

Uterine cancer is the most prevalent gynecologic malignancy in women worldwide. Endometrial cancer (EC) has an 81% five-year survival rate, depending on disease stage and time of diagnosis. While endometrial cancer is largely treatable when detected early, no established screening techniques are available in clinical practice. As a result, one of the most significant issues in the medical field is the development of novel ways for early cancer identification, which could boost treatment success rates. Liquid chromatography-high-resolution mass spectrometry (LC-HRMS)-based metabolomics was employed to explore the metabolomic markers and pathways unique to this cancer type and link them to the benign endometrial hyperplasia that may progress to cancer in 5% to 25% of patients. The study involved 59 postmenopausal participants, 20 with EC type 1, 20 with benign hyperplasia, and 19 healthy participants. Metabolite distribution changes were analyzed, and 338 of these features were dysregulated and significant. The first two main components, PC1 and PC2, were responsible for 11.5% and 12.2% of the total metabolites, respectively. Compared with the control group (CO), EC samples had 203 differentially expressed metabolites (180 upregulated and 23 downregulated); in hyperplasia (HP), 157 metabolites were dysregulated (127 upregulated and 30 downregulated) compared to the CO group while 21 metabolites exhibited differential regulation (16 upregulated and 5 downregulated) in EC plasma samples compared to the HP group. Hyperplasia samples exhibited similar metabolic changes to those reported in cancer, except for alterations in triglyceride levels, 7a,12 b-dihydroxy-5b-Cholan-24-oic acid, and Hept-2-enedioyl carnitine levels. The metabolites N-heptanoyl glycine and -(Methylthio)-2,3-isopentyl phosphate and formimino glutamic acid can be specific markers for hyperplasia conditions and dimethyl phosphatidyl ethanolamine and 8-isoprostaglandin E2 can be specific markers for EC conditions. Metabolic activities rely on mitochondrial oxidative phosphorylation for energy generation. The changes in metabolites identified in our study indicate that endometrial cancer cells adopt alternative strategies to increase energy production to meet the energy demand, thereby supporting proliferation.

Identification of Plasma Biomarkers from Rheumatoid Arthritis Patients Using an Optimized Sequential Window Acquisition of All THeoretical Mass Spectra (SWATH) Proteomics Workflow

Rheumatoid arthritis (RA) is a systemic autoimmune and inflammatory disease. Plasma biomarkers are critical for understanding disease mechanisms, treatment effects, and diagnosis. Mass spectrometry-based proteomics is a powerful tool for unbiased biomarker discovery. However, plasma proteomics is significantly hampered by signal interference from high-abundance proteins, low overall protein coverage, and high levels of missing data from data-dependent acquisition (DDA). To achieve quantitative proteomics analysis for plasma samples with a balance of throughput, performance, and cost, we developed a workflow incorporating plate-based high abundance protein depletion and sample preparation, comprehensive peptide spectral library building, and data-independent acquisition (DIA) SWATH mass spectrometry-based methodology. In this study, we analyzed plasma samples from both RA patients and healthy donors. The results showed that the new workflow performance exceeded that of the current state-of-the-art depletion-based plasma proteomic platforms in terms of both data quality and proteome coverage. Proteins from biological processes related to the activation of systemic inflammation, suppression of platelet function, and loss of muscle mass were enriched and differentially expressed in RA. Some plasma proteins, particularly acute-phase reactant proteins, showed great power to distinguish between RA patients and healthy donors. Moreover, protein isoforms in the plasma were also analyzed, providing even deeper proteome coverage. This workflow can serve as a basis for further application in discovering plasma biomarkers of other diseases.

Quantitative proteomic analysis comparing grades ICRS1 and ICRS3 in patients with osteoarthritis

Osteoarthritis (OA), which is caused by joint damage, is the most common form of arthritis, affecting millions of people worldwide. This damage can accumulate over time, which is why aging is one of the main contributors to joint damage associated with OA. The OA-related proteins that have been reported to date have been identified by the comparative analysis of OA patients with normal controls, following surgical or pharmacological treatment. For the first time, the present study analyzed OA-related proteins in patients with OA according to the International Cartilage Repair Society (ICRS) scale. Changes in protein expression can be observed during the OA process. The present study demonstrated differential protein expression patterns in articular cartilage from ICRS1- and ICRS3-graded OA patients. ICRS grade-matched OA knee samples from 12 OA patients, 6 ICRS grade 1 patients and 6 ICRS3 patients were subjected to proteomic analysis using the LTQ-Orbitrap mass spectrometry system. A total of 231 unique proteins were identified as expressed across the ICRS1 and ICRS3 OA patient groups. Relative differences in protein expression associated with the following classifications were observed: Biological adhesion, cell killing, cellular process, development process and molecular function. Although some of these proteins have been previously reported to be associated with rheumatoid arthritis, including cartilage oligomeric matrix protein, collagen types, angiogenin, complement C5 and CD59 glycoprotein, numerous additional proteins were newly identified, which may further help our understanding of disease pathogenesis. These findings suggested that these proteins may be used to develop novel therapeutic targets for OA.

ITGA2 protein is associated with rheumatoid arthritis in Chinese and affects cellular function of T cells

BACKGROUND

We identified proteins significant for rheumatoid arthritis (RA) in peripheral blood mononuclear cells (PBMCs), and to clarify mechanisms mediated by underlying proteins that may involve in the pathogenesis of RA.

METHODS

Proteome-wide protein expressions were profiled by employing label-free quantitative proteomics methodology (Easy-nLC1000 and Q-exactive). The t-test was applied to identify differentially expressed proteins (DEP, p ≤ 0.05) between RA case and control samples. Gene Ontology enrichment analyses and Protein-Protein Interaction analyses were performed to annotate functions of DEPs. The selected DEP was validated in independent samples using Simple Western assay. Plasma protein level of α2 component of integrin (ITGA2) was measured by using ELISA. The DEP, ITGA2, was assessed for its effects on T cell proliferation, cell cycle, apoptosis, and inflammatory cytokine expression.

RESULTS

Sixty-four DEPs (p < 0.05) were identified in PBMCs. The selected ITGA2 (Fold Change, FC = 2.20, p = 1.49E-02) was validated to be up-regulated (FC = 12.33, p = 4.90E-2) with RA, and plasma ITGA2 protein level significantly elevated in RA patients vs. controls. Over-expression of ITGA2 could promote proliferation and inhibit apoptosis of Jurkat T cell, and induce IL-8, IFN-γ and TNF-α expression in Jurkat T cells.

CONCLUSIONS

ITGA2 protein was significantly over-expressed in PBMCs in RA patients, and affects T cell growth and pro-inflammatory cytokine expression in T cells.

Quantitative Proteomic Analysis of Synovial Tissue Reveals That Upregulated OLFM4 Aggravates Inflammation in Rheumatoid Arthritis

Tandem mass tag (TMT)-coupled liquid chromatography coupled with tandem mass spectrometry is a powerful method to investigate synovial tissue protein profiles in patients with rheumatoid arthritis (RA) and osteoarthritis (OA). Protein was isolated from synovial tissue samples of 22 patients and labeled with a TMT kit. Over 500 proteins were identified as the differential expression protein on comparing RA and OA synovial tissue, including 239 upregulated and 271 downregulated proteins. Data are available via ProteomeXchange with identifier PXD027703. Gene ontology and Kyoto Encyclopedia of Genes and Genomes analysis showed that the majority participated in the developmental processes and protein processing in the endoplasmic reticulum. Olfactomedin 4 (OLFM4), a secreted glycoprotein, in joint inflammation of RA was explored. OLFM4 was upregulated in RA synovial tissue samples. In fibroblast-like synoviocytes (FLS), inflammation cytokines, TNF-α, interleukin (IL)-1β, and LPS can upregulate OLFM4. After OLFM4 knockdown under TNF-α stimulation, RA FLS proliferation was inhibited and the expression of CXCL9, CXCL11, and MMP-1 was decreased. Overall, the RA synovial tissue protein expression profile by proteomic analysis shows some unique targets in RA pathophysiology, and OLFM4 in FLS plays an important role in RA joint inflammation. OLFM4 can be a promising therapeutic target in RA synovial tissue.

Precision Medicine for Rheumatoid Arthritis: The Right Drug for the Right Patient-Companion Diagnostics

Despite the growing number of biologic and JAK inhibitor therapeutic agents available to treat various systemic autoimmune illnesses, the lack of a validated companion diagnostic (CDx) to accurately predict drug responsiveness for an individual results in many patients being treated for years with expensive, ineffective, or toxic drugs. This review will focus primarily on rheumatoid arthritis (RA) therapeutics where the need is greatest due to poor patient outcomes if the optimum drug is delayed. We will review current FDA-approved biologic and small molecule drugs and why RA patients switch these medications. We will discuss the sampling of various tissues for potential CDx and review early results from studies investigating drug responsiveness utilizing advanced technologies including; multiplex testing of cytokines and proteins, autoantibody profiling, genomic analysis, proteomics, miRNA analysis, and metabolomics. By using these new technologies for CDx the goal is to improve RA patient outcomes and achieve similar successes like those seen in oncology using precision medicine guided therapeutics.

Machine learning model for identifying important clinical features for predicting remission in patients with rheumatoid arthritis treated with biologics

Background

We developed a model to predict remissions in patients treated with biologic disease-modifying anti-rheumatic drugs (bDMARDs) and to identify important clinical features associated with remission using explainable artificial intelligence (XAI).

Methods

We gathered the follow-up data of 1204 patients treated with bDMARDs (etanercept, adalimumab, golimumab, infliximab, abatacept, and tocilizumab) from the Korean College of Rheumatology Biologics and Targeted Therapy Registry. Remission was predicted at 1-year follow-up using baseline clinical data obtained at the time of enrollment. Machine learning methods (e.g., lasso, ridge, support vector machine, random forest, and XGBoost) were used for the predictions. The Shapley additive explanation (SHAP) value was used for interpretability of the predictions.

Results

The ranges for accuracy and area under the receiver operating characteristic of the newly developed machine learning model for predicting remission were 52.8–72.9% and 0.511–0.694, respectively. The Shapley plot in XAI showed that the impacts of the variables on predicting remission differed for each bDMARD. The most important features were age for adalimumab, rheumatoid factor for etanercept, erythrocyte sedimentation rate for infliximab and golimumab, disease duration for abatacept, and C-reactive protein for tocilizumab, with mean SHAP values of − 0.250, − 0.234, − 0.514, − 0.227, − 0.804, and 0.135, respectively.

Conclusions

Our proposed machine learning model successfully identified clinical features that were predictive of remission in each of the bDMARDs. This approach may be useful for improving treatment outcomes by identifying clinical information related to remissions in patients with rheumatoid arthritis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13075-021-02567-y.

Efficacy, safety and cost-effectiveness of a web-based platform delivering the results of a biomarker-based predictive model of biotherapy response for rheumatoid arthritis patients: a protocol for a randomized multicenter single-blind active controlled clinical trial (PREDIRA)

BACKGROUND

Rheumatoid arthritis (RA) is one of the leading chronic inflammatory rheumatism. First-line therapy with synthetic disease-modifying antirheumatic drugs (sDMARD) is insufficiently effective in 40% of cases and these patients are treated with biotherapies. The increased use of these drugs each year is becoming a public health issue with considerable economic burden. This cost is 20 times higher than that of sDMARD. However, among patients treated with biotherapies, clinical practice shows that about one third will not respond to the selected drug. In nonresponse cases, practitioners currently have no choice but to perform an empirical switching between different treatments, because no tool capable of predicting the response or nonresponse to these molecules is currently available.

METHODS

The study is a prospective, phase III, controlled, multicenter, and randomized, single-blind (patient) clinical trial, including RA patients with a previous failure to anti-TNF therapies. The main objective is the analysis of the clinical and pharmacoeconomic impact after 6 months of treatment. Intervention arm: prescription of biotherapy (rituximab, adalimumab, abatacept) using SinnoTest® software, a prediction software based on proteomic biomarkers. Control arm: prescription of biotherapy based on current practice, without the SinnoTest® software (any biotherapy). In addition, a substudy will be carried out within this trial to generate a biobank and further analyze the proteomic profile of the patients and their modification throughout the study.

DISCUSSION

This clinical trial study will be the first validation study of a biotherapy response prediction software, bringing personalized medicine into the management of RA. We expect that the findings from this study will bring several benefits for the patient and the Health Care System.

TRIAL REGISTRATION

ClincalTrials.gov NCT04147026 . Registered on 31 October, 2019.

Comparative label-free proteomic analysis of equine osteochondrotic chondrocytes

Osteochondrosis is a developmental orthopedic disease affecting growing cartilage in young horses. In this study we compared the proteomes of equine chondrocytes obtained from healthy and osteochondrotic cartilage using a label-free mass spectrometry approach. Quantitative changes of some proteins selected for their involvement in different functional pathways highlighted by the bioinformatics analysis, were validated by western blotting, while biochemical alterations of extracellular matrix were confirmed via Raman spectroscopy analysis. In total 1637 proteins were identified, of which 59 were differentially abundant. Overall, the results highlighted differentially represented proteins involved in metabolic and functional pathways that may be related to the failure of the endochondral ossification process occurring in osteochondrosis. In particular, we identified proteins involved in extracellular matrix degradation and organization, vitamin metabolism, osteoblast differentiation, apoptosis, protein folding and localization, signalling and gene expression modulation and lysosomal activities. These results provide valuable new insights to elucidate the underlying molecular mechanisms associated with the development and progression of osteochondrosis. SIGNIFICANCE: Osteochondrosis is a common articular disorder in young horses mainly due to defects in endochondral ossification. The pathogenesis of osteochondrosis is still poorly understood and only a limited number of proteomic studies have been conducted. This study provides a comprehensive characterization of proteomic alterations occurring in equine osteochondrotic chondrocytes, the only resident cell type that modulates differentiation and maturation of articular cartilage. The results evidenced alterations in abundance of proteins involved in functional and metabolic pathways and in extracellular matrix remodelling. These findings could help clarify some molecular aspects of osteochondrosis and open new fields of research for elucidating the pathogenesis of this disease.

Serum Peptidomic Profile as a Novel Biomarker for Rheumatoid Arthritis

Over the last decades, there has been an increasing need to discover new diagnostic RA biomarkers, other than the current serologic biomarkers, which can assist early diagnosis and response to treatment. The purpose of this study was to analyze the serum peptidomic profile in patients with rheumatoid arthritis (RA) by using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS). The study included 35 patients with rheumatoid arthritis (RA), 35 patients with primary osteoarthritis (OA) as the disease control (DC), and 35 healthy controls (HC). All participants were subjected to serum peptidomic profile analysis using magnetic bead (MB) separation (MALDI-TOF-MS). The trial showed 113 peaks that discriminated RA from OA and 101 peaks that discriminated RA from HC. Moreover, 95 peaks were identified and discriminated OA from HC; 38 were significant (p < 0.05) and 57 nonsignificant. The genetic algorithm (GA) model showed the best sensitivity and specificity in the three trials (RA versus HC, OA versus HC, and RA versus OA). The present data suggested that the peptidomic pattern is of value for differentiating individuals with RA from OA and healthy controls. We concluded that MALDI-TOF-MS combined with MB is an effective technique to identify novel serum protein biomarkers related to RA.

Proteomic analysis of human synovial fluid reveals potential diagnostic biomarkers for ankylosing spondylitis

BACKGROUND

Ankylosing spondylitis (AS) is a chronic inflammatory rheumatic disease affecting the axial skeleton and peripheral joints. The etiology of this disease remains poorly understood, but interactions between genetic and environmental factors have been implicated. The present study identified differentially expressed proteins in the synovial fluid (SF) of AS patients to elucidate the underlying cause of AS.

METHODS

A cohort of 40 SF samples from 10 AS and 10 each of rheumatoid arthritis (RA), gout, and osteoarthritis (OA) patients were analyzed by liquid chromatography tandem mass spectrometry (LC-MS/MS) to identify differentially expressed proteins specific to AS. The label-free LC-MS/MS results were verified by western blotting.

RESULTS

We identified 8 proteins that were > 1.5-fold upregulated in the SF of AS patients compared to that of the disease control groups, including HP, MMP1, MMP3, serum amyloid P-component (APCS), complement factor H-related protein 5 (CFHR5), mannose-binding lectin 2 (MBL2), complement component C9 (C9), and complement C4-A (C4A). CFHR5 and C9 were previously found in serum from AS patients, while APCS was previously found in SF as well as in serum. However, the present study has identified C4A, and MBL2 as potential AS biomarkers for the first time. The expression levels of MMP3, C9, and CFHR5 were verified in AS SF using western blotting.

CONCLUSION

We performed quantitative comparative proteomic analysis using by LC-MS/MS of the SF from four disease states: RA, gout, and OA. This systematic comparison revealed novel differentially expressed proteins in AS SF, as well as two previously reported candidate biomarkers. We further verified the expression of MMP3, C9 and CFHR5 by western blot. These proteins may serve as diagnostic or prognostic biomarkers in patients with AS, and may thus improve the clinical outcomes of this serious disease.

New Insights for RANKL as a Proinflammatory Modulator in Modeled Inflammatory Arthritis

Receptor activator of nuclear factor-κB ligand (RANKL), a member of the Tumor Necrosis Factor (TNF) superfamily, constitutes the master regulator of osteoclast formation and bone resorption, whereas its involvement in inflammatory diseases remains unclear. Here, we used the human TNF transgenic mouse model of erosive inflammatory arthritis to determine if the progression of inflammation is affected by either genetic inactivation or overexpression of RANKL in transgenic mouse models. TNF-mediated inflammatory arthritis was significantly attenuated in the absence of functional RANKL. Notably, TNF overexpression could not compensate for RANKL-mediated osteopetrosis, but promoted osteoclastogenesis between the pannus and bone interface, suggesting RANKL-independent mechanisms of osteoclastogenesis in inflamed joints. On the other hand, simultaneous overexpression of RANKL and TNF in double transgenic mice accelerated disease onset and led to severe arthritis characterized by significantly elevated clinical and histological scores as shown by aggressive pannus formation, extended bone resorption, and massive accumulation of inflammatory cells, mainly of myeloid origin. RANKL and TNF cooperated not only in local bone loss identified in the inflamed calcaneous bone, but also systemically in distal femurs as shown by microCT analysis. Proteomic analysis in inflamed ankles from double transgenic mice overexpressing human TNF and RANKL showed an abundance of proteins involved in osteoclastogenesis, pro-inflammatory processes, gene expression regulation, and cell proliferation, while proteins participating in basic metabolic processes were downregulated compared to TNF and RANKL single transgenic mice. Collectively, these results suggest that RANKL modulates modeled inflammatory arthritis not only as a mediator of osteoclastogenesis and bone resorption but also as a disease modifier affecting inflammation and immune activation.

Early supplemental α2-macroglobulin attenuates cartilage and bone damage by inhibiting inflammation in collagen II-induced arthritis model

OBJECTIVE

To determine if early supplemental intra-articular α2-macroglobulin (A2M) has a chondroprotective effect in a collagen II-induced arthritis (CIA) mice model.

METHODS

DBA/1 mice were randomized into four groups (n = 15/group): (a) CIA + 1.2 μg of A2M; (b) CIA + 0.8 μg of A2M; (c) CIA + 0.4 μg of A2M; (d) vehicle + phosphate-buffered saline (PBS). A2M was injected into right ankles and PBS was injected into the left ankles simultaneously as internal control at days 36, 43 and 50. The CIA inflammation clinical score and ankle thickness were recorded every other day starting on day 21 until sacrifice. Changes in inflammation were monitored by in vivo fluorescence molecular tomography (FMT). Inflammation, cartilage and bone damage were assessed with X-ray, histology and immunohistochemistry. Cartilage and inflammation-related gene expression was quantified by real-time polymerase chain reaction (PCR).

RESULTS

All mice showed ankle inflammation on day 33. After day 43, lower clinical scores, ankle thickness and Sharp/van der Heijde method scores in A2M-treated ankles compared with PBS-treated ankles. FMT data indicated that the inflammation markers MMPSense and ProSense were significantly elevated in the PBS-treated ankles than A2M-treated ankles. Histology and X-ray analyses indicated that A2M administration resulted in lower levels of inflammatory infiltration and synovial hyperplasia, as well as more typical cartilage and bone organization with increased COL II and Aggrecan staining when compared with PBS-treated ankles. In addition, real-time PCR showed that,matrix metalloproteinase-3, -9, -13, COL X and Runx2 were significantly less expressed in A2M-treated groups than PBS-treated animals.

CONCLUSION

Early supplemental intra-articular A2M exerts an anti-inflammatory effect and attenuates cartilage and bone damage in a CIA model.

Integrative Approaches to Understanding the Pathogenic Role of Genetic Variation in Rheumatic Diseases

The use of high-throughput omics may help to understand the contribution of genetic variants to the pathogenesis of rheumatic diseases. We discuss the concept of missing heritability: that genetic variants do not explain the heritability of rheumatoid arthritis and related rheumatologic conditions. In addition to an overview of how integrative data analysis can lead to novel insights into mechanisms of rheumatic diseases, we describe statistical approaches to prioritizing genetic variants for future functional analyses. We illustrate how analyses of large datasets provide hope for improved approaches to the diagnosis, treatment, and prevention of rheumatic diseases.

Anti-inflammatory effects of ursolic acid-3-acetate on human synovial fibroblasts and a murine model of rheumatoid arthritis

Ursolic acid (UA), a pentacyclic triterpenoid, is a common natural substance known to be effective in the treatment of inflammation, oxidative stress, and ulcers in arthritis. This study examined the effects of ursolic acid-3-acetate (UAA), a derivative of UA, on rheumatoid arthritis (RA) and verified the underlying mechanism of action by using a type-II collagen-induced arthritis (CIA) mice model and tumor necrosis factor (TNF)-α-stimulated RA synovial fibroblasts. The oral administration of UAA showed a decrease in clinical arthritis symptoms, paw thickness, histologic and radiologic changes, and serum IgG1 and IgG2a levels. UAA administration reduced Th1/Th17 phenotype CD4+ T lymphocyte expansion and inflammatory cytokine production in draining lymph nodes. In addition, UAA effectively reduced the expression and production of inflammatory mediators, including cytokines and matrix metalloproteinase-1/3 in the knee joint tissue and RA synovial fibroblasts, through the downregulation of IKKα/β, ΙκBα, and nuclear factor-κB. Our findings showed that UAA modulated helper T cell immune responses and matrix-degrading enzymes. The effects of UAA were comparable with those of the positive control drug, dexamethasone. In summary, all the evidence presented in this paper suggest that UAA could be a therapeutic candidate for the treatment of RA.

Urinary proteomics can define distinct diagnostic inflammatory arthritis subgroups

Current diagnostic tests applied to inflammatory arthritis lack the necessary specificity to appropriately categorise patients. There is a need for novel approaches to classify patients with these conditions. Herein we explored whether urinary proteomic biomarkers specific for different forms of arthritis (rheumatoid arthritis (RA), psoriatic arthritis (PsA), osteoarthritis (OA)) or chronic inflammatory conditions (inflammatory bowel disease (IBD)) can be identified. Fifty subjects per group with RA, PsA, OA or IBD and 50 healthy controls were included in the study. Two-thirds of these populations were randomly selected to serve as a training set, while the remaining one-third was reserved for validation. Sequential comparison of one group to the other four enabled identification of multiple urinary peptides significantly associated with discrete pathological conditions. Classifiers for the five groups were developed and subsequently tested blind in the validation test set. Upon unblinding, the classifiers demonstrated excellent performance, with an area under the curve between 0.90 and 0.97 per group. Identification of the peptide markers pointed to dysregulation of collagen synthesis and inflammation, but also novel inflammatory markers. We conclude that urinary peptide signatures can reliably differentiate between chronic arthropathies and inflammatory conditions with discrete pathogenesis.

Folate Receptor-Targeted Diagnostics and Therapeutics for Inflammatory Diseases

Inflammation, an innate immune response mediated by macrophages, forms the first line of defence to protect our body from the invasion of various pathogens. Although inflammation is a defensive response, chronic inflammation has been regarded as the major cause of many types of human diseases such as inflammatory/autoimmune diseases, cancers, neurological diseases, and cardiovascular diseases. Folate receptor (FR) is a cell surface glycosylphosphatidylinositol (GPI)-anchored glycoprotein, and its three isoforms, FR-α, FR-β, and FR-γ, are found in humans. Interestingly, FRs are highly expressed on a variety of cells, including cancer cells and activated macrophages, whereas their expression on normal cells is undetectable, indicating that FR-targeting could be a good selective strategy for the diagnosis and therapeutic treatment of cancers and activated macrophage-mediated inflammatory diseases. Previous studies successfully showed FR-targeted imaging of many types of cancers in animal models as well as human patients. Recently, a number of emerging studies have found that activated macrophages, which are critical players for a variety of inflammatory diseases, highly express FRs, and selective targeting of these FR-positive activated macrophages is a good approach to diagnose and treat inflammatory diseases. In this review, we describe the characteristics and structure of FRs, and further discuss FR-targeted diagnostics and therapeutics of human diseases, in particular, activated macrophage-mediated inflammatory diseases.

Methotrexate affects HMGB1 expression in rheumatoid arthritis, and the downregulation of HMGB1 prevents rheumatoid arthritis progression

High-mobility group box 1 (HMGB1) is associated with the development of rheumatoid arthritis (RA). Recent studies have shown that methotrexate (MTX) may inhibit the expression of HMGB1. This study examined whether HMGB1 might be involved in the treatment of RA using MTX. Synovial tissues were collected from RA patients who were treated with MTX for at least 6 months (RA-MTX group, 7 cases) and from those without MTX treatment (RA-noMTX group, 7 cases). Additionally, patients with osteoarthritis (OA group, 7 cases) were used as controls. The expression and locations of HMGB1 in the tissues were detected using real-time PCR, western blot, and immunohistochemistry. Additionally, OA-fibroblast-like synoviocytes (FLSs) and RA-FLSs were isolated and cultured, and the expression of HMGB1 was reduced in these cells by transfection with HMGB1 siRNA. Cell proliferation, migration, and invasion abilities were detected. Furthermore, the effects of HMGB1 on matrix metalloproteinase (MMP)-2 and MMP-13 were measured using western blot analysis. At the tissue level, HMGB1 expression in synovial membrane did not differ significantly between the OA and RA-MTX groups, but was significantly lower in these groups than in the RA-noMTX group. In cell experiments, the cell doubling time in the RA-FLS HMGB1 siRNA group was significantly extended compared with that in the RA-FLS negative control (NC)-siRNA group. The amount of cell migration and invasion in the RA-FLS HMGB1 siRNA group was significantly lower compared with that in the NC-siRNA group; the MMP-2 and MMP-13 expression levels were also lower. These results showed that MTX reduced HMGB1 expression in RA synovial tissues, and through the downregulation of HMGB1 expression in tissues, MTX may slow disease progression of RA.

Identification of a 48 kDa form of unconventional myosin 1c in blood serum of patients with autoimmune diseases

We searched for protein markers present in blood serum of multiple sclerosis (MS), rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE) patients in comparison to healthy human individuals. We used precipitation/extraction methods and MALDI TOF/TOF mass spectrometry, and identified a protein with Mr ~46 kDa as a fragment of human unconventional myosin IC isoform b (Myo1C). Western blotting with specific anti-human Myo1C antibodies confirmed the identity. Screening of blood serum samples from different autoimmune patients for the presence of Myo1c revealed its high level in MS and RA patients, relatively low level in SLE patients, and undetected in healthy donors. These data are suggesting that the level of p46 Myo1C in blood serum is a potential marker for testing of autoimmune diseases.