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Background/aims: Synovial fibrosis is a pathological process that is observed in several musculoskeletal disorders and characterized by the excessive deposition of extracellular matrix, as well as cell migration and proliferation. Despite the fact that glucocorticoids are widely employed in the treatment of rheumatic pathologies such as osteoarthritis (OA) and rheumatoid arthritis, the mechanisms by which glucocorticoids act in the joint and their impacts on pro-fibrotic pathways are still unclear., Materials: Human OA synovial fibroblasts were obtained from knee and hip joints. Cells were treated with prednisolone (1 mM) or transforming growth factor-beta 1 (TGF-β1) (10 ng/ml) for 1 and 7 days for quantification of RNA and protein expression (by real-time quantitative reverse transcription-PCR and western blot, respectively), 72 h for immunocytochemistry analysis, and 48 h for proliferation (by BrdU assay) and migration (by wound assay) studies. In addition, cells were preincubated with prednisolone and/or the peroxisome proliferator-activated receptor gamma (PPAR-γ) agonist 15-deoxy-Δ-12,14-prostaglandin J2 (15d-PGJ2) for 6 h before adding TGF-β1. pSmad1/5, pSmad2 and β-catenin levels were analyzed by Western blot. The activin receptor-like kinase-5 (ALK-5) inhibitor (SB-431542) was employed for the mechanistic assays., Results: Prednisolone showed a predominant anti-fibrotic impact on fibroblast-like synoviocytes as it attenuated the spontaneous and TGF-β-induced gene expression of pro-fibrotic markers. Prednisolone also reduced α-sma protein and type III collagen levels, as well as cell proliferation and migration after TGF-β stimulation. However, prednisolone did not downregulate the gene expression of all the pro-fibrotic markers tested and did not restore the reduced PPAR-γ levels after TGF-β stimulation. Interestingly, anti-fibrotic actions of the glucocorticoid were reinforced in the presence of the PPAR-γ agonist 15d-PGJ2. Combined pretreatment modulated Smad2/3 levels and, similar to the ALK-5 inhibitor, blocked β-catenin accumulation elicited by TGF-β., Conclusions: Prednisolone, along with 15d-PGJ2, modulates pro-fibrotic pathways activated by TGF-β in synovial fibroblasts at least partially through the inhibition of ALK5/Smad2 signaling and subsequent β-catenin accumulation. These findings shed light on the potential therapeutic effects of glucocorticoids treatment combined with a PPAR-γ agonist against synovial fibrosis, although future studies are warranted to further evaluate this concern., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Osteoarthritis (OA) is a degenerative joint disease characterized by progressive cartilage degradation but also synovial membrane inflammation, osteophyte formation and subchondral bone sclerosis. Medical care is mainly based on alleviating pain symptoms, but to date, no effective drug can stop the disease progression. Cartilage is a tissue composed of only one cell type, chondrocytes, wrapped in a collagen rich extracellular matrix they synthesize. Chondrocytes can adopt different phenotypes in vivo and in vitro, defined by the collagen type they produce. Isolated from their matrix, chondrocytes present the particularity to dedifferentiate, producing fibroblastic type I and III collagens. With OA onset, chondrocytes undergo multiple changes, in terms of proliferation, viability, but also secretory profile. The acquisition of a hypertrophic phenotype (producing aberrant type X collagen and catabolic MMP-13 protease) by chondrocytes is well documented and contributes to OA development. However, it is increasingly believed that chondrocytes rather acquire a variety of degenerated phenotypes at the onset of OA, including a "dedifferentiated-like" phenotype that might also contribute to OA progression. In this review, we will (i) present molecular knowledge underlying dedifferentiation process, (ii) emphasize connections between dedifferentiation and OA and (iii) consider OA therapeutic strategies aiming at the maintenance of chondrogenic phenotype., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Objectives: Infliximab is the first anti-TNFalpha accepted by the Food and Drug Administration for use in inflammatory bowel disease treatment. Few clinical, biological and genetic factors tend to predict response in Crohn's disease (CD) patient subcategories, none widely predicting response to infliximab., Design and Methods: Twenty CD patients showing clinical response or non response to infliximab were used for serum proteomic profiling on Surface Enhanced Lazer Desorption Ionisation-Time of Flight-Mass Spectrometry (SELDI-TOF-MS), each before and after treatment. Univariate and multivariate data analysis were performed for prediction and characterization of response to infliximab., Results: We obtained a model of classification predicting response to treatment and selected relevant potential biomarkers, among which platelet aggregation factor 4 (PF4). We quantified PF4, sCD40L and IL-6 by ELISA for correlation studies., Conclusions: This first proteomic pilot study on response to infliximab in CD suggests association between platelet metabolism and response to infliximab and requires validation studies on a larger cohort of patients.

Crohn's disease and ulcerative colitis known as inflammatory bowel diseases (IBD) are chronic immuno-inflammatory pathologies of the gastrointestinal tract. These diseases are multifactorial, polygenic and of unknown etiology. Clinical presentation is non-specific and diagnosis is based on clinical, endoscopic, radiological and histological criteria. Novel markers are needed to improve early diagnosis and classification of these pathologies. We performed a study with 120 serum samples collected from patients classified in 4 groups (30 Crohn, 30 ulcerative colitis, 30 inflammatory controls and 30 healthy controls) according to accredited criteria. We compared protein sera profiles obtained with a Surface Enhanced Laser Desorption Ionization-Time of Flight-Mass Spectrometer (SELDI-TOF-MS). Data analysis with univariate process and a multivariate statistical method based on multiple decision trees algorithms allowed us to select some potential biomarkers. Four of them were identified by mass spectrometry and antibody based methods. Multivariate analysis generated models that could classify samples with good sensitivity and specificity (minimum 80%) discriminating groups of patients. This analysis was used as a tool to classify peaks according to differences in level on spectra through the four categories of patients. Four biomarkers showing important diagnostic value were purified, identified (PF4, MRP8, FIBA and Hpalpha2) and two of these: PF4 and Hpalpha2 were detected in sera by classical methods. SELDI-TOF-MS technology and use of the multiple decision trees method led to protein biomarker patterns analysis and allowed the selection of potential individual biomarkers. Their downstream identification may reveal to be helpful for IBD classification and etiology understanding.