Osteoarthritis (OA) is the most common rheumatic pathology and is characterized primarily by articular cartilage degradation. Despite its high prevalence, there is no effective therapy to slow disease progression or regenerate the damaged tissue. Therefore, new diagnostic and monitoring tests for OA are urgently needed, which would also promote the development of alternative therapeutic strategies. In the present study, we have performed an iTRAQ-based quantitative proteomic analysis of secretomes from healthy human articular cartilage explants, comparing their protein profile to those from unwounded (early disease) and wounded (advanced disease) zones of osteoarthritic tissue. This strategy allowed us to identify a panel of 76 proteins that are distinctively released by the diseased tissue. Clustering analysis allowed the classification of proteins according to their different profile of release from cartilage. Among these proteins, the altered release of osteoprotegerin (decreased in OA) and periostin (increased in OA), both involved in bone remodelling processes, was verified in further analyses. Moreover, periostin was also increased in the synovial fluid of OA patients. Altogether, the present work provides a novel insight into the mechanisms of human cartilage degradation and a number of new cartilage-characteristic proteins with possible biomarker value for early diagnosis and prognosis of OA.
Chondroitin sulfate (CS) is a symptomatic slow acting drug for osteoarthritis (OA) widely used for the treatment of this highly prevalent disease, characterized by articular cartilage degradation. However, little is known about its mechanism of action, and recent large scale clinical trials have reported variable results on OA symptoms. Herein, we aimed to study the modulations in the intracellular proteome and the secretome of human articular cartilage cells (chondrocytes) treated with three different CS compounds, with different origin or purity, by two complementary proteomic approaches. Osteoarthritic cells were treated with 200 g/ml of each brand of CS. Quantitative proteomics experiments were carried out by the DIGE and stable isotope labeling with amino acids in cell culture (SILAC) techniques, followed by LC-MALDI-MS/MS analysis. The DIGE study, carried out on chondrocyte whole cell extracts, led to the detection of 46 spots that were differential between conditions in our study: 27 were modulated by CS1, 4 were modulated by CS2, and 15 were modulated by CS3. The SILAC experiment, carried out on the subset of chondrocyte-secreted proteins, allowed us to identify 104 different proteins. Most of them were extracellular matrix components, and 21 were modulated by CS1, 13 were modulated by CS2, and 9 were modulated by CS3. Each of the studied compounds induces a characteristic protein profile in OA chondrocytes. CS1 displayed the widest effect but increased the mitochondrial superoxide dismutase, the cartilage oligomeric matrix protein, and some catabolic or inflammatory factors like interstitial collagenase, stromelysin-1, and pentraxin-related protein. CS2 and CS3, on the other hand, increased a number of structural proteins, growth factors, and extracellular matrix proteins. Our study shows how, from the three CS compounds tested, CS1 induces the activation of inflammatory and catabolic pathways, whereas CS2 and CS3 induce an anti-inflammatory and anabolic response. The data presented emphasize the importance of employing high quality CS compounds, supported by controlled clinical trials, in the therapy of OA. Finally, the present work exemplifies the usefulness of proteomic approaches in pharmacological studies. Molecular & Cellular Proteomics
Osteoarthritis (OA) is the most common rheumatic disease and one of the most disabling pathologies worldwide. To date, the diagnostic methods of OA are very limited, and there are no available medications capable of halting its characteristic cartilage degeneration. Therefore, there is a significant interest in new biomarkers useful for the early diagnosis, prognosis, and therapeutic monitoring. In the recent years, protein microarrays have emerged as a powerful proteomic tool to search for new biomarkers. In this study, we have used two concepts for generating protein arrays, antigen microarrays, and NAPPA (nucleic acid programmable protein arrays), to characterize differential autoantibody profiles in a set of 62 samples from OA, rheumatoid arthritis (RA), and healthy controls. An untargeted screen was performed on 3840 protein fragments spotted on planar antigen arrays, and 373 antigens were selected for validation on bead-based arrays. In the NAPPA approach, a targeted screening was performed on 80 preselected proteins. The autoantibody targeting CHST14 was validated by ELISA in the same set of patients. Altogether, nine and seven disease related autoantibody target candidates were identified, and this work demonstrates a combination of these two array concepts for biomarker discovery and their usefulness for characterizing disease-specific autoantibody profiles.
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