Connective tissue growth factor (CTGF)/CCN family member 2 (CCN2) is a CCN family member of matricellular signaling modulators. It has been shown that CCN2/CTGF mediates cell adhesion, aggregation and migration in a large variety of cell types, including vascular endothelial cells, fibroblasts, epithelial cells, aortic smooth muscle and also pluripotent stem cells. Others matricellular proteins are capable of interacting with CCN2/CTGF to mediate its function. Cell migration is a key feature for tumor cell invasion and metastasis. CCN2/CTGF seems to be a prognostic marker for cancer. In addition, here we intend to discuss recent discoveries and a new strategy to develop therapies against CCN2/CTGF, in order to treat cancer metastasis.
Purpose: Investigate the metabolomic profile of synovial fluid from patients with and without knee osteoarthritis (OA), in order to identify new metabolic markers for therapeutic targets. Methods: Synovial fluid (SF) was collected from patients submitted to knee arthroscopy (n ¼ 23 K-L 0) or knee replacement (n ¼ 37, 9 K-L 3 and 28 K-L 4), and centrifuged to isolate cells from the fluid. Fluid samples were frozen at À80 C. Non-OA and OA synovial fluids were thawed in room temperature and centrifuged at 4000Âg for 20 min. 500uL of supernatant was mixtured with 1500uL of 50 mM phosphate buffer pH 7.4, encompassing 10% D 2 O and 0.1 mM DSS (4,4-dimethyl-4silapentane-1-sulfonic acid). Mixture was filtered on amicon ultra with 3KD of cutoff (#UFC200324), as fabricant recommendations, and the flow-through was put in a NMR tube. NMR spectra from synovial fluid samples were acquired on Bruker 400MHZ spectrometer. 1 H onedimensional spectra were acquired with ZGESGP, 1K scans, TD of 64K, and SW of 20 ppm. Two-dimensional, 1 H-1 HTOCSY and 13 C-1 H HSQC, were acquired for assignments. Inversion-recovery-T1 was acquired to each sample to observe viscosity. All spectra were processed, phase and baseline corrected, on TopSpin 3.2 software (Bruker). CCPNMR V2 software, with metabolomics package installed, HMDB 3.0, and BMRB, were used to assignments. For multivariate analysis, 1D spectra were aligned, normalized by sum of intensities, 0.02 ppm binned and pareto scaled, on AMIX software (Bruker). PLS-DA, VIP-score, and cross-validation, were done on MetaboAnalyst 3.0. For univariate analysis, we did multiple t-test, with 95% CI, and same SD between control/disease samples, on GraphPad Prism 6 software. Results: 1 H 1D NMR spectra of synovial fluids from 30 patients with OA and 5 control patients showed several different metabolites (figures A and B). In addition, 3D PLS-DA score-plot (figure C) displayed a completely distinct metabolic profile in OA and control patients (red and green colors, respectively). Conclusions: Synovial fluid from OA patients has a specific metabolic profile. These specific OA metabolic markers can be future targets for osteoarthritis treatment.
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