In vitro tissue models are useful tools for the development of novel therapy strategies in cartilage repair and care. The limited availability of human primary tissue and high costs of animal models hamper preclinical tests of innovative substances and techniques. In this study we tested the potential of porcine chondrocyte micromass cultures to mimic human articular cartilage and essential aspects of osteoarthritis (OA) in vitro. Primary chondrocytes were enzymatically isolated from porcine femoral condyles and were maintained in 96-multiwell format to establish micromass cultures in a high-throughput scale. Recombinant porcine tumor necrosis factor alpha (TNF-α) was used to induce OA-like changes documented on histological (Safranin O, collagen type II staining), biochemical (hydroxyproline assay, dimethylmethylene blue method), and gene expression level (Affymetrix porcine microarray, real time PCR) and were compared with published data from human articular cartilage and human micromass cultures. After 14 days in micromass culture, porcine primary chondrocytes produced ECM rich in proteoglycans and collagens. On gene expression level, significant correlations of detected genes with porcine cartilage (r = 0.90), human cartilage (r = 0.71), and human micromass culture (r = 0.75) were observed including 34 cartilage markers such as COL2A1, COMP, and aggrecan. TNF-α stimulation led to significant proteoglycan (-75%) and collagen depletion (-50%). Comparative expression pattern analysis revealed the involvement of catabolic enzymes (MMP1, -2, -13, ADAM10), chemokines (IL8, CCL2, CXCL2, CXCL12, CCXL14), and genes associated with cell death (TNFSF10, PMAIPI, AHR) and skeletal development (GPNMB, FRZB) including transcription factors (WIF1, DLX5, TWIST1) and growth factors (IGFBP1, -3, TGFB1) consistent with published data from human OA cartilage. Expression of genes related to cartilage ECM formation (COL2A1, COL9A1, COMP, aggrecan) as well as hypertrophic bone formation (COL1A1, COL10A1) was predominantly found decreased. These findings indicating significant parallels between human articular cartilage and the presented porcine micromass model and vice versa confirm the applicability of known cartilage marker and their characteristics in the porcine micromass model. TNF-α treatment enabled the initiation of typical OA reaction patterns in terms of extensive ECM loss, cell death, formation of an inflammatory environment through the induction of genes coding for chemokines and enzymes, and the modulation of genes involved in skeletal development such as growth factors, transcription factors, and cartilage ECM-forming genes. In conclusion, the porcine micromass model represents an alternative tissue platform for the evaluation of innovative substances and techniques for the treatment of OA.

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Purpose: Today, for regenerative treatment of injured or early osteoarthritic cartilage, ACI and MACI are clinically applied. Also mesenchymal stem cell based approaches have reached the clinic. Here, AMICÒ combines microfracture with implantation of a collagen membrane, and ChondrotissueÒ microfracture with a PGA/hyaluronan scaffold. AMICÒ is a passive approach; endogenous MSC flow into the membrane. ChondrotissueÒ, in whose development we were involved, is between passive and active; MSC flow into the scaffold is enhanced by the addition of MSC recruiting serum. Our aim is to develop an active in situ approach, wherein the implantation of scaffolds, loaded with MSC recruiting chemokines and differentiation factors, combined with microfracture, allows the use of endogenous MSC to promote OA cartilage regeneration. Methods: MSC were isolated from bone marrow of normal donor and OA hip joint cancellous bone and characterized (morphology, growth, surface marker, multilineage potential). Also their Ck receptor profile was elucidated (qPCR, immunohistochemistry). Cartilage and chondrocytes were harvested from ND and OA femoral heads, and supernatants were analyzed for their Ck profile (protein array). Then, the recruitment potential of supernatants and Ck on MSC was examined (chemotaxis assay), and Pertussis toxin, siRNA and antibodies were applied to block Ck receptors. Moreover, expression profiles of Ck

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Background and Objective Knowledge about gene networks is of great importance for analysis of transcriptome data. However, current tools mainly rely on information about direct molecular interactions between proteins, which is not directly connected to expression levels. These differences between transcriptome based perception of biological information and tools for network analysis are the main reason for difficulties in functional interpretation. Therefore, we started to use transcriptome data of biologically well-defined states to define functional markers and signatures as tools for future analysis. Materials and Methods GeneChip HG-U133 Plus 2.0 transcriptomes from highly purified blood cell types (granulocytes, monocytes, CD4+ and CD8+ T-cell, B-cells, NK-cells) as well as from monocyte stimulation with LPS, TNF and type 1 IFN were selected from the BioRetis database (). Correlations of expression between all probesets were calculated to filter for co-regulation Correlation matrices were calculated, clustered and displayed in heat maps The web-platform was constructed based on Ruby on Rails to provide a framework for analysis and storage of data The database and the correlation-algorithm will be provided on our homepage . Results Initially, correlation matrices were determined for each individual stimulation condition and its control. Stepwise combination of the three different conditions for calculation of correlation coefficients revealed a reduction of the correlation network and a reduction of overlap between the networks. This indicates increasing functional specificity of the identified candidates. All of the typical previously published IFN related genes were identified and thus confirmed our strategy. In a similar way, cell type specific co-expression networks were determined. Additional filtering for high signal intensity provides candidates for sensitive detection of the function related patterns even in highly diluted conditions. These marker panels are currently tested for detection and quantification of functional signatures in biopsies of inflamed tissue. Conclusions Correlating transcription between genes in well-defined biological states identifies function-related markers and signatures. Depending on the type of function, appropriate conditions have to be selected.