232 research outputs found

    Src kinase inhibition promotes the chondrocyte phenotype

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    Regulated differentiation of chondrocytes is essential for both normal skeletal development and maintenance of articular cartilage. The intracellular pathways that control these events are incompletely understood, and our ability to modulate the chondrocyte phenotype in vivo or in vitro is therefore limited. Here we examine the role played by one prominent group of intracellular signalling proteins, the Src family kinases, in regulating the chondrocyte phenotype. We show that the Src family kinase Lyn exhibits a dynamic expression pattern in the chondrogenic cell line ATDC5 and in a mixed population of embryonic mouse chondrocytes in high-density monolayer culture. Inhibition of Src kinase activity using the pharmacological compound PP2 (4-Amino-5-(4-chlorophenyl)-7-(t-butyl)pyrazolo [3,4-d]pyrimidine) strongly reduced the number of primary mouse chondrocytes. In parallel, PP2 treatment increased the expression of both early markers (such as Sox9, collagen type II, aggrecan and xylosyltransferases) and late markers (collagen type X, Indian hedgehog and p57) markers of chondrocyte differentiation. Interestingly, PP2 repressed the expression of the Src family members Lyn, Frk and Hck. It also reversed morphological de-differentiation of chondrocytes in monolayer culture and induced rounding of chondrocytes, and reduced stress fibre formation and focal adhesion kinase phosphorylation. We conclude that the Src kinase inhibitor PP2 promotes chondrogenic gene expression and morphology in monolayer culture. Strategies to block Src activity might therefore be useful both in tissue engineering of cartilage and in the maintenance of the chondrocyte phenotype in diseases such as osteoarthritis

    Genome-wide analyses of gene expression during mouse endochondral ossification

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    Background: Endochondral ossification is a complex process involving a series of events that are initiated by the establishment of a chondrogenic template and culminate in its replacement through the coordinated activity of osteoblasts, osteoclasts and endothelial cells. Comprehensive analyses of in vivo gene expression profiles during these processes are essential to obtain a complete understanding of the regulatory mechanisms involved. Methodology/Principal Findings: To address these issues, we completed a microarray screen of three zones derived from manually segmented embryonic mouse tibiae. Classification of genes differentially expressed between each respective zone, functional categorization as well as characterization of gene expression patterns, cytogenetic loci, signaling pathways and functional motifs both confirmed reported data and provided novel insights into endochondral ossification. Parallel comparisons of the microdissected tibiae data set with our previously completed micromass culture screen further corroborated the suitability of micromass cultures for modeling gene expression in chondrocyte development. The micromass culture system demonstrated striking similarities to the in vivo microdissected tibiae screen; however, the micromass system was unable to accurately distinguish gene expression differences in the hypertrophic and mineralized zones of the tibia. Conclusions/Significance: These studies allow us to better understand gene expression patterns in the growth plate and endochondral bones and provide an important technical resource for comparison of gene expression in diseased or experimentally-manipulated cartilages. Ultimately, this work will help to define the genomic context in which genes are expressed in long bones and to understand physiological and pathological ossification. © 2010 James et al

    Genome-Wide Analyses of Gene Expression during Mouse Endochondral Ossification

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    Endochondral ossification is a complex process involving a series of events that are initiated by the establishment of a chondrogenic template and culminate in its replacement through the coordinated activity of osteoblasts, osteoclasts and endothelial cells. Comprehensive analyses of in vivo gene expression profiles during these processes are essential to obtain a complete understanding of the regulatory mechanisms involved.To address these issues, we completed a microarray screen of three zones derived from manually segmented embryonic mouse tibiae. Classification of genes differentially expressed between each respective zone, functional categorization as well as characterization of gene expression patterns, cytogenetic loci, signaling pathways and functional motifs both confirmed reported data and provided novel insights into endochondral ossification. Parallel comparisons of the microdissected tibiae data set with our previously completed micromass culture screen further corroborated the suitability of micromass cultures for modeling gene expression in chondrocyte development. The micromass culture system demonstrated striking similarities to the in vivo microdissected tibiae screen; however, the micromass system was unable to accurately distinguish gene expression differences in the hypertrophic and mineralized zones of the tibia.These studies allow us to better understand gene expression patterns in the growth plate and endochondral bones and provide an important technical resource for comparison of gene expression in diseased or experimentally-manipulated cartilages. Ultimately, this work will help to define the genomic context in which genes are expressed in long bones and to understand physiological and pathological ossification

    C-type natriuretic peptide regulates endochondral bone growth through p38 MAP kinase-dependent and – independent pathways

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    BACKGROUND: C-type natriuretic peptide (CNP) has recently been identified as an important anabolic regulator of endochondral bone growth, but the molecular mechanisms mediating its effects are not completely understood. RESULTS: We demonstrate in a tibia organ culture system that pharmacological inhibition of p38 blocks the anabolic effects of CNP. We further show that CNP stimulates endochondral bone growth largely through expansion of the hypertrophic zone of the growth plate, while delaying mineralization. Both effects are reversed by p38 inhibition. We also performed Affymetrix microarray analyses on micro-dissected tibiae to identify CNP target genes. These studies confirmed that hypertrophic chondrocytes are the main targets of CNP signaling in the growth plate, since many more genes were regulated by CNP in this zone than in the others. While CNP receptors are expressed at similar levels in all three zones, cGMP-dependent kinases I and II, important transducers of CNP signaling, are expressed at much higher levels in hypertrophic cells than in other areas of the tibia, providing a potential explanation for the spatial distribution of CNP effects. In addition, our data show that CNP induces the expression of NPR3, a decoy receptor for natriuretic peptides, suggesting the existence of a feedback loop to limit CNP signaling. Finally, detailed analyses of our microarray data showed that CNP regulates numerous genes involved in BMP signaling and cell adhesion. CONCLUSION: Our data identify novel target genes of CNP and demonstrate that the p38 pathway is a novel, essential mediator of CNP effects on endochondral bone growth, with potential implications for understanding and treatment of numerous skeletal diseases

    Systems Biology Markup Language (SBML): Language Specification for Level 3 Version 2 Core Release 2

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    Computational models can help researchers to interpret data, understand biological functions, and make quantitative predictions. The Systems Biology Markup Language (SBML) is a file format for representing computational models in a declarative form that different software systems can exchange. SBML is oriented towards describing biological processes of the sort common in research on a number of topics, including metabolic pathways, cell signaling pathways, and many others. By supporting SBML as an input/output format, different tools can all operate on an identical representation of a model, removing opportunities for translation errors and assuring a common starting point for analyses and simulations. This document provides the specification for Release 2 of Version 2 of SBML Level 3 Core. The specification defines the data structures prescribed by SBML as well as their encoding in XML, the eXtensible Markup Language. Release 2 corrects some errors and clarifies some ambiguities discovered in Release 1. This specification also defines validation rules that determine the validity of an SBML document, and provides many examples of models in SBML form. Other materials and software are available from the SBML project website at http://sbml.org/

    BRCA2 polymorphic stop codon K3326X and the risk of breast, prostate, and ovarian cancers

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    Background: The K3326X variant in BRCA2 (BRCA2*c.9976A>T; p.Lys3326*; rs11571833) has been found to be associated with small increased risks of breast cancer. However, it is not clear to what extent linkage disequilibrium with fully pathogenic mutations might account for this association. There is scant information about the effect of K3326X in other hormone-related cancers. Methods: Using weighted logistic regression, we analyzed data from the large iCOGS study including 76 637 cancer case patients and 83 796 control patients to estimate odds ratios (ORw) and 95% confidence intervals (CIs) for K3326X variant carriers in relation to breast, ovarian, and prostate cancer risks, with weights defined as probability of not having a pathogenic BRCA2 variant. Using Cox proportional hazards modeling, we also examined the associations of K3326X with breast and ovarian cancer risks among 7183 BRCA1 variant carriers. All statistical tests were two-sided. Results: The K3326X variant was associated with breast (ORw = 1.28, 95% CI = 1.17 to 1.40, P = 5.9x10- 6) and invasive ovarian cancer (ORw = 1.26, 95% CI = 1.10 to 1.43, P = 3.8x10-3). These associations were stronger for serous ovarian cancer and for estrogen receptor–negative breast cancer (ORw = 1.46, 95% CI = 1.2 to 1.70, P = 3.4x10-5 and ORw = 1.50, 95% CI = 1.28 to 1.76, P = 4.1x10-5, respectively). For BRCA1 mutation carriers, there was a statistically significant inverse association of the K3326X variant with risk of ovarian cancer (HR = 0.43, 95% CI = 0.22 to 0.84, P = .013) but no association with breast cancer. No association with prostate cancer was observed. Conclusions: Our study provides evidence that the K3326X variant is associated with risk of developing breast and ovarian cancers independent of other pathogenic variants in BRCA2. Further studies are needed to determine the biological mechanism of action responsible for these associations

    Evaluation of polygenic risk scores for breast and ovarian cancer risk prediction in BRCA1 and BRCA2 mutation carriers

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    Background: Genome-wide association studies (GWAS) have identified 94 common single-nucleotide polymorphisms (SNPs) associated with breast cancer (BC) risk and 18 associated with ovarian cancer (OC) risk. Several of these are also associated with risk of BC or OC for women who carry a pathogenic mutation in the high-risk BC and OC genes BRCA1 or BRCA2. The combined effects of these variants on BC or OC risk for BRCA1 and BRCA2 mutation carriers have not yet been assessed while their clinical management could benefit from improved personalized risk estimates. Methods: We constructed polygenic risk scores (PRS) using BC and OC susceptibility SNPs identified through population-based GWAS: for BC (overall, estrogen receptor [ER]-positive, and ER-negative) and for OC. Using data from 15 252 female BRCA1 and 8211 BRCA2 carriers, the association of each PRS with BC or OC risk was evaluated using a weighted cohort approach, with time to diagnosis as the outcome and estimation of the hazard ratios (HRs) per standard deviation increase in the PRS. Results: The PRS for ER-negative BC displayed the strongest association with BC risk in BRCA1 carriers (HR = 1.27, 95% confidence interval [CI] = 1.23 to 1.31, P = 8.2 x 10(53)). In BRCA2 carriers, the strongest association with BC risk was seen for the overall BC PRS (HR = 1.22, 95% CI = 1.17 to 1.28, P = 7.2 x 10(-20)). The OC PRS was strongly associated with OC risk for both BRCA1 and BRCA2 carriers. These translate to differences in absolute risks (more than 10% in each case) between the top and bottom deciles of the PRS distribution; for example, the OC risk was 6% by age 80 years for BRCA2 carriers at the 10th percentile of the OC PRS compared with 19% risk for those at the 90th percentile of PRS. Conclusions: BC and OC PRS are predictive of cancer risk in BRCA1 and BRCA2 carriers. Incorporation of the PRS into risk prediction models has promise to better inform decisions on cancer risk management

    Systems Biology Markup Language (SBML): Language Specification for Level 3 Version 2 Core Release 2

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    Computational models can help researchers to interpret data, understand biological functions, and make quantitative predictions. The Systems Biology Markup Language (SBML) is a file format for representing computational models in a declarative form that different software systems can exchange. SBML is oriented towards describing biological processes of the sort common in research on a number of topics, including metabolic pathways, cell signaling pathways, and many others. By supporting SBML as an input/output format, different tools can all operate on an identical representation of a model, removing opportunities for translation errors and assuring a common starting point for analyses and simulations. This document provides the specification for Release 2 of Version 2 of SBML Level 3 Core. The specification defines the data structures prescribed by SBML as well as their encoding in XML, the eXtensible Markup Language. Release 2 corrects some errors and clarifies some ambiguities discovered in Release 1. This specification also defines validation rules that determine the validity of an SBML document, and provides many examples of models in SBML form. Other materials and software are available from the SBML project website at http://sbml.org/
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