Article: Global gene expression profiling of human osteosarcomas reveals metastasis-associated chemokine pattern.Heidi M Namløs, Stine H Kresse, Christoph R Müller, Jørn Henriksen, Rita Holdhus, Gunnar Sæter, Oyvind S Bruland, Bodil Bjerkehagen, Vidar M Steen, Ola Myklebost[show abstract] [hide abstract]
ABSTRACT: Global gene expression analysis was performed on a panel of 23 osteosarcoma samples of primary and metastatic origin using the Applied Biosystems Gene Expression Array System. When comparing the primary tumours with the metastases, we found a significantly increased expression of genes involved in immunological processes, for example coding for cytokines and chemokines, in the metastatic samples. In addition, a comparison of the gene expression in primary samples from patients with or without metastases demonstrated that patients who later developed metastases had high expression of the chemokine (C-X-C motif) receptor 4 (CXCR4), similar to the metastatic samples, suggesting that these signal molecules play an important role in promoting metastasis. Increased knowledge of mechanisms and interactions between specified molecular signalling pathways in osteosarcomas could lead to a more rational strategy for development of targeted therapy.Sarcoma 01/2012; 2012:639038.
Article: mRNA expression profiles of primary high-grade central osteosarcoma are preserved in cell lines and xenografts.Marieke L Kuijjer, Heidi M Namløs, Esther I Hauben, Isidro Machado, Stine H Kresse, Massimo Serra, Antonio Llombart-Bosch, Pancras C W Hogendoorn, Leonardo A Meza-Zepeda, Ola Myklebost, Anne-Marie Cleton-Jansen[show abstract] [hide abstract]
ABSTRACT: Conventional high-grade osteosarcoma is a primary malignant bone tumor, which is most prevalent in adolescence. Survival rates of osteosarcoma patients have not improved significantly in the last 25 years. Aiming to increase this survival rate, a variety of model systems are used to study osteosarcomagenesis and to test new therapeutic agents. Such model systems are typically generated from an osteosarcoma primary tumor, but undergo many changes due to culturing or interactions with a different host species, which may result in differences in gene expression between primary tumor cells, and tumor cells from the model system. We aimed to investigate whether gene expression profiles of osteosarcoma cell lines and xenografts are still comparable to those of the primary tumor. We performed genome-wide mRNA expression profiling on osteosarcoma biopsies (n = 76), cell lines (n = 13), and xenografts (n = 18). Osteosarcoma can be subdivided into several histological subtypes, of which osteoblastic, chondroblastic, and fibroblastic osteosarcoma are the most frequent ones. Using nearest shrunken centroids classification, we generated an expression signature that can predict the histological subtype of osteosarcoma biopsies. The expression signature, which consisted of 24 probes encoding for 22 genes, predicted the histological subtype of osteosarcoma biopsies with a misclassification error of 15%. Histological subtypes of the two osteosarcoma model systems, i.e. osteosarcoma cell lines and xenografts, were predicted with similar misclassification error rates (15% and 11%, respectively). Based on the preservation of mRNA expression profiles that are characteristic for the histological subtype we propose that these model systems are representative for the primary tumor from which they are derived.BMC Medical Genomics 09/2011; 4:66. · 3.69 Impact Factor
Article: Adipocyte differentiation of human bone marrow-derived stromal cells is modulated by microRNA-155, microRNA-221, and microRNA-222.[show abstract] [hide abstract]
ABSTRACT: Human mesenchymal stromal cells (hMSCs) are capable of limited self-renewal and multilineage differentiation in vitro. Several studies have demonstrated that microRNAs (miRNAs, miRs), post-transcriptional modifiers of mRNA stability and protein translation, play crucial roles in the regulation of these complex processes. To gain knowledge regarding the role of miRNAs in human adipocyte differentiation, we examined the miRNA expression profile of the immortalized human bone marrow-derived stromal cell line hMSC-Tert20. Such a model system has the advantage of a reproducible and consistent phenotype while maintaining important properties of the primary donor cells, including the potential to differentiate to adipocytes, osteoblasts, and chondrocytes. We identified 12 miRNAs that were differentially expressed during adipogenesis, of which several have been previously shown to play important roles in adipocyte biology. Among these, the expression of miRNA-155, miRNA-221, and miRNA-222 decreased during the adipogenic program of both immortalized and primary hMSCs, suggesting that they act as negative regulators of differentiation. Interestingly, ectopic expression of the miRNAs significantly inhibited adipogenesis and repressed induction of the master regulators PPARγ and CCAAT/enhancer-binding protein alpha. Our study provides the first experimental evidence that miRNA-155, miRNA-221, and miRNA-222 have an important function in human adipocyte differentiation, and that their downregulation is necessary to relieve the repression of genes crucial for this process.Stem cells and development 08/2011; 21(6):873-83. · 4.15 Impact Factor
Eva W Stratford, Russell Castro, Anna Wennerstrom, Ruth Holm, Else Munthe, Silje Lauvrak, Bodil Bjerkehagen, Ola Myklebost[show abstract] [hide abstract]
ABSTRACT: Aldehyde dehydrogenase (ALDH) has recently been shown to be a marker of cancer stem-like cells (CSCs) across tumour types. The primary goals of this study were to investigate whether ALDH is expressed in liposarcomas, and whether CSCs can be identified in the ALDHhigh subpopulation. We have demonstrated that ALDH is indeed expressed in 10 out of 10 liposarcoma patient samples. Using a liposarcoma xenograft model, we have identified a small population of cells with an inducible stem cell potential, expressing both ALDH and CD133 following culturing in stem cell medium. This potential CSC population, which makes up for 0,1-1,7 % of the cells, displayed increased self-renewing abilities and increased tumourigenicity, giving tumours in vivo from as few as 100 injected cells.Clinical sarcoma research. 08/2011; 1(1):8.
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ABSTRACT: Human tumors transplanted into immunodeficient mice (xenografts) are good preclinical models, and it is important to identify possible systematic changes during establishment and passaging in mice. High-resolution microarray-based comparative genomic hybridization (array CGH) was used to investigate how well a series of sarcoma xenografts, including 9 patient/xenograft pairs and 8 early versus late xenograft passage pairs, represented the patient tumor from which they originated. In all analyses, the xenografts were more similar to their tumor of origin than other xenografts of the same type. Most changes in aberration patterns were toward a more normal genome complement, and the increased aberrations observed were mostly toward more loss. In general, the changes were scattered over the genome, but some changes were significant in osteosarcomas. These were rather focused and consistent with amplifications frequent in patient samples, involving the genes platelet-derived growth factor receptor A (PDGFRA), cysteine-rich hydrophobic domain 2 (CHIC2), FIP-like 1 (FIP1L1), ligand of numb-protein X1 (LNX1), RAS-like family 11 member B (RASL11B), and sec1 family domain containing 2 (SCFD2), probably a sign of continued tumor progression. Some changes that disappeared may have been involved in host-stroma interactions or chemotherapy resistance, possibly because of the absence of selection in the mouse. Direct xenografts reflected well the genomic patterns of their tumors of origin. The few significant aberrations that were lost during passaging in immune-defective mice may have been caused by the lack of selection in the new host, whereas aberrations that were gained appeared to be the result of general tumor progression rather than model-specific artifacts.Cancer 06/2011; 118(2):558-70. · 4.77 Impact Factor