Heidi M. Namløs

Modulation of the Osteosarcoma Expression Phenotype by MicroRNAs

Background Osteosarcomas are the most common primary malignant tumors of bone and show multiple and complex genomic aberrations. miRNAs are non-coding RNAs capable of regulating gene expression at the post transcriptional level, and miRNAs and their target genes may represent novel therapeutic targets or biomarkers for osteosarcoma. In order to investigate the involvement of miRNAs in osteosarcoma development, global microarray analyses of a panel of 19 human osteosarcoma cell lines was performed. Principal findings We identified 177 miRNAs that were differentially expressed in osteosarcoma cell lines relative to normal bone. Among these, miR-126/miR-126*, miR-142-3p, miR-150, miR-223, miR-486-5p and members of the miR-1/miR-133a, miR-144/miR-451, miR-195/miR-497 and miR-206/miR-133b clusters were found to be downregulated in osteosarcoma cell lines. All miRNAs in the paralogous clusters miR-17-92, miR-106b-25 and miR-106a-92 were overexpressed. Furthermore, the upregulated miRNAs included miR-9/miR-9*, miR-21*, miR-31/miR-31*, miR-196a/miR-196b, miR-374a and members of the miR-29 and miR-130/301 families. The most interesting inversely correlated miRNA/mRNA pairs in osteosarcoma cell lines included miR-9/TGFBR2 and miR-29/p85α regulatory subunit of PI3K. PTEN mRNA correlated inversely with miR-92a and members of the miR-17 and miR-130/301 families. Expression profiles of selected miRNAs were confirmed in clinical samples. A set of miRNAs, miR-1, miR-18a, miR-18b, miR-19b, miR-31, miR-126, miR-142-3p, miR-133b, miR-144, miR-195, miR-223, miR-451 and miR-497 was identified with an intermediate expression level in osteosarcoma clinical samples compared to osteoblasts and bone, which may reflect the differentiation level of osteosarcoma relative to the undifferentiated osteoblast and fully differentiated normal bone. Significance: This study provides an integrated analysis of miRNA and mRNA in osteosarcoma, and gives new insight into the complex genetic mechanisms of osteosarcoma development and progression.

Diagnostic and prognostic gene expression signatures in 177 soft tissue sarcomas: hypoxia-induced transcription profile signifies metastatic potential

BackgroundSoft tissue sarcoma (STS) diagnosis is challenging because of a multitude of histopathological subtypes, different genetic characteristics, and frequent intratumoral pleomorphism. One-third of STS metastasize and current risk-stratification is suboptimal, therefore, novel diagnostic and prognostic markers would be clinically valuable. We assessed the diagnostic and prognostic value of array-based gene expression profiles using 27 k cDNA microarrays in 177, mainly high-grade, STS of 13 histopathological subtypes.ResultsUnsupervised analysis resulted in two major clusters – one mainly containing STS characterized by type-specific genetic alterations and the other with a predominance of genetically complex and pleomorphic STS. Synovial sarcomas, myxoid/round-cell liposarcomas, and gastrointestinal stromal tumors clustered tightly within the former cluster and discriminatory signatures for these were characterized by developmental genes from the EGFR, FGFR, Wnt, Notch, Hedgehog, RAR and KIT signaling pathways. The more pleomorphic STS subtypes, e.g. leiomyosarcoma, malignant fibrous histiocytoma/undifferentiated pleomorphic sarcoma and dedifferentiated/pleomorphic liposarcoma, were part of the latter cluster and were characterized by relatively heterogeneous profiles, although subclusters herein were identified. A prognostic signature partly characterized by hypoxia-related genes was identified among 89 genetically complex pleomorphic primary STS and could, in a multivariate analysis including established prognostic markers, independently predict the risk of metastasis with a hazard ratio of 2.2 (P = 0.04).ConclusionDiagnostic gene expression profiles linking signaling pathways to the different STS subtypes were demonstrated and a hypoxia-induced metastatic profile was identified in the pleomorphic, high-grade STS. These findings verify diagnostic utility and application of expression data for improved selection of high-risk STS patients.

Array Comparative Genomic Hybridization Reveals Distinct DNA Copy Number Differences between Gastrointestinal Stromal Tumors and Leiomyosarcomas

Leiomyosarcomas are spindle cell tumors showing smooth muscle differentiation. Until recently, most gastrointestinal stromal tumors (GIST) were also classified as smooth muscle tumors, but now GISTs are recognized as a separate entity, defined as spindle cell and/or epithelioid tumors localized in the gastrointestinal tract. Using microarray-based comparative genomic hybridization (array CGH), we have created a detailed map of DNA copy number changes for 7 GISTs and 12 leiomyosarcomas. Considerable gains and losses of chromosomal segments were observed in both tumor types. The most frequent aberration observed in GISTs was loss of chromosomes 14 and 22, with minimal recurrent regions in 14q11.2-q32.33 (71% of the tumors) and 22q12.2-q13.31 (100%). In leiomyosarcomas, frequent loss of chromosome 10 and 13q was observed, with minimal recurrent regions in 10q21.3 (75%) and 13q14.2-q14.3 (75%). Recurrent high-level amplification of 17p13.1-p11.2 was detected in leiomyosarcomas. Expression profiling using cDNA microarrays revealed four candidate genes in this region with high expression (AURKB, SREBF1, MFAP4, and FLJ10847). Altered expression of AURKB and SREBF1 has been observed previously in other malignancies. Hierarchical clustering of all samples separated GISTs and leiomyosarcomas into two distinct clusters. Statistical analysis identified six chromosomal regions, 1p36.11-p13.1, 9q21.11-9q34.3, 14q11.2-q23.2, 14q31.3-q32.33, 15q24.3-q26.3, and 22q11.21-q13.31, which were significantly different in copy number between GISTs and leiomyosarcomas. Our results show the potential of using array comparative genomic hybridization to classify histologically similar tumors such as GISTs and leiomyosarcomas.

Functional characterisation of osteosarcoma cell lines and identification of mRNAs and miRNAs associated with aggressive cancer phenotypes

Background:Osteosarcoma is the most common primary malignant bone tumour, predominantly affecting children and adolescents. Cancer cell line models are required to understand the underlying mechanisms of tumour progression and for preclinical investigations.Methods:To identify cell lines that are well suited for studies of critical cancer-related phenotypes, such as tumour initiation, growth and metastasis, we have evaluated 22 osteosarcoma cell lines for in vivo tumorigenicity, in vitro colony-forming ability, invasive/migratory potential and proliferation capacity. Importantly, we have also identified mRNA and microRNA (miRNA) gene expression patterns associated with these phenotypes by expression profiling.Results:The cell lines exhibited a wide range of cancer-related phenotypes, from rather indolent to very aggressive. Several mRNAs were differentially expressed in highly aggressive osteosarcoma cell lines compared with non-aggressive cell lines, including RUNX2, several S100 genes, collagen genes and genes encoding proteins involved in growth factor binding, cell adhesion and extracellular matrix remodelling. Most notably, four genes—COL1A2, KYNU, ACTG2 and NPPB—were differentially expressed in high and non-aggressive cell lines for all the cancer-related phenotypes investigated, suggesting that they might have important roles in the process of osteosarcoma tumorigenesis. At the miRNA level, miR-199b-5p and mir-100-3p were downregulated in the highly aggressive cell lines, whereas miR-155-5p, miR-135b-5p and miR-146a-5p were upregulated. miR-135b-5p and miR-146a-5p were further predicted to be linked to the metastatic capacity of the disease.Interpretation:The detailed characterisation of cell line phenotypes will support the selection of models to use for specific preclinical investigations. The differentially expressed mRNAs and miRNAs identified in this study may represent good candidates for future therapeutic targets. To our knowledge, this is the first time that expression profiles are associated with functional characteristics of osteosarcoma cell lines.

Adipocyte differentiation of human bone marrow-derived stromal cells is modulated by MicroRNA-155, MicroRNA-221, and MicroRNA-222

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.

Integrative analysis reveals relationships of genetic and epigenetic alterations in osteosarcoma.

Background Osteosarcomas are the most common non-haematological primary malignant tumours of bone, and all conventional osteosarcomas are high-grade tumours showing complex genomic aberrations. We have integrated genome-wide genetic and epigenetic profiles from the EuroBoNeT panel of 19 human osteosarcoma cell lines based on microarray technologies. Principal Findings The cell lines showed complex patterns of DNA copy number changes, where genomic copy number gains were significantly associated with gene-rich regions and losses with gene-poor regions. By integrating the datasets, 350 genes were identified as having two types of aberrations (gain/over-expression, hypo-methylation/over-expression, loss/under-expression or hyper-methylation/under-expression) using a recurrence threshold of 6/19 (>30%) cell lines. The genes showed in general alterations in either DNA copy number or DNA methylation, both within individual samples and across the sample panel. These 350 genes are involved in embryonic skeletal system development and morphogenesis, as well as remodelling of extracellular matrix. The aberrations of three selected genes, CXCL5, DLX5 and RUNX2, were validated in five cell lines and five tumour samples using PCR techniques. Several genes were hyper-methylated and under-expressed compared to normal osteoblasts, and expression could be reactivated by demethylation using 5-Aza-2′-deoxycytidine treatment for four genes tested; AKAP12, CXCL5, EFEMP1 and IL11RA. Globally, there was as expected a significant positive association between gain and over-expression, loss and under-expression as well as hyper-methylation and under-expression, but gain was also associated with hyper-methylation and under-expression, suggesting that hyper-methylation may oppose the effects of increased copy number for detrimental genes. Conclusions Integrative analysis of genome-wide genetic and epigenetic alterations identified dependencies and relationships between DNA copy number, DNA methylation and mRNA expression in osteosarcomas, contributing to better understanding of osteosarcoma biology.

DNA copy number changes in high-grade malignant peripheral nerve sheath tumors by array CGH

BackgroundMalignant peripheral nerve sheath tumors (MPNSTs) are rare and highly aggressive soft tissue tumors showing complex chromosomal aberrations. In order to identify recurrent chromosomal regions of gain and loss, and thereby novel gene targets of potential importance for MPNST development and/or progression, we have analyzed DNA copy number changes in seven high-grade MPNSTs using microarray-based comparative genomic hybridization (array CGH).ResultsConsiderable more gains than losses were observed, and the most frequent minimal recurrent regions of gain included 1q24.1-q24.2, 1q24.3-q25.1, 8p23.1-p12, 9q34.11-q34.13 and 17q23.2-q25.3, all gained in five of seven samples. The 17q23.2-q25.3 region was gained in all five patients with poor outcome and not in the two patients with disease-free survival. cDNA microarray analysis and quantitative real-time reverse transcription PCR were used to investigate expression of genes located within these regions. The gene lysyl oxidase-like 2 (LOXL2) was identified as a candidate target for the 8p23.1-p12 gain. Within 17q, the genes topoisomerase II-α (TOP2A), ets variant gene 4 (E1A enhancer binding protein, E1AF) (ETV4) and baculoviral IAP repeat-containing 5 (survivin) (BIRC5) showed increased expression in all samples compared to two benign tumors. Increased expression of these genes has previously been associated with poor survival in other malignancies, and for TOP2A, in MPNSTs as well. In addition, we have analyzed the expression of five micro RNAs located within the 17q23.2-q25.3 region, but none of them showed high expression levels compared to the benign tumors.ConclusionOur study shows the potential of using DNA copy number changes obtained by array CGH to predict the prognosis of MPNST patients. Although no clear correlations between the expression level and patient outcome were observed, the genes TOP2A, ETV4 and BIRC5 are interesting candidate targets for the 17q gain associated with poor survival.

mRNA expression profiles of primary high-grade central osteosarcoma are preserved in cell lines and xenografts.

BackgroundConventional 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.MethodsWe 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.ResultsThe 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).ConclusionsBased 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.

Global Gene Expression Profiling of Human Osteosarcomas Reveals Metastasis-Associated Chemokine Pattern

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.

Lessons from genetic profiling in soft tissue sarcomas.

Soft tissue sarcomas represent a heterogeneous group of tumors and include over 50 histotypes. Some of these tumor types are characterized by specific chromosomal translocations, whereas other types show complex genetic aberrations. The recent developments within gene expression technologies have now been applied to studies of soft tissue sarcomas (STS) and the first results indicate that genetic signatures are useful for classification and diagnosis. Distinctive expression profiles have been found in e.g. gastrointestinal stromal tumors (GISTs), synovial sarcomas, malignant peripheral nerve sheath tumors (MPNSTs), and in subsets of liposarcomas. The more pleomorphic tumor types, such as high-grade variants of leiomyosarcomas, malignant fibrous histiocytomas (MFHs), fibrosarcomas, and subtypes of liposarcomas, show a greater variability among the expression profiles, but interestingly subsets with distinctive expression profiles can be identified also among these tumors. The data available place many of the genes hypothesized to be involved in the development of a certain type of STS, such as the KIT gene in GIST development, among the top discriminating genes. Thereby expression profiling provides novel insights into the pathogenesis of STS. Although much work remains to be done to validate the data and to define optimal discriminating gene lists, the current lessons from gene expression studies in STS are encouraging and imply that genetic signatures may serve as diagnostic and prognostic markers and may help identify novel therapeutic strategies.