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      Integrative Analysis Reveals Relationships of Genetic and Epigenetic Alterations in Osteosarcoma

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          Abstract

          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.

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          Most cited references40

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          The Hox genes and their roles in oncogenesis.

          Hox genes, a highly conserved subgroup of the homeobox superfamily, have crucial roles in development, regulating numerous processes including apoptosis, receptor signalling, differentiation, motility and angiogenesis. Aberrations in Hox gene expression have been reported in abnormal development and malignancy, indicating that altered expression of Hox genes could be important for both oncogenesis and tumour suppression, depending on context. Therefore, Hox gene expression could be important in diagnosis and therapy.
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            Model-based variance-stabilizing transformation for Illumina microarray data

            Variance stabilization is a step in the preprocessing of microarray data that can greatly benefit the performance of subsequent statistical modeling and inference. Due to the often limited number of technical replicates for Affymetrix and cDNA arrays, achieving variance stabilization can be difficult. Although the Illumina microarray platform provides a larger number of technical replicates on each array (usually over 30 randomly distributed beads per probe), these replicates have not been leveraged in the current log2 data transformation process. We devised a variance-stabilizing transformation (VST) method that takes advantage of the technical replicates available on an Illumina microarray. We have compared VST with log2 and Variance-stabilizing normalization (VSN) by using the Kruglyak bead-level data (2006) and Barnes titration data (2005). The results of the Kruglyak data suggest that VST stabilizes variances of bead-replicates within an array. The results of the Barnes data show that VST can improve the detection of differentially expressed genes and reduce false-positive identifications. We conclude that although both VST and VSN are built upon the same model of measurement noise, VST stabilizes the variance better and more efficiently for the Illumina platform by leveraging the availability of a larger number of within-array replicates. The algorithms and Supplementary Data are included in the lumi package of Bioconductor, available at: www.bioconductor.org.
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              Improvement in histologic response but not survival in osteosarcoma patients treated with intensified chemotherapy: a randomized phase III trial of the European Osteosarcoma Intergroup.

              Previous randomized controlled trials that used the two-drug chemotherapy regimen of cisplatin and doxorubicin as the conventional arm showed no evidence of benefit from an increase in the number of agents or the length of treatment. It was then proposed that survival could be improved by increasing the planned dose intensity of cisplatin and doxorubicin. Previously untreated patients with nonmetastatic, high-grade, central osteosarcoma of an extremity were randomly assigned to Regimen-C (conventional treatment with six 3-week cycles of cisplatin [100 mg/m2 by 24-hour infusion] and doxorubicin [25 mg/m2/day by 4-hour infusion for 3 days]) or to Regimen-DI (intensified treatment with identical total doses of cisplatin and doxorubicin, planned as six 2-week cycles supported by granulocyte colony stimulating factor (G-CSF). Surgery was scheduled for week 6 in both arms. Primary and secondary outcome measures were overall and progression-free survival, respectively. Intention-to-treat analyses were performed using standard survival analysis methods. Landmark analyses were performed in patients with known surgical details and centrally reviewed histologic response. All statistical tests were two-sided. Between May 1993 and September 2002, treatment was randomly allocated to 497 eligible patients. Six cycles of chemotherapy were completed by 78% of patients in Regimen-C and 80% of patients in Regimen-DI. The delivered preoperative median dose intensity of cisplatin was 86% in Regimen-C and 111% in Regimen-DI (as the percentage of that planned for the conventional regimen). Postoperative median dose intensity of cisplatin was 82% in Regimen-C and 110% in Regimen-DI (the corresponding figures for doxorubicin dose intensity were similar). Regimen-DI was associated with lower risks of severe leucopenia and neutropenia and higher risks of thrombocytopenia and mucositis. Good histologic response (>90% tumor necrosis) was observed in 36% of Regimen-C patients and 50% of Regimen-DI patients (P = .003, chi2 test). There was no evidence of a difference in overall survival (hazard ratio [HR] = 0.94, 95% CI = 0.71 to 1.24; P = .64) or progression-free survival (HR = 0.98, 95% CI = 0.77 to 1.24; P = .83). Landmark analyses showed similar results. Planned intensification of chemotherapy with cisplatin and doxorubicin increased received dose intensity and resulted in a statistically significant increase in favorable histologic response rate, but not in increased progression-free or overall survival. Our results call into question the use of histologic response as a surrogate outcome measure in trials of this disease.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2012
                7 November 2012
                : 7
                : 11
                : e48262
                Affiliations
                [1 ]Department of Tumour Biology, The Norwegian Radium Hospital, Oslo University Hospital, Oslo, Norway
                [2 ]Department of Informatics, University of Oslo, Oslo, Norway
                [3 ]Norwegian Microarray Consortium, Department of Molecular Biosciences, University of Oslo, Oslo, Norway
                [4 ]Department of Pathology, Leiden University Medical Center, Leiden, The Netherlands
                [5 ]Laboratory of Experimental Oncology, Istituto Ortopedico Rizzoli, Bologna, Italy
                The Chinese University of Hong Kong, Hong Kong
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: SHK OM LAMZ. Performed the experiments: SHK M. Skårn AHBP. Analyzed the data: SHK HR HMN KL EH OM LAMZ. Contributed reagents/materials/analysis tools: M. Serra. Wrote the paper: SHK HR OM LAMZ. Provided mRNA expression data: AMCJ PCWH. Organised the network that facilitated this study: PCWH.

                Article
                PONE-D-12-09542
                10.1371/journal.pone.0048262
                3492335
                23144859
                330462c8-9fd3-499b-a7cb-96ea63bc71fb
                Copyright @ 2012

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 4 April 2012
                : 21 September 2012
                Page count
                Pages: 20
                Funding
                This work was supported by the European Network to Promote Research into Uncommon Cancers in Adults and Children: Pathology, Biology and Genetics of Bone Tumours (EuroBoNeT), the Norwegian Cancer Society (Ragnvarda F. Sørvik and Håkon Starheim’s legacy) and the Norwegian Research Council. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology
                Computational Biology
                Genomics
                Epigenomics
                Genome Expression Analysis
                Microarrays
                Genetics
                Cancer Genetics
                Epigenetics
                Gene Expression
                Genomics
                Medicine
                Oncology
                Cancers and Neoplasms
                Bone and Soft Tissue Sarcomas
                Osteosarcoma
                Basic Cancer Research

                Uncategorized
                Uncategorized

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