Genome-wide gene expression analysis of high-grade osteosarcoma
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ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Marieke Kuijjer
PROVIDER: E-GEOD-33382 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
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Project description: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 into 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. 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 have generated an expression profile that can predict these histological subtypes in both osteosarcoma biopsies (n=66), as well as in two osteosarcoma model systems, i.e. osteosarcoma cell lines (n=13) and xenografts (n=18). Based on the preservation of mRNA expression profiles that are characteristic for the histological subtype we propose that these model systems are representative to the primary tumor from which they are derived. Genome-wide expression profiling was performed on pre-treatment diagnostic biopsies of 76 resectable high-grade osteosarcoma patients from the EuroBoNet consortium (www.eurobonet.eu). Samples with a main histological subtype (n=66) were selected for subsequent subtype analyses. Out of the EuroBoNeT panel of 19 cell lines, 13 cell lines were recorded to belong to a main histological subtype. This set of 13 cell lines contained 4 cell lines derived from fibroblastic, and 9 cell lines derived from osteoblastic osteosarcomas. The 13 osteosarcoma cell lines IOR/MOS, IOR/OS10, IOR/OS14, IOR/OS15, IOR/OS18, IOR/OS9, IOR/SARG, KPD, MG-63, MHM, OHS, OSA, and ZK-58 were maintained in RPMI 1640 (Invitrogen, Carlsbad, CA, USA) supplemented with 10% fetal calf serum and 1% Penicillin/Streptomycin (Invitrogen) as previously described (PMID: 19787792). The osteosarcoma xenograft model is described in Kresse et al. (PMID: 21713766) In short, human tumors were implanted directly from patient samples and successively passaged subcutaneously in nude mice. Eighteen different xenografts were used, of which 3 were derived from chondroblastic, and 15 from osteoblastic osteosarcomas. Osteosarcoma and xenograft tissue was handled as previously described in Buddingh, Kuijjer et al. (PMID: 21372215) Osteosarcoma cell lines were prepared as in Ottaviano et al. (PMID: 19787792) RNA isolation, synthesis of cDNA, cRNA amplification, and hybridization of cRNA onto the Illumina Human-6 v2.0 Expression BeadChips were performed as described in Buddingh, Kuijjer, et al. (PMID: 21372215) Microarray data processing and quality control were performed using the statistical language R as described in Buddingh, Kuijjer, et al. (PMID: 21372215) We performed a factorial LIMMA analysis comparing 50 osteoblastic, 9 chondroblastic, and 7 fibroblastic osteosarcomas pre-chemotherapy biopsies. Probes with Benjamini and Hochberg False discovery rate-adjusted P-values < 0.05 were considered to be significantly differentially expressed. The gene expression profile was generated on the dataset of biopsies using Bioconductor package PAMR. Internal cross-validation was performed 50 times. A threshold was selected where the error rate of the prediction profile was minimal. The minimum error rate was representative of 50 independent simulations. In order to minimize optimization bias, we validated the profile on an independent dataset of osteosarcoma biopsies (n=5), containing 1 chondroblastic osteosarcoma and 4 osteoblastic osteosarcomas. We subsequently applied the validated prediction profile to two independent datasets, the first consisting of gene expression data of osteosarcoma cell lines, the second of xenografts. Expression of the probes that composed the prediction profile was verified using a factorial LIMMA analysis, comparing chondroblastic, fibroblastic, and osteoblastic osteosarcoma biopsy samples.
2011-09-20 | E-GEOD-30699 | biostudies-arrayexpress
Project description:High-grade osteosarcoma is a tumor with a complex genomic profile, occurring primarily in adolescents with a second peak at middle age. The extensive genomic alterations obscure the identification of genes driving tumorigenesis during osteosarcoma development. In order to identify such driver genes, we integrated DNA copy number profiles (Affymetrix SNP 6.0) of 32 diagnostic biopsies with 84 expression profiles (Illumina Human-6 v2.0) of high-grade osteosarcoma as compared with its putative progenitor cells, i.e. mesenchymal stem cells (n=12) or osteoblasts (n=3). In addition, we performed paired analyses between copy number and expression profiles of a subset of 29 patients for which both DNA and mRNA profiles were available. Integrative analyses were performed in Nexus Copy Number software and statistical language R. Paired analyses were performed on all probes detecting significantly differentially expressed genes in corresponding LIMMA analyses. For both non-paired and paired analyses, copy number aberration frequency was set to >35%. Non-paired and paired integrative analyses resulted in 45 and 101 genes, respectively, which were present in both analyses using different control sets. Paired analyses detected >90% of all genes found with the corresponding non-paired analyses. Remarkably, approximately twice as many genes as found in the corresponding non-paired analyses were detected. Affected genes were intersected with differentially expressed genes in osteosarcoma cell lines, resulting in 31 new osteosarcoma driver genes. Cell division related genes, such as MCM4 and LATS2, were overrepresented and genomic-instability was predictive for metastasis-free survival, suggesting that deregulation of the cell cycle is a driver of osteosarcomagenesis. This SuperSeries is composed of the following subset Series: GSE28974: Genome-wide gene expression profiling of mesenchymal stem cells GSE33153: Copy number analysis of high-grade osteosarcoma GSE33382: Genome-wide gene expression analysis of high-grade osteosarcoma For data processing, we refer to the individual series. We performed both non-paired and paired integrative analyses on SNP and gene expression data. Non-paired integrative analysis was performed by importing lists of differentially expressed genes into the Copy Number module of Nexus software version 5 (BioDiscovery, CA). Based on the length of the gene list, Nexus software performs a Fisher's exact test in order to determine whether the number of differentially expressed genes in a specific region with a significant copy number alteration is larger than expected by chance. Genes present in such regions of copy number alteration with FDR-adjusted P-values (Q-bounds in Nexus software) < 0.05 were returned from this integrative analysis. Nexus software only reports genes which are both gained and overexpressed, or both deleted and downregulated. For the paired integrative analysis, copy number data of all autosomal overlapping genes between the copy number and gene expression arrays were exported from Nexus software, and converted into a binary file containing all genes with a gain (1) and no gain (0), and a similar binary file for losses. As in the non-paired integrative analysis, we did not apply any restrictions on the size of copy number alterations. Gene expression data of each probe for each sample were normalized against average gene expression of the corresponding probes over all control samples (either expression data from 12 MSCs, or from 3 osteoblasts). This was performed by subtracting the average expression of the control samples from the expression levels of the sample of interest, since these are log-transformed expression values. For both analyses, only genes that were significantly differentially expressed between the 84 osteosarcoma samples and the specific control set were analyzed, in order to make sure that no genes returned from the integrative analysis were not significantly differentially expressed. Subse quently, genes that overlapped between the copy number binary files and that matched the fold change of expression (upregulation for genes with gains, and downregulation for genes with losses) were returned.
2012-03-27 | E-GEOD-33383 | biostudies-arrayexpress
Project description:This SuperSeries is composed of the SubSeries listed below. Refer to individual Series
2012-12-19 | E-GEOD-42352 | biostudies-arrayexpress
Project description:Genome-wide gene expression profiling of mesenchymal stem cells (MSCs). 12 MSC samples were hybridized on Illumina Human-6 v2.0 BeadChips.
2012-03-27 | E-GEOD-28974 | biostudies-arrayexpress
Project description:We performed genome-wide gene expression data of high-grade osteosarcoma cell lines, as well as on mesenchymal stem cells, and osteoblasts, and performed global test analysis in order to determine the most significantly affected KEGG pathways. Genome-wide gene expression analysis was performed on 19 high-grade osteosarcoma cell lines. Significantly differentially expressed genes were determined between osteosarcoma cells and two different sets of control samples - osteoblasts [n=3, GEO accession number GSE33382] and mesenchymal stem cells [n=12, GEO accession number GSE28974]. Global test was applied to the different analyses, in order to determine the most affected signaling pathways in osteosarcoma cells.
2013-06-06 | E-GEOD-42351 | biostudies-arrayexpress
Project description:High-grade osteosarcoma is a malignant primary bone tumor with a peak incidence in puberty. Overall survival of patients with metastatic disease is approximately twenty percent. Mechanisms behind the development of metastases in osteosarcoma are unknown. To identify gene signatures that play a role in metastasis, we performed genome-wide gene expression profiling on pre-chemotherapy biopsies of osteosarcoma patients who developed metastases within 5yrs and patients who did not develop metastases within 5yrs. Pre-chemotherapy biopsies of osteosarcoma patients who developed metastases within 5yrs (n=34) were compared with pre-chemotherapy biopsies of osteosarcoma patients who did not develop metastases within 5yrs (n=19).
2011-02-11 | E-GEOD-21257 | biostudies-arrayexpress
Project description:We performed a microarray experiment to test the hypothesis that pre-labour premature rupture of fetal membranes (PPROM) has a different underlying pathology from spontaneous premature labour with intact membranes (PTL). We thought that the different genetic signature would be detected in the cervical tissue. Our study included cervical biopsies obtained as previously described from women undergoing caesarean section (CS) following PPROM, PTL, term labour (TL) or delivering at term prior to the presentation of labour (Term no labour âTNL). After quality control of the expression arrays, any association between sample covariates was evaluated and no evidence was found of unexpected associations. The differences in expression levels for each statistical comparison were then computed. We identified genes that were differentially expressed with an adjusted pvalue < 0.01 from hypothesis testing together with a fold change >= 2. The strongest effect, i.e. the contrast with the highest number of DEGs, was observed for âTerm labour vs Term not labourâ (1,285 genes) while the contrast with the fewest DEGs was âTerm labour vs Preterm premature rupture of membranesâ (16 genes). A table showing the number of differentially expressed genes, for each comparison, can be found in the Results section of this report. We then examined the number of genes overlapping between the statistical comparisons performed (see section 2.5 of the Results) and found that the contrast âTerm labour vs Term not labourâ had a large number of DEGs in common with the five other contrasts.
2016-12-22 | E-MTAB-5354 | biostudies-arrayexpress
Project description:Expression profiling of papillary carcinoma of the breast and grade- and ER-matched cases of invasive ductal breast cancer To identify differential expression between papillary carcinomas of the breast and grade- and ER-matched invasive ductal breast cancers, we performed expression profiling of 16 cases of papillary carcinomas of the breast and 16 cases of grade- and ER-matched invasive ducatal carcinoma of no special subtype. We further reviewed the papillary carcinomas of the breast and classified them into 3 subtypes, namely, invasive papillary carcinoma, encapsulated papillary carcinoma and solid papillary carcinoma. We also performed a hypothesis-generating comparison of differential expression between the 3 subtypes of papillary carcinoma of the breast. Expression profiling of 16 cases of papillary carcinioma of the brest and 16 cases of invasive ducal carcinomas using the Illumina HT-12 v4 arrays
2014-06-20 | E-GEOD-55639 | biostudies-arrayexpress
Project description:The immune system illustrates the challenges of assigning risk to low dose radiation (LDR) exposure in a population. While high radiation doses clearly suppress immune function, a number of studies have shown that LDR affects immune cell subpopulations in ways that could be beneficial. In the intact organism, defining the consequences of LDR is further complicated by the impact of genetic background, particularly in systems such as the immune system for which both radiosensitivity and genetic effects are profound. We employed a systems genetics approach to test for heritable differences in LDR responses. Mice from 39 BXD recombinant inbred (RI) strains were exposed to 10cGy gamma radiation to determine effects on immune function and oxidative stress 48h after irradiation. LDR significantly enhanced neutrophil phagocytosis in a manner that was independent of genetic background. In contrast, genetic background significantly impacted LDR-induced changes in spleen superoxide dismutase activity. Transcriptome data from spleens of the BXD parental strains highlighted the impact of genetic background on LDR responses and also indicate that genetic variation in radiosensitivity is further unmasked at low radiation doses. Taken together, these data highlight the need to consider genetic variation when assessing LDR outcomes. Adult C57BL/6J and DBA/2J mice (10 weeks old) were exposed to low dose (10cGy) or high dose (1Gy) gamma radiation. Mice were sacrificed 24h after radiation or sham exposure & spleens were harvested for transcriptomic analysis.
2011-04-01 | E-GEOD-21562 | biostudies-arrayexpress
Project description:Osteosarcomas are the most common primary malignant tumours of bone, and almost 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. The cell lines showed complex patterns of DNA copy number changes, where copy number gains were significantly associated with gene-rich regions of the genome and losses with gene-poor areas. Integration of the datasets showed that the mRNA levels were regulated by either alterations in DNA copy number or DNA methylation. Using a recurrence threshold of 6/19 (> 30 %) cell lines, 348 genes were identified as having alterations of two data types (gain or hypo-methylation/over-expression, loss or hyper-methylation/under-expression). These genes are involved in embryonic skeletal system development and morphogenesis, as well as remodelling of extracellular matrix. Several genes were hyper-methylated and under-expressed compared to normal osteoblasts, and expression could be reactivated by demethylation using 5-Aza-2M-bM-^@M-^Y-deoxycytidine treatment for all four genes tested. 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 some genes. Integrative analysis of genome-wide genetic and epigenetic alterations identified mechanistic dependencies and relationships between DNA copy number and DNA methylation in terms of regulating mRNA expression levels in osteosarcomas, contributing to better understanding of osteosarcoma biology. Comparison of gene expression patterns in 19 osteosarcoma cell lines and 6 normal samples (osteoblasts and bones)
2012-12-06 | E-GEOD-36001 | biostudies-arrayexpress