Gene expression data of primary Osteosarcomas
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE87437 | GEO | 2017/02/09
SECONDARY ACCESSION(S): PRJNA344767
REPOSITORIES: GEO
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Project description:To explore whether KSHV infection is a risk factor for osteosarcoma development in ethnic Uyghur population. Sarcoma specimens including tumor, adjacent normal tissues and paired blood samples were obtained from several osteosarcoma patients of Xinjiang China. Then, osteosarcoma clinical samples were subjected to analysis for the presence of the KSHV genome and proteins. Gene expression profiles of these osteosarcomas were analyzed to reveal the pathogenesis of KSHV-positive and -negative osteosarcomas.
2019-09-01 | GSE126209 | GEO
Project description:The aim of this study was to identify molecular markers able to classify osteosarcoma patients as good or poor responders before therapy. Methods: Gene expression profiling of 20 non-metastatic high-grade osteosarcoma patients was performed using cDNA nylon microarray which contained 8,032 unique sequenced-verified cDNA clones, representing 5,776 distinct genes. Expression of selected genes was validated using RTQ-PCR. For correlated genes, corresponding proteins were explored. Immunohistochemistry (IHC) on sections of tissue microarrays (TMA) were performed on a cohort of 50 patients, out of which 30 were new patients. Furthermore, fluorescent in situ hybridization (FISH) was performed on gene which could not be tested using IHC. Results: We have found that HSD17B10 gene expression was upregulated in the group of poor responders and that IHC expression of HSD17B10 in biopsy done before treatment was correlated to response to chemotherapy in 50 patients. Other relevant results include correlation of IFITM2, IFITM3 and RPL8 gene expression to response to chemotherapy. RPL8 gene expression also had a prognostic value for event-free survival. Moreover, a significant statistical correlation was found between polysomy 8 of RPL8 and good response to chemotherapy. Conclusion: These data suggest that HSD17B10 gene may be a biological marker and a therapeutic target in conventional osteosarcoma. This study highlights the prognostic and the predictive value of RPL8. RPL8 and IFITM2 may be useful in the assessment of patients with osteosarcoma at diagnosis and for stratifying patients taking part in randomized trials. Keywords: Gene-expression profiling Gene expression profiling of 20 non-metastatic high-grade osteosarcoma patients was performed using spotted cDNA nylon membrane
2010-02-14 | E-GEOD-11127 | biostudies-arrayexpress
Project description: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, e.g. coding for cytokines and chemokines, in the metastatic samples, suggesting that these signal molecules play an important role in promoting metastasis. 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. 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. Total RNA was isolated from tumor tissue of osteosarcoma patients. Gene expression patterns of metastatic versus primary samples were compared, as well as primary samples from patients who did or did not later develop metastases.
2012-01-01 | E-GEOD-32981 | biostudies-arrayexpress
Project description: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, e.g. coding for cytokines and chemokines, in the metastatic samples, suggesting that these signal molecules play an important role in promoting metastasis. 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. 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.
2012-01-01 | GSE32981 | GEO
Project description:The aim of this study was to identify molecular markers able to classify osteosarcoma patients as good or poor responders before therapy. Methods: Gene expression profiling of 20 non-metastatic high-grade osteosarcoma patients was performed using cDNA nylon microarray which contained 8,032 unique sequenced-verified cDNA clones, representing 5,776 distinct genes. Expression of selected genes was validated using RTQ-PCR. For correlated genes, corresponding proteins were explored. Immunohistochemistry (IHC) on sections of tissue microarrays (TMA) were performed on a cohort of 50 patients, out of which 30 were new patients. Furthermore, fluorescent in situ hybridization (FISH) was performed on gene which could not be tested using IHC. Results: We have found that HSD17B10 gene expression was upregulated in the group of poor responders and that IHC expression of HSD17B10 in biopsy done before treatment was correlated to response to chemotherapy in 50 patients. Other relevant results include correlation of IFITM2, IFITM3 and RPL8 gene expression to response to chemotherapy. RPL8 gene expression also had a prognostic value for event-free survival. Moreover, a significant statistical correlation was found between polysomy 8 of RPL8 and good response to chemotherapy. Conclusion: These data suggest that HSD17B10 gene may be a biological marker and a therapeutic target in conventional osteosarcoma. This study highlights the prognostic and the predictive value of RPL8. RPL8 and IFITM2 may be useful in the assessment of patients with osteosarcoma at diagnosis and for stratifying patients taking part in randomized trials. Keywords: Gene-expression profiling
2010-02-15 | GSE11127 | GEO
Project description:DNA microarrays were used to define the transcriptional profiles of tumor samples to compare 12 high-grade pediatric osteosarcoma tumor samples on their ALT and ATRX status.
2022-07-12 | E-MTAB-11743 | biostudies-arrayexpress
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: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
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 DNA methylation patterns in 19 osteosarcoma cell lines and 6 normal samples (osteoblasts and bones)
2012-12-06 | E-GEOD-36002 | 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 DNA copy number changes in 19 osteosarcoma cell lines
2012-12-06 | E-GEOD-36003 | biostudies-arrayexpress