Human osteosarcoma and adjacent normal tissues
Ontology highlight
ABSTRACT:
INSTRUMENT(S): Q Exactive HF
ORGANISM(S): Homo Sapiens (human)
TISSUE(S): Whole Body
SUBMITTER: 
Lin Qi
LAB HEAD: Lin Qi
PROVIDER: PXD038452 | Pride | 2025-05-13
REPOSITORIES: Pride
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| 1811-.msf | Msf | |||
| 1811-1.raw | Raw | |||
| 1811-10.raw | Raw | |||
| 1811-11.raw | Raw | |||
| 1811-12.raw | Raw |
Items per page: 5 1 - 5 of 16 |
Publications
Integrated multiomic analysis and high-throughput screening reveal potential gene targets and synergetic drug combinations for osteosarcoma therapy.
Zhang Wenchao W Qi Lin L Liu Zhongyue Z He Shasha S Wang Cheng-Zhi CZ Wu Ying Y Han Lianbin L Liu Zhenxin Z Fu Zheng Z Tu Chao C Li Zhihong Z
MedComm 20230712 4
Although great advances have been made over the past decades, therapeutics for osteosarcoma are quite limited. We performed long-read RNA sequencing and tandem mass tag (TMT)-based quantitative proteome on osteosarcoma and the adjacent normal tissues, next-generation sequencing (NGS) on paired osteosarcoma samples before and after neoadjuvant chemotherapy (NACT), and high-throughput drug combination screen on osteosarcoma cell lines. Single-cell RNA sequencing data were analyzed to reveal the he ...[more]
Similar Datasets
Project description:Osteosarcoma is the most common primary bone tumours of dogs. Canine osteosarcoma contains a sub-population of cancer stem cells. Here we used canine-specific microarrays to compare the global gene expression profiles of osteosarcoma stem cells to adherent cancer cells and canine mesenchymal stem cells. Canine osteosarcoma spheres were isolated by their ability to form tumourspheres. Spheres, adherent cells and mesenchymal stem cells were harvested and used for RNA extraction and hybridisation on Affymetrix microarrays (Canine 2.0). Four biological replicates of each sample were included.
2013-11-05 | E-GEOD-52063 | biostudies-arrayexpress
Project description:Osteosarcoma is the most common primary bone cancer in children, adolescents and young adults. It is a rare cancer type. To comprehensively reveal the transcriptomic characteristics of osteosarcoma, we performed Oxford Nanopore Technologies (ONT) long-read RNA-Seq of tumor and adjacent normal tissues from 23 patients with osteosarcoma.
2023-07-19 | GSE218035 | GEO
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: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:In osteosarcoma patients, the development of metastases, often to the lungs, is the most frequent cause of death. To improve this situation, a deeper understanding of the molecular mechanisms governing osteosarcoma development and dissemination and the identification of novel drug targets for an improved treatment are needed. Towards this aim, we characterized osteosarcoma tissue samples compared to primary osteoblast cells using Affymetrix HG U133A microarrays. mRNA from 5 frozen conventional osteosarcoma and 4 osteosarcoma lung metastases tumor samples and mRNA from fresh primary osteoblast cells were extracted and hybridized to HG U133A microarrays.
2010-07-30 | E-GEOD-14359 | biostudies-arrayexpress
Project description:Serum alkaline phosphatase (ALP) concentration is a prognostic factor for osteosarcoma in multiple studies, though its biological significance remains incompletely understood. To determine whether gene expression patterns differed in osteosarcoma from patients with differing serum ALP concentrations, microarray analysis was performed on 18 primary osteosarcoma samples and six osteosarcoma cell lines from dogs with normal and increased serum ALP concentration. No differences in gene expression patterns were noted between tumors or cell lines with differing serum ALP concentration using a gene-specific two-sample t-test. Using a more sensitive empirical Bayes procedure, DCUN1D1 was increased in both the tissue and cell lines of the normal ALP group. Using QPCR, differences in DCUN1D1 expression between the two groups failed to reach significance. The homogeneity of gene expression patterns of osteosarcoma associated differing serum ALP concentrations are consistent with previous studies suggesting serum ALP concentration is not associated with intrinsic differences of osteosarcoma cells. A total of 18 canine primary osteosarcoma tumor samples were used in this study. 9 tumor samples were from patients having a normal serum alkaline phosphatase concentration. 9 tumor samples were from patients having an increased serum alkaline phosphatase concentration. There were no reference tissues or controls used in this study.
2014-11-19 | E-GEOD-63476 | biostudies-arrayexpress
Project description:Osteosarcoma (OS) is the most common primary malignant tumor of bone; it occurs most commonly in the metaphyseal regions of long bones in adolescents and young adults. Conventional osteosarcoma is characterized by complex karyotypes with a high degree of aneuploidy and numerous structural aberrations such as copy number alterations (CNAs) and genomic rearrangements. The data comprise of array copy number data (N=113) from pre-therapeutic osteosarcoma. These have been derived from Affymetrix CytoscanHD. The study searches for driver genes and examines cancer evolution. Note (added 8th June 2016): This experiment is extended in an experiment described under accession E-MTAB-4815. It contains data for 97 samples from this experiment are also included in E-MTAB-4815.
2015-11-09 | E-MTAB-3998 | biostudies-arrayexpress
Project description:Osteosarcoma is the most common malignancy of bone, and occurs most frequently in children and adolescents. Currently, the most reliable technique for prognostication is measuring histopathologic tumor necrosis following preoperative chemotherapy, and favourable prognosis is signified by 90% or greater estimated necrosis of the tumour. Neither genetic testing nor molecular biomarkers have been described for this tumour. We used the novel nanoString mRNA expression analysis system to analyzed total RNA from 35 flash-frozen sporadic paediatric osteosarcoma biopsy and resection specimens to quantify mRNA expression for 17 oncogenes and tumour suppressor genes. Three oncogenes, cell cycle regulator gene CDC5L, the RecQ DNA helicase gene RECQL4, and the cyclin-dependent kinase gene CDK4, were more highly expressed (p<0.05) in tumours which responded poorly to neoadjuvant chemotherapy. A similar trend (p<0.10) was identified for the osteoblast-specific transcription factor gene RUNX2. No statistically significant difference existed in comparing expression of CDC5L, RECQL4, CDK4, and RUNX2 between biopsy and resection samples. Additionally, analysis of expression data in the context of histological subtype yielded preliminary results for deducing molecular subtypes of osteosarcomas. Osteoblastic osteosarcomas possessed higher expression of CDKN1A, PTEN, and RUNX2 relative to their fibroblastic counterparts (p<0.05). This research study shows that CDC5L, RECQL4, and CDK4 tumour expression levels may be useful for identifying patients who may not benefit from the current standardized chemotherapy regimen. Total RNA was isolated from 52 pediatric osteosarcoma samples (prechemotherapy biopsies and resections), 3 osteosarcoma cell lines, and normal human osteoblasts. nanoString mRNA expression analysis was applied to samples split between 3 batches to compare samples based on clinical and pathologic data reports, and to compare samples with normal human osteoblasts. For 43 samples, there were complete data and the RNA was successfully assayed. Analysis was performed using R.
2016-03-15 | E-GEOD-45275 | biostudies-arrayexpress
Project description:Osteosarcoma is the most common primary malignant tumour of bone occurring in children and young adolescents. Osteosarcoma is characterized by considerable phenotypic and genomic heterogeneity, and few recurrent targetable genetic changes have been reported. Osteosarcoma exhibits a complex karyotype with high genomic and chromosomal instability; and harbours multiple rearrangements across the genome, kataegis and chromothripsis as well as epigenetic changes. Here we have performed DNA methylation profiling on 10 osteosarcoma patient samples and four bones using the Infinium HumanMethylation450 BeadChip from Illumina, covering 485,000 CpG sites across the genome.
2022-01-31 | GSE161407 | GEO
Project description:Investigation of whole genome gene expression level changes in human osteosarcoma cell line MNNG/HOS treated by TGF-beta1 for three days (mesophase) and five days (sarcospheres iOSCs), compared to non-treatment cells (residual adherent cells). A three chip study using total RNA cover from three cultures of non-treatment human osteosarcoma cell line MNNG/HOS (residual adherent cells), TGF-beta1 treated three days osteosarcoma cell line MNNG/HOS (mesophase) and TGF-beta1 treated five days osteosarcoma cell line MNNG/HOS ( only collected the suspending sarcospheres iOSCs). Each chip measures the expression level of 45033 genes from osteosarcoma cell line MNNG/HOS.
2012-05-22 | E-GEOD-38133 | biostudies-arrayexpress