Microarray profiling analysis ofcircular RNAs expression in osteosarcoma
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ABSTRACT:
PROVIDER: PRJNA589051 | ENA |
REPOSITORIES: ENA
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Project description:Strategies targeted vascular endothelial growth factor (VEGF)-dependent osteosarcoma progression are limited although important progress has been made in illustrating the mechanisms. Here we identified circ_001621 as one of the significantly upregulated circular RNAs (circRNAs) by circRNAs microarrays. We found that patients with high circ_001621 expression had a shorter survival time. Moreover, we found several potential sponge micro RNAs (miRNA) of circ_001621 with Circular RNA Interactome database. Among the candidate sponge, we elucidated the association of circ_001621 and miR-578. In addition, we demonstrated that miR-578 targeted circ_001621 directly. Functionally, we set up the experimental system to investigate the effects of circ_001621/miR-578/VEGF interaction in vitro and in vivo. Results indicated circ_001621 promoted osteosarcoma proliferation and migration via attenuating the inhibition of cyclin-dependent kinase 4 (CDK4) and matrix metallopeptidase 9 (MMP9) by miR-578, respectively. Nude mice experiment was further performed to estimate the promotion of metastasis by circ_001621. The present study evaluated the mechanisms underlying circ_001621 enhanced osteosarcoma progression and provided novel therapeutic targets for advanced osteosarcoma. Circular RNAs profiling by array
2020-01-14 | GSE140256 | GEO
Project description:Microarray profiling analysis of whole transcriptome expression in osteosarcoma
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Project description:Seven human osteosarcoma cell lines (U2OS, U2OS/MTX300, HOS, MG63, 143B, ZOS, ZOSM) and the human osteoblast hFOB1.19 were included in the study. Microarray based circRNA expression profiles were acquired using the Arraystar Human circRNA Array (8x15K, Arraystar). We identified circRNAs differentially expressed in human osteosarcoma cell lines compared to human osteoblast hFOB1.19 (control).
2017-04-12 | GSE96964 | GEO
Project description:Osteosarcoma (OS)is a rare primary malignant bone tumor in adolescents and children with a poor prognosis. Identification of prognostic genes lags far behind the advance of the treatments. We identified differential genes by microarray analysis from paired OS tissues. Hub genes, gene set enrichment analysis, and pathway analysis were performed to gain an insight into the pathway alterations of OS. These results showed CPE could be served as a prognostic factor in osteoblastic OS and should be further investigated as potential therapeutic target. The present study evaluated the whole transcriptome expression of osteosarcoma progression and provided novel therapeutic targets for advanced osteosarcoma.
2023-03-01 | GSE225588 | GEO
Project description:Microarray profiling analysis of circular RNAs expression in bladder cancer
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Project description:Microarray profiling analysis of circular RNAs expression in bladder cancer [miRNA profiling]
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Project description:Microarray profiling analysis of circular RNAs expression in bladder cancer [lncRNA profiling]
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Project description:Microarray profiling analysis of long non-coding RNAs expression in osteoarthritis
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Project description:Osteosa rcoma is an aggressive malignant neoplasm that exhibits osteoblastic differentiation and produces malignant osteoid. The aim of this study was to find feature genes associated with osteosarcoma and correlative gene functions which can distinguish cancer tissues from non-tumor tissues. Gene expression profile GSE14359 was downloaded from Gene Expression Omnibus (GEO) database, including 10 osteosarcoma samples and 2 normal samples. The differentially expressed genes (DEGs) between osteosarcoma and normal specimens were identified using limma package of R. DAVID was applied to mine osteosarcoma associated genes and analyze the GO enrichment on gene functions and KEGG pathways. Then, corresponding protein-protein interaction (PPI) network of DEGs was constructed based on the data collected from STRING datasets. Principal component of top10 DEGs and PPI network of top 20 DEGs were further analyzed. Finally, transcription factors were predicted by uploading the two groups of DEGs to TfactS database. A total of 437 genes, including 114 up-regulated genes and 323 down-regulated genes, were filtered as DEGs, of which 46 were associated with osteosarcoma by Disease Module. GO and KEGG pathway enrichment analysis showed that genes mainly affected the process of immune response and the development of skeletal and vascular system. The PPI network analysis elucidated that hemoglobin and histocompatibility proteins and enzymes, which were associated with immune response, were closely associated with osteosarcoma. Transcription factors MYC and SP1 were predicted to be significantly related to osteosarcoma. The discovery of gene functions and transcription factors has the potential to use in clinic for diagnosis of osteosarcoma in future. In addition, it will pave the way to studying mechanism and effective therapies for osteosarcoma.
| S-EPMC4565213 | biostudies-literature
Project description:Osteoarthritis (OA) is the most common motor system disease in aging people, characterized by matrix degradation, chondrocyte death, and osteophyte formation. OA etiology is unclear, but long noncoding RNAs (lncRNAs) that participate in numerous pathological and physiological processes may be key regulators in the onset and development of OA. Because profiling of lncRNAs and their biological function in OA is not understood, we measured lncRNA and mRNA expression profiles using high-throughput microarray to study human knee OA. We identified 2,042 lncRNAs and 2,011 mRNAs that were significantly differentially expressed in OA compared to non-OA tissue (>2.0- or <-2.0-fold change; p<0.5), including 1,137 lncRNAs that were upregulated and 905 lncRNAs that were downregulated. Also, 1,386 mRNA were upregulated and 625 mRNAs were downregulated. Gene Ontology analysis and the Kyoto Encyclopedia of Genes and Genomes was used to study the biological function enrichment of differentially expressed mRNA. Additionally, coding-non-coding gene co-expression (CNC) network construction was performed to explore the relevance of dysregulated lncRNAs and mRNAs. Finally, QPCR was used to validate chip results. In general, this study provides a preliminary database for further exploring lncRNA-related mechnisms in OA. OA cartilage were collected from 19 patients undergoing total knee joint replacement due to severe OA, and normal cartilage were collected from 11 patients (trauma, thromboangiities obliterans, or osteosarcoma, or limb amputation) without history of rheumatoid arthritis or OA
2018-05-11 | GSE113825 | GEO