Biological analysis of cancer specific microRNAs on function modeling in osteosarcoma

Abstract Osteosarcoma (OS) is the most common bone tumor characterized with a high risk of amputation and malignant morbidity among teenagers and adolescents. However, relevant pathogenic/biological mechanisms underlying OS-genesis remains to be ambiguous. The aim of this study was to elucidate func...

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Auteurs principaux: Hao Wang, Min Tang, Liping Ou, Mengyi Hou, Tianyu Feng, Yu-E Huang, Yaqian Jin, Heng Zhang, Guowei Zuo
Format: article
Langue:EN
Publié: Nature Portfolio 2017
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Accès en ligne:https://doaj.org/article/fc97dee1a04742e09602f6a3be29aeee
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Résumé:Abstract Osteosarcoma (OS) is the most common bone tumor characterized with a high risk of amputation and malignant morbidity among teenagers and adolescents. However, relevant pathogenic/biological mechanisms underlying OS-genesis remains to be ambiguous. The aim of this study was to elucidate functional relationship about microRNAs-mRNAs networks and to identify potential molecular markers via a computational method. Gene expression profile (GSE70415) was recruited from Gene Expression Omnibus. 3856 differentially expressed genes and 250 significantly expressed microRNAs were identified by using GCBI. The results of GO and KEGG pathways associated proteomics analysis indicated that extracellular matrix organization, small molecule metabolic process, cell adhesion (GO IDs: 0030198, 0044281, 0007155) and pathways in cancer, PI3K-Akt signaling pathway, metabolic pathways (pathway IDs: 5200, 4151, 1100) were significantly enriched. In addition, CKMT2, miR-93b-5p, miR-29b-3p were found to be positively/negatively correlated with TP53, EGFR, and MMP members mediated OS development, including angiogenesis, migration and invasion. Further visualization of collective effect of 1181 microRNAs-mRNAs pairs and protein-protein interactions was realized by applying with cytosacpe. In summary, our work provided a better understanding of non-coding regulatory mechanisms of transcriptomics and unraveled essential molecular biomarkers in osteosarcoma.