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• W2801263295 abstract "Uterine leiomyosarcoma (uLMS) is a rare but malignant gynaecological tumour with a poor survival outcome. The present study was aimed at identifying the key genes and pathways in the development of uLMS through bioinformatics analysis. To minimize the frequency of false-positive results of the bioinformatics analysis, 3 microarrays including GSE764, GSE64763 and GSE68312 were downloaded from Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) were screened out using the online tool GEO2R. Then, Gene Ontology and Kyoto Encyclopaedia of Genes and Genomes pathway enrichment analyses were performed using the Database for Annotation, Visualization and Integrated Discovery. Finally, a protein-protein interaction (PPI) network of the DEGs was constructed using Cytoscape, and module analysis was conducted using the plug-in MCODE. A total of 95 DEGs including 21 upregulated genes and 74 downregulated genes were identified. The upregulated DEGs were annotated with 'DNA metabolic process', 'nucleobase-containing compound biosynthetic process' and 'cellular macromolecule biosynthetic process', while the downregulated DEGs were annotated with 'cellular response to chemical stimulus', 'movement of cell or subcellular component' and 'response to inorganic substances'. The results of the PPI network analysis demonstrated that matrix metallopeptidase 9, apolipoprotein E, cyclin E1 and syndecan 1 were the predominant upregulated genes in uLMS. Additionally, the genes in the main module were enriched in 'proteoglycans in cancer', 'p53 signalling pathway' and 'extracellular matrix-receptor interaction'. The key genes and pathways identified in the present study may provide valuable clues for clarifying the molecular mechanism underlying the development of uLMS and demonstrate promise for use as diagnostic markers and therapeutic targets." @default.
• W2801263295 created "2018-05-17" @default.
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• W2801263295 date "2018-04-16" @default.
• W2801263295 modified "2023-10-01" @default.
• W2801263295 title "Identification of key genes and pathways in uterine leiomyosarcoma through bioinformatics analysis" @default.
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• W2801263295 doi "https://doi.org/10.3892/ol.2018.8503" @default.
• W2801263295 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/5958873" @default.
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