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pmid:29844831
Identification of key genes and pathways in uterine leiomyosarcoma through bioinformatics analysis.
Yuqin Zang · Lina Gu · Yanfang Zhang · Yingmei Wang · Fengxia Xue
Oncology letters · 2018 doi:10.3892/ol.2018.8503
Paper
complete
Experiment
partial
Data
partial
Analysis
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Execution
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Complete file
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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'. 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