Differentially expressed genes and are potential prognostic biomarkers for gastric cancer.

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ID: 74503
2019
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Abstract
Gastric cancer (GC) is one of the most common malignancies worldwide. To the best of our knowledge, no biomarkers have been widely accepted for the early diagnosis and prognostic prediction of GC. This study aimed to identify potential novel prognostic biomarkers for GC. The dataset GSE29272, which originates from the public database Gene Expression Omnibus, was employed in the present study. The online tool GEO2R was used to calculate the differentially expressed genes (DEGs) in GSE29272 between tumour tissues and adjacent tissues. CytoHubba and MCODE plugins of Cytoscape software were used to obtain hub genes and modules of DEGs. The online tools Database for Annotation, Visualisation and Integrated Discovery and Search Tool for the Retrieval of Interacting Genes were employed to conduct Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes pathway analysis, and to construct protein-protein interaction networks. A total of 117 DEGs were extracted from GSE29272. In addition, 15 hub genes and seven modules were identified in the 117 DEGs. The enrichment analysis revealed that they were mainly enriched in GO biological process and cellular component domains, and the 'ECM-receptor interaction', 'focal adhesion', 'metabolism of xenobiotics by cytochrome P450' and 'drug metabolism' pathways. The hub genes asporin (), collagen type I α1 chain (), fibronectin 1 (), versican () and mucin 5AC () were demonstrated to have prognostic value for patients with GC. The and genes were significantly associated with overall survival and disease-free survival (log-rank P=0.025, 0.038, 0.0014 and 0.015, respectively). and were significantly associated with overall survival (log-rank P=0.013 and 0.05, respectively), and was significantly associated with disease-free survival (log-rank P=0.027). Results from the present study suggested that and may represent novel prognostic biomarkers for GC.
Reference Key
jiang2019differentiallyoncology Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Jiang, Kaiyuan;Liu, Hongmei;Xie, Dongyi;Xiao, Qiang;
Journal oncology letters
Year 2019
DOI
10.3892/ol.2019.9952
URL
Keywords
Biomarker prognosis differentially expressed genes gastric cancer geo database

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