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Article

Molecular dysexpression in gastric cancer revealed by integrated analysis of transcriptome data

  • Authors:
    • Xiaomei Li
    • Weiwei Dong
    • Xueling Qu
    • Huixia Zhao
    • Shuo Wang
    • Yixin Hao
    • Qiuwen Li
    • Jianhua Zhu
    • Min Ye
    • Wenhua Xiao
  • View Affiliations / Copyright

    Affiliations: Department of Oncology, The First Affiliated Hospital of PLA General Hospital, Beijing 100048, P.R. China
  • Pages: 3177-3185
    |
    Published online on: March 3, 2017
       https://doi.org/10.3892/ol.2017.5798
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Abstract

Gastric cancer (GC) is often diagnosed in the advanced stages and is associated with a poor prognosis. Obtaining an in depth understanding of the molecular mechanisms of GC has lagged behind compared with other cancers. This study aimed to identify candidate biomarkers for GC. An integrated analysis of microarray datasets was performed to identify differentially expressed genes (DEGs) between GC and normal tissues. Gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were then performed to identify the functions of the DEGs. Furthermore, a protein-protein interaction (PPI) network of the DEGs was constructed. The expression levels of the DEGs were validated in human GC tissues using reverse transcription‑quantitative polymerase chain reaction (RT‑qPCR). A set of 689 DEGs were identified in GC tissues, as compared with normal tissues, including 202 upregulated DEGs and 487 downregulated DEGs. The KEGG pathway analysis suggested that various pathways may play important roles in the pathology of GC, including pathways related to protein digestion and absorption, extracellular matrix‑receptor interaction, and the metabolism of xenobiotics by cytochrome P450. The PPI network analysis indicated that the significant hub proteins consisted of SPP1, TOP2A and ARPC1B. RT‑qPCR validation indicated that the expression levels of the top 10 most significantly dysexpressed genes were consistent with the illustration of the integrated analysis. The present study yielded a reference list of reliable DEGs, which represents a robust pool of candidates for further evaluation of GC pathogenesis and treatment.
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Copy and paste a formatted citation
Spandidos Publications style
Li X, Dong W, Qu X, Zhao H, Wang S, Hao Y, Li Q, Zhu J, Ye M, Xiao W, Xiao W, et al: Molecular dysexpression in gastric cancer revealed by integrated analysis of transcriptome data. Oncol Lett 13: 3177-3185, 2017.
APA
Li, X., Dong, W., Qu, X., Zhao, H., Wang, S., Hao, Y. ... Xiao, W. (2017). Molecular dysexpression in gastric cancer revealed by integrated analysis of transcriptome data. Oncology Letters, 13, 3177-3185. https://doi.org/10.3892/ol.2017.5798
MLA
Li, X., Dong, W., Qu, X., Zhao, H., Wang, S., Hao, Y., Li, Q., Zhu, J., Ye, M., Xiao, W."Molecular dysexpression in gastric cancer revealed by integrated analysis of transcriptome data". Oncology Letters 13.5 (2017): 3177-3185.
Chicago
Li, X., Dong, W., Qu, X., Zhao, H., Wang, S., Hao, Y., Li, Q., Zhu, J., Ye, M., Xiao, W."Molecular dysexpression in gastric cancer revealed by integrated analysis of transcriptome data". Oncology Letters 13, no. 5 (2017): 3177-3185. https://doi.org/10.3892/ol.2017.5798
Copy and paste a formatted citation
x
Spandidos Publications style
Li X, Dong W, Qu X, Zhao H, Wang S, Hao Y, Li Q, Zhu J, Ye M, Xiao W, Xiao W, et al: Molecular dysexpression in gastric cancer revealed by integrated analysis of transcriptome data. Oncol Lett 13: 3177-3185, 2017.
APA
Li, X., Dong, W., Qu, X., Zhao, H., Wang, S., Hao, Y. ... Xiao, W. (2017). Molecular dysexpression in gastric cancer revealed by integrated analysis of transcriptome data. Oncology Letters, 13, 3177-3185. https://doi.org/10.3892/ol.2017.5798
MLA
Li, X., Dong, W., Qu, X., Zhao, H., Wang, S., Hao, Y., Li, Q., Zhu, J., Ye, M., Xiao, W."Molecular dysexpression in gastric cancer revealed by integrated analysis of transcriptome data". Oncology Letters 13.5 (2017): 3177-3185.
Chicago
Li, X., Dong, W., Qu, X., Zhao, H., Wang, S., Hao, Y., Li, Q., Zhu, J., Ye, M., Xiao, W."Molecular dysexpression in gastric cancer revealed by integrated analysis of transcriptome data". Oncology Letters 13, no. 5 (2017): 3177-3185. https://doi.org/10.3892/ol.2017.5798
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