Open Access

Screening for genes and subnetworks associated with pancreatic cancer based on the gene expression profile

  • Authors:
    • Jin Long
    • Zhe Liu
    • Xingda Wu
    • Yuanhong Xu
    • Chunlin Ge
  • View Affiliations

  • Published online on: March 18, 2016     https://doi.org/10.3892/mmr.2016.5007
  • Pages: 3779-3786
  • Copyright: © Long et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

Metrics: Total Views: 0 (Spandidos Publications: | PMC Statistics: )
Total PDF Downloads: 0 (Spandidos Publications: | PMC Statistics: )


Abstract

The present study aimed to screen for potential genes and subnetworks associated with pancreatic cancer (PC) using the gene expression profile. The expression profile GSE 16515 was downloaded from the Gene Expression Omnibus database, which included 36 PC tissue samples and 16 normal samples. Limma package in R language was used to screen differentially expressed genes (DEGs), which were grouped as up‑ and downregulated genes. Then, PFSNet was applied to perform subnetwork analysis for all the DEGs. Moreover, Gene Ontology (GO) and REACTOME pathway enrichment analysis of up‑ and downregulated genes was performed, followed by protein‑protein interaction (PPI) network construction using Search Tool for the Retrieval of Interacting Genes Search Tool for the Retrieval of Interacting Genes. In total, 1,989 DEGs including 1,461 up‑ and 528 downregulated genes were screened out. Subnetworks including pancreatic cancer in PC tissue samples and intercellular adhesion in normal samples were identified, respectively. A total of 8 significant REACTOME pathways for upregulated DEGs, such as hemostasis and cell cycle, mitotic were identified. Moreover, 4 significant REACTOME pathways for downregulated DEGs, including regulation of β‑cell development and transmembrane transport of small molecules were screened out. Additionally, DEGs with high connectivity degrees, such as CCNA2 (cyclin A2) and PBK (PDZ binding kinase), of the module in the protein‑protein interaction network were mainly enriched with cell‑division cycle. CCNA2 and PBK of the module and their relative pathway cell‑division cycle, and two subnetworks (pancreatic cancer and intercellular adhesion subnetworks) may be pivotal for further understanding of the molecular mechanism of PC.
View Figures
View References

Related Articles

Journal Cover

May-2016
Volume 13 Issue 5

Print ISSN: 1791-2997
Online ISSN:1791-3004

Sign up for eToc alerts

Recommend to Library

Copy and paste a formatted citation
x
Spandidos Publications style
Long J, Liu Z, Wu X, Xu Y and Ge C: Screening for genes and subnetworks associated with pancreatic cancer based on the gene expression profile. Mol Med Rep 13: 3779-3786, 2016
APA
Long, J., Liu, Z., Wu, X., Xu, Y., & Ge, C. (2016). Screening for genes and subnetworks associated with pancreatic cancer based on the gene expression profile. Molecular Medicine Reports, 13, 3779-3786. https://doi.org/10.3892/mmr.2016.5007
MLA
Long, J., Liu, Z., Wu, X., Xu, Y., Ge, C."Screening for genes and subnetworks associated with pancreatic cancer based on the gene expression profile". Molecular Medicine Reports 13.5 (2016): 3779-3786.
Chicago
Long, J., Liu, Z., Wu, X., Xu, Y., Ge, C."Screening for genes and subnetworks associated with pancreatic cancer based on the gene expression profile". Molecular Medicine Reports 13, no. 5 (2016): 3779-3786. https://doi.org/10.3892/mmr.2016.5007