Open Access

Identification of potential therapeutic targets for colorectal cancer by bioinformatics analysis

  • Authors:
    • Ming Yan
    • Maomin Song
    • Rixing Bai
    • Shi Cheng
    • Wenmao Yan
  • View Affiliations

  • Published online on: October 31, 2016     https://doi.org/10.3892/ol.2016.5328
  • Pages: 5092-5098
  • Copyright: © Yan et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

The aim of the present study was to identify potential therapeutic targets for colorectal cancer (CRC). The gene expression profile GSE32323, containing 34 samples, including 17 specimens of CRC tissues and 17 of paired normal tissues from CRC patients, was downloaded from the Gene Expression Omnibus database. Following data preprocessing using the Affy and preprocessCore packages, the differentially‑expressed genes (DEGs) between the two types of samples were identified with the Linear Models for Microarray Analysis package. Next, functional and pathway enrichment analysis of the DEGs was performed using the Database for Annotation Visualization and Integrated Discovery. The protein‑protein interaction (PPI) network was established using the Search Tool for the Retrieval of Interacting Genes database. Utilizing WebGestalt, the potential microRNAs (miRNAs/miRs) of the DEGs were screened and the integrated miRNA‑target network was built. A cohort of 1,347 DEGs was identified, the majority of which were mainly enriched in cell cycle-related biological processes and pathways. Cyclin-dependent kinase 1 (CDK1), cyclin B1 (CCNB1), MAD2 mitotic arrest deficient-like 1 (MAD2L1) and BUB1 mitotic checkpoint serine/threonine kinase B (BUB1B) were prominent in the PPI network, while the over‑represented genes in the integrated miRNA‑target network were SRY (sex determining region Y)-box 4 (SOX4; targeted by hsa-mir-129), v‑myc avian myelocytomatosis viral oncogene homolog (MYC; targeted by hsa‑let‑7c and hsa-mir-145) and cyclin D1 (CCND1; targeted by hsa‑let‑7b). CDK1, CCNB1 and CCND1 were also associated with the p53 signaling pathway. Overall, several genes associated with the cell cycle and p53 pathway were identified as biomarkers for CRC. CDK1, CCNB1, MAD2L1, BUB1B, SOX4, collagen type I α2 chain and MYC may play significant roles in CRC progression by affecting the cell cycle‑related pathways, while CDK1, CCNB1 and CCND1 may serve as crucial regulators in the p53 signaling pathway. Furthermore, SOX4, MYC and CCND1 may be targets of miR‑129, hsa‑mir‑145 and hsa‑let‑7c, respectively. However, further validation of these data is required.
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December-2016
Volume 12 Issue 6

Print ISSN: 1792-1074
Online ISSN:1792-1082

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Spandidos Publications style
Yan M, Song M, Bai R, Cheng S and Yan W: Identification of potential therapeutic targets for colorectal cancer by bioinformatics analysis. Oncol Lett 12: 5092-5098, 2016
APA
Yan, M., Song, M., Bai, R., Cheng, S., & Yan, W. (2016). Identification of potential therapeutic targets for colorectal cancer by bioinformatics analysis. Oncology Letters, 12, 5092-5098. https://doi.org/10.3892/ol.2016.5328
MLA
Yan, M., Song, M., Bai, R., Cheng, S., Yan, W."Identification of potential therapeutic targets for colorectal cancer by bioinformatics analysis". Oncology Letters 12.6 (2016): 5092-5098.
Chicago
Yan, M., Song, M., Bai, R., Cheng, S., Yan, W."Identification of potential therapeutic targets for colorectal cancer by bioinformatics analysis". Oncology Letters 12, no. 6 (2016): 5092-5098. https://doi.org/10.3892/ol.2016.5328