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Int J Oncol. 2012 Jan;40(1):85-92. doi: 10.3892/ijo.2011.1172. Epub 2011 Aug 19.

Identification of genes involved in radioresistance of nasopharyngeal carcinoma by integrating gene ontology and protein-protein interaction networks.

Author information

1
Department of Radiation Oncology, Cancer Hospital of Guangxi Medical University, Cancer Institute of Guangxi Zhuang Autonomous Region, Nanning 530021, P.R. China.

Abstract

Radioresistance remains one of the important factors in relapse and metastasis of nasopharyngeal carcinoma. Thus, it is imperative to identify genes involved in radioresistance and explore the underlying biological processes in the development of radioresistance. In this study, we used cDNA microarrays to select differential genes between radioresistant CNE-2R and parental CNE-2 cell lines. One hundred and eighty-three significantly differentially expressed genes (p<0.05) were identified, of which 138 genes were upregulated and 45 genes were downregulated in CNE-2R. We further employed publicly available bioinformatics related software, such as GOEAST and STRING to examine the relationship among differentially expressed genes. The results show that these genes were involved in type I interferon-mediated signaling pathway biological processes; the nodes tended to have high connectivity with the EGFR pathway, IFN-related pathways, NF-κB. The node STAT1 has high connectivity with other nodes in the protein-protein interaction (PPI) networks. Finally, the reliability of microarray data was validated for selected genes by semi-quantitative RT-PCR and Western blotting. The results were consistent with the microarray data. Our study suggests that microarrays combined with gene ontology and protein interaction networks have great value in the identification of genes of radioresistance in nasopharyngeal carcinoma; genes involved in several biological processes and protein interaction networks may be relevant to NPC radioresistance; in particular, the verified genes CCL5, STAT1-α, STAT2 and GSTP1 may become potential biomarkers for predicting NPC response to radiotherapy.

PMID:
21874234
DOI:
10.3892/ijo.2011.1172
[Indexed for MEDLINE]

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