title: Identification of genes involved in radioresistance of nasopharyngeal             carcinoma by integrating gene ontology and protein-protein interaction networks.
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.
authors.affiliation: Department of Radiation Oncology, Cancer Hospital of Guangxi                     Medical University, Cancer Institute of Guangxi Zhuang Autonomous Region,                     Nanning 530021, P.R. China.
authors.forename: Ya
authors.initials: Y
authors.lastname: Guo
authors.forename: Xiao-Dong
authors.initials: XD
authors.lastname: Zhu
authors.forename: Song
authors.initials: S
authors.lastname: Qu
authors.forename: Ling
authors.initials: L
authors.lastname: Li
authors.forename: Fang
authors.initials: F
authors.lastname: Su
authors.forename: Ye
authors.initials: Y
authors.lastname: Li
authors.forename: Shi-Ting
authors.initials: ST
authors.lastname: Huang
authors.forename: Dan-Rong
authors.initials: DR
authors.lastname: Li
mesh_terms: D015153:Blotting, Western; D002277:Carcinoma; D045744:Cell Line, Tumor; D015972:Gene Expression Regulation, Neoplastic; D006801:Humans; D000077274:Nasopharyngeal Carcinoma; D009303:Nasopharyngeal Neoplasms / Q000235:genetics* / Q000378:metabolism / Q000532:radiotherapy*; D020411:Oligonucleotide Array Sequence Analysis; D060066:Protein Interaction Maps; D012333:RNA, Messenger / Q000235:genetics; D011836:Radiation Tolerance / Q000235:genetics; D020133:Reverse Transcriptase Polymerase Chain Reaction
chemical_list: D012333:RNA, Messenger