| 朱小东,郭亚,曲颂,李龄,黄诗婷,黎丹戎,张玮.应用蛋白质的相互作用网络图筛选鼻咽癌放射抗拒相关基因[J].中华放射医学与防护杂志,2012,32(1):20-24 |
| 应用蛋白质的相互作用网络图筛选鼻咽癌放射抗拒相关基因 |
| Radioresistance related genes screened by protein-protein interaction network analysis in nasopharyngeal carcinoma |
| 投稿时间：2011-03-08 |
| DOI：10.3760/cma.j.issn.0254-5098.2012.01.005 |
| 中文关键词: 鼻咽癌 放射抗拒 基因芯片 蛋白质相互作用网络 |
| 英文关键词:Nasopharyngeal carcinoma Radioresistance Gene chip Protein-protein inter-action network |
| 基金项目:国家自然科学基金(30860329);广西壮族自治区自然科学基金(桂科自0832229);广西大型仪器协作共用网测试补助项目(851-2009-055);广西2010年研究生教育创新计划资助项目(2010105981002M214) |
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| 中文摘要: |
| 目的 应用蛋白质相互作用网络图,寻找鼻咽癌放射抗拒相关的分子标志物,探讨鼻咽癌放射抗拒机制。方法 应用全基因组表达谱芯片,初步筛选出2种不同放射敏感性细胞株CNE-2R与CNE-2的差异表达基因。采用计算机软件随机选取4个差异表达基因,分别设计引物,用半定量RT-PCR技术检测验证。将2次实验中均出现的差异有统计学意义的基因导入SNOW在线数据库进行分析,绘制差异基因相互作用网络图,网络中心节点作为鼻咽癌放射抗拒相关分子标志物;进一步采用Western blot检测关键节点STAT1 在CNE-2R与CNE-2表达差异。结果 CNE-2R与CNE-2相比,2次芯片实验中均出现的差异基因374个,其中差异有统计学意义的基因197个;随机选取的4个差异表达基因RT-PCR结果与芯片扫描结果相似,具有相同的方向性。197个共有的差异有统计学意义的基因编码蛋白经SNOW分析存在相互作用,并构成一个复杂的相互作用网络图,寻找到了关键性的节点为STAT1和JUN。Western blot结果显示,STAT1-α在CNE-2R中表达明显高于CNE-2(t=4.96,P<0.05)。结论 关键性的节点STAT1和JUN 可能是引起鼻咽癌放射抗拒的分子标志物,STAT1-α可能与鼻咽癌放射抗拒发生密切相关。 |
| 英文摘要: |
| Objective To discover radioresistance associated molecular biomarkers and its mechanism in nasopharyngeal carcinoma by protein-protein interaction network analysis. Methods Whole genome expression microarray was applied to screen out differentially expressed genes in two cell lines CNE-2R and CNE-2 with different radiosensitivity. Four differentially expressed genes were randomly selected for further verification by the semi-quantitative RT-PCR analysis with self-designed primers. The common differentially expressed genes from two experiments were analyzed with the SNOW online database in order to find out the central node related to the biomarkers of nasopharyngeal carcinoma radioresistance. The expression of STAT1 in CNE-2R and CNE-2 cells was measured by Western blot. Results Compared with CNE-2 cells, 374 genes in CNE-2R cells were differentially expressed while 197 genes showed significant differences. Four randomly selected differentially expressed genes were verified by RT-PCR and had same change trend in consistent with the results of chip assay. Analysis with the SNOW database demonstrated that those 197 genes could form a complicated interaction network where STAT1 and JUN might be two key nodes. Indeed, the STAT1-α expression in CNE-2R was higher than that in CNE-2 (t=4.96, P<0.05). Conclusions The key nodes of STAT1 and JUN may be the molecular biomarkers leading to radioresistance in nasopharyngeal carcinoma, and STAT1-α might have close relationship with radioresistance. |
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