口腔医学研究

口腔医学研究 ›› 2015, Vol. 31 ›› Issue (5): 493-496.

• 临床研究论著 • 上一篇    下一篇

耐药和非耐药口腔鳞癌Tca8113代谢组学方法鉴定的初步研究

王辉1*, 孟雅1, 张平2   

  1. 1. 唐山职业技术学院口腔系 河北 唐山 063004;
    2. 四川大学口腔疾病研究国家重点实验室
  • 收稿日期:2014-11-07 出版日期:2015-05-28 发布日期:2016-04-29
  • 通讯作者: 王辉,E-mail:wkate@126.com
  • 作者简介:王辉(1984~ ),男,山西大同人,硕士,讲师,主要从事口腔基础研究。

Preliminary Study on Identification of Drug Resistant and Non-drug Resistant Oral Squamous Carcinoma Cell line Tca8113 Using Metabolomics.

WANG Hui, Meng Ya, ZHANG Ping.   

  1. Department of Stomatology of Tangshan Vocational & Technical College, Tangshan 063004
  • Received:2014-11-07 Online:2015-05-28 Published:2016-04-29

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摘要： 目的:初步将基于氢谱核磁共振(1H-NMR)的代谢组学方法应用于口腔耐药和非耐药口腔鳞癌Tca8113的鉴定。方法:MTT法绘制细胞生长曲线并检测药物敏感性,免疫组织化学检测与多药耐药现象相关蛋白P-gp的表达情况;收集胞外代谢产物进行核磁共振检测,用主成分分析法进行数据分析。结果:主成分分析法显示耐药细胞和非耐药细胞数据内部有集中的聚类关系,基于氢谱核磁共振的代谢组学方法可以区分耐药和非耐药的Tca8113。结论:代谢组学方法在产生耐药性的口腔癌细胞的快速鉴定中具有良好的应用前景,有望成为一种新的检测手段。

关键词: 口腔鳞癌, 多药耐药, 代谢组学, 核磁共振, 主成分分析

Abstract: Objective: To identify the drug resistant and non-drug resistant of oral squamous carcinoma Tca8113. Methods: Cell growth curve was drafted and drug sensitivity were detected by the MTT assay. The immunohistochemistry was applied to detect the expression of P-gp which was related to multidrug resistance phenomenon in drug resistant cells. Extracellular metabolites of all cell lines was collected and was detected by nuclear magnetic resonance (NMR). Data analysis used principal component analysis(PCA). Results: The principal component analysis showed the obvious clustering relations in the data of drug resistant and non-drug resistant cells, indicating 1H NMR-based metabolomics method could distinguish between drug resistant and non-drug resistant Tca8113. Conclusion: The metabolomics is expected to be favorable application prospect in rapid identification of oral cancer cells with resistance, and it is expected to become a new testing method in future.

Key words: Oral squamous carcinoma , Multidrug resistance(MDR) , Metabolomics, Nuclear magneticresonance(NMR) , Principal components analysis(PCA)

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