摘要
肿瘤是一种代谢疾病,癌基因表达对肿瘤细胞代谢的影响是目前肿瘤研究的热点之一.本文利用基于核磁共振氢谱(1H NMR)的代谢组学方法对癌基因SIRT7低表达胶质瘤细胞株的代谢特征进行分析,寻找与SIRT7基因表达相关的特征性代谢物和代谢通路.分析结果表明,SIRT7基因低表达组与对照组细胞的代谢轮廓存在显著性差异,其细胞水溶性萃取物中有22种代谢物浓度发生明显变化.与对照组相比,SIRT7基因低表达胶质瘤细胞株中乳酸、甘氨酸、谷氨酸等12种代谢物浓度升高;缬氨酸、亮氨酸、赖氨酸等10种代谢物浓度降低.通路富集分析提示氨酰-tRNA生物合成、氨基酸代谢等代谢通路与SIRT7低表达密切相关.以上结果为进一步阐明癌基因SIRT7调控胶质瘤细胞代谢的作用机制提供了理论依据.
Tumor is a metabolic disease.The effect of oncogene expression on the metabolism of cancer cells is one of the hotspots in cancer research.In this study,1H NMR-based metabonomics analysis was used to explore the metabolic characteristics of glioma cell lines with low expression of SIRT7,and to identify the characteristic metabolites and metabolic pathways related to the expression of SIRT7.The results showed that there were significant differences in metabolic profiles between the SIRT7 low expression group and the control group,and 22 aqueous metabolites were found to vary significantly.Compared with the control group,the concentration of 12 metabolites including lactate,glycine,and glutamate,and so on,increased in SIRT7 low expression glioma cell lines,while the concentration of 10 metabolites such as valine,leucine,lysine,et al.decreased.Pathway enrichment analysis indicated that the metabolic pathways of aminoacyl-tRNA biosynthesis,tyrosine metabolism,and so on,were closely related to the low expression of SIRT7.The results provide a theoretical basis for further mechanism elucidation of SIRT7 regulating glioma cell metabolism.
作者
邵巍
林清源
杨文圣
黄彩华
林东海
SHAO Wei;LIN Qing-yuan;YANG Wen-sheng;HUANG Cai-hua;LIN Dong-hai(Chenggong Hospital Affiliated Xiamen University,Xiamen 361005,China;College of Chemistry and Chemical Engineering,High-Field Nuclear Magnetic Resonance Research Center,Xiamen University,Xiamen 361005,China;Research and Communication Center of Exercise and Health,Xiamen University of Technology,Xiamen 361024,China)
出处
《波谱学杂志》
CAS
北大核心
2019年第4期517-524,共8页
Chinese Journal of Magnetic Resonance
基金
厦门市科技计划社会发展项目(3502Z20184064)
关键词
核磁共振氢谱
代谢组学
去乙酰化酶
特征性代谢物
代谢通路
proton nuclear magnetic resonance
metabonomics
Sirtuin7
characteristic metabolites
metabolic pathways