Biotransformation-based metabolomics profiling method for determining and quantitating cancer-related metabolites

被引:11
作者
Yue, Xiaofei [1 ,2 ]
He, Jiuming [1 ,2 ]
Zhang, Ruiping [1 ,2 ]
Xu, Jing [1 ,2 ]
Zhou, Zhi [1 ,2 ]
Zhang, Rui [1 ,2 ]
Bi, Nan [3 ,4 ,5 ]
Wang, Zhonghua [6 ]
Sun, Chenglong [1 ,2 ]
Wang, Luhua [3 ,4 ,5 ]
Chen, Yanhua [1 ,2 ]
Abliz, Zeper [1 ,6 ]
机构
[1] Chinese Acad Med Sci, Inst Mat Med, State Key Lab Bioact Subst & Funct Nat Med, Beijing 100050, Peoples R China
[2] Peking Union Med Coll, Beijing 100050, Peoples R China
[3] Chinese Acad Med Sci, Inst Canc, Beijing 100021, Peoples R China
[4] Chinese Acad Med Sci, Canc Hosp, Beijing 100021, Peoples R China
[5] Peking Union Med Coll, Beijing 100021, Peoples R China
[6] Minzu Univ China, Ctr Bioimaging & Syst Biol, Beijing 100081, Peoples R China
基金
国家高技术研究发展计划(863计划); 中国国家自然科学基金;
关键词
Metabolomics; Biotransformation; based Biomarkers; Small-cell lung cancer; Arginine metabolism; PLASMA METABOLOMICS; URINARY; MS/MS; IDENTIFICATION; METABONOMICS; BIOMARKERS;
D O I
10.1016/j.chroma.2018.10.034
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
The discovery and identification of reliable disease biomarkers and relevant disrupted metabolic pathways is still a major challenge in metabolomics. Here, we proposed a biotransformation-based metabolomics profiling method to identify reliable disease biomarkers by simultaneous quantitation and qualification of cancer-related metabolites and their metabolic pathways via liquid chromatography tandem mass spectrometry (LC-MS/MS). The approach was based on selecting a subset of known cancer-related metabolites from our previous metabolomics work, cancer research literature and biological significance. The metabolic profiling of pathway-related metabolites was developed by predicted multiple reaction monitoring (MRM) of ion pairs based on their chemical structures and biotransformation. Then, a high-throughput quantitative method was established. Overall, this approach enables the sensitive and accurate detection of cancer-related metabolites and the identification of other relevant metabolites, which facilitates better data quality and in-depth investigation of dysregulated metabolic pathways. As a proof of concept, the approach was applied to a small-cell lung cancer (SCLC) study. The results showed that 43 metabolites were significantly changed, and arginine metabolism was apparently disturbed, which proved the proposed approach could be a powerful tool for discovering reliable disease biomarkers and aberrant metabolic pathways. (C) 2018 Elsevier B.V. All rights reserved.
引用
收藏
页码:80 / 89
页数:10
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