代谢组学
医学
肺癌
癌症
生物信息学
计算生物学
肿瘤科
内科学
生物
作者
Chenchen Zhao,Xianbin Kong,Shuang Han,Xiaojiang Li,Tong Wu,Jie Zhou,Yuzhu Guo,Zhichao Bu,Chuanxin Liu,Chenning Zhang,Yingjie Jia
出处
期刊:Future Oncology
[Future Medicine]
日期:2020-05-01
卷期号:16 (18): 1269-1287
被引量:14
标识
DOI:10.2217/fon-2019-0818
摘要
Aim: Based on metabonomics, the metabolic markers of lung cancer patients were analyzed, combined with bioinformatics to explore the underlying disease mechanism. Materials & methods: Based on case–control design, using UPLC-Q-TOF/MS, urine metabolites were detected in discovery and validation set. Multivariate statistical analysis were performed to identify potential markers for lung cancer. A network analysis was constructed to integrate lung cancer disease targets with the above metabolic markers, and its possible mechanism and biological significance were explained. Results: A total of 35 potential markers were identified, 11 of which overlapped. Five key markers have a good linear correlation with serum biochemical indicators. Conclusion: The occurrence and development of lung cancer are closely related to disturbance of D-Glutamine and D-glutamate metabolism, amino acid imbalance. This test was registered on China clinical trial registration center (www.chictr.org.cn/index.aspx), registration number was ChiCTR1900025543.
科研通智能强力驱动
Strongly Powered by AbleSci AI