Ren Junling, Zhang Dan, Liu Yujie, Zhang Ruiqing, Fang Huiling, Guo Shuai, Zhou Dan, Zhang Mo, Xu Yupin, Qiu Ling, Li Zhili
Department of Biophysics and Structural Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences &School of Basic Medicine, Peking Union Medical College, Beijing 100005, P. R. China.
Department of Clinical Laboratory, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences &Peking Union Medical College, Beijing, 100730, P. R. China.
Sci Rep. 2016 Sep 30;6:34201. doi: 10.1038/srep34201.
In this study, we have employed graphene oxide as a matrix to simultaneously and directly quantify serum nonesterified and esterified fatty acids (FAs) using matrix-assisted laser/desorption ionization-Fourier transform ion cyclotron resonance mass spectrometry (MALDI-FTICR MS). Twelve serum nonesterified FAs combined with their individual esterified FAs (i.e., C, C, C, C, C, C, C, C, C, C, C, and C) were quantified based on their calibration curves with the correlation coefficients of >0.99, along with the analytical time of <1 min each sample. As a result, serum levels of twelve total FAs (TFAs) in 1440 serum samples from 487 healthy controls (HCs), 479 patients with benign lung diseases (BLDs) and 474 patients with lung cancer (LC) were determined. Statistical analysis indicated that significantly increased levels of C, C, C, C, C, C, and C and decreased levels of C were observed in LC patients compared with BLDs. Receiver operating characteristic (ROC) analysis revealed that panel a (C, C, C, C, C, and C), panel b (C, C, C, and C), and panel c (C, C, C, C, and C) have exhibited good diagnostic ability to differentiate BLDs from LC relative to clinical uses of tumor markers (CEA and Cyfra 21-1).
在本研究中,我们采用氧化石墨烯作为基质,使用基质辅助激光解吸电离傅里叶变换离子回旋共振质谱(MALDI-FTICR MS)同时直接定量血清中非酯化和酯化脂肪酸(FAs)。基于校准曲线对十二种血清非酯化脂肪酸及其各自的酯化脂肪酸(即C、C、C、C、C、C、C、C、C、C、C和C)进行了定量,相关系数>0.99,每个样品的分析时间<1分钟。结果,测定了来自487名健康对照(HCs)、479名良性肺病(BLDs)患者和474名肺癌(LC)患者的1440份血清样本中十二种总脂肪酸(TFAs)的血清水平。统计分析表明,与BLDs患者相比,LC患者中C、C、C、C、C、C和C的水平显著升高,而C的水平降低。受试者工作特征(ROC)分析显示,相对于肿瘤标志物(CEA和Cyfra 21-1)的临床应用,a组(C、C、C、C、C和C)、b组(C、C、C和C)和c组(C、C、C、C和C)在区分BLDs和LC方面具有良好的诊断能力。