Ministry of Education Key Laboratory of Systems Biomedicine, Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai, PR China.
J Proteome Res. 2013 Jun 7;12(6):3000-9. doi: 10.1021/pr400337b. Epub 2013 May 29.
Recent studies suggest that biofluid-based metabonomics may identify metabolite markers promising for colorectal cancer (CRC) diagnosis. We report here a follow-up replication study, after a previous CRC metabonomics study, aiming to identify a distinct serum metabolic signature of CRC with diagnostic potential. Serum metabolites from newly diagnosed CRC patients (N = 101) and healthy subjects (N = 102) were profiled using gas chromatography time-of-flight mass spectrometry (GC-TOFMS) and ultraperformance liquid chromatography quadrupole time-of-flight mass spectrometry (UPLC-QTOFMS). Differential metabolites were identified with statistical tests of orthogonal partial least-squares-discriminant analysis (VIP > 1) and the Mann-Whitney U test (p < 0.05). With a total of 249 annotated serum metabolites, we were able to differentiate CRC patients from the healthy controls using an orthogonal partial least-squares-discriminant analysis (OPLS-DA) in a learning sample set of 62 CRC patients and 62 matched healthy controls. This established model was able to correctly assign the rest of the samples to the CRC or control groups in a validation set of 39 CRC patients and 40 healthy controls. Consistent with our findings from the previous study, we observed a distinct metabolic signature in CRC patients including tricarboxylic acid (TCA) cycle, urea cycle, glutamine, fatty acids, and gut flora metabolism. Our results demonstrated that a panel of serum metabolite markers is of great potential as a noninvasive diagnostic method for the detection of CRC.
最近的研究表明，基于生物流体的代谢组学可能会发现对结直肠癌（CRC）诊断有希望的代谢标志物。在之前的 CRC 代谢组学研究之后，我们在此报告了一项后续复制研究，旨在确定具有诊断潜力的 CRC 的独特血清代谢特征。使用气相色谱飞行时间质谱（GC-TOFMS）和超高效液相色谱四极杆飞行时间质谱（UPLC-QTOFMS）对新诊断的 CRC 患者（N=101）和健康受试者（N=102）的血清代谢物进行了分析。使用正交偏最小二乘判别分析（VIP>1）和曼-惠特尼 U 检验（p<0.05）的统计检验来鉴定差异代谢物。利用总共 249 个注释的血清代谢物，我们能够使用正交偏最小二乘判别分析（OPLS-DA）将 62 名 CRC 患者和 62 名匹配的健康对照者的学习样本集中的 CRC 患者与健康对照组区分开来。该建立的模型能够在 39 名 CRC 患者和 40 名健康对照组的验证集中正确地将其余样本分配到 CRC 或对照组。与我们之前研究的结果一致，我们观察到 CRC 患者中存在明显的代谢特征，包括三羧酸（TCA）循环、尿素循环、谷氨酰胺、脂肪酸和肠道菌群代谢。我们的结果表明，一组血清代谢标志物作为非侵入性诊断方法用于检测 CRC 具有很大的潜力。
