Graduate Institute of Biomedical Sciences, College of Medicine, Chang Gung University, Taoyuan, Taiwan.
Molecular Medicine Research Center, College of Medicine, Chang Gung University, Taoyuan, Taiwan.
J Food Drug Anal. 2019 Apr;27(2):460-474. doi: 10.1016/j.jfda.2018.11.008. Epub 2019 Jan 7.
Metabolomics is considered an effective approach for understanding metabolic responses in complex biological systems. Accordingly, it has attracted increasing attention for biomarker discovery, especially in cancer. In this study, we used a non-invasive method to evaluate four urine metabolite biomarker candidates-o-phosphoethanolamine, 3-amio-2-piperidone, uridine and 5-hydroxyindoleactic acid-for their potential as bladder cancer diagnostic biomarkers. To analyze these targeted amine- and phenol-containing metabolites, we used differential C-/C-dansylation labeling coupled with liquid chromatography/tandem mass spectrometry, which has previously been demonstrated to exhibit high sensitivity and reproducibility. Specifically, we used ultra-performance liquid chromatography (UPLC) coupled with high-resolution Fourier transform ion-cyclotron resonance MS system (LC-FT/MS) and an ion trap MS with MRM function (LC-HCT/MS) for targeted quantification. The urinary metabolites of interest were well separated and quantified using this approach. To apply this approach to clinical urine specimens, we spiked samples with C-dansylatedsynthetic compounds, which served as standards for targeted quantification of C-dansylated urinary endogenous metabolites using LC-FT/MS as well as LC-HCT/MS with MRM mode. These analyses revealed significant differences in two of the four metabolites of interest-o-phosphoethanolamine and uridine-between bladder cancer and non-cancer groups. O-phosphoethanolamine was the most promising single biomarker, with an area-under-the-curve (AUC) value of 0.709 for bladder cancer diagnosis. Diagnostic performance was improved by combining uridine and o-phosphoethanolamine in a marker panel, yielding an AUC value of 0.726. This study confirmed discovery-phase features of the urine metabolome of bladder cancer patients and verified their importance for further study.
代谢组学被认为是理解复杂生物系统代谢反应的有效方法。因此,它在生物标志物发现方面受到了越来越多的关注,尤其是在癌症方面。在这项研究中,我们使用一种非侵入性方法来评估四种尿代谢物生物标志物候选物 - o-磷酸乙醇胺、3-氨基-2-哌啶酮、尿苷和 5-羟基吲哚乙酸 - 作为膀胱癌诊断生物标志物的潜力。为了分析这些靶向含胺和酚的代谢物,我们使用了差分 C-/C-丹磺酰化标记与液相色谱/串联质谱联用技术,该技术以前已经证明具有高灵敏度和重现性。具体来说,我们使用超高效液相色谱 (UPLC) 与高分辨率傅里叶变换离子回旋共振 MS 系统 (LC-FT/MS) 和具有 MRM 功能的离子阱 MS (LC-HCT/MS) 进行靶向定量。使用这种方法可以很好地分离和定量感兴趣的尿代谢物。为了将这种方法应用于临床尿标本,我们用 C-丹磺酰化合成化合物对样品进行了加标,这些化合物可作为使用 LC-FT/MS 以及 LC-HCT/MS 与 MRM 模式对 C-丹磺酰化尿内源性代谢物进行靶向定量的标准。这些分析表明,在四个感兴趣的代谢物中的两个 - o-磷酸乙醇胺和尿苷 - 之间,膀胱癌和非癌症组之间存在显著差异。o-磷酸乙醇胺是最有前途的单一生物标志物,其用于膀胱癌诊断的曲线下面积 (AUC) 值为 0.709。通过在标记物组合中结合尿苷和 o-磷酸乙醇胺,诊断性能得到了提高,AUC 值为 0.726。本研究证实了膀胱癌患者尿液代谢组学的发现阶段特征,并验证了其对进一步研究的重要性。