Department of Paediatric Surgery, Nagoya University Graduate School of Medicine, 65 Tsurumai, Showa, Nagoya, 466-8550, Japan.
Hitachi, Ltd., R & D Group, Centre for Exploratory Research, Tokyo, 185-8601, Japan.
Sci Rep. 2021 Feb 18;11(1):4055. doi: 10.1038/s41598-021-83619-w.
Urine is a complex liquid containing numerous small molecular metabolites. The ability to non-invasively test for cancer biomarkers in urine is especially beneficial for screening child patients. This study attempted to identify neuroblastoma biomarkers by comprehensively analysing urinary metabolite samples from children. A total of 87 urine samples were collected from 54 participants (15 children with neuroblastoma and 39 without cancer) and used to perform a comprehensive analysis. Urine metabolites were extracted using liquid chromatography/mass spectrometry and analysed by Metabolon, Inc. Biomarker candidates were extracted using the Wilcoxon rank sum test, random forest method (RF), and orthogonal partial least squares discriminant analysis (OPLS-DA). RF identified three important metabolic pathways in 15 samples from children with neuroblastoma. One metabolite was selected from each of the three identified pathways and combined to create a biomarker candidate (3-MTS, CTN, and COR) that represented each of the three pathways; using this candidate, all 15 cases were accurately distinguishable from the control group. Two cases in which known biomarkers were negative tested positive using this new biomarker. Furthermore, the predictive value did not decrease in cases with a low therapeutic effect. This approach could be effectively applied to identify biomarkers for other cancer types.
尿液是一种含有众多小分子代谢物的复杂液体。能够无创地检测尿液中的癌症生物标志物,特别有益于儿童患者的筛查。本研究试图通过综合分析儿童尿液代谢物样本来鉴定神经母细胞瘤的生物标志物。共采集了 54 名参与者(15 名神经母细胞瘤患儿和 39 名无癌症患儿)的 87 份尿液样本,并进行了综合分析。采用液相色谱/质谱法提取尿液代谢物,由 Metabolon,Inc. 进行分析。采用 Wilcoxon 秩和检验、随机森林法(RF)和正交偏最小二乘判别分析(OPLS-DA)提取生物标志物候选物。RF 从 15 名神经母细胞瘤患儿的 15 个样本中识别出三个重要的代谢途径。从三个鉴定出的途径中各选择一个代谢物,组合成一个代表三个途径的生物标志物候选物(3-MTS、CTN 和 COR);使用这个候选物,15 个病例均能准确地区分于对照组。两种已知标志物为阴性的病例,使用这个新的生物标志物呈阳性。此外,在治疗效果不佳的病例中,其预测价值并没有降低。该方法可有效地应用于鉴定其他癌症类型的生物标志物。