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用于预测肾细胞癌(RCC)的尿液代谢组学:色氨酸代谢作为肾细胞癌的重要途径

Urine Metabolomics for Renal Cell Carcinoma (RCC) Prediction: Tryptophan Metabolism as an Important Pathway in RCC.

作者信息

Liu Xiaoyan, Zhang Mingxin, Liu Xiang, Sun Haidan, Guo Zhengguang, Tang Xiaoyue, Wang Zhan, Li Jing, Li Hanzhong, Sun Wei, Zhang Yushi

机构信息

School of Basic Medicine, Institute of Basic Medical Sciences, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China.

Department of Urology, Peking Union Medical College Hospital, Chinese Academy of Medical Science, Beijing, China.

出版信息

Front Oncol. 2019 Jul 17;9:663. doi: 10.3389/fonc.2019.00663. eCollection 2019.

Abstract

Renal cell carcinoma (RCC) is the second most lethal urinary cancer. RCC is frequently asymptomatic and it is already metastatic at diagnosis. There is an urgent necessity for RCC specific biomarkers selection for diagnostic and prognostic purposes. In present study, we applied liquid chromatography-mass spectrometry (LC-MS) based metabolomics to analyze urine samples of 100 RCC, 34 benign kidney tumors and 129 healthy controls. Differential metabolites were analyzed to investigate if urine metabolites could differentiate RCC from non-RCC. A panel consisting of 9 metabolites showed the best predictive ability for RCC from the health controls with an area under the curve (AUC) values of 0.905 for the training dataset and 0.885 for the validation dataset. Separation was observed between the RCC and benign samples with an AUC of 0.816. RCC clinical stages (T1 and T2 vs. T3 and T4) could be separated using a panel of urine metabolites with an AUC of 0.813. One metabolite, N-formylkynurenine, was discovered to have potential value for RCC diagnosis from non-RCC subjects with an AUC of 0.808. Pathway enrichment analysis indicated that tryptophan metabolism was an important pathway in RCC. Our data concluded that urine metabolomics could be used for RCC diagnosis and would provide candidates for further targeted metabolomics analysis of RCC.

摘要

肾细胞癌(RCC)是第二大致命性泌尿系统癌症。肾细胞癌通常无症状,在诊断时就已经发生转移。迫切需要选择肾细胞癌特异性生物标志物用于诊断和预后评估。在本研究中,我们应用基于液相色谱 - 质谱联用(LC - MS)的代谢组学方法分析了100例肾细胞癌患者、34例良性肾肿瘤患者和129例健康对照者的尿液样本。对差异代谢物进行分析,以研究尿液代谢物是否能区分肾细胞癌和非肾细胞癌。由9种代谢物组成的检测组对区分健康对照者中的肾细胞癌具有最佳预测能力,训练数据集的曲线下面积(AUC)值为0.905,验证数据集的AUC值为0.885。肾细胞癌样本和良性样本之间存在分离,AUC为0.816。使用一组尿液代谢物可以分离肾细胞癌的临床分期(T1和T2与T3和T4),AUC为0.813。发现一种代谢物N - 甲酰犬尿氨酸在区分肾细胞癌与非肾细胞癌受试者方面具有潜在价值,AUC为0.808。通路富集分析表明色氨酸代谢是肾细胞癌中的一条重要通路。我们的数据表明,尿液代谢组学可用于肾细胞癌的诊断,并将为肾细胞癌进一步的靶向代谢组学分析提供候选物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0724/6653643/4399dd124579/fonc-09-00663-g0001.jpg

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