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基于超高效液相色谱-傅里叶变换质谱联用仪和超高效液相色谱-离子阱质谱联用仪的前列腺癌尿液代谢组学分析

Urinary Metabolomic Analysis of Prostate Cancer by UPLC-FTMS and UPLC-Ion Trap MS.

作者信息

Chen Chien-Lun, Chen Yi-Ting, Liao Wen-Yu, Chang Yu-Sun, Yu Jau-Song, Juo Bao-Rong

机构信息

Molecular Medicine Research Center, Chang Gung University, Kwei-San, Taoyuan 33302, Taiwan.

Department of Urology, Chang Gung Memorial Hospital, College of Medicine, Chang Gung University, Kwei-San, Taoyuan 33305, Taiwan.

出版信息

Diagnostics (Basel). 2023 Jul 4;13(13):2270. doi: 10.3390/diagnostics13132270.

Abstract

Accumulative evidence suggests metabolic disorders correlate with prostate cancer. Metabolic profiling of urine allows the measurement of numerous metabolites simultaneously. This study set up a metabolomic platform consisting of UPLC-FTMS and UPLC-ion trap MS for urine metabolome analysis. The platform improved retention time, mass accuracy, and signal stability. Additionally, the product ion spectrum obtained from ion trap MS facilitated structure elucidation of candidate metabolites, especially when authentic standards were not available. Urine samples from six hernia patients and six BPH patients were used for the initial establishment of the analytic platform. This platform was further employed to analyze the urine samples of 27 PCa and 49 BPH patients. Choosing the upper and lower 16% of metabolites, 258 metabolite candidates were selected. Twenty-four of them with AUC values larger than 0.65 were further selected. Eighteen of the twenty-four features can be matched in METLIN and HMDB. Eleven of the eighteen features can be interpreted by MS experiments. They were used for the combination achieving the best differential power. Finally, four metabolites were combined to reach the AUC value of 0.842 (CI 95, 0.7559 to 0.9279). This study demonstrates the urinary metabolomic analysis of prostate cancer and sheds light on future research.

摘要

越来越多的证据表明,代谢紊乱与前列腺癌相关。尿液代谢谱分析能够同时检测多种代谢物。本研究建立了一个由超高效液相色谱-傅里叶变换质谱(UPLC-FTMS)和超高效液相色谱-离子阱质谱(UPLC-ion trap MS)组成的代谢组学平台,用于尿液代谢组分析。该平台改善了保留时间、质量精度和信号稳定性。此外,离子阱质谱获得的产物离子谱有助于候选代谢物的结构解析,尤其是在没有标准品的情况下。来自6名疝气患者和6名良性前列腺增生(BPH)患者的尿液样本用于该分析平台的初步建立。该平台进一步用于分析27例前列腺癌(PCa)患者和49例BPH患者的尿液样本。选择代谢物含量上下16%的样本,筛选出258种候选代谢物。进一步筛选出其中24种曲线下面积(AUC)值大于0.65的代谢物。这24种特征中有18种可以在METLIN和人类代谢组数据库(HMDB)中匹配。这18种特征中有11种可以通过质谱实验进行解释。它们被用于组合以实现最佳的鉴别能力。最后,将4种代谢物组合,得到AUC值为0.842(95%置信区间,0.7559至0.9279)。本研究展示了前列腺癌的尿液代谢组学分析,并为未来的研究提供了思路。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac95/10340632/c8002aab9381/diagnostics-13-02270-g001.jpg

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