Prostate Cancer Patients-Negative Biopsy Controls Discrimination by Untargeted Metabolomics Analysis of Urine by LC-QTOF: Upstream Information on Other Omics.
Prostate Cancer Patients-Negative Biopsy Controls Discrimination by Untargeted Metabolomics Analysis of Urine by LC-QTOF: Upstream Information on Other Omics.
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DOI：
10.1038/srep38243
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发表时间：
2016-12-02
影响因子：
4.6
通讯作者：
Priego-Capote F
中科院分区：
文献类型：
--
作者：
Fernández-Peralbo MA;Gómez-Gómez E;Calderón-Santiago M;Carrasco-Valiente J;Ruiz-García J;Requena-Tapia MJ;Luque de Castro MD;Priego-Capote F
现有的前列腺癌（PCa）诊断临床生物标志物远非理想（例如，前列腺特异性抗原（PSA）血清水平缺乏特异性，经常出现假阳性，导致过度诊断）。寻找微创测试来补充或替代 PSA 的关键一步应该得到 PCa 患者与活检阴性对照个体相比生化途径所经历的变化的支持。在这项研究中，通过 LC-QTOF 对 62 名具有临床意义的 PCa 患者和 42 名健康个体的尿液进行了全面的分析，两组均经活检证实。未配对 t 检验（p 值<<0.05）提供了尿液中初步鉴定的 28 种显着代谢物，用于开发偏最小二乘判别分析 (PLS-DA) 模型，其敏感性和特异性分别为 88.4% 和 92.9%。在 28 种重要代谢物中，有 27 种在 PCa 患者中的浓度低于对照个体，而只有一种报告在 PCa 患者中的浓度较高。它们所涉及的生化途径（DNA 甲基化、组蛋白上的表观遗传标记和 RNA 帽甲基化）之间的联系可以解释 PCa 的浓度变化，并再次支持代谢组学在上游过程中的作用。
The existing clinical biomarkers for prostate cancer (PCa) diagnosis are far from ideal (e.g., the prostate specific antigen (PSA) serum level suffers from lack of specificity, providing frequent false positives leading to over-diagnosis). A key step in the search for minimum invasive tests to complement or replace PSA should be supported on the changes experienced by the biochemical pathways in PCa patients as compared to negative biopsy control individuals. In this research a comprehensive global analysis by LC–QTOF was applied to urine from 62 patients with a clinically significant PCa and 42 healthy individuals, both groups confirmed by biopsy. An unpaired t-test (p-value < 0.05) provided 28 significant metabolites tentatively identified in urine, used to develop a partial least squares discriminant analysis (PLS-DA) model characterized by 88.4 and 92.9% of sensitivity and specificity, respectively. Among the 28 significant metabolites 27 were present at lower concentrations in PCa patients than in control individuals, while only one reported higher concentrations in PCa patients. The connection among the biochemical pathways in which they are involved (DNA methylation, epigenetic marks on histones and RNA cap methylation) could explain the concentration changes with PCa and supports, once again, the role of metabolomics in upstream processes.
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