前列腺癌中的代谢学:使用前列腺按摩后的尿液来预测格里森等级的最小侵入性方法
Jorge Panach-Navarrete1,2,3, Vannina González-Marrachelli1,2,4, José Manuel Morales-Tatay1,2,5
1Department of Urology, University Clinic Hospital of Valencia, 46010 Valencia, Spain.
Archivos espanoles de urologia
|December 3, 2025
概括
这项研究使用核磁共振 (NMR) 确定了尿路生物标志物,以预测高度前列腺癌 (格里森等级≥8). 该模型结合了代谢物和数字直肠检查 (DRE) 发现,在风险分层方面显示出高准确性.
科学领域:
- 生物化学 生化学
- 在瘤学瘤学.
- 医学诊断 医学诊断 医学诊断
背景情况:
- 前列腺癌的诊断和分级对于治疗决策至关重要.
- 确定侵袭性前列腺癌 (格里森等级≥8) 的生物标志物是必不可少的.
- 核磁共振 (NMR) 光谱为生物标志物发现提供了一个潜在的工具.
研究的目的:
- 为了探索尿路生物标志物预测前列腺癌与格里森等级8或更高.
- 利用基于NMR的代谢学和临床数据开发一个预测模型.
- 为了评估模型的准确性,根据格里森等级对患者进行分层.
主要方法:
- 从接受前列腺活检的患者收集尿液样本.
- 使用NMR光谱分析尿液代谢物.
- 进行了单变量和多变量分析,结合了像数字直肠检查 (DRE) 这样的临床变量.
- 使用部分最小方程差异分析 (PLS-DA) 构建了一个预测模型.
主要成果:
- 该研究分析了107名前列腺癌患者 (73名格里森6-7,34名格里森≥8) 的数据.
- 一个包含29个显著代谢物和DRE发现的预测模型实现了0.92.9的AUC.
- 该模型显示高灵敏度 (82%),特异性 (92%),PPV (84%) 和NPV (90%) 预测格里森等级≥8.8.
- 关键代谢物与氨基酸代谢和糖解有关.
结论:
- 尿路代谢物和临床数据 (DRE) 的综合模型通过格里森等级有效地分层前列腺癌风险.
- 参与糖解和氨基酸代谢的代谢物是重要的预测因素.
- 这种最少的侵入性方法可以帮助临床决策,等待在更大的研究中验证.
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