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膀胱癌的靶向和非靶向尿代谢组学分析。

Targeted and untargeted urinary metabolic profiling of bladder cancer.

机构信息

Department of Urology, John Paul II Hospital, Grunwaldzka 4 St., 36-100 Kolbuszowa, Poland.

Rzeszów University of Technology, Faculty of Chemistry, 6 Powstańców Warszawy Ave., 35-959 Rzeszów, Poland.

出版信息

J Pharm Biomed Anal. 2023 Sep 5;233:115473. doi: 10.1016/j.jpba.2023.115473. Epub 2023 May 22.

Abstract

Bladder cancer (BC) is frequent cancer affecting the urinary tract and is one of the most prevalent malignancies worldwide. No biomarkers that can be used for effective monitoring of therapeutic interventions for this cancer have been identified to date. This study investigated polar metabolite profiles in urine samples from 100 BC patients and 100 normal controls (NCs) using nuclear magnetic resonance (NMR) and two methods of high-resolution nanoparticle-based laser desorption/ionization mass spectrometry (LDI-MS). Five urine metabolites were identified and quantified using NMR spectroscopy to be potential indicators of bladder cancer. Twenty-five LDI-MS-detected compounds, predominantly peptides and lipids, distinguished urine samples from BC and NCs individuals. Level changes of three characteristic urine metabolites enabled BC tumor grades to be distinguished, and ten metabolites were reported to correlate with tumor stages. Receiver-Operating Characteristics analysis showed high predictive power for all three types of metabolomics data, with the area under the curve (AUC) values greater than 0.87. These findings suggest that metabolite markers identified in this study may be useful for the non-invasive detection and monitoring of bladder cancer stages and grades.

摘要

膀胱癌(BC)是一种常见的影响泌尿系统的癌症,也是全球最普遍的恶性肿瘤之一。迄今为止,尚未发现可用于有效监测这种癌症治疗干预的生物标志物。本研究使用核磁共振(NMR)和两种基于高分辨率纳米颗粒的激光解吸/电离质谱(LDI-MS)方法,对 100 名膀胱癌患者和 100 名正常对照(NC)的尿液样本中的极性代谢物图谱进行了研究。使用 NMR 光谱法鉴定和定量了 5 种尿液代谢物,这些代谢物可能是膀胱癌的潜在标志物。25 种 LDI-MS 检测到的化合物,主要是肽和脂质,可区分膀胱癌和 NC 个体的尿液样本。三种特征尿液代谢物水平的变化可区分膀胱癌的肿瘤分级,有 10 种代谢物与肿瘤分期相关。受试者工作特征分析显示,所有三种代谢组学数据均具有较高的预测能力,曲线下面积(AUC)值大于 0.87。这些发现表明,本研究中鉴定的代谢标志物可能有助于膀胱癌的非侵入性检测和分期及分级监测。

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