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Discovery and validation of potential urinary biomarkers for bladder cancer diagnosis using a pseudotargeted GC-MS metabolomics method

机译:使用伪靶向GC-MS代谢组学方法发现和验证用于膀胱癌诊断的潜在尿液生物标志物

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摘要

Bladder cancer (BC) is the second most prevalent malignancy in the urinary system and is associated with significant mortality; thus, there is an urgent need for novel noninvasive diagnostic biomarkers. A urinary pseudotargeted method based on gas chromatography–mass spectrometry was developed and validated for a BC metabolomics study. The method exhibited good repeatability, intraday and interday precision, linearity and metabolome coverage. A total of 76 differential metabolites were defined in the discovery sample set, 58 of which were verified using an independent validation urine set. The verified differential metabolites revealed that energy metabolism, anabolic metabolism and cell redox states were disordered in BC. Based on a binary logistic regression analysis, a four-biomarker panel was defined for the diagnosis of BC. The area under the receiving operator characteristic curve was 0.885 with 88.0% sensitivity and 85.7% specificity in the discovery set and 0.804 with 78.0% sensitivity and 70.3% specificity in the validation set. The combinatorial biomarker panel was also useful for the early diagnosis of BC. This approach can be used to discriminate non-muscle invasive and low-grade BCs from healthy controls with satisfactory sensitivity and specificity. The results show that the developed urinary metabolomics method can be employed to effectively screen noninvasive biomarkers.
机译:膀胱癌(BC)是泌尿系统中第二常见的恶性肿瘤,并伴有明显的死亡率。因此,迫切需要新型的非侵入性诊断生物标志物。开发了一种基于气相色谱-质谱法的尿假靶向方法,并已用于BC代谢组学研究的验证。该方法具有良好的重复性,日内和日间精度,线性和代谢组覆盖率。在发现样品集中共定义了76种差异代谢物,其中58种使用独立的验证尿液集进行了验证。验证的差异代谢物表明,在卑诗省,能量代谢,合成代谢代谢和细胞氧化还原状态异常。基于二元逻辑回归分析,定义了一个用于诊断BC的四生物标志物组。接收算子特征曲线下的面积在发现集中为0.885,灵敏度为88.0%,特异性为85.7%;在验证组中为0.804,灵敏度为78.0%,特异性为70.3%。组合生物标志物组也可用于BC的早期诊断。该方法可用于以良好的敏感性和特异性将非肌肉浸润性和低度BC与健康对照区分开。结果表明,开发的尿液代谢组学方法可用于有效筛选非侵入性生物标志物。

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