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用于肺癌筛查的人体汗液代谢组学

Human sweat metabolomics for lung cancer screening.

作者信息

Calderón-Santiago Mónica, Priego-Capote Feliciano, Turck Natacha, Robin Xavier, Jurado-Gámez Bernabé, Sanchez Jean C, Luque de Castro María D

机构信息

Department of Analytical Chemistry, Annex Marie Curie Building, Campus of Rabanales, University of Córdoba, 14071, Córdoba, Spain.

出版信息

Anal Bioanal Chem. 2015 Jul;407(18):5381-92. doi: 10.1007/s00216-015-8700-8. Epub 2015 May 3.

DOI:10.1007/s00216-015-8700-8
PMID:25935675
Abstract

Sweat is one of the less employed biofluids for discovery of markers in spite of its increased application in medicine for detection of drugs or for diagnostic of cystic fibrosis. In this research, human sweat was used as clinical sample to develop a screening tool for lung cancer, which is the carcinogenic disease with the highest mortality rate owing to the advanced stage at which it is usually detected. In this context, a method based on the metabolite analysis of sweat to discriminate between patients with lung cancer versus smokers as control individuals is proposed. The capability of the metabolites identified in sweat to discriminate between both groups of individuals was studied and, among them, a trisaccharide phosphate presented the best independent performance in terms of the specificity/sensitivity pair (80 and 72.7%, respectively). Additionally, two panels of metabolites were configured using the PanelomiX tool as an attempt to reduce false negatives (at least 80% specificity) and false positives (at least 80% sensitivity). The first panel (80% specificity and 69% sensitivity) was composed by suberic acid, a tetrahexose, and a trihexose, while the second panel (69% specificity and 80% sensitivity) included nonanedioic acid, a trihexose, and the monoglyceride MG(22:2). Thus, the combination of the five metabolites led to a single panel providing 80% specificity and 79% sensitivity, reducing the false positive and negative rates to almost 20%. The method was validated by estimation of within-day and between-days variability of the quantitative analysis of the five metabolites.

摘要

尽管汗液在医学上用于药物检测或囊性纤维化诊断的应用有所增加,但它仍是用于发现生物标志物的较少被使用的生物流体之一。在本研究中,人体汗液被用作临床样本,以开发一种肺癌筛查工具,肺癌是一种由于通常在晚期才被检测到而死亡率最高的致癌疾病。在此背景下,提出了一种基于汗液代谢物分析的方法,以区分肺癌患者与作为对照个体的吸烟者。研究了汗液中鉴定出的代谢物区分两组个体的能力,其中,磷酸三糖在特异性/敏感性对方面表现出最佳的独立性能(分别为80%和72.7%)。此外,使用PanelomiX工具配置了两组代谢物,试图减少假阴性(至少80%的特异性)和假阳性(至少80%的敏感性)。第一组(80%的特异性和69%的敏感性)由壬二酸、一种四己糖和一种三己糖组成,而第二组(69%的特异性和80%的敏感性)包括壬二酸、一种三己糖和甘油单酯MG(22:2)。因此,这五种代谢物的组合形成了一个单一的组,提供了80%的特异性和79%的敏感性,将假阳性和假阴性率降低到近20%。通过估计这五种代谢物定量分析的日内和日间变异性对该方法进行了验证。

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