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用于检测膀胱癌相关挥发性有机化合物的光学感应阵列。

Optical sensory arrays for the detection of urinary bladder cancer-related volatile organic compounds.

机构信息

Cancer Research Division, School of Medicine, University of Dundee, Dundee, UK.

Mechanical and Electronic Engineering, School of Science and Engineering, University of Dundee, Dundee, UK.

出版信息

J Biophotonics. 2019 Oct;12(10):e201800165. doi: 10.1002/jbio.201800165. Epub 2019 Jul 28.

Abstract

Non-invasive detection of urinary bladder cancer remains a significant challenge. Urinary volatile organic compounds (VOCs) are a promising alternative to cell-based biomarkers. Herein, we demonstrate a novel diagnosis system based on an optic fluorescence sensor array for detecting urinary bladder cancer VOCs biomarkers. This study describes a fluorescence-based VOCs sensor array detecting system in detail. The choice of VOCs for the initial part was based on an extensive systematic search of the literature and then followed up using urinary samples from patients with urinary bladder transitional cell carcinoma. Canonical discriminant analysis and partial least squares discriminant analysis (PLS-DA) were employed and correctly detected 31/48 urinary bladder cancer VOC biomarkers and achieved an overall 77.75% sensitivity and 93.25% specificity by PLS-DA modelling. All five urine samples from bladder cancer patients, and five healthy controls were successfully identified with the same sensor arrays. Overall, the experiments in this study describe a real-time platform for non-invasive bladder cancer diagnosis using fluorescence-based gas-sensor arrays. Pure VOCs and urine samples from the patients proved such a system to be promising; however, further research is required using a larger population sample.

摘要

非侵入式膀胱癌检测仍然是一个重大挑战。尿液挥发性有机化合物 (VOCs) 是替代细胞生物标志物的有前途的选择。在此,我们展示了一种基于光学荧光传感器阵列的新型诊断系统,用于检测膀胱癌 VOCs 生物标志物。本研究详细描述了一种基于荧光的 VOCs 传感器阵列检测系统。最初选择的 VOCs 是基于对文献的广泛系统搜索,然后使用膀胱癌移行细胞癌患者的尿液样本进行后续研究。采用典型判别分析和偏最小二乘判别分析(PLS-DA),正确检测到 48 个膀胱癌 VOC 生物标志物中的 31 个,并通过 PLS-DA 模型实现了 77.75%的总体灵敏度和 93.25%的特异性。使用相同的传感器阵列成功识别了 5 例膀胱癌患者和 5 例健康对照者的所有尿液样本。总的来说,本研究中的实验描述了一种使用基于荧光的气体传感器阵列进行非侵入性膀胱癌诊断的实时平台。纯 VOCs 和来自患者的尿液样本证明了该系统具有很大的潜力;然而,需要使用更大的人群样本进行进一步研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fec3/7065633/c01653d1860c/JBIO-12-e201800165-g001.jpg

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