Classification of lung cancer histology by gold nanoparticle sensors.
Classification of lung cancer histology by gold nanoparticle sensors.
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DOI：
10.1016/j.nano.2011.10.001
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发表时间：
2012-07
期刊：
影响因子：
--
通讯作者：
Haick H
中科院分区：
文献类型：
--
作者：
Barash O;Peled N;Tisch U;Bunn PA Jr;Hirsch FR;Haick H
我们提出了一种用于肺癌(LC)组织学分类的纳米医学装置。该设备使用金纳米颗粒(GNP)传感器对液晶盒(亚型)顶空中的挥发性有机化合物(VOC)进行分析，该传感器适用于检测通过气相色谱-质谱分析确定的LC特有的VOC谱模式。通过支持向量机分析GNP传感信号，可以显著区分(I)LC和健康细胞；(Ii)小细胞LC和非小细胞LC；以及(Iii)非小细胞LC的两个亚型：腺癌和鳞癌。然后，GNP传感器的分辨能力与每个LC状态的顶空VOCs的化学性质和组成联系在一起。这些概念验证结果可能会彻底改变LC的筛查和诊断，并最终可能使LC亚型的早期和鉴别诊断与可检测到或无法触及的肺结节的诊断成为可能。
We propose a nanomedical device for the classification of lung cancer (LC) histology. The device profiles volatile organic compounds (VOCs) in the headspace of (subtypes of) LC cells, using gold nanoparticle (GNP) sensors that are suitable for detecting LC-specific patterns of VOC profiles, as determined by gas chromatography–mass spectrometry analysis. Analyzing the GNP sensing signals by support vector machine allowed significant discrimination between (i) LC and healthy cells; (ii) small cell LC and non–small cell LC; and between (iii) two subtypes of non–small cell LC: adenocarcinoma and squamous cell carcinoma. The discriminative power of the GNP sensors was then linked with the chemical nature and composition of the headspace VOCs of each LC state. These proof-of-concept findings could totally revolutionize LC screening and diagnosis, and might eventually allow early and differential diagnosis of LC subtypes with detectable or unreachable lung nodules.