Breath analysis by gas chromatography-mass spectrometry and electronic nose to screen for pleural mesothelioma: a cross-sectional case-control study.
Breath analysis by gas chromatography-mass spectrometry and electronic nose to screen for pleural mesothelioma: a cross-sectional case-control study.
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DOI：
10.18632/oncotarget.21335
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发表时间：
2017-10-31
期刊：
影响因子：
--
通讯作者：
van Meerbeeck JP
中科院分区：
文献类型：
--
作者：
Lamote K;Brinkman P;Vandermeersch L;Vynck M;Sterk PJ;Van Langenhove H;Thas O;Van Cleemput J;Nackaerts K;van Meerbeeck JP
恶性胸膜间皮瘤（MPM）主要是由于以前接触石棉纤维，预后不良。由于暴露和诊断之间的潜伏期较长，MPM发病率预计将在2020-2025年达到峰值。据信，对接触石棉的个人进行筛查可以改善早期发现，从而改善MPM管理。最近的发展集中在用于筛查的呼吸分析上，因为呼吸包含反映细胞代谢的挥发性有机化合物（VOC）。这项横断面病例对照研究的目的是利用气相色谱-质谱（GC-MS）识别MPM患者呼出气中的VOC，并评估呼吸分析，以使用电子鼻（eNose）筛查MPM。从64名受试者中采集呼吸和背景样本：16名健康对照（HC），19名无症状的前石棉暴露（AEx）个体，15名良性石棉相关疾病（ARD）患者和14名MPM患者。用GC-MS和eNose分析样品。使用GC-MS，AEx个体与MPM患者区分的准确率为97%，乙醚，柠檬烯，壬醛，甲基环戊烷和环己烷作为重要的VOCs。这通过eNose分析得到了验证。通过GC-MS和eNose将MPM患者与AEx+ARD参与者区分开来，准确率分别为94%和74%。GC-MS法的敏感性、特异性、阳性预测值和阴性预测值分别为100%、91%、82%和100%，eNose法分别为82%、55%、82%和55%。这项研究表明，通过GC-MS和呼出VOC的eNose分析，可以准确区分MPM患者和无症状石棉暴露风险人群，并为MPM筛查提供呼吸分析的原理证明。
Malignant pleural mesothelioma (MPM) is mainly caused by previous exposure to asbestos fibers and has a poor prognosis. Due to a long latency period between exposure and diagnosis, MPM incidence is expected to peak between 2020-2025. Screening of asbestos-exposed individuals is believed to improve early detection and hence, MPM management. Recent developments focus on breath analysis for screening since breath contains volatile organic compounds (VOCs) which reflect the cell’s metabolism. The goal of this cross-sectional, case-control study is to identify VOCs in exhaled breath of MPM patients with gas chromatography-mass spectrometry (GC-MS) and to assess breath analysis to screen for MPM using an electronic nose (eNose). Breath and background samples were taken from 64 subjects: 16 healthy controls (HC), 19 asymptomatic former asbestos-exposed (AEx) individuals, 15 patients with benign asbestos-related diseases (ARD) and 14 MPM patients. Samples were analyzed with both GC-MS and eNose. Using GC-MS, AEx individuals were discriminated from MPM patients with 97% accuracy, with diethyl ether, limonene, nonanal, methylcyclopentane and cyclohexane as important VOCs. This was validated by eNose analysis. MPM patients were discriminated from AEx+ARD participants by GC-MS and eNose with 94% and 74% accuracy, respectively. The sensitivity, specificity, positive and negative predictive values were 100%, 91%, 82%, 100% for GC-MS and 82%, 55%, 82%, 55% for eNose, respectively. This study shows accurate discrimination of patients with MPM from asymptomatic asbestos-exposed persons at risk by GC-MS and eNose analysis of exhaled VOCs and provides proof-of-principle of breath analysis for MPM screening.
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影响因子：
3.8
作者：
Lamote, Kevin;Nackaerts, Kristiaan;van Meerbeeck, Jan P.
通讯作者：
van Meerbeeck, Jan P.
DOI：
10.1007/s12127-011-0078-5
发表时间：
2011-12-01
影响因子：
--
作者：
Baumbach, J. I.;Maddula, S.;Darwiche, K.
通讯作者：
Darwiche, K.
影响因子：
168.9
作者：
Phillips, M;Gleeson, K;McVay, WP
通讯作者：
McVay, WP
DOI：
10.1056/nejmoa1115050
发表时间：
2012-10-11
期刊：
The New England journal of medicine
影响因子：
--
作者：
Pass HI;Levin SM;Harbut MR;Melamed J;Chiriboga L;Donington J;Huflejt M;Carbone M;Chia D;Goodglick L;Goodman GE;Thornquist MD;Liu G;de Perrot M;Tsao MS;Goparaju C
通讯作者：
Goparaju C
影响因子：
3.8
作者：
Lamote, Kevin;Vynck, Matthijs;van Meerbeeck, Jan P.
通讯作者：
van Meerbeeck, Jan P.