Lamote Kevin, Brinkman Paul, Vandermeersch Lore, Vynck Matthijs, Sterk Peter J, Van Langenhove Herman, Thas Olivier, Van Cleemput Joris, Nackaerts Kristiaan, van Meerbeeck Jan P
Department of Respiratory Medicine, Ghent University Hospital, Ghent, Belgium.
Department of Internal Medicine, Ghent University, Ghent, Belgium.
Oncotarget. 2017 Sep 27;8(53):91593-91602. doi: 10.18632/oncotarget.21335. eCollection 2017 Oct 31.
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
恶性胸膜间皮瘤（MPM）主要由既往接触石棉纤维引起，预后较差。由于接触与诊断之间存在较长的潜伏期，预计MPM发病率将在2020年至2025年达到峰值。对接触石棉的个体进行筛查被认为可改善早期检测，从而改善MPM的管理。近期的进展集中在用于筛查的呼吸分析，因为呼出气体中含有反映细胞代谢的挥发性有机化合物（VOCs）。
本横断面病例对照研究的目的是通过气相色谱 - 质谱联用（GC-MS）鉴定MPM患者呼出气体中的VOCs，并使用电子鼻（eNose）评估用于筛查MPM的呼吸分析。
从64名受试者采集呼出气体和背景样本：16名健康对照（HC）、19名无症状既往接触石棉（AEx）个体、15名患有良性石棉相关疾病（ARD）的患者和14名MPM患者。样本用GC-MS和eNose进行分析。
使用GC-MS，AEx个体与MPM患者的区分准确率为97%，其中乙醚、柠檬烯、壬醛、甲基环戊烷和环己烷为重要的VOCs。这通过eNose分析得到验证。GC-MS和eNose分别以94%和74%的准确率将MPM患者与AEx + ARD参与者区分开来。GC-MS的敏感性、特异性、阳性和阴性预测值分别为100%、91%、82%、100%，eNose的分别为82%、55%、82%、55%。
本研究表明，通过对呼出VOCs进行GC-MS和eNose分析，能够准确区分MPM患者与有风险的无症状石棉接触者，并为MPM筛查的呼吸分析提供了原理证明。
