Matsumori Sei, Hashimoto Takashi, Nasu Motomi, Kaga Naoko, Taka Hikari, Fujimura Tsutomu, Ueno Takashi, Miura Yoshiki, Kajiyama Yoshiaki
Juntendo Iji Zasshi. 2022 Oct 4;68(5):499-504. doi: 10.14789/jmj.JMJ22-0023-OA. eCollection 2022.
Since esophageal carcinoma progresses asymptomatically, for many patients the disease is already advanced at the time of diagnosis. The main methods that are currently used to diagnose esophageal carcinoma are upper gastrointestinal radiographic contrast examinations and upper gastrointestinal endoscopy, but early discovery of this disease remains difficult. There is a need to develop a diagnostic method using biomarkers that is non-invasive while both highly sensitive and specific.
Exhaled breath was collected from 17 patients with esophageal squamous cell carcinoma (ESCC), as well as 9 control subjects without history of any cancer. For each fasting subject, 1L of exhaled breath was collected in a gas sampling bag. Volatile organic compounds (VOCs) were then extracted from each sample using Solid phase micro-extraction (SPME) fibers and analyzed by gas chromatography-mass spectrometry (GC-MS).
Levels of acetonitrile, acetic acid, acetone, and 2-butanone in exhaled breath were significantly higher in the patient group than in the control group (p = 0.0037, 0.0024, 0.0024 and 0.0037, respectively). ROC curves were drawn for these 4 VOCs, and the results for the area-under-the-curve (AUC) indicated that ESCC patients can be identified with a high probability of 0.93.
We found distinctive VOCs in exhaled breath of ESCC patients. These VOCs have a potential as new clinical biomarkers for ESCC. The measurement of VOCs in exhaled breath may be a useful, non-invasive method for diagnosis of ESCC.
由于食管癌在无症状的情况下进展,许多患者在诊断时疾病已处于晚期。目前用于诊断食管癌的主要方法是上消化道造影检查和上消化道内镜检查,但早期发现这种疾病仍然困难。有必要开发一种使用生物标志物的诊断方法,该方法既无创又具有高敏感性和特异性。
收集了17例食管鳞状细胞癌(ESCC)患者以及9例无任何癌症病史的对照受试者的呼出气体。对于每位空腹受试者,在气体采样袋中收集1L呼出气体。然后使用固相微萃取(SPME)纤维从每个样品中提取挥发性有机化合物(VOCs),并通过气相色谱 - 质谱联用(GC - MS)进行分析。
患者组呼出气体中乙腈、乙酸、丙酮和2 - 丁酮的水平显著高于对照组(分别为p = 0.0037、0.0024、0.0024和0.0037)。针对这4种VOCs绘制了受试者工作特征曲线(ROC曲线),曲线下面积(AUC)结果表明,ESCC患者能够以0.93的高概率被识别出来。
我们在ESCC患者的呼出气体中发现了独特的VOCs。这些VOCs有潜力成为ESCC新的临床生物标志物。测量呼出气体中的VOCs可能是一种用于诊断ESCC的有用的无创方法。