학술논문

Exhaled breath condensate biomarkers for the early diagnosis of lung cancer using proteomics
Document Type
Report
Author abstract
Source
American Journal of Physiology (Consolidated). Oct, 2017, Vol. 313 Issue 4, pL664, 13 p.
Subject
Lung cancer -- Physiological aspects
Lung cancer -- Diagnosis
Biological markers -- Physiological aspects
Breath tests -- Methods
Breath tests -- Usage
Biological sciences
Language
English
ISSN
0002-9513
Abstract
We explored whether the proteomic analysis of exhaled breath condensate (EBC) may provide biomarkers for noninvasive screening for the early detection of lung cancer (LC). EBC was collected from 192 individuals [49 control (C), 49 risk factor-smoking (S), 46 chronic obstructive pulmonary disease (COPD) and 48 LC], With the use of liquid chromatography and tandem mass spectrometry, 348 different proteins with a different pattern among the four groups were identified in EBC samples. Significantly more proteins were identified in the EBC from LC compared with other groups (C: 12.4 [+ or -] 1.3; S: 15.3 [+ or -] 1; COPD: 14 [+ or -] 1.6; LC: 24.2 [+ or -] 3.6; P = 0.0001). Furthermore, the average number of proteins identified per sample was significantly higher in LC patients, and receiver operating characteristic curve (ROC) analysis showed an area under the curve of 0.8, indicating diagnostic value. Proteins frequently detected in EBC, such as dermcidin and hornerin, along with others much less frequently detected, such as hemoglobin and histones, were identified. Cytokeratins (KRTs) were the most abundant proteins in EBC samples, and levels of KRT6A, KRT6B, and KRT6C isoforms were significantly higher in samples from LC patients (P = 0.0031, 0.0011, and 0.0009, respectively). Moreover, the amount of most KRTs in EBC samples from LC patients showed a significant positive correlation with tumor size. Finally, we used a random forest algorithm to generate a robust model using EBC protein data for the diagnosis of patients with LC where the area under the ROC curve obtained indicated a good classification (82%). Thus this study demonstrates that the proteomic analysis of EBC samples is an appropriated approach to develop biomarkers for the diagnosis of lung cancer. proteome; noninvasive technique; pulmonary disease doi: 10.1152/ajplung.001119.2017.

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