Proteomics of exhaled breath condensate in lung cancer and controls using data-independent acquisition (DIA): a pilot study

Author(s):  
Lin Ma ◽  
Joshua Muscat ◽  
Raghu Sinha ◽  
Dongxiao Sun ◽  
Guangli Xiu
Lung Cancer ◽  
2010 ◽  
Vol 67 (1) ◽  
pp. 108-113 ◽  
Author(s):  
Giovanna E. Carpagnano ◽  
Antonio Spanevello ◽  
Grazia P. Palladino ◽  
Claudia Gramiccioni ◽  
Cinzia Ruggieri ◽  
...  

2018 ◽  
Vol 61 (1) ◽  
pp. 8-16
Author(s):  
Eva Peterová ◽  
Jaroslav Chládek ◽  
Darina Kohoutová ◽  
Veronika Knoblochová ◽  
Paula Morávková ◽  
...  

Analysis of Exhaled breath condensate (EBC) is a re-discovered approach to monitoring the course of the disease and reduce invasive methods of patient investigation. However, the major disadvantage and shortcoming of the EBC is lack of reliable and reproducible standardization of the method. Despite many articles published on EBC, until now there is no clear consensus on whether the analysis of EBC can provide a clue to diagnosis of the diseases. The purpose of this paper is to investigate our own method, to search for possible standardization and to obtain our own initial experience. Thirty healthy volunteers provided the EBC, in which we monitored the density, pH, protein, chloride and urea concentration. Our results show that EBC pH is influenced by smoking, and urea concentrations are affected by the gender of subjects. Age of subjects does not play a role. The smallest coefficient of variation between individual volunteers is for density determination. Current limitations of EBC measurements are the low concentration of many biomarkers. Standardization needs to be specific for each individual biomarker, with focusing on optimal condensate collection. EBC analysis has a potential become diagnostic test, not only for lung diseases.


2016 ◽  
Vol 9 ◽  
pp. MRI.S40864 ◽  
Author(s):  
Naseer Ahmed ◽  
Tedros Bezabeh ◽  
Omkar B. Ijare ◽  
Renelle Myers ◽  
Reem Alomran ◽  
...  

Objectives Lung cancer is one of the most lethal cancers. Currently, there are no biomarkers for early detection, monitoring treatment response, and detecting recurrent lung cancer. We undertook this study to determine if 1H magnetic resonance spectroscopy (MRS) of sputum and exhaled breath condensate (EBC), as a noninvasive tool, can identify metabolic biomarkers of lung cancer. Materials and Methods Sputum and EBC samples were collected from 20 patients, comprising patients with pathologically confirmed non-small cell lung cancer ( n = 10) and patients with benign respiratory conditions ( n = 10). Both sputum and EBC samples were collected from 18 patients; 2 patients provided EBC samples only. 1H MR spectra were obtained on a Bruker Avance 400 MHz nuclear magnetic resonance (NMR) spectrometer. Sputum samples were further confirmed cytologically to distinguish between true sputum and saliva. Results In the EBC samples, median concentrations of propionate, ethanol, acetate, and acetone were higher in lung cancer patients compared to the patients with benign conditions. Median concentration of methanol was lower in lung cancer patients (0.028 mM) than in patients with benign conditions (0.067 mM; P = 0.028). In the combined sputum and saliva and the cytologically confirmed sputum samples, median concentrations of N-acetyl sugars, glycoprotein, propionate, lysine, acetate, and formate were lower in the lung cancer patients than in patients with benign conditions. Glucose was found to be consistently absent in the combined sputum and saliva samples (88%) as well as in the cytologically confirmed sputum samples (86%) of lung cancer patients. Conclusion Absence of glucose in sputum and lower concentrations of methanol in EBC of lung cancer patients discerned by 1H MRS may serve as metabolic biomarkers of lung cancer for early detection, monitoring treatment response, and detecting recurrence.


2016 ◽  
Vol 16 (2) ◽  
pp. 550-558 ◽  
Author(s):  
Xiaoling Zang ◽  
María Eugenia Monge ◽  
Nael A. McCarty ◽  
Arlene A. Stecenko ◽  
Facundo M. Fernández

2016 ◽  
Vol 71 (2) ◽  
pp. 134-139 ◽  
Author(s):  
K. U. Fedorchenko ◽  
A. M. Ryabokon ◽  
A. S. Kononikhin ◽  
S. I. Mitrofanov ◽  
V. V. Barmin ◽  
...  

2019 ◽  
Vol 13 (4) ◽  
pp. 044002 ◽  
Author(s):  
Annalisa Campanella ◽  
Simona De Summa ◽  
Stefania Tommasi

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