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Lung disease diagnostic method based on proteomic analysis of exhaled breath condensateтезисы доклада
Информация о цитировании статьи получена из
Web of Science
Дата последнего поиска статьи во внешних источниках: 24 февраля 2021 г.
- Авторы: Kononikhin Alexey, Fedorchenko Kristina, Kushaeva Mia, Anaev Eldar, Mitrofanov Sergey, Ryabokon Anna, Popov Igor, Barmin Vitaliy, Indeykina Maria, Pikin Oleg, Nikolaev Evgeny, Varfolomeev Sergey, Chuchalin Alexander
- Сборник: Monitoring airway disease
- Том: 54
- Тезисы
- Год издания: 2019
- Издательство: European Respiratory Society
- Местоположение издательства: Switzerland
- Первая страница: 3583
- Последняя страница: 3583
- DOI: 10.1183/13993003.congress-2019.oa3583
- Аннотация: Abstract Objective: non-invasive approach to differential diagnosis of socially significant lung diseases by analyzing the protein composition of the exhaled breath condensate using ultra-high resolution mass spectrometry. Materials and methods: We examined 19 patients with BA, 32 patients with COPD, 26-with community-acquired pneumonia, 46-with NSCLC and 61 healthy volunteers. EBC was collected using ECoScreen. EBC-samples were lyophilized, hydrolyzed and analyzed by HPLC and tandem mass spectrometry. Results: Based on the study of EBC protein composition of patients with BA, COPD, pneumonia and lung cancer, it was shown that the results of the proteome analysis in groups differ from each other and are consistent with the clinical picture of the diseases under consideration. Protein biomarker panels included human growth hormone and sarcolectin for BA-group; cystatins B and M, annexins A1 and A2, HSP90B1 and laminin for pneumonia group; peroxiredoxin for COPD-group; POTEE, serine/arginine-rich splicing factor 1−6, protein spindly, septin-7 for cancer group. Based on the study of EBC peptide composition a linear analytical model was developed for predicting the presence of lung cancer against the background of other respiratory diseases. The model was cross-validated and showed good prognostic ability. Conclusions: We found that samples of EBC groups of healthy donors, patients with BA, COPD, pneumonia and NSCLC have a characteristic protein spectrum. The identified proteins could be offered as a diagnostic panel for these diseases based on EBC analysis. The identified peptides have been used for developing a diagnostic model for EBC proteomic data. The study was supported by RFBR (project no. 18-29-09158).
- Добавил в систему: Рябоконь Анна Монолитовна