Abstract 2797: Proteomic signature in exhaled breath condensates for a non-invasive diagnostics of lung cancer

Abstract Because of the invasiveness of examination methods as bronchoscopy for the diagnosis of lung cancer, there is currently no preventive screening for this disease. Thus, lung cancer is usually diagnosed in stage 3 or 4, when it is too late for successful treatment. However, if diagnosed early, it can be cured entirely. Therefore, it is necessary to find a suitable method to screen the high-risk populations and reveal lung cancer in the early stages. Since the mucous membranes of the respiratory tract are naturally moistened by fluids containing proteins, metabolites, chemoattractants and growth factors released by the highly active epithelium, the collection of the respiratory tract fluids can be used to diagnose malignant and benign respiratory tract diseases. The most commonly used method in this sense is bronchoalveolar lavage. However, the technique itself is not pleasant and can be accompanied by possible complications. Therefore, intensive research work is conducted to develop non-invasive methods for biomarker detection in exhaled breath, sputum, saliva or nasal secretion. We have studied an exhaled breath condensate (EBC) matrix, which is collected non-invasively and the patients are not suffering from its collection. Several studies have reported proteomic analysis of EBC while identifying low hundreds of proteins by mass spectrometry (MS). We have developed a potent gel-free MS-based approach for sample preparation and analysis. Together with a powerful search tool, we were able to identify a ten times higher number of proteins across a comparable group of individuals of about three hundred peoples’ samples. Our approach seems to be highly reproducible and applicable to various respiratory and systemic diseases. In our work focused on non-small lung cancer biomarkers compared to chronic obstructive pulmonary disease (COPD) and healthy controls, we have identified 7694 proteins and of them, 6525 proteins were quantified at least in one replicate across 296 individuals’ samples measured in triplicates. Combining univariate and multivariate statistical approaches and sensitivity analysis, we have suggested biomarkers that could distinguish lung cancer patients from COPD and healthy individuals. This research was supported by grants from the Czech Ministry of Education, Youth and Sports (EATRIS-CZ - LM2018133), European Regional Development Fund - Project ENOCH (No. CZ.02.1.01/0.0/0.0/16_019/0000868) and IGA_LF_2021_036 (Palacky University in Olomouc). Citation Format: Jana Vaclavkova, Jana Vrbkova, Pavla Kourilova, Dusan Holub, Juraj Kultan, Petr Jakubec, Ondrej Fischer, Frantisek Kopriva, Vendula Latalova, Tatiana Gvozdiakova, Marian Hajduch, Petr Dzubak. Proteomic signature in exhaled breath condensates for a non-invasive diagnostics of lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2797.