Lung cancer, the leading cause of cancer mortality worldwide has a poor prognosis. To develop a non-invasive method for early lung cancer detection, exhaled breath condensate (EBC) was explored in this study. EBC samples were collected from lung cancer patients (n = 10) and healthy controls (n = 10), and a proteomic study was performed to identify potential biomarkers. Data-dependent acquisition was used to build the spectral library, and a data-independent acquisition (DIA) approach was applied for quantification of EBC proteomics. A total of 1151 proteins were identified, and several proteins were significantly upregulated in the lung cancer group compared to the control group. The Gene Ontology analysis revealed that most of the proteins were located within several organelles in the cells and were involved in binding and catalytic activity, and the Kyoto Encyclopedia Genes and Genomes results revealed that the proteins were mainly related to organismal systems and human disease. And S100A11, ANXA1, ENO1, and FABP5 might play a vital role in the EBC proteome. In summary, we demonstrated that the DIA-based quantification method was efficient in performing proteomic analysis in individual EBC samples, and some of the proteins might be novel biomarkers for lung cancer.
All Science Journal Classification (ASJC) codes
- Pulmonary and Respiratory Medicine