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E.J. Sim
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P1.05 - Poster Session with Presenters Present (ID 457)
- Event: WCLC 2016
- Type: Poster Presenters Present
- Track: Early Stage NSCLC
- Presentations: 1
- Moderators:
- Coordinates: 12/05/2016, 14:30 - 15:45, Hall B (Poster Area)
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P1.05-026 - High Resolution Metabolomics on Exhaled Breath Condensate to Discover Lung Cancer's Biomarker (ID 5617)
14:30 - 14:30 | Author(s): E.J. Sim
- Abstract
Background:
Early and non-invasive detection of lung cancer is a desirable prognostic tool for prevention of lung cancer at early stages. Previously, unusual human breath smell of lung cancer patients detected by trained dogs played an important role in early detection of lung cancer. Which suggests that exhaled breath condensate (EBC) is a promising source for searching potential biomarkers in lung cancer patient.
Methods:
EBC sample collected using specific device called R-tube, containing both the volatile organic compounds (VOCs) and non-volatile organic compounds (NVOCs), were obtained from patients with lung cancer (n = 20) and control healthy individuals (n = 5). The EBC samples were applied to high resolution metabolomics (HRM) based LC-MS for comparison of metabolic differences among healthy people and lung cancer patients in order to detect potential biomarkers. The multivariate statistical analysis was performed, including a false discovery rate (FDR) of q=0.05, to determine the significant metabolites between the groups. 2-way hierarchical clustering analysis (HCA) was done for determining the classification of significant features between the control healthy and lung cancer patients. The significant features were annotated using Metlin database (metlin.scripps.edu/) and the identified features were then mapped on the human metabolic pathway of the Kyoto Encyclopedia of Genes and Genomes (KEGG). This study was approved by Korea University Guro Hosipital Institutional review board (KUGH14273)
Results:
Using metablomics-wide associated study (MWAS), metabolic changes among healthy group and lung cancer patients were determined. The 2-way HCA identified the different metabolic profile in lung cancer patients from healthy control. The identified potential biomarkers are Acetophenone (m/z 103.0542, [M+H-H~2~O][+]), P-tolualdehyde (m/z 138.0914, [M+NH4][+]), 2,4,6-Trichlorophenol (m/z 218.9134, [M+Na][+]) and 11(R)-HETE (m/z 343.2233, [M+Na][+]). The top 5 of affected KEGG pathways are Arachidonic acid metabolism, Glycerophospholipid metabolism, Bile secretion, Inflammatory mediator regulation of TRP channels and Tyrosine metabolism.
Conclusion:
Our result shows that Acetophenone, P-tolualdehyde, 2,4,6-Trichlorophenol and 11(R)-HETE are significantly higher in lung cancer patients. Acetophenone and 2,4,6-Trichlorophenol are classified as a Group D human carcinogen approved by US Environmental Protection Agency (EPA), while 11(R)-HETE is associated with Arachidonic acid metabolism and P-tolualdehyde is related to xylene degradation pathway and degradation of aromatic compounds pathway. Our identified metabolites can be the potential biomarkers in EBC for the early and non-invasive detection of lung cancer.
