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M. Sugimoto
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P2.02 - Biology/Pathology (ID 616)
- Event: WCLC 2017
- Type: Poster Session with Presenters Present
- Track: Biology/Pathology
- Presentations: 1
- Moderators:
- Coordinates: 10/17/2017, 09:30 - 16:00, Exhibit Hall (Hall B + C)
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P2.02-009 - Metabolomic Analysis in Lung Cancer (ID 8521)
09:30 - 09:30 | Author(s): M. Sugimoto
- Abstract
Background:
Metabolomics measures low weight molecules, generally called metabolites, and it is an effective technique to understand how metabolism is changed by various factors, including environment and disease, particularly malignant disease. Body fluids, for example sputum or urine, harvested non-invasively havebeen used in remarkable recent developments of omics analysis technology, yielding highly precise results for diagnosis of oral cancer, breast cancer, and pancreatic cancer. Metabolomic analysis has begun to be reported based on the pattern information of metabolites. It can be used for practical clinical early detection of carcinoma of various organs. However, practical metabolomic analysis regarding lung cancer has not been repored yet. We used surgically resected specimen of lung cancer to analyze and clarify metabolomics as an aspect of lung cancer.
Method:
We obtained resected specimens from patients with lung cancer after obtaining informed consent for this study, and compared the metabolism profile of the normal tissue portion with carcinoma tissue in 80 patients in terms of various clinical aspects. Metabolomic analysis was performed by capillary electrophoresis / time-of-flight mass spectrometry (CE-TOFMS) of metabolites of the lung tissue and analysed ionized tissue which contained the most main metabolites.
Result:
Analysis of serum and metabolite organization by CE-TOFMS revealed that the intermediate metabolite levels of several pathways changed markedly in lung cancer tissue. We can identify a characteristic metabolic marker in advanced lung cancer tissue with metabolomic clinical information by analysing the association with the overall metabolism profile.
Conclusion:
We identified metabolomic biomarkers which were characteristic of lung cancer using resected tissue in this study. At present, we are analysing various body fluids for analysis of lung cancer cases including prognostic implications. Applications to non-invasive, simple, easy and cheap cancer screening are expected in the future.
