Author of

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  P2.11 - Screening and Early Detection (Not CME Accredited Session) (ID 960)

  • Event: WCLC 2018
  • Type: Poster Viewing in the Exhibit Hall
  • Track:
  • Presentations: 1
  • Moderators:
  • Coordinates: 9/25/2018, 16:45 - 18:00, Exhibit Hall

  • 27134

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    P2.11-12 - Metabolomic Analysis in Lung Cancer for Screening and Early Detection (ID 12131)

    16:45 - 18:00  |  Author(s): Hisayoshi Shimada
    • Abstract
    • Slides

    Background
    

    Metabolomics, a simultaneous measurment technique for hundsleds of low weight molecules, generally called metabolites, is an effective technique to understand how metabolism is changed by various factors, including environment and diseases, particularly malignant diseases. Body fluids, such as urine or saliva, harvested non-invasively have been used in this analytical technology, which yielded a potential of precise diagnosis of various cancers. 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 metabolomic profiles as an aspect of lung cancer.

    a9ded1e5ce5d75814730bb4caaf49419 Method
    

    We obtained blood and saliva from 110 patients with lung cancer after obtaining informed consent for this study and compared the metabolomic profiles of both blood and saliva in 83 who has neither pulmonary disease nor past history of any cancer in terms of various clinical aspects. Metabolomic analysis was performed by capillary electrophoresis time-of-flight mass spectrometry (CE-TOFMS) of metabolites of the blood and saliva, then analysed ionized sample which contained the most metabolites in primary pathways.

    4c3880bb027f159e801041b1021e88e8 Result
    

    Analysis of serum and metabolite organization by CE-TOFMS revealed that the intermediate metabolite levels of several pathways changed markedly in lung cancer blood and saliva. We identified characteristic metabolomic patterns in advanced lung cancer with metabolomic clinical information by analysing the association with the overall metabolism profile.

    8eea62084ca7e541d918e823422bd82e Conclusion
    

    We identified metabolomic biomarkers which were characteristic of lung cancer using blood and saliva 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 low-cost cancer screening are expected in the future.

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