Author of

• 20156

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  P1.07 - Immunology and Immunotherapy (ID 693)

  • Event: WCLC 2017
  • Type: Poster Session with Presenters Present
  • Track: Immunology and Immunotherapy
  • Presentations: 1
  • Moderators:
  • Coordinates: 10/16/2017, 09:30 - 16:00, Exhibit Hall (Hall B + C)

  • 22704

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    P1.07-036 - LC-HRMS Metabolomics Profiling in Advanced NSCLC Treated with Anti PD-1 Agents. Metabolic Features at Diagnosis and at Response Evaluation (ID 10320)

    09:30 - 16:00  |  Presenting Author(s): Ana Laura Ortega Granados
    • Abstract

    Background:
    Non-small cell lung cancer (NSCLC) is one of the most common cancer types wolrldwide. In the metastatic setting, palliative approaches include chemotherapy and immunotherapy, including anti PD-1 agents, that have become a standard approach in second line, but unfortunately, except for immunohistochemistry of PD-L1, any markers have been established to predict which patients can benefit from anti PD-1 agents. Metabolomics, which is the profiling of metabolites in biofluids, cells and tissues, is applied as a tool for biomarker discovery. The platform more used nowadays is liquid chromatography-mass spectrometry (LC-MS). Our objective is to study blood metabolites of advanced NSCLC patients to establish a profile to differentiate patients with clinical benefit (B-P) or without benefit (NB-P, that is, progressive disease) to anti PD-1 therapy.
    
    Method:
    We have analysed by LC-HRMS of serum samples, performing an untargeted metabolomic analysis from advanced NSCLC before immunotherapy (n= 11 patients, vs 10 healthy controls), at the first radiological evaluation and at the progression. Reverse phase and HILIC chromatographic modes were applied to deal with highly polar as well as hydrophobic as required for untargeted metabolomics. For identification of potential biomarkers, we used in combination two independent variable selection techniques: principal component analysis and Student t test.
    
    Result:
    From the total of 11 patients, 6 had some clinical benefit (partial response or stable disease) and 5 experienced as best response a progressive disease. We observed differences in metabolic profile between patients with NSCLC & healthy controls and B-P & NB-P to anti PD-1 therapy. Six identified metabolites contributed most to the differentiating between B-P and NB-P
    
    Conclusion:
    There are different metabolomic phenotypes among patients B-P and NB-P to anti PD-1 therapy, so our data demonstrates the potential of metabolimics in identifying biomarkers of response to anti PD-1 agents in NSCLC. Further studies may validate a metabolomic signature to allow a prediction of clinical benefit in patients treated with anti PD-1 agents.