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  P1.11 - Screening and Early Detection (Not CME Accredited Session) (ID 943)

  • Event: WCLC 2018
  • Type: Poster Viewing in the Exhibit Hall
  • Track:
  • Presentations: 1
  • Moderators:
  • Coordinates: 9/24/2018, 16:45 - 18:00, Exhibit Hall

  • 26558

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    P1.11-12 - Interrogation of an Exhaled MicroRNA Panel for Lung Cancer Risk Assessment (ID 14317)

    16:45 - 18:00  |  Presenting Author(s): Simon D Spivack
    • Abstract

    Background
    

    Background: There is a need for non-invasive airway-based biomarkers in lung carcinogenesis for both risk assessment of the ex-smoker, and earlier diagnosis. Exhaled breath condensate (EBC) contains airway lining fluid molecules, including nucleic acids, presumably in part from epithelial cellular origins. MicroRNAs play important regulatory roles in many processes, including carcinogenesis. Here we further develop and begin validation of the detection of microRNAs in EBC from lung cancer patients and controls.

    a9ded1e5ce5d75814730bb4caaf49419 Method
    

    EBC was collected non-invasively, using a handheld commercial RTube® device in a clinical series of ambulatory subjects. We generated a 40 miR panel based on literature-derived microRNAs, bronchial brushed microRNA discovery by collaboration, and a lung parenchymal tissue discovery effort we have performed using microRNA-seq on lung tumors and surrounding non-tumor tissue. The PCR primers were designed using our previously published RNA-specific RT-PCR technique. All samples were run twice with positive and negative controls. Calls was made of individual miR present or absent in a given EBC sample, by one of two replicates being positive. The data were analyzed by random forests.

    4c3880bb027f159e801041b1021e88e8 Result
    

    We applied the panel to EBC from 177 individuals, 89 NSCLC predominantly early stage (I and II) cases and 88 controls of similar smoking history. We used an empirically-derived base clinical model that included age, smoking status, pack-years, quit-years, and underlying lung disease. MicroRNA signatures alone discriminated cases from controls with ROC-AUCs of 0.64-0.76. Both analyses revealed a small set of incrementally informative miRs (e.g., miRs-21**, 33b**, 96*,105*, `130b.3p*, 200a*, 200b**, 205, 212***, 221***, 345***, 767**, 944*, 1269a***, 1293*, 1910**, 3648*, 3662*, where number of ‘*’ implies number of appearances in each of three models). Here some modest incremental case-control discriminant capacity was conferred by the respective microRNA signature over and above the base clinical model. The magnitude of the increment was typically 2-3% [RF AUC 0.84 clinical model=>0.86 clinical+microRNA (all lung cancer histologies, Welch p=1.33e-05); 0.82=>0.84 (adenocarcinomas, Welch p=3.13e-03); 0.84=>0.86 (NSCLC, Welch p=4.10e-05). Quantitative RT-PCR using this platform set-up was not sufficiently robust to further analyze.

    8eea62084ca7e541d918e823422bd82e Conclusion
    

    This new exhaled biomarker platform can yield case-control discriminant microRNA sets. albeit modest in incremental impact as formulated so far. Once quantified, further distilled and validated, our goal is to test this non-invasive biomarker approach to prospective cohorts for non-invasive lung cancer risk assessment, in order to non-invasively better select higher risk individuals to undergo effective CT screening.

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