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N. Ramnath



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    MINI 12 - Biomarkers and Lung Nodule Management (ID 109)

    • Event: WCLC 2015
    • Type: Mini Oral
    • Track: Screening and Early Detection
    • Presentations: 1
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      MINI12.01 - A Novel Serum 4-MicroRNA Signature for Lung Cancer Detection (ID 585)

      16:45 - 16:50  |  Author(s): N. Ramnath

      • Abstract
      • Presentation
      • Slides

      Background:
      Early detection of lung cancer using low-dose CT led to a 20% reduction in mortality. However, this strategy has several limitations including high false-positive rates, potential over-diagnosis, and the potential harm associated with radiation exposure. The aim of this study was to identify differentially-expressed miRNAs in the serum of non-small cell lung cancer (NSCLC) patients that might be a clinically-useful tool for lung cancer early detection.

      Methods:
      We performed miRNA expression profile analysis using TaqMan OpenArray Human panel in a discovery set of 70 serum samples obtained at lung tumor resection including lung adenocarcinoma (AD) and lung squamous carcinoma (SCC) and 22 non-cancer subjects (NC). To construct the diagnostic signature, the miRNA candidates were selected based upon the following criteria: miRNAs significantly up-regulated (adjusted t-test p < 0.001) in the NSCLC tissue and serum as compared to normal lung tissue and NC serum respectively, not overexpressed in circulating blood cells and with Area Under the Curve (AUC) > 0.840 for discriminating stage I LC from NC in the receiver-operating characteristic (ROC) plots. Selected serum miRNAs were then validated by quantitative PCR using an independent validation set of serum samples from LC patients (n=84) and NC (n=23).

      Results:
      Sixty miRNAs were significantly up-regulated and 31 were down-regulated in the serum from NSCLC patients versus NC (adjusted p<0.001). Four miRNAs (miR-193b, miR-301, miR-141 and miR-200b) were selected for validating their diagnostic value in an independent cohort. A diagnostic signature was obtained by logistic regression based upon the expression values of these 4 serum miRNAs in the discovery set. This miRNA signature generated an AUC of 0.985 (95% CI 0.961 – 1.000, p < 0.001) for detecting NSCLC (all stages) and of 0.989 (95% CI 0.967 – 1.000, p < 0.001) for detecting stage I NSCLC in the discovery set. In the test set, the diagnostic utility of this miRNA signature was validated and exhibited an AUC of 0.993 (95% CI 0.979 – 1.000, p < 0.001).

      Conclusion:
      We identified a serum 4-miRNA signature that discriminated with high accuracy lung cancer patients from NC. Further prospective validation of this miRNA signature is warranted using an independent cohort of serum samples from patients who participated in a lung cancer screening program.

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