MicroRNAs Derived from Circulating Exosomes as Noninvasive Biomarkers for Screening and Diagnosing Lung Cancer Riccardo Cazzoli, PhD, Fiamma Buttitta,

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microRNAs Derived from Circulating Exosomes as Noninvasive Biomarkers for Screening and Diagnosing Lung Cancer Riccardo Cazzoli, PhD, Fiamma Buttitta, MD, PhD, Marta Di Nicola, PhD, Sara Malatesta, MD, Antonio Marchetti, MD, PhD, William N. Rom, MD, MPH, Harvey I. Pass, MD Journal of Thoracic Oncology Volume 8, Issue 9, Pages 1156-1162 (September 2013) DOI: 10.1097/JTO.0b013e318299ac32 Copyright © 2013 International Association for the Study of Lung Cancer Terms and Conditions

FIGURE 1 A and B, Exosome stability in time. We analyzed exosome stability in frozen samples using raw Ct of mir-20a, mir-221, and Let-7a. Graphs show reverse-transcriptase polymerase chain reaction of resulting raw Ct of the same plasma sample, divided in several aliquots and RNA extracted from fresh plasma aliquot and frozen plasma aliquots at 24 hours, 48 hours, 1 week, 1 month, and 2 months. Graph (A) shows raw Cts of the various aliquots and the duplicate tests divided by microRNAs. Graph (B) compares microRNA trends in time. There is no detectable oscillation of microRNA raw Cts from fresh aliquot to the one frozen for 2 months. Journal of Thoracic Oncology 2013 8, 1156-1162DOI: (10.1097/JTO.0b013e318299ac32) Copyright © 2013 International Association for the Study of Lung Cancer Terms and Conditions

FIGURE 2 Overview of microRNA expression levels. After data set normalization, the log10 of 2(−ΔΔCt) was taken each microRNA. The graph shows expression level value of each microRNA, one for lung adenocarcinomas from healthy controls (reported as cancer bars in the graph) and another for lung granulomas from healthy controls (reported as granuloma bars in the graph). Concerning lung granuloma expression levels, three to 14 microRNAs showed slight down-regulation, 10 microRNAs were found up-regulated. miR-151a-5p showed no expression levels compared with normal donors. All 14 microRNAs resulted in up-regulation in lung adenocarcinoma expression levels. Journal of Thoracic Oncology 2013 8, 1156-1162DOI: (10.1097/JTO.0b013e318299ac32) Copyright © 2013 International Association for the Study of Lung Cancer Terms and Conditions

FIGURE 3 Screening model ROC curve. ROC plot for screening model microRNA set. The screening model distinguishes between control subjects and patients with any kind of nodules (lung adenocarcinomas and granulomas) with an area under the curve = 0.908 (p < 0.001). ROC, receiver operating characteristic. Journal of Thoracic Oncology 2013 8, 1156-1162DOI: (10.1097/JTO.0b013e318299ac32) Copyright © 2013 International Association for the Study of Lung Cancer Terms and Conditions

FIGURE 4 Diagnosis model ROC curve. ROC plot for diagnostic model microRNA set. The diagnostic model distinguishes between lung adenocarcinoma and granuloma patients with an area under the curve = 0.760 (p < 0.001). ROC, receiver operating characteristic. Journal of Thoracic Oncology 2013 8, 1156-1162DOI: (10.1097/JTO.0b013e318299ac32) Copyright © 2013 International Association for the Study of Lung Cancer Terms and Conditions