Early Detection Research Network


Overall, these findings strengthen the observation that circulating miRNA in plasma is detectable well before clinical disease detection by spiral CT, indicating the possibility to select high-risk groups on the basis of miRNA profiling.
Plasma samples collected at surgery or at time of disease detection by spiral CT were compared with pools of disease-free individuals to identify a miRNA profile associated with lung cancer diagnosis. The signature for diagnosis of lung cancer, a panel of 16 ratios involving 13 different miRNAs, classified 16 of 19 patients with a sensitivity of 84% and a specificity of 80% in the training set. In the validation set plasma samples, 12 of 16 patients were correctly discriminated, with a sensitivity of 75% and a specificity of 100% (AUC-ROC = 0.88, P < 0.0001). This diagnostic signature was then used for class prediction of predisease plasma samples in the same series. In the training set, 11 of 20 (55%) cases were classified as individuals with disease and, very interestingly, 10 of these 11 cases were characterized by poor prognosis (dead or alive with disease) or belonged to the group of patients identified from 3rd to 5th y of screening. In the validation set, similar results were obtained, with presence of the disease signature already in 10 of 15 (66.6%) predisease plasma samples.

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