title: MicroRNA signatures in tissues and plasma predict development and prognosis of computed tomography detected lung cancer.
abstract: The efficacy of computed tomography (CT) screening for early lung cancer detection in heavy smokers is currently being tested by a number of randomized trials. Critical issues remain the frequency of unnecessary treatments and impact on mortality, indicating the need for biomarkers of aggressive disease. We explored microRNA (miRNA) expression profiles of lung tumors, normal lung tissues and plasma samples from cases with variable prognosis identified in a completed spiral-CT screening trial with extensive follow-up. miRNA expression patterns significantly distinguished: (i) tumors from normal lung tissues, (ii) tumor histology and growth rate, (iii) clinical outcome, and (iv) year of lung cancer CT detection. Interestingly, miRNA profiles in normal lung tissues also displayed remarkable associations with clinical features, suggesting the influence of a permissive microenvironment for tumor development. miRNA expression analyses in plasma samples collected 1-2 y before the onset of disease, at the time of CT detection and in disease-free smokers enrolled in the screening trial, resulted in the generation of miRNA signatures with strong predictive, diagnostic, and prognostic potential (area under the ROC curve ≥ 0.85). These signatures were validated in an independent cohort from a second randomized spiral-CT trial. These results indicate a role for miRNAs in lung tissues and plasma as molecular predictors of lung cancer development and aggressiveness and have theoretical and clinical implication for lung cancer management.
authors.affiliation: Tumor Genomics Unit, Department of Experimental Oncology and Molecular Medicine, and Unit of Thoracic Surgery, Fondazione IRCCS Istituto Nazionale Tumori, 20133 Milan, Italy.
authors.forename: Mattia
authors.initials: M
authors.lastname: Boeri
authors.forename: Carla
authors.initials: C
authors.lastname: Verri
authors.forename: Davide
authors.initials: D
authors.lastname: Conte
authors.forename: Luca
authors.initials: L
authors.lastname: Roz
authors.forename: Piergiorgio
authors.initials: P
authors.lastname: Modena
authors.forename: Federica
authors.initials: F
authors.lastname: Facchinetti
authors.forename: Elisa
authors.initials: E
authors.lastname: Calabrò
authors.forename: Carlo M
authors.initials: CM
authors.lastname: Croce
authors.forename: Ugo
authors.initials: U
authors.lastname: Pastorino
authors.forename: Gabriella
authors.initials: G
authors.lastname: Sozzi
mesh_terms: D016000:Cluster Analysis; D015331:Cohort Studies; D019295:Computational Biology; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic; D006801:Humans; D007558:Italy; D053208:Kaplan-Meier Estimate; D008168:Lung / Q000378:metabolism* / Q000473:pathology; D008175:Lung Neoplasms / Q000097:blood / Q000000981:diagnostic imaging* / Q000235:genetics*; D035683:MicroRNAs / Q000097:blood* / Q000235:genetics* / Q000378:metabolism; D009928:Organ Specificity / Q000235:genetics; D011379:Prognosis; D015203:Reproducibility of Results; D013997:Time Factors; D014057:Tomography, X-Ray Computed
chemical_list: D035683:MicroRNAs