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M. Boeri

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    MS02 - Stem Cells and Epigenetics in Lung Cancer (ID 19)

    • Event: WCLC 2013
    • Type: Mini Symposia
    • Track: Biology
    • Presentations: 1
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      MS02.3 - Micro-RNA in Lung Cancer (ID 464)

      14:00 - 15:30  |  Author(s): M. Boeri

      • Abstract
      • Presentation
      • Slides

      Lung cancer, for its high incidence and mortality, is the most common cause of death from cancer in many developed countries. In contrast to other cancers, there has been almost no improvement in the 5-year survival rates of lung cancer in the past 30 years, rate just above 10% in Europe, primarily because lung cancer is detected in most cases in an advanced stage. Detecting lung cancer at an earlier stage and, ideally, predicting who will develop the disease and particularly the most aggressive forms of cancer are the biggest challenge. Imaging via low-dose computed tomography (LDCT) scanning is being actively evaluated as a screening tool for early detection of lung cancer in high risk patients but, although the positive results in mortality reduction reported in the large NLST trial (1) were very promising, at present, the real efficacy of LDCT lung cancer screening in heavy smokers remains a controversial issue (2). Nonetheless, the high false positive rates of LDCT, leading to multiple screening rounds, the issue of over-diagnosis, the unnecessary and sometimes harmful diagnostic follow-up and the costs underscore the need for non-invasive complementary biomarkers for standardized use. MicroRNAs are small, non coding, endogenous single–stranded ribonucleic acids with regulatory functions that are involved in tuning of many important pathways, including developmental and oncogenic pathways. Because of their fundamental role in development and differentiation, their involvement in the biological mechanisms underlying tumorigenesis, as well as their low complexity, stability and easily detection, they represent a promising class of tissue and blood-based biomarkers of cancer (3). We explored miRNA expression profiles of lung tumors and normal lung tissues from cases with variable prognosis identified in a completed spiral-CT screening trial with extensive follow-up (4). We found a panel of deregulated miRNAs discriminating normal lung tissue versus lung cancer and significant association of miRNA expression profiles in both tumor and non-involved lung tissue with clinical-pathological characteristics of the patients such as tumor histotype, tumor growth rate, disease free survival. miRNA expression profile in tumor and normal lung tissues from patients identifed in the first two years of the screening, including mainly Stage Ia ADC with excellent survival, was found to be significantly different from the profile of subjects with more aggressive tumors appearing in later years of screening, independently from tumor Stage. Overall these results indicate that, both in tumors and in non involved lung tissues, miRNA signatures are able to discriminate patients according to tumor aggressiveness, independently from Stage and type. We have then investigated mirRNA profiles in plasma samples from cases and controls belonging to two independent LDCT screening trials with extensive follow-up where multiple plasma samples, collected before and at time of disease detection were available. We reported that miRNA profiling in plasma samples collected 1–2 yrs before the onset of disease, at the time of lung cancer detection by LDCT and in disease-free smokers, resulted in the generation of four miRNA signatures with strong predictive, diagnostic, and prognostic potential (4). Overall, these results suggest that plasma miRNA profiles might be helpful in pinpointing those early stage tumors at high risk of aggressive evolution that would need additional treatments. We recently completed a large validation study where the diagnostic performance of the plasma-based miRNA test was retrospectively evaluated in samples prospectively collected from smoker subjects within the MILD trial. In this study, 1,000 consecutive MILD plasma samples collected from June 2009 to July 2010 among lung cancer-free individuals enrolled in the trial and all patients with lung cancer diagnosed by September 2012 (n=85) were obtained. In patients we analyzed plasma samples collected both pre-disease (four to 35 months before lung cancer detection, median lag time of 15 months) and at the time of diagnosis. Custom-made microfluidic cards containing the 24 microRNAs composing the signatures identified in the exploratory study were created, and on each card eight plasma samples were analyzed per time. Since the goal of this study was to combine the plasma miRNA assay with LDCT results, in order to have a clinical useful tool to classify plasma samples, we developed a three-level miRNA signature classifier (MSC) of Low, Intermediate, or High risk of disease with subject categorization to one of these three risk groups based on pre-defined cut-points of positivity for the four different expression signatures of the 24 miRNAs previously identified. The results of this large validation study indicates that MSC is a significant diagnostic instrument for lung cancer detection with prognostic performance and support the combined use of MSC and LDCT to improve the efficacy of lung cancer screening (5). References 1. Kramer BS, Berg CD, Aberle DR et al. Lung cancer screening with low-dose helical CT: results from the National Lung Screening Trial (NLST). J Med Screen. 2011;18:109-111. 2. Pastorino U, Rossi M, Rosato V, Marchianò A, Sverzellati N, Morosi C, Fabbri A, Galeone C, Negri E, Sozzi G, Pelosi G, La Vecchia C. Annual or biennial CT screening versus observation in heavy smokers: 5-year results of the MILD trial. Eur J Cancer Prev. 2012 May;21(3):308-15 3. Boeri M., Pastorino U. and Sozzi G. Role of MicroRNAs in Lung Cancer: MicroRNA Signatures in Cancer Prognosis. Cancer J. 2012 May;18(3):268-74 4. Boeri M, Verri C, Conte D, Roz L, Modena P, Facchinetti F, Calabrò E, Croce CM, Pastorino U, Sozzi G. MicroRNA signatures in tissues and plasma predict development and prognosis of computed tomography detected lung cancer. Proc Natl Acad Sci U S A. 2011 Mar 1;108(9):3713-8. 5. Sozzi G, Boeri M, Rossi M, Verri C, Suatoni P, Bravi F, Roz L, Conte D, Grassi M, Sverzellati N, Marchiano’ A, Negri, La Vecchia C, Pastorino U. Clinical Utility of a Plasma-based microRNA Signature Classifier within Computed Tomography Lung Cancer Screening: A Correlative MILD Trial Study. 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