Information de reference pour ce titreAccession Number: | 01243894-201103000-00011.
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Author: | Foss, Kristen M. BS *; Sima, Chao PhD *; Ugolini, Donatella BS +++; Neri, Monica PhD [S]; Allen, Kristi E. BS *; Weiss, Glen J. MD *[//]
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Institution: | *Translational Genomics Research Institute, Phoenix, Arizona; +Department of Oncology, Biology and Genetics, University of Genoa, Genoa; ++Unit of Epidemiology, Biostatistics and Clinical Trials, National Cancer Research Institute, Genoa; [S]Rehabilitative Pneumology, IRCCS San Raffaele Pisana, Rome, Italy; and [//]Virginia G. Piper Cancer Center at Scottsdale Healthcare, Scottsdale, Arizona.
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Title: | |
Source: | Journal of Thoracic Oncology. 6(3):482-488, March 2011.
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Abstract: | Introduction: The ability to diagnose non-small cell lung cancer (NSCLC) at an early stage may lead to improved survival. The aim of this study was to identify differentially expressed serum-based microRNAs (miRNAs) between patients with early-stage NSCLC and controls. These miRNAs may serve as biomarkers for NSCLC early detection.
Methods: miRNA profiling was performed on total RNA extracted from serum obtained from 22 individuals (11 controls and 11 patients with early-stage NSCLC). Quantitative polymerase chain reaction (qPCR) was used to validate the profiling results in the discovery set and in a validation set of 31 controls and 22 patients with early-stage NSCLC. Additionally, six matched plasma samples (four NSCLC cases and two controls) and three serum mesothelioma samples were analyzed by qPCR. Receiver operating characteristic curves were generated for each possible combination of the miRNAs measured by qPCR.
Results: The expression of hsa-miR-1254 and hsa-miR-574-5p was significantly increased in the early-stage NSCLC samples with respect to the controls. Receiver operating characteristic curves plotting these two miRNAs were able to discriminate early-stage NSCLC samples from controls with 82% and 77% of sensitivity and specificity, respectively, in the discovery cohort and with 73% and 71% of sensitivity and specificity, respectively, in the validation cohort. The mesothelioma and plasma samples did not seem to classify into either NSCLC or control groups.
Conclusions: Serum miRNAs are differentially expressed between patients with early-stage NSCLC and controls. The utility of miR-1254 and miR-574-5p serum-based biomarkers as minimally invasive screening and triage tools for subsequent diagnostic evaluation warrants additional validation.
(C) 2011International Association for the Study of Lung Cancer
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Author Keywords: | MicroRNAs; Biomarker; Early-stage disease; Non-small cell lung cancer; Early detection.
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References: | 1. Jemal A, Siegel R, Ward E, et al. Cancer statistics, 2009. CA Cancer J Clin 2009;59:225-249.
2. Swensen SJ, Jett JR, Hartman TE, et al. CT screening for lung cancer: five-year prospective experience. Radiology 2005;235:259-265.
3. Henschke CI, Yankelevitz DF, Libby DM, et al. Early lung cancer action project: annual screening using single slice helical CT. Ann NY Acad Sci 2001;952:124-134.
4. Mahadevia PJ, Fleisher LA, Frick KD, et al. Lung cancer screening with helical computed tomography in older adult smokers: a decision and cost effectiveness analysis. JAMA 2003;289:313-322.
5. Bach PB, Jett JR, Pastorino U, et al. Computed tomography screening and lung cancer outcomes. JAMA 2007;297:953-961.
6. Chen X, Ba Y, Ma L, et al. Characterization of microRNAs in serum: a novel class of biomarkers for diagnosis of cancer and other diseases. Cell Res 2008;1-10.
7. Rosenfeld N, Aharonov R, Meiri E, et al. MicroRNAs accurately identify cancer tissue origin. Nat Biotechnol 2008;26:462-469.
8. Lau SK, Boutros PC, Pintilie M, et al. Three-gene prognostic classifier for early-stage non small-cell lung cancer. J Clin Oncol 2007;25:5562-5569.
9. Ugolini D, Neri M, Canessa PA, et al. The CREST biorepository: a tool for molecular epidemiology and translational studies on malignant mesothelioma, lung cancer, and other respiratory tract diseases. Cancer Epidemiol Biomarkers Prev 2008;17:3013-3019.
10. Kroh EM, Parkin RK, Mitchell PS, et al. Analysis of circulating microRNA biomarkers in plasma and serum using quantitative reverse transcription-PCR (qRT-PCR). Methods 2010;50:298-301.
11. Mitchell PS, Parkin RK, Kroh EM, et al. Circulating microRNAs as stable blood-based markers for cancer detection. Proc Natl Acad Sci USA 2008;105:10513-10518.
12. Spira A, Beane JE, Shah V, et al. Airway epithelial gene expression in the diagnostic evaluation of smokers with suspect lung cancer. Nat Med 2007;13:361-366.
13. Showe MK, Vachani A, Kossenkov AV, et al. Gene expression profiles in peripheral blood mononuclear cells can distinguish patients with non-small cell lung cancer from patients with nonmalignant lung disease. Cancer Res 2009;69:9202-9210.
14. Keller A, Leidinger P, Borries A, et al. miRNAs in lung cancer-studying complex finger prints in patient's blood cells by microarray experiments. BMC Cancer 2009;9:353.
15. Ranade AR, Cherba D, Sridhar S, et al. MicroRNA 92a-2*, a biomarker predictive for chemoresistance and prognostic for survival in small cell lung cancer patients. J Thoracic Oncol 2010;5:1273-1278.
16. Patz EF, Campa MJ, Gottlin EB, et al. Panel of serum biomarkers for the diagnosis of lung cancer. J Clin Oncol 2007;25:5578-5583.
17. Young RP, Hopkins RJ, Hay BA, et al. A gene-based risk score for lung cancer susceptibility in smokers and ex-smokers. Postgrad Med J 2009;85:515-524.
18. Yu L, Todd NW, Xing L, et al. Early detection of lung adenocarcinoma in sputum by a panel of microRNA markers. Int J Cancer 2010;127:2870-2878.
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Language: | English.
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Document Type: | Original Articles.
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Journal Subset: | Nursing. Clinical Medicine. Public Health.
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ISSN: | 1556-0864
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DOI Number: | https://dx.doi.org/10.1097/JTO.0...- ouverture dans une nouvelle fenêtre
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