Assessment of Circulating microRNAs in Plasma of Lung Cancer Patients
Lung cancer is the most common cause of cancer deaths worldwide and numerous ongoing research efforts are directed to identify new strategies for its early detection. The development of non-invasive blood-based biomarkers for cancer detection in its preclinical phases is crucial to improve the outco...
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Published in | Molecules (Basel, Switzerland) Vol. 19; no. 3; pp. 3038 - 3054 |
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Main Authors | , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Switzerland
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10.03.2014
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ISSN | 1420-3049 1420-3049 |
DOI | 10.3390/molecules19033038 |
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Abstract | Lung cancer is the most common cause of cancer deaths worldwide and numerous ongoing research efforts are directed to identify new strategies for its early detection. The development of non-invasive blood-based biomarkers for cancer detection in its preclinical phases is crucial to improve the outcome of this deadly disease. MicroRNAs (miRNAs) are a new promising class of circulating biomarkers for cancer detection and prognosis definition, but lack of consensus on data normalization methods for circulating miRNAs and the critical issue of haemolysis, has affected the identification of circulating miRNAs with diagnostic potential. We describe here an interesting approach for profiling circulating miRNAs in plasma samples based on the evaluation of reciprocal miRNA levels measured by quantitative Real-Time PCR. By monitoring changes of plasma miRNA-ratios, it is possible to assess the deregulation of tumor-related miRNAs and identify signatures with diagnostic and prognostic value. In addition, to avoid bias due to the release of miRNAs from blood cells, a miRNA-ratios signature distinguishing haemolyzed samples was identified. The method described was validated in plasma samples of lung cancer patients, but given its reproducibility and reliability, could be potentially applied for the identification of diagnostic circulating miRNAs in other diseases. |
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AbstractList | Lung cancer is the most common cause of cancer deaths worldwide and numerous ongoing research efforts are directed to identify new strategies for its early detection. The development of non-invasive blood-based biomarkers for cancer detection in its preclinical phases is crucial to improve the outcome of this deadly disease. MicroRNAs (miRNAs) are a new promising class of circulating biomarkers for cancer detection and prognosis definition, but lack of consensus on data normalization methods for circulating miRNAs and the critical issue of haemolysis, has affected the identification of circulating miRNAs with diagnostic potential. We describe here an interesting approach for profiling circulating miRNAs in plasma samples based on the evaluation of reciprocal miRNA levels measured by quantitative Real-Time PCR. By monitoring changes of plasma miRNA-ratios, it is possible to assess the deregulation of tumor-related miRNAs and identify signatures with diagnostic and prognostic value. In addition, to avoid bias due to the release of miRNAs from blood cells, a miRNA-ratios signature distinguishing haemolyzed samples was identified. The method described was validated in plasma samples of lung cancer patients, but given its reproducibility and reliability, could be potentially applied for the identification of diagnostic circulating miRNAs in other diseases.Lung cancer is the most common cause of cancer deaths worldwide and numerous ongoing research efforts are directed to identify new strategies for its early detection. The development of non-invasive blood-based biomarkers for cancer detection in its preclinical phases is crucial to improve the outcome of this deadly disease. MicroRNAs (miRNAs) are a new promising class of circulating biomarkers for cancer detection and prognosis definition, but lack of consensus on data normalization methods for circulating miRNAs and the critical issue of haemolysis, has affected the identification of circulating miRNAs with diagnostic potential. We describe here an interesting approach for profiling circulating miRNAs in plasma samples based on the evaluation of reciprocal miRNA levels measured by quantitative Real-Time PCR. By monitoring changes of plasma miRNA-ratios, it is possible to assess the deregulation of tumor-related miRNAs and identify signatures with diagnostic and prognostic value. In addition, to avoid bias due to the release of miRNAs from blood cells, a miRNA-ratios signature distinguishing haemolyzed samples was identified. The method described was validated in plasma samples of lung cancer patients, but given its reproducibility and reliability, could be potentially applied for the identification of diagnostic circulating miRNAs in other diseases. Lung cancer is the most common cause of cancer deaths worldwide and numerous ongoing research efforts are directed to identify new strategies for its early detection. The development of non-invasive blood-based biomarkers for cancer detection in its preclinical phases is crucial to improve the outcome of this deadly disease. MicroRNAs (miRNAs) are a new promising class of circulating biomarkers for cancer detection and prognosis definition, but lack of consensus on data normalization methods for circulating miRNAs and the critical issue of haemolysis, has affected the identification of circulating miRNAs with diagnostic potential. We describe here an interesting approach for profiling circulating miRNAs in plasma samples based on the evaluation of reciprocal miRNA levels measured by quantitative Real-Time PCR. By monitoring changes of plasma miRNA-ratios, it is possible to assess the deregulation of tumor-related miRNAs and identify signatures with diagnostic and prognostic value. In addition, to avoid bias due to the release of miRNAs from blood cells, a miRNA-ratios signature distinguishing haemolyzed samples was identified. The method described was validated in plasma samples of lung cancer patients, but given its reproducibility and reliability, could be potentially applied for the identification of diagnostic circulating miRNAs in other diseases. |
Author | Sozzi, Gabriella Suatoni, Paola Boeri, Mattia Mensah, Mavis Pastorino, Ugo Verri, Carla Conte, Davide Fortunato, Orazio |
AuthorAffiliation | 1 Tumor Genomics Unit, Department of Experimental Oncology and Molecular Medicine, Fondazione IRCCS Istituto Nazionale dei Tumori, via Venezian 1, Milan 20133, Italy; E-Mails: orazio.fortunato@istitutotumori.mi.it (O.F.); mattia.boeri@istitutotumori.mi.it (M.B.); carla.verri@istitutotumori.mi.it (C.V.); davide.conte@istitutotumori.mi.it (D.C.); mensah.mavis@istitutotumori.mi.it (M.M.) 2 Thoracic Surgery Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, via Venezian 1, Milan 20133, Italy; E-Mails: paola.suatoni@istitutotumori.mi.it (P.S.); ugo.pastorino@istitutotumori.mi.it (U.P.) |
AuthorAffiliation_xml | – name: 1 Tumor Genomics Unit, Department of Experimental Oncology and Molecular Medicine, Fondazione IRCCS Istituto Nazionale dei Tumori, via Venezian 1, Milan 20133, Italy; E-Mails: orazio.fortunato@istitutotumori.mi.it (O.F.); mattia.boeri@istitutotumori.mi.it (M.B.); carla.verri@istitutotumori.mi.it (C.V.); davide.conte@istitutotumori.mi.it (D.C.); mensah.mavis@istitutotumori.mi.it (M.M.) – name: 2 Thoracic Surgery Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, via Venezian 1, Milan 20133, Italy; E-Mails: paola.suatoni@istitutotumori.mi.it (P.S.); ugo.pastorino@istitutotumori.mi.it (U.P.) |
Author_xml | – sequence: 1 givenname: Orazio surname: Fortunato fullname: Fortunato, Orazio – sequence: 2 givenname: Mattia surname: Boeri fullname: Boeri, Mattia – sequence: 3 givenname: Carla orcidid: 0000-0002-1414-799X surname: Verri fullname: Verri, Carla – sequence: 4 givenname: Davide surname: Conte fullname: Conte, Davide – sequence: 5 givenname: Mavis surname: Mensah fullname: Mensah, Mavis – sequence: 6 givenname: Paola surname: Suatoni fullname: Suatoni, Paola – sequence: 7 givenname: Ugo surname: Pastorino fullname: Pastorino, Ugo – sequence: 8 givenname: Gabriella surname: Sozzi fullname: Sozzi, Gabriella |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/24619302$$D View this record in MEDLINE/PubMed |
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SubjectTerms | biomarkers Biomarkers, Tumor Cluster Analysis early diagnosis Gene Expression Profiling haemolysis Hemolysis Humans Lung cancer Lung Neoplasms - blood Lung Neoplasms - genetics MicroRNAs - blood MicroRNAs - genetics miRNAs Quality Control real-time PCR Reproducibility of Results |
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Title | Assessment of Circulating microRNAs in Plasma of Lung Cancer Patients |
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