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An integromic signature for lung cancer early detection

We previously developed three microRNAs (miRs-21, 210, and 486-5p), two long noncoding RNAs (lncRNAs) (SNHG1 and RMRP), and two fucosyltransferase (FUT) genes (FUT8 and POFUT1) as potential plasma biomarkers for lung cancer. However, the diagnostic performance of the individual panels is not suffici...

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Autores principales: Leng, Qixin, Lin, Yanli, Zhan, Min, Jiang, Feng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals LLC 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5973873/
https://www.ncbi.nlm.nih.gov/pubmed/29872497
http://dx.doi.org/10.18632/oncotarget.25227
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author Leng, Qixin
Lin, Yanli
Zhan, Min
Jiang, Feng
author_facet Leng, Qixin
Lin, Yanli
Zhan, Min
Jiang, Feng
author_sort Leng, Qixin
collection PubMed
description We previously developed three microRNAs (miRs-21, 210, and 486-5p), two long noncoding RNAs (lncRNAs) (SNHG1 and RMRP), and two fucosyltransferase (FUT) genes (FUT8 and POFUT1) as potential plasma biomarkers for lung cancer. However, the diagnostic performance of the individual panels is not sufficient to be used in the clinics. Given the heterogeneity of lung tumors developed from multifactorial molecular aberrations, we determine whether integrating the different classes of molecular biomarkers can improve diagnosis of lung cancer. By using droplet digital PCR, we analyze expression of the seven genes in plasma of a development cohort of 64 lung cancer patients and 33 cancer-free individuals. The panels of three miRNAs (miRs-21, 210, and 486-5p), two lncRNAs (SNHG1 and RMRP), and two FUTs (FUT8 and POFUT1) have a sensitivity of 81-86% and a specificity of 84-87% for diagnosis of lung cancer. From the seven genes, an integromic plasma signature comprising miR-210, SNHG1, and FUT8 is developed that produces higher sensitivity (95.45%) and specificity (96.97%) compared with the individual biomarker panels (all p<0.05). The diagnostic value of the signature was confirmed in a validation cohort of 40 lung cancer patients and 29 controls, independent of stage and histological type of lung tumor, and patients’ age, sex, and smoking status (all p>0.05). The integration of the different categories of biomarkers might improve diagnosis of lung cancer.
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spelling pubmed-59738732018-06-05 An integromic signature for lung cancer early detection Leng, Qixin Lin, Yanli Zhan, Min Jiang, Feng Oncotarget Research Paper We previously developed three microRNAs (miRs-21, 210, and 486-5p), two long noncoding RNAs (lncRNAs) (SNHG1 and RMRP), and two fucosyltransferase (FUT) genes (FUT8 and POFUT1) as potential plasma biomarkers for lung cancer. However, the diagnostic performance of the individual panels is not sufficient to be used in the clinics. Given the heterogeneity of lung tumors developed from multifactorial molecular aberrations, we determine whether integrating the different classes of molecular biomarkers can improve diagnosis of lung cancer. By using droplet digital PCR, we analyze expression of the seven genes in plasma of a development cohort of 64 lung cancer patients and 33 cancer-free individuals. The panels of three miRNAs (miRs-21, 210, and 486-5p), two lncRNAs (SNHG1 and RMRP), and two FUTs (FUT8 and POFUT1) have a sensitivity of 81-86% and a specificity of 84-87% for diagnosis of lung cancer. From the seven genes, an integromic plasma signature comprising miR-210, SNHG1, and FUT8 is developed that produces higher sensitivity (95.45%) and specificity (96.97%) compared with the individual biomarker panels (all p<0.05). The diagnostic value of the signature was confirmed in a validation cohort of 40 lung cancer patients and 29 controls, independent of stage and histological type of lung tumor, and patients’ age, sex, and smoking status (all p>0.05). The integration of the different categories of biomarkers might improve diagnosis of lung cancer. Impact Journals LLC 2018-05-15 /pmc/articles/PMC5973873/ /pubmed/29872497 http://dx.doi.org/10.18632/oncotarget.25227 Text en Copyright: © 2018 Leng et al. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/) 3.0 (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Paper
Leng, Qixin
Lin, Yanli
Zhan, Min
Jiang, Feng
An integromic signature for lung cancer early detection
title An integromic signature for lung cancer early detection
title_full An integromic signature for lung cancer early detection
title_fullStr An integromic signature for lung cancer early detection
title_full_unstemmed An integromic signature for lung cancer early detection
title_short An integromic signature for lung cancer early detection
title_sort integromic signature for lung cancer early detection
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5973873/
https://www.ncbi.nlm.nih.gov/pubmed/29872497
http://dx.doi.org/10.18632/oncotarget.25227
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