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Exosomal miRs in Lung Cancer: A Mathematical Model

Lung cancer, primarily non-small-cell lung cancer (NSCLC), is the leading cause of cancer deaths in the United States and worldwide. While early detection significantly improves five-year survival, there are no reliable diagnostic tools for early detection. Several exosomal microRNAs (miRs) are over...

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Detalles Bibliográficos
Autores principales: Lai, Xiulan, Friedman, Avner
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5176278/
https://www.ncbi.nlm.nih.gov/pubmed/28002496
http://dx.doi.org/10.1371/journal.pone.0167706
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author Lai, Xiulan
Friedman, Avner
author_facet Lai, Xiulan
Friedman, Avner
author_sort Lai, Xiulan
collection PubMed
description Lung cancer, primarily non-small-cell lung cancer (NSCLC), is the leading cause of cancer deaths in the United States and worldwide. While early detection significantly improves five-year survival, there are no reliable diagnostic tools for early detection. Several exosomal microRNAs (miRs) are overexpressed in NSCLC, and have been suggested as potential biomarkers for early detection. The present paper develops a mathematical model for early stage of NSCLC with emphasis on the role of the three highest overexpressed miRs, namely miR-21, miR-205 and miR-155. Simulations of the model provide quantitative relationships between the tumor volume and the total mass of each of the above miRs in the tumor. Because of the positive correlation between these miRs in the tumor tissue and in the blood, the results of the paper may be viewed as a first step toward establishing a combination of miRs 21, 205, 155 and possibly other miRs as serum biomarkers for early detection of NSCLC.
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spelling pubmed-51762782017-01-04 Exosomal miRs in Lung Cancer: A Mathematical Model Lai, Xiulan Friedman, Avner PLoS One Research Article Lung cancer, primarily non-small-cell lung cancer (NSCLC), is the leading cause of cancer deaths in the United States and worldwide. While early detection significantly improves five-year survival, there are no reliable diagnostic tools for early detection. Several exosomal microRNAs (miRs) are overexpressed in NSCLC, and have been suggested as potential biomarkers for early detection. The present paper develops a mathematical model for early stage of NSCLC with emphasis on the role of the three highest overexpressed miRs, namely miR-21, miR-205 and miR-155. Simulations of the model provide quantitative relationships between the tumor volume and the total mass of each of the above miRs in the tumor. Because of the positive correlation between these miRs in the tumor tissue and in the blood, the results of the paper may be viewed as a first step toward establishing a combination of miRs 21, 205, 155 and possibly other miRs as serum biomarkers for early detection of NSCLC. Public Library of Science 2016-12-21 /pmc/articles/PMC5176278/ /pubmed/28002496 http://dx.doi.org/10.1371/journal.pone.0167706 Text en © 2016 Lai, Friedman http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Lai, Xiulan
Friedman, Avner
Exosomal miRs in Lung Cancer: A Mathematical Model
title Exosomal miRs in Lung Cancer: A Mathematical Model
title_full Exosomal miRs in Lung Cancer: A Mathematical Model
title_fullStr Exosomal miRs in Lung Cancer: A Mathematical Model
title_full_unstemmed Exosomal miRs in Lung Cancer: A Mathematical Model
title_short Exosomal miRs in Lung Cancer: A Mathematical Model
title_sort exosomal mirs in lung cancer: a mathematical model
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5176278/
https://www.ncbi.nlm.nih.gov/pubmed/28002496
http://dx.doi.org/10.1371/journal.pone.0167706
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