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Emerging non-invasive detection methodologies for lung cancer

The potential for non-invasive lung cancer (LC) diagnosis based on molecular, cellular and volatile biomarkers has been attracting increasing attention, with the development of advanced techniques and methodologies. It is standard practice to tailor the treatments of LC for certain specific genetic...

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Detalles Bibliográficos
Autores principales: Li, Zhen, Shu, Jinian, Yang, Bo, Zhang, Zuojian, Huang, Jingyun, Chen, Yang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: D.A. Spandidos 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7115116/
https://www.ncbi.nlm.nih.gov/pubmed/32269611
http://dx.doi.org/10.3892/ol.2020.11460
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author Li, Zhen
Shu, Jinian
Yang, Bo
Zhang, Zuojian
Huang, Jingyun
Chen, Yang
author_facet Li, Zhen
Shu, Jinian
Yang, Bo
Zhang, Zuojian
Huang, Jingyun
Chen, Yang
author_sort Li, Zhen
collection PubMed
description The potential for non-invasive lung cancer (LC) diagnosis based on molecular, cellular and volatile biomarkers has been attracting increasing attention, with the development of advanced techniques and methodologies. It is standard practice to tailor the treatments of LC for certain specific genetic alterations, including the epidermal growth factor receptor, anaplastic lymphoma kinase and BRAF genes. Despite these advances, little is known about the internal mechanisms of different types of biomarkers and the involvement of their related biochemical pathways during the development of LC. The development of faster and more effective techniques is essential for the identification of different biomarkers. The present review summarizes some of the latest methods used for detecting molecular, cellular and volatile biomarkers in LC and their potential use in clinical diagnosis and targeted therapy.
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spelling pubmed-71151162020-04-08 Emerging non-invasive detection methodologies for lung cancer Li, Zhen Shu, Jinian Yang, Bo Zhang, Zuojian Huang, Jingyun Chen, Yang Oncol Lett Review The potential for non-invasive lung cancer (LC) diagnosis based on molecular, cellular and volatile biomarkers has been attracting increasing attention, with the development of advanced techniques and methodologies. It is standard practice to tailor the treatments of LC for certain specific genetic alterations, including the epidermal growth factor receptor, anaplastic lymphoma kinase and BRAF genes. Despite these advances, little is known about the internal mechanisms of different types of biomarkers and the involvement of their related biochemical pathways during the development of LC. The development of faster and more effective techniques is essential for the identification of different biomarkers. The present review summarizes some of the latest methods used for detecting molecular, cellular and volatile biomarkers in LC and their potential use in clinical diagnosis and targeted therapy. D.A. Spandidos 2020-05 2020-03-12 /pmc/articles/PMC7115116/ /pubmed/32269611 http://dx.doi.org/10.3892/ol.2020.11460 Text en Copyright: © Li et al. This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
spellingShingle Review
Li, Zhen
Shu, Jinian
Yang, Bo
Zhang, Zuojian
Huang, Jingyun
Chen, Yang
Emerging non-invasive detection methodologies for lung cancer
title Emerging non-invasive detection methodologies for lung cancer
title_full Emerging non-invasive detection methodologies for lung cancer
title_fullStr Emerging non-invasive detection methodologies for lung cancer
title_full_unstemmed Emerging non-invasive detection methodologies for lung cancer
title_short Emerging non-invasive detection methodologies for lung cancer
title_sort emerging non-invasive detection methodologies for lung cancer
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7115116/
https://www.ncbi.nlm.nih.gov/pubmed/32269611
http://dx.doi.org/10.3892/ol.2020.11460
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