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Identification of tumor-educated platelet biomarkers of non-small-cell lung cancer

BACKGROUND: Lung cancer is a severe cancer with a high death rate. The 5-year survival rate for stage III lung cancer is much lower than stage I. Early detection and intervention of lung cancer patients can significantly increase their survival time. However, conventional lung cancer-screening metho...

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Autores principales: Sheng, Meiling, Dong, Zhaohui, Xie, Yanping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove Medical Press 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6241732/
https://www.ncbi.nlm.nih.gov/pubmed/30532555
http://dx.doi.org/10.2147/OTT.S177384
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author Sheng, Meiling
Dong, Zhaohui
Xie, Yanping
author_facet Sheng, Meiling
Dong, Zhaohui
Xie, Yanping
author_sort Sheng, Meiling
collection PubMed
description BACKGROUND: Lung cancer is a severe cancer with a high death rate. The 5-year survival rate for stage III lung cancer is much lower than stage I. Early detection and intervention of lung cancer patients can significantly increase their survival time. However, conventional lung cancer-screening methods, such as chest X-rays, sputum cytology, positron-emission tomography (PET), low-dose computed tomography (CT), magnetic resonance imaging, and gene-mutation, -methylation, and -expression biomarkers of lung tissue, are invasive, radiational, or expensive. Liquid biopsy is non-invasive and does little harm to the body. It can reflect early-stage dysfunctions of tumorigenesis and enable early detection and intervention. METHODS: In this study, we analyzed RNA-sequencing data of tumor-educated platelets (TEPs) in 402 non-small-cell lung cancer (NSCLC) patients and 231 healthy controls. A total of 48 biomarker genes were selected with advanced minimal-redundancy, maximal-relevance, and incremental feature-selection (IFS) methods. RESULTS: A support vector-machine (SVM) classifier based on the 48 biomarker genes accurately predicted NSCLC with leave-one-out cross-validation (LOOCV) sensitivity, specificity, accuracy, and Matthews correlation coefficients of 0.925, 0.827, 0.889, and 0.760, respectively. Network analysis of the 48 genes revealed that the WASF1 actin cytoskeleton module, PRKAB2 kinase module, RSRC1 ribosomal protein module, PDHB carbohydrate-metabolism module, and three intermodule hubs (TPM2, MYL9, and PPP1R12C) may play important roles in NSCLC tumorigenesis and progression. CONCLUSION: The 48-gene TEP liquid-biopsy biomarkers will facilitate early screening of NSCLC and prolong the survival of cancer patients.
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spelling pubmed-62417322018-12-07 Identification of tumor-educated platelet biomarkers of non-small-cell lung cancer Sheng, Meiling Dong, Zhaohui Xie, Yanping Onco Targets Ther Original Research BACKGROUND: Lung cancer is a severe cancer with a high death rate. The 5-year survival rate for stage III lung cancer is much lower than stage I. Early detection and intervention of lung cancer patients can significantly increase their survival time. However, conventional lung cancer-screening methods, such as chest X-rays, sputum cytology, positron-emission tomography (PET), low-dose computed tomography (CT), magnetic resonance imaging, and gene-mutation, -methylation, and -expression biomarkers of lung tissue, are invasive, radiational, or expensive. Liquid biopsy is non-invasive and does little harm to the body. It can reflect early-stage dysfunctions of tumorigenesis and enable early detection and intervention. METHODS: In this study, we analyzed RNA-sequencing data of tumor-educated platelets (TEPs) in 402 non-small-cell lung cancer (NSCLC) patients and 231 healthy controls. A total of 48 biomarker genes were selected with advanced minimal-redundancy, maximal-relevance, and incremental feature-selection (IFS) methods. RESULTS: A support vector-machine (SVM) classifier based on the 48 biomarker genes accurately predicted NSCLC with leave-one-out cross-validation (LOOCV) sensitivity, specificity, accuracy, and Matthews correlation coefficients of 0.925, 0.827, 0.889, and 0.760, respectively. Network analysis of the 48 genes revealed that the WASF1 actin cytoskeleton module, PRKAB2 kinase module, RSRC1 ribosomal protein module, PDHB carbohydrate-metabolism module, and three intermodule hubs (TPM2, MYL9, and PPP1R12C) may play important roles in NSCLC tumorigenesis and progression. CONCLUSION: The 48-gene TEP liquid-biopsy biomarkers will facilitate early screening of NSCLC and prolong the survival of cancer patients. Dove Medical Press 2018-11-14 /pmc/articles/PMC6241732/ /pubmed/30532555 http://dx.doi.org/10.2147/OTT.S177384 Text en © 2018 Sheng et al. This work is published and licensed by Dove Medical Press Limited The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed.
spellingShingle Original Research
Sheng, Meiling
Dong, Zhaohui
Xie, Yanping
Identification of tumor-educated platelet biomarkers of non-small-cell lung cancer
title Identification of tumor-educated platelet biomarkers of non-small-cell lung cancer
title_full Identification of tumor-educated platelet biomarkers of non-small-cell lung cancer
title_fullStr Identification of tumor-educated platelet biomarkers of non-small-cell lung cancer
title_full_unstemmed Identification of tumor-educated platelet biomarkers of non-small-cell lung cancer
title_short Identification of tumor-educated platelet biomarkers of non-small-cell lung cancer
title_sort identification of tumor-educated platelet biomarkers of non-small-cell lung cancer
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6241732/
https://www.ncbi.nlm.nih.gov/pubmed/30532555
http://dx.doi.org/10.2147/OTT.S177384
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