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Detecting the stable point of therapeutic effect of chronic myeloid leukemia based on dynamic network biomarkers

BACKGROUND: Most researches of chronic myeloid leukemia (CML) are currently focused on the treatment methods, while there are relatively few researches on the progress of patients’ condition after drug treatment. Traditional biomarkers of disease can only distinguish normal state from disease state,...

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Autores principales: Xu, Junhua, Wu, Min, Zhu, Shanshan, Lei, Jinzhi, Gao, Jie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6509869/
https://www.ncbi.nlm.nih.gov/pubmed/31074387
http://dx.doi.org/10.1186/s12859-019-2738-0
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author Xu, Junhua
Wu, Min
Zhu, Shanshan
Lei, Jinzhi
Gao, Jie
author_facet Xu, Junhua
Wu, Min
Zhu, Shanshan
Lei, Jinzhi
Gao, Jie
author_sort Xu, Junhua
collection PubMed
description BACKGROUND: Most researches of chronic myeloid leukemia (CML) are currently focused on the treatment methods, while there are relatively few researches on the progress of patients’ condition after drug treatment. Traditional biomarkers of disease can only distinguish normal state from disease state, and cannot recognize the pre-stable state after drug treatment. RESULTS: A therapeutic effect recognition strategy based on dynamic network biomarkers (DNB) is provided for CML patients’ gene expression data. With the DNB criteria, the DNB with 250 genes is selected and the therapeutic effect index (TEI) is constructed for the detection of individual disease. The pre-stable state before the disease condition becomes stable is 1 month. Through functional analysis for the DNB, some genes are confirmed as key genes to affect the progress of CML patients’ condition. CONCLUSIONS: The results provide a certain theoretical direction and theoretical basis for medical personnel in the treatment of CML patients, and find new therapeutic targets in the future. The biomarkers of CML can help patients to be treated promptly and minimize drug resistance, treatment failure and relapse, which reduce the mortality of CML significantly. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12859-019-2738-0) contains supplementary material, which is available to authorized users.
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spelling pubmed-65098692019-06-05 Detecting the stable point of therapeutic effect of chronic myeloid leukemia based on dynamic network biomarkers Xu, Junhua Wu, Min Zhu, Shanshan Lei, Jinzhi Gao, Jie BMC Bioinformatics Research BACKGROUND: Most researches of chronic myeloid leukemia (CML) are currently focused on the treatment methods, while there are relatively few researches on the progress of patients’ condition after drug treatment. Traditional biomarkers of disease can only distinguish normal state from disease state, and cannot recognize the pre-stable state after drug treatment. RESULTS: A therapeutic effect recognition strategy based on dynamic network biomarkers (DNB) is provided for CML patients’ gene expression data. With the DNB criteria, the DNB with 250 genes is selected and the therapeutic effect index (TEI) is constructed for the detection of individual disease. The pre-stable state before the disease condition becomes stable is 1 month. Through functional analysis for the DNB, some genes are confirmed as key genes to affect the progress of CML patients’ condition. CONCLUSIONS: The results provide a certain theoretical direction and theoretical basis for medical personnel in the treatment of CML patients, and find new therapeutic targets in the future. The biomarkers of CML can help patients to be treated promptly and minimize drug resistance, treatment failure and relapse, which reduce the mortality of CML significantly. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12859-019-2738-0) contains supplementary material, which is available to authorized users. BioMed Central 2019-05-01 /pmc/articles/PMC6509869/ /pubmed/31074387 http://dx.doi.org/10.1186/s12859-019-2738-0 Text en © The Author(s) 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Xu, Junhua
Wu, Min
Zhu, Shanshan
Lei, Jinzhi
Gao, Jie
Detecting the stable point of therapeutic effect of chronic myeloid leukemia based on dynamic network biomarkers
title Detecting the stable point of therapeutic effect of chronic myeloid leukemia based on dynamic network biomarkers
title_full Detecting the stable point of therapeutic effect of chronic myeloid leukemia based on dynamic network biomarkers
title_fullStr Detecting the stable point of therapeutic effect of chronic myeloid leukemia based on dynamic network biomarkers
title_full_unstemmed Detecting the stable point of therapeutic effect of chronic myeloid leukemia based on dynamic network biomarkers
title_short Detecting the stable point of therapeutic effect of chronic myeloid leukemia based on dynamic network biomarkers
title_sort detecting the stable point of therapeutic effect of chronic myeloid leukemia based on dynamic network biomarkers
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6509869/
https://www.ncbi.nlm.nih.gov/pubmed/31074387
http://dx.doi.org/10.1186/s12859-019-2738-0
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