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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,...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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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. |
format | Online Article Text |
id | pubmed-6509869 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
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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