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BMC Bioinformatics. 2019 May 1;20(Suppl 7):202. doi: 10.1186/s12859-019-2738-0.

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

Author information

1
School of Science,Jiangnan University, Wuxi, 214122, China.
2
Zhou Pei-Yuan Center for Applied Mathematics, Tsinghua University, Beijing, 100084, China.
3
School of Science,Jiangnan University, Wuxi, 214122, China. gaojie@jiangnan.edu.cn.

Abstract

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.

KEYWORDS:

Chronic myeloid leukemia (CML); Differentially expressed genes (DEGs); Dynamic network biomarkers (DNB); Pre-stable state; Therapeutic effect index (TEI); Treatment time

PMID:
31074387
PMCID:
PMC6509869
DOI:
10.1186/s12859-019-2738-0
[Indexed for MEDLINE]
Free PMC Article

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