Abstract
BackgroundMost 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.ResultsA 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.ConclusionsThe 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.
Highlights
Chronic myeloid leukemia (CML) is a clonal myeloproliferative disorder of a pluripotent stem cell
Datasets in CEL files are standardized by Robust Multichip Averaging (RMA) implemented in the affy package, and return the log2 conversion intensity [12], and the probe sets are mapped to unique gene symbols by the averaging method
Samples of CML diagnosed are defined as control groups. 8927 genes can be obtained from the same gene of each Gene Expression Omnibus (GEO) dataset
Summary
Chronic myeloid leukemia (CML) is a clonal myeloproliferative disorder of a pluripotent stem cell. It is mainly caused by the disorder of differentiation and maturation of hematopoietic stem cells. The use of ABL kinase inhibitors (e.g. imatinib) for the treatment of CML can inhibit the activity of BCR-ABL kinase effectively, inhibit the malignant proliferation of leukemia cells, and extend the survival time of patients significantly. There will be a stable point in CML drug response [2]. It’s urgent to discover and validate stable points through bioinformatics for CML drug therapy. 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
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
