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

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.

SUBMITTER: Xu J

PROVIDER: S-EPMC6509869 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

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

Xu Junhua J Wu Min M Zhu Shanshan S Lei Jinzhi J Gao Jie J

BMC bioinformatics 20190501 Suppl 7

<h4>Background</h4>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.<h4>Results</h4>A therapeutic effect recognition strategy based on dynamic network biomarkers (DNB) is provided for CML patients' ...[more]

PMID: 31074387

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Project description:BACKGROUND: Chronic Myeloid Leukemia (CML) is a malignant pluripotent stem cells disorder of myeloid cells. In CML patients, polymorphonuclear leukocytes (PMNL) the terminally differentiated cells of myeloid series exhibit defects in several actin dependent functions such as adhesion, motility, chemotaxis, agglutination, phagocytosis and microbicidal activities. A definite and global abnormality was observed in stimulation of actin polymerization in CML PMNL. Signalling molecules ras and rhoGTPases regulate spatial and temporal polymerization of actin and thus, a broad range of physiological processes. Therefore, status of these GTPases as well as actin was studied in resting and fMLP stimulated normal and CML PMNL. METHODS: To study expression of GTPases and actin, Western blotting and flow cytometry analysis were done, while spatial expression and colocalization of these proteins were studied by using laser confocal microscopy. To study effect of inhibitors on cell proliferation CCK-8 assay was done. Significance of differences in expression of proteins within the samples and between normal and CML was tested by using Wilcoxon signed rank test and Mann-Whitney test, respectively. Bivariate and partial correlation analyses were done to study relationship between all the parameters. RESULTS: In CML PMNL, actin expression and its architecture were altered and stimulation of actin polymerization was absent. Differences were also observed in expression, organization or stimulation of all the three GTPases in normal and CML PMNL. In normal PMNL, ras was the critical GTPase regulating expression of rhoGTPases and actin and actin polymerization. But in CML PMNL, rhoA took a central place. In accordance with these, treatment with rho/ROCK pathway inhibitors resulted in specific growth inhibition of CML cell lines. CONCLUSIONS: RhoA has emerged as the key molecule responsible for functional defects in CML PMNL and therefore can be used as a therapeutic target in CML.

Project description:Background:Chronic Myeloid Leukemia (CML) is a myeloproliferative neoplasm related to chromosomal reciprocal translocation t(9;22). Tyrosine kinase inhibitors (TKIs) such as imatinib have drastically revolutionized the course and the prognosis of this hematologic malignancy. As we know, the association pregnancy-CML is an infrequent situation. Also the use of TKI in pregnant women is unsafe with a lack of alternatives and effective therapeutic options. Thus its cessation during gestation puts those patients at high risk of developing blast crisis characterized by poor outcomes. Case Report:A 37-year-old pregnant woman, gravida 2, para 2, with a previous cesarean section in 2011, presented to the obstetric unit. Her medical past revealed that she is a newly diagnosed patient with CML managed by TKI during her preconception period. Due to the perilous use of TKI during her pregnancy, a switch to interferon-? administration was adopted. But after the completion of 36 weeks of gestation, disease progression (relapse with blast crisis), attested by biological worsening, a white blood cell count = 245000/mm3 with 32% blasts in the peripheral blood, urged the medical team to opt for cesarean delivery. She underwent general endotracheal anesthesia without any perioperative incidents and gave birth to a healthy newborn. Ten days later, the patient was started on TKI. Discussion:Although data on this specific and challenging situation are limited, this case highlights the difficulties encountered by the anesthesiologists when choosing the accurate anesthetic strategy and how important it is to weigh the risks and benefits inherent to each technique. Above all, taking into consideration the possible central nervous system (CNS) contamination by circulating blast cells when performing spinal or epidural approach is primordial. This potential adverse event (CNS blast crisis) is extremely scarce but it is responsible for high rates of morbidity and mortality.

Project description:BackgroundIn traditional Chinese medicine (TCM) clinical practice, TCM syndromes help to understand human homeostasis and guide individualized treatment. However, the TCM syndrome changes with disease progression, of which the scientific basis and mechanism remain unclear.MethodsTo demonstrate the underlying mechanism of dynamic changes in the TCM syndrome, we applied a dynamic network biomarker (DNB) algorithm to obtain the DNBs of changes in the TCM syndrome, based on the transcriptomic data of patients with chronic hepatitis B and typical TCM syndromes, including healthy controls and patients with liver-gallbladder dampness-heat syndrome (LGDHS), liver-depression spleen-deficiency syndrome (LDSDS), and liver-kidney yin-deficiency syndrome (LKYDS). The DNB model exploits collective fluctuations and correlations of the observed genes, then diagnoses the critical state.ResultsOur results showed that the DNBs of TCM syndromes were comprised of 52 genes and the tipping point occurred at the LDSDS stage. Meanwhile, there were numerous differentially expressed genes between LGDHS and LKYDS, which highlighted the drastic changes before and after the tipping point, implying the 52 DNBs could serve as early-warning signals of the upcoming change in the TCM syndrome. Next, we validated DNBs by cytokine profiling and isobaric tags for relative and absolute quantitation (iTRAQ). The results showed that PLG (plasminogen) and coagulation factor XII (F12) were significantly expressed during the progression of TCM syndrome from LGDHS to LKYDS.ConclusionsThis study provides a scientific understanding of changes in the TCM syndrome. During this process, the cytokine system was involved all the time. The DNBs PLG and F12 were confirmed to significantly change during TCM-syndrome progression and indicated a potential value of DNBs in auxiliary diagnosis of TCM syndrome in CHB.Trial registration Identifier: NCT03189992. Registered on June 4, 2017. Retrospectively registered (http://www.clinicaltrials.gov).

Dataset Information

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

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

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