Detection of cytokine expression patterns in the peripheral blood of patients with acute leukemia by antibody microarray analysis

Qing Li , Mei Li , Yao-hui Wu , Xiao-jian Zhu , Chen Zeng , Ping Zou , Zhi-chao Chen

Current Medical Science ›› 2014, Vol. 34 ›› Issue (2) : 176 -180.

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Current Medical Science ›› 2014, Vol. 34 ›› Issue (2) : 176 -180. DOI: 10.1007/s11596-014-1254-8
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Detection of cytokine expression patterns in the peripheral blood of patients with acute leukemia by antibody microarray analysis

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Abstract

The cytokines of acute leukemia (AL) patients have certain expression patterns, forming a complex network involved in diagnosis, progression, and prognosis. We collected the serum of different AL patients before and after complete remission (CR) for detection of cytokines by using an antibody chip. The expression patterns of cytokines were determined by using bioinformatics computational analysis. The results showed that there were significant differences in the cytokine expression patterns between AL patients and normal controls, as well as between acute myeloid leukemia (AML) and acute lymphoblastic leukemia (ALL). In confirmatory test, ELISA revealed the expression of uPAR in AL. Moreover, the bioinformatic analysis showed that the differentially expressed cytokines among the AL groups were involved in different biological behaviors and were closely related with the development of the disease. It was concluded that the cytokine expression pattern of AL patients is significantly different from that of healthy volunteers. Also, differences of cytokine expression patterns exist between AML and ALL, and between before and after CR in the same subtype of AL, which holds important clinical significance for revealing disease progression.

Keywords

cytokine / microarray / acute leukemia / expression patterns / bioinformatics

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Qing Li, Mei Li, Yao-hui Wu, Xiao-jian Zhu, Chen Zeng, Ping Zou, Zhi-chao Chen. Detection of cytokine expression patterns in the peripheral blood of patients with acute leukemia by antibody microarray analysis. Current Medical Science, 2014, 34(2): 176-180 DOI:10.1007/s11596-014-1254-8

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