Preliminarily screening of serum characteristic markers in acute myeloid leukemia and clinical significance.
- Author:
Ai-Li HE
1
;
Ju BAI
;
Chen HUANG
;
Wang-Gang ZHANG
;
Juan YANG
;
Jian-Li WANG
;
Xin MENG
;
Wei TIAN
Author Information
1. Department of Hematology, Second Affiliated Hospital, Xi'an Jiaotong University Medical College, Xi'an 710004, Shaanxi Province, China. heaili@mail.xjtu.edu.cn
- Publication Type:Journal Article
- MeSH:
Adult;
Aged;
Biomarkers;
Biomarkers, Tumor;
blood;
Case-Control Studies;
Female;
Humans;
Leukemia, Myeloid, Acute;
blood;
diagnosis;
Male;
Middle Aged;
Prognosis;
Protein Array Analysis;
methods;
Proteomics;
Sensitivity and Specificity;
Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization;
methods;
Young Adult
- From:
Journal of Experimental Hematology
2010;18(5):1132-1137
- CountryChina
- Language:Chinese
-
Abstract:
This study was purposed to preliminarily screen characteristic tumor markers of acute myeloid leukemia (AML) and to investigate the serum proteomics characteristics of patients with AML and their significance in pathogenesis. 14 patients with AML and 28 healthy controls were enrolled in this study. The serum protein components were captured by weak cation exchange nanometer magnetic beads, the protein mass-spectra of all samples were detected by Autoflex II matrix-assisted laser desorption/ionization time of flight mass spectrometer, and the detection data were analyzed by means of CliprotoolsTM2.2 software, then the differential protein molecules were screened and the diagnostic model was established. Sera of 7 AML patients and 14 healthy controls were selected to verify the established model by using blind test. The results indicated that about 69 protein peaks could be detected within the range of 0.7-10 kD in protein spectra of serum samples from AML patients and controls. Compared with healthy controls, there were 44 statistically differential expression peaks in AML group (p<0.0001). Among them, 10 protein peaks were upregulated protein peaks and 34 protein peaks were downregulated. Diagnostic model was established on the basis of Quick Classifier Algorithm (QC), and the three mass peaks had the strongest power for software to automatically distinguish AML group from control group. Mass charge ratios (m/z) were 3216.57, 4089.7, and 7762.87 respectively. Sensitivity was expected as 86.4% while 82.8% in this established model group. Category validation showed that this diagnostic model correctly identified all 6 cases out of AML and 12 cases out of 14 healthy controls. In cross validation, the model sensitivity and specificity both were 85.7%. It is concluded that the AML QC model is composed of three protein peaks, which can effectively distinguish AML patients from healthy controls. Owing to higher sensitivity and specificity, they may act as serum tumor markers of AML. Among the three proteins, the one with m/z 7762.87 is the platelet-derived protein chemokine (PF4) protein. This finding will probably provide significant experimental evidence for understanding pathogenesis, molecular type, prognosis and treatment effect of AML.
