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首页> 外文期刊>International Journal of Clinical and Experimental Pathology >Construction of protein profile classification model and screening of proteomic signature of acute leukemia
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Construction of protein profile classification model and screening of proteomic signature of acute leukemia

机译:急性白血病蛋白质谱分类模型的建立和蛋白质组学特征的筛选

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The French-American-British (FAB) and WHO classifications provide important guidelines for the diagnosis, treatment, and prognostic prediction of acute leukemia, but are incapable of accurately differentiating all subtypes, and not well correlated with the clinical outcomes. In this study, we performed the protein profiling of the bone marrow mononuclear cells from the patients with acute leukemia and the health volunteers (control) by surface enhanced laser desorption/ionization-time of flight mass spectrometry (SELDI_TOF_MS). The patients with acute leukemia were analyzed as unitary by the profiling that were grouped into acute promyelocytic leukemia (APL), acute myeloid leukemia-granulocytic (AML-Gran), acute myeloid leukemia-monocytic (AML-Mon) acute lymphocytic leukemia (ALL), and control. Based on 109 proteomic signatures, the classification models of acute leukemia were constructed to screen the predictors by the improvement of the proteomic signatures and to detect their expression characteristics. According to the improvement and the expression characteristics of the predictors, the proteomic signatures (M3829, M1593, M2121, M2536, M1016) characterized successively each group (CON, APL, AML-Gra, AML-Mon, ALL) were screened as target molecules for identification. Meanwhile, the proteomic-based class of determinant samples could be made by the classification models. The credibility of the proteomic-based classification passed the evaluation of Biomarker Patterns Software 5.0 (BPS 5.0) scoring and validated application in clinical practice. The results suggested that the proteomic signatures characterized by different blasts were potential for developing new treatment and monitoring approaches of leukemia blasts. Moreover, the classification model was potential in serving as new diagnose approach of leukemia.
机译:法国-美国-英国(FAB)和WHO的分类为急性白血病的诊断,治疗和预后预测提供了重要指南,但无法准确地区分所有亚型,并且与临床结局关系不大。在这项研究中,我们通过表面增强的激光解吸/电离飞行时间质谱(SELDI_TOF_MS)对来自急性白血病患者和健康志愿者(对照)的骨髓单个核细胞进行了蛋白分析。通过分析将急性白血病患者作为一个整体进行分析,将其分为急性早幼粒细胞白血病(APL),急性髓性白血病-粒细胞性(AML-Gran),急性髓性白血病-单核细胞(AML-Mon)急性淋巴细胞性白血病(ALL)和控制。基于109个蛋白质组学特征,构建了急性白血病分类模型,通过对蛋白质组学特征的改进来筛选预测因子并检测其表达特征。根据预测因子的改进和表达特征,依次筛选各组(CON,APL,AML-Gra,AML-Mon,ALL)表征的蛋白质组学特征(M3829,M1593,M2121,M2536,M1016)作为目标分子用于识别。同时,可以通过分类模型建立基于蛋白质组学的行列式样本。基于蛋白质组学的分类的信誉通过了Biomarker Patterns Software 5.0(BPS 5.0)评分的评估,并在临床实践中得到了验证。结果表明,以不同胚泡为特征的蛋白质组学特征对于开发白血病胚泡的新治疗和监测方法具有潜力。此外,分类模型有可能作为白血病的新诊断方法。

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