title: Construction of protein profile classification model and screening of proteomic signature of acute leukemia.
abstract: 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.
authors.affiliation: Central Laboratory, Shenzhen Second People's Hospital Shenzhen, Guangdong, China.
authors.forename: Yun
authors.initials: Y
authors.lastname: Xu
authors.affiliation: Institue of Hemotology, Shenzhen Second People's Hospital Shenzhen, Guangdong, China.
authors.forename: Jiacai
authors.initials: J
authors.lastname: Zhuo
authors.affiliation: Central Laboratory, Shenzhen Second People's Hospital Shenzhen, Guangdong, China.
authors.forename: Yonggang
authors.initials: Y
authors.lastname: Duan
authors.affiliation: Department of Civil and Environmental Engineering, Rice University Houston, TX 77005, USA.
authors.forename: Benhang
authors.initials: B
authors.lastname: Shi
authors.affiliation: Central Laboratory, Shenzhen Second People's Hospital Shenzhen, Guangdong, China.
authors.forename: Xuhong
authors.initials: X
authors.lastname: Chen
authors.affiliation: Central Laboratory, Shenzhen Second People's Hospital Shenzhen, Guangdong, China.
authors.forename: Xiaoli
authors.initials: X
authors.lastname: Zhang
authors.affiliation: Central Laboratory, Shenzhen Second People's Hospital Shenzhen, Guangdong, China.
authors.forename: Liang
authors.initials: L
authors.lastname: Xiao
authors.affiliation: Institue of Hemotology, Shenzhen Second People's Hospital Shenzhen, Guangdong, China.
authors.forename: Jin
authors.initials: J
authors.lastname: Lou
authors.affiliation: Institue of Hemotology, Shenzhen Second People's Hospital Shenzhen, Guangdong, China.
authors.forename: Ruihong
authors.initials: R
authors.lastname: Huang
authors.affiliation: Institue of Hemotology, Shenzhen Second People's Hospital Shenzhen, Guangdong, China.
authors.forename: Qiongli
authors.initials: Q
authors.lastname: Zhang
authors.affiliation: Institue of Hemotology, Shenzhen Second People's Hospital Shenzhen, Guangdong, China.
authors.forename: Xin
authors.initials: X
authors.lastname: Du
authors.affiliation: Institue of Hemotology, Shenzhen Second People's Hospital Shenzhen, Guangdong, China.
authors.forename: Ming
authors.initials: M
authors.lastname: Li
authors.affiliation: Central Laboratory, Shenzhen Second People's Hospital Shenzhen, Guangdong, China.
authors.forename: Daping
authors.initials: D
authors.lastname: Wang
authors.affiliation: Institue of Hemotology, Shenzhen Second People's Hospital Shenzhen, Guangdong, China.
authors.forename: Dunyun
authors.initials: D
authors.lastname: Shi
mesh_terms: D000328:Adult; D014408:Biomarkers, Tumor / Q000032:analysis*; D016022:Case-Control Studies; D019295:Computational Biology; D003663:Decision Trees; D005260:Female; D006801:Humans; D015470:Leukemia, Myeloid, Acute / Q000145:classification / Q000378:metabolism* / Q000473:pathology; D015473:Leukemia, Promyelocytic, Acute / Q000145:classification / Q000378:metabolism* / Q000473:pathology; D008297:Male; D009363:Neoplasm Proteins / Q000032:analysis*; D054198:Precursor Cell Lymphoblastic Leukemia-Lymphoma / Q000145:classification / Q000378:metabolism* / Q000473:pathology; D011237:Predictive Value of Tests; D011379:Prognosis; D040081:Protein Array Analysis; D040901:Proteomics / Q000379:methods*; D015203:Reproducibility of Results; D012986:Software Validation; D019032:Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization
chemical_list: D014408:Biomarkers, Tumor; D009363:Neoplasm Proteins
keywords: Leukemia; classification model; proteomic signatures