Construction of A Multiple Myeloma Diagnostic Model by Magnetic Bead-Based MALDI-TOF Mass Spectrometry of Serum and Pattern Recognition Software

Authors

  • Qing-Tao Wang,

    1. Department of Clinical Laboratory, Chao Yang Hospital, Capital Medical University, Beijing, China
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    • Qing-Tao Wang and Yong-Zhe Li contributed equally to this work.

  • Yong-Zhe Li,

    1. Department of Clinical Laboratory, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China
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    • Qing-Tao Wang and Yong-Zhe Li contributed equally to this work.

  • Yu-Fang Liang,

    1. Department of Clinical Laboratory, Chao Yang Hospital, Capital Medical University, Beijing, China
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  • Chao-Jun Hu,

    1. Department of Clinical Laboratory, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China
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  • Yu-Hua Zhai,

    1. Department of Clinical Laboratory, Chao Yang Hospital, Capital Medical University, Beijing, China
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  • Guan-Fei Zhao,

    1. Department of Clinical Laboratory, Chao Yang Hospital, Capital Medical University, Beijing, China
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  • Jian Zhang,

    1. Division of Hematology and Oncology, Department of Medicine, University of Pittsburgh Medical School, Pittsburgh, Pennsylvania
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  • Ning Li,

    1. IMS Health Management, Ltd., Huzhou, China
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  • An-Ping Ni,

    1. Department of Clinical Laboratory, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China
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  • Wen-Ming Chen,

    Corresponding author
    1. Department of Clinical Laboratory, Chao Yang Hospital, Capital Medical University, Beijing, China
    • Department of Clinical Laboratory, Chao Yang Hospital, Capital Medical University, Beijing 100020, China
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  • Yang Xu

    Corresponding author
    1. Center for Clinical Laboratory Development, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China
    • Center for Clinical Laboratory Development, Peking Union Medical College & Chinese Academy of Medical Sciences, Beijing 102206, China and Center for Organelle Proteomics of Diseases, Zhejiang University School of Basic Medical Science, Hangzhou 310058, China
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Abstract

A diagnosis of multiple myeloma (MM) is difficult to make on the basis of any single laboratory test result. Accurate diagnosis of MM generally results from a number of costly and invasive laboratory tests and medical procedures. The aim of this work is to find a new, highly specific and sensitive method for MM diagnosis. Serum samples were tested in groups representing MM (n = 54) and non-MM (n = 108). These included a subgroup of 17 plasma cell dyscrasias, a subgroup of 17 reactive plasmacytosis, 5 B cell lymphomas, and 7 other tumors with osseus metastasis, as well as 62 healthy donors as controls. Bioinformatic calculations associated with MM were performed. The decision algorithm, with a panel of three biomarkers, correctly identified 24 of 24 (100%) MM samples and 46 of 49 (93.88%) non-MM samples in the training set. During the masked test for the discriminatory model, 26 of 30 MM patients (sensitivity, 86.67%) were precisely recognized, and all 34 normal donors were successfully classified; patients with reactive plasmacytosis were also correctly classified into the non-MM group, and 11 of the other patients were incorrectly classified as MM. The results suggested that proteomic fingerprint technology combining magnetic beads with MALDI-TOF-MS has the potential for identifying individuals with MM. The biomarker classification model was suitable for preliminary assessment of MM and could potentially serve as a useful tool for MM diagnosis and differentiation diagnosis. Anat Rec, 292:604–610, 2009. © 2009 Wiley-Liss, Inc.

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