Pojero Fanny, Casuccio Alessandra, Parrino Maria Francesca, Cardinale Giovanni, Colonna Romano Giuseppina, Caruso Calogero, Gervasi Francesco
D.S.O.U. Specialistic Laboratory Oncology, Hematology and Cell Cultures for Clinical Use, ARNAS Civico, Piazza Nicola Leotta 4, Palermo, 90127, Italy; Department of Pathobiology and Medical and Forensic Biotechnologies, University of Palermo, Corso Tukory 211, Palermo, 90134, Italy.
Cytometry B Clin Cytom. 2015 May-Jun;88(3):165-82. doi: 10.1002/cyto.b.21218. Epub 2015 Feb 3.
Multiple myeloma is an incurable disease characterized by proliferation of clonal malignant plasma cells (CPCs), which can be immunophenotypically distinguished from polyclonal plasma cells (PPCs) by multiparameter flow cytometry (MFC). The utility of PPCs analysis in detecting prognostic and predictive information is still a matter of debate.
we tested the ability of 11 MFC markers in detecting differences in the immunophenotype of CPCs and PPCs among patients in various disease stages; we verified if these markers could be associated with disease stage/response to therapy despite the role of clinical parameters.
significant changes in the expression of markers occurred both in CPCs and PPCs. CD58 on PPCs of responding patients was downregulated compared with PPC of relapsing group. Fraction of CD200 expressing PCs was lower in control subjects than in PPCs from MGUS and myeloma groups. CD11a levels of expression on both CPCs and PPCs showed an upregulation in newly diagnosed and relapsing patients versus PCs of controls; CD20 was less expressed on control PCs than on MGUS CPCs and PPCs. CD49d revealed to be advantageous in discrimination of PPCs from CPCs. In our multiple regression model, CD19 and CD49d on CPCs, and CD45, CD58 and CD56 on PPCs maintained their association with groups of patients independently of other prognostic variables.
we provide a feasible start point to put in order ranges of expression on PPCs in healthy and myeloma subjects; we propose a new approach based on PPC analysis to monitor the stages of the disease.
多发性骨髓瘤是一种无法治愈的疾病，其特征为克隆性恶性浆细胞（CPC）增殖，通过多参数流式细胞术（MFC）可在免疫表型上区分CPC与多克隆浆细胞（PPC）。PPC分析在检测预后和预测信息方面的实用性仍存在争议。
我们测试了11种MFC标志物在检测不同疾病阶段患者中CPC和PPC免疫表型差异的能力；我们验证了尽管有临床参数的作用，但这些标志物是否与疾病阶段/治疗反应相关。
CPC和PPC中标志物的表达均发生了显著变化。与复发组的PPC相比，缓解患者的PPC上的CD58下调。表达CD200的浆细胞比例在对照组中低于来自意义未明的单克隆丙种球蛋白病（MGUS）和骨髓瘤组的PPC。与对照组的浆细胞相比，新诊断和复发患者的CPC和PPC上的CD11a表达水平均上调；对照组浆细胞上的CD20表达低于MGUS的CPC和PPC。CD49d在区分PPC与CPC方面具有优势。在我们的多元回归模型中，CPC上的CD19和CD49d，以及PPC上的CD45、CD58和CD56与患者组的关联独立于其他预后变量。
我们提供了一个可行的起点，以梳理健康和骨髓瘤患者中PPC的表达范围；我们提出了一种基于PPC分析的新方法来监测疾病阶段。
