[1]邓 娜,吴冠宇,杨 柳,等.流式细胞术在多发性骨髓瘤治疗中的应用价值[J].医学信息,2022,35(02):75-78.[doi:10.3969/j.issn.1006-1959.2022.02.018]
　DENG Na,WU Guan-yu,YANG Liu,et al.Application Value of Flow Cytometry in the Treatment of Multiple Myeloma[J].Medical Information,2022,35(02):75-78.[doi:10.3969/j.issn.1006-1959.2022.02.018]
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流式细胞术在多发性骨髓瘤治疗中的应用价值()
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医学信息[ISSN:1006-1959/CN:61-1278/R]

卷:
35卷
期数:
2022年02期
页码:
75-78
栏目:
论著
出版日期:
2022-01-15

文章信息/Info

Title:
Application Value of Flow Cytometry in the Treatment of Multiple Myeloma
文章编号:
1006-1959（2022）02-0075-04
作者:
邓 娜; 吴冠宇; 杨 柳; 谷和先; 盛德菁; 周 娜; 王何惧
马鞍山市人民医院血液科，安徽 马鞍山 243000
Author(s):
DENG Na; WU Guan-yu; YANG Liu; GU He-xian; SHENG De-jing; ZHOU Na; WANG He-ju
Department of Hematology,Maanshan People’s Hospital,Maanshan 243000,Anhui,China
关键词:
流式细胞术; 免疫表型; 多发性骨髓瘤
Keywords:
Flow cytometry; Immunophenotype; Multiple myeloma
分类号:
R738.1
DOI:
10.3969/j.issn.1006-1959.2022.02.018
文献标志码:
A
摘要:
目的 使用流式细胞仪分析免疫表型在初诊多发性骨髓瘤中的特点，并分析在疾病不同分型及分期中表达类型的差异及其与预后的关系。方法 选取2015年4月-2020年3月我院收治的34例初诊多发性骨髓瘤患者为研究对象，使用双激光四色流式细胞仪分析免疫表型，比较不同分期、不同分型的多发性骨髓瘤疾病中的表达差异。结果 CD38、CD138阳性率为100.00%。CD45、CD38、CD19、CD56、CD20、CD28、CD117、CD9、CD23的表达与疾病分型无关（P＞0.05），CD33的表达与疾病分型有关（P＜0.05）。CD45、CD38、CD56、CD20、CD28、CD117、CD9、CD23、CD33的表达与ISS分期无关（P＞0.05），CD19的表达与ISS分期有关（P＜0.05）。结论 免疫表型的分析更符合诊断标准，能更准确的区分良、恶性浆细胞，对于多发性骨髓瘤的预后及治疗后的监测均有临床意义。
Abstract:
Objective To analyze the characteristics of immunophenotype in newly diagnosed multiple myeloma by flow cytometry, and to analyze the difference of expression types in different types and stages of the disease and its relationship with prognosis.Methods A total of 34 patients with newly diagnosed multiple myeloma in our hospital from April 2015 to March 2020 were selected as the research objects. The immunophenotype was analyzed by double laser four-color flow cytometry, and the expression differences of multiple myeloma diseases in different stages and different types were compared.Results The positive rates of CD38 and CD138 were 100.00%. The expression of CD45, CD38, CD19, CD56, CD20, CD28, CD117, CD9 and CD23 was not correlated with disease classification (P>0.05); the expression of CD33 was correlated with disease classification (P<0.05). The expression of CD45, CD38, CD56, CD20, CD28, CD117, CD9, CD23 and CD33 was not correlated with ISS stage (P>0.05); the expression of CD19 was correlated with ISS stage (P<0.05).Conclusion The analysis of immunophenotype is more consistent with the diagnostic criteria and can distinguish benign and malignant plasma cells more accurately, which is of significance for the prognosis and post-treatment monitoring of multiple myeloma.

参考文献/References:

[1]张静洁,郑志兵,李松.多发性骨髓瘤的靶向治疗[J].沈阳药科大学学报,2017,34(8):723-728.[2]张津京,李艳.初诊多发性骨髓瘤合并肾功能不全患者的临床特点和疗效分析[J].中国医科大学学报,2016,45(6):494-498.[3]杜鹃,侯健.《中国多发性骨髓瘤诊治指南(2015年修订)》诊断部分解读[J].中华内科杂志,2016,55(2):91-92.[4]Liu J,Liu W,Mi L,et al.Union for China Lymphoma Investigators of the Chinese Society of Clinical Oncology; Union for China Leukemia Investigators of the Chinese Society of Clinical Oncology. Incidence and mortality of multiple myeloma in China, 2006-2016: an analysis of the Global Burden of Disease Study 2016[J].J Hematol Oncol,2019,12(1):136.[5]McKinnon KM.Flow Cytometry: An Overview[J].Curr Protoc Immunol,2018(120):5.1.1-5.1.11.[6]Rihova L,Vsianska P,Bezdekova R,et al.Minimal Residual Disease Assessment in Multiple Myeloma by Multiparametric Flow Cytometry[J].Klin Onkol,2017,30(Supplementum2):21-28.[7]Flores-Montero J,Sanoja-Flores L,Paiva B,et al.Next Generation Flow for highly sensitive and standardized detection of minimal residual disease in multiple myeloma[J].Leukemia,2017,31(10):2094-2103.[8]Rajkumar SV.Multiple myeloma: Every year a new standard?[J].Hematol Oncol,2019(37 Suppl 1):62-65.[9]Flores-Montero J,de Tute R,Paiva B,et al.Immunophenotype of normal vs. myeloma plasma cells: Toward antibody panel specifications for MRD detection in multiple myeloma[J].Cytometry B Clin Cytom,2016,90(1):61-72.[10]Alaterre E,Raimbault S,Garcia JM,et al.Automated and simplified identification of normal and abnormal plasma cells in Multiple Myeloma by flow cytometry[J].Cytometry B Clin Cytom,2018,94(3):484-492.[11]Skerget M,Skopec B,Zadnik V,et al.CD56 Expression Is an Important Prognostic Factor in Multiple Myeloma Even with Bortezomib Induction[J].Acta Haematol,2018,139(4):228-234.[12]Drent E,Poels R,Ruiter R,et al.Combined CD28 and 4-1BB Costimulation Potentiates Affinity-tuned Chimeric Antigen Receptor-engineered T Cells[J].Clin Cancer Res,2019,25(13):4014-4025.[13]Wang J,Zheng Y,Tu C,et al.Identification of the immune checkpoint signature of multiple myeloma using mass cytometry-based single-cell analysis[J].Clin Transl Immunology,2020,9(5):e01132.[14]Ceran F,Falay M,Dagdas S,et al.The Assessment of CD56 and CD117 Expressions at the Time of the Diagnosis in Multiple Myeloma Patients[J].Turk J Haematol,2017,34(3):226-232.[15]Wang H,Zhou X,Zhu JW,et al.Association of CD117 and HLA-DR expression with shorter overall survival and/or progression-free survival in patients with multiple myeloma treated with bortezomib and thalidomide combination treatment without transplantation[J].Oncol Lett,2018,16(5):5655-5666.[16]Shi J,Sun K,Zhu ZM,et al.Prognostic significance of CD56 and CD117 expression in patients with newly diagnosed multiple myeloma treated with bortezomib-based first-line therapy[J].Chin J Hematol,2019,40(8):693-696.[17]Huang B,Li J,Liu J,et al.CD20-positive multiple myeloma: can conventional chemotherapy still be used to achieve ideal outcome for these patients?[J].Leuk Lymphoma,2016,57(2):335-340.[18]Muchtar E,Gertz MA.The colorful landscape of multiple myeloma[J].Leuk Lymphoma,2019,60(9):2099-2100.[19]刘帅,李曌博,张帆,等.37例CD45阳性的多发性骨髓瘤浆细胞免疫学表型特征[J].检验医学,2017,32(2):76-80.[20]朱杰,赵成艳,王敏,等.多发性骨髓瘤免疫表型及胞浆轻链检测的临床意义[J].实用检验医师杂志,2013,17(6):1068-1071.[21]Moore S,Suttle JM,Nicola M.Cytoplasmic Immunoglobulin Light Chain Revelation and Interphase Fluorescence In Situ Hybridization in Myeloma[J].Methods Mol Biol,2017(1541):127-142. [22]Papanikolaou X,Alapat D,Rosenthal A,et al.The flow cytometry-defined light chain cytoplasmic immunoglobulin index and an associated 12-gene expression signature are independent prognostic factors in multiple myeloma[J].Leukemia,2015,29(8):1713-1720.

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更新日期/Last Update: 1900-01-01