A quantitative exploration of surface antigen expression in common B-cell malignancies using flow cytometry
A quantitative exploration of surface antigen expression in common B-cell malignancies using flow cytometry
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DOI：
10.1080/08820130500496878
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发表时间：
2006-02-01
影响因子：
2.8
通讯作者：
Czuczman, MS
中科院分区：
文献类型：
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作者：
Olejniczak, SH;Stewart, CC;Czuczman, MS
使用流式细胞术诊断血液恶性肿瘤已成为常规，因为它能够经常区分基于恶性细胞表面上表达的抗原的形态学相似的疾病。为了扩大流式细胞术在B细胞恶性肿瘤研究中的应用，我们使用了最可靠的定量方法QIFI。采用间接免疫荧光定量分析法，检测384例常见B系恶性肿瘤组织中CD 5、CD 10、CD 11 c、CD 19、CD 20、CD 22、CD 23和CD 79 b的表达，包括：B-ALL、CLL、SLL、毛细胞白血病、弥漫性大B细胞淋巴瘤和滤泡性淋巴瘤。这项广泛的、单一机构的表面抗原研究背后的动力是双重的：评估B细胞肿瘤之间抗原表达的相似性和差异，并为所产生的定量流式细胞术数据寻找额外的临床实用性。我们的研究结果表明，每一个不同的恶性组织学有自己的表面抗原表达的定量模式。在大多数情况下，这些定量模式不会增加流式细胞术区分它们的能力。然而，特定B细胞恶性肿瘤上特异性抗原的高表达可能潜在地确定当前和/或未来基于单克隆抗体的疗法的最佳治疗靶点。
The use of flow cytometry to diagnose hematological malignancies has become routine due to its ability to often differentiate between morphologically similar diseases based on antigens expressed on the surface of malignant cells. In an attempt to expand on the utility of flow cytometry in the study of B-cell malignancies we have used the most reliable quantitative methodology, QIFI (quantitative indirect immunoflourescence assay), to study the expression of CD5, CD10, CD11c, CD19, CD20, CD22, CD23, and CD79b in 384 cases of several common B-lineage malignancies, including: B-ALL, CLL, SLL, hairy cell leukemia, diffuse large B-cell lymphoma, and follicular lymphoma. The impetus behind this extensive, single institution study of surface antigens was two-fold: evaluating similarities and differences of antigen expression between B-cell neoplasms and finding additional clinical utility for the quantitative flow cytometric data generated. Our results show that each distinct malignant histology has its own quantitative pattern of surface antigen expression. In most cases, these quantitative patterns do not increase the ability of flow cytometry to distinguish between them. However, a high expression of specific antigens on a given B-cell malignancy may potentially identify optimal therapeutic targets for current and/or future monoclonal antibody-based therapies.