Abdulrazzaq Alheraky, Kees Meijer, Marije T. Nijk, Saskia K. Klein, Hanneke N. G. Oude Elberink, Ido P. Kema, André B. Mulder
{"title":"系统性肥大细胞增多症患者肥大细胞流式细胞术分析的关键缺陷。","authors":"Abdulrazzaq Alheraky, Kees Meijer, Marije T. Nijk, Saskia K. Klein, Hanneke N. G. Oude Elberink, Ido P. Kema, André B. Mulder","doi":"10.1002/cyto.a.24950","DOIUrl":null,"url":null,"abstract":"<p>Systemic mastocytosis (SM) is a neoplastic disease characterized by abnormal mast cell (MC) activation and proliferation. Accurate diagnosis often relies on flow cytometry to detect aberrant CD25, CD2, and CD30 expression on MCs in bone marrow (BM). However, the frequently low abundance of MCs in BM, lack of completely specific antigens, and strong and highly variable autofluorescence can cause misinterpretation and lead to diagnostic misclassifications. We investigated the potentially interfering cell populations in flow cytometric analysis of MCs based on literature and expert insights, focusing on CD117, CD45, CD203c, and FcεR1. Additionally, we determined the most appropriate approach to quantify aberrant CD25, CD2, and CD30 expression. Apoptotic granulocytes frequently cause misinterpretation by mimicking strong CD117 and aberrant CD25, CD2, and CD30 expression, and must be distinguished from MCs with a viability dye like DRAQ7. CD117-positive myeloblasts and promyelocytes overlap with CD117-reduced immature MCs in advanced SM disease and can be differentiated using CD203c. Quantifying CD25, CD2, and CD30 expression is skewed on log-transformed scales due to the strong and highly heterogeneous autofluorescence of MCs. Linear calculation of net expression levels of CD25, CD2, and CD30 yields the highest accuracies in predicting SM with a Youden index of 0.96, 0.93, and 0.88, respectively. Incorporating a viability dye like DRAQ7 and CD203c into the flow cytometric analysis for MC identification, along with the linear quantification of aberrant expression, significantly enhances the correct identification of MCs and increases the diagnostic accuracy of aberrant CD25, CD2, and CD30 expression for SM.</p>","PeriodicalId":11068,"journal":{"name":"Cytometry Part A","volume":"107 8","pages":"538-550"},"PeriodicalIF":2.1000,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cyto.a.24950","citationCount":"0","resultStr":"{\"title\":\"Critical Pitfalls in the Flow Cytometric Analysis of Mast Cells in Patients With Systemic Mastocytosis\",\"authors\":\"Abdulrazzaq Alheraky, Kees Meijer, Marije T. Nijk, Saskia K. Klein, Hanneke N. G. Oude Elberink, Ido P. Kema, André B. Mulder\",\"doi\":\"10.1002/cyto.a.24950\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Systemic mastocytosis (SM) is a neoplastic disease characterized by abnormal mast cell (MC) activation and proliferation. Accurate diagnosis often relies on flow cytometry to detect aberrant CD25, CD2, and CD30 expression on MCs in bone marrow (BM). However, the frequently low abundance of MCs in BM, lack of completely specific antigens, and strong and highly variable autofluorescence can cause misinterpretation and lead to diagnostic misclassifications. We investigated the potentially interfering cell populations in flow cytometric analysis of MCs based on literature and expert insights, focusing on CD117, CD45, CD203c, and FcεR1. Additionally, we determined the most appropriate approach to quantify aberrant CD25, CD2, and CD30 expression. Apoptotic granulocytes frequently cause misinterpretation by mimicking strong CD117 and aberrant CD25, CD2, and CD30 expression, and must be distinguished from MCs with a viability dye like DRAQ7. CD117-positive myeloblasts and promyelocytes overlap with CD117-reduced immature MCs in advanced SM disease and can be differentiated using CD203c. Quantifying CD25, CD2, and CD30 expression is skewed on log-transformed scales due to the strong and highly heterogeneous autofluorescence of MCs. Linear calculation of net expression levels of CD25, CD2, and CD30 yields the highest accuracies in predicting SM with a Youden index of 0.96, 0.93, and 0.88, respectively. Incorporating a viability dye like DRAQ7 and CD203c into the flow cytometric analysis for MC identification, along with the linear quantification of aberrant expression, significantly enhances the correct identification of MCs and increases the diagnostic accuracy of aberrant CD25, CD2, and CD30 expression for SM.</p>\",\"PeriodicalId\":11068,\"journal\":{\"name\":\"Cytometry Part A\",\"volume\":\"107 8\",\"pages\":\"538-550\"},\"PeriodicalIF\":2.1000,\"publicationDate\":\"2025-07-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cyto.a.24950\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cytometry Part A\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/cyto.a.24950\",\"RegionNum\":4,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"BIOCHEMICAL RESEARCH METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cytometry Part A","FirstCategoryId":"99","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/cyto.a.24950","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
Critical Pitfalls in the Flow Cytometric Analysis of Mast Cells in Patients With Systemic Mastocytosis
Systemic mastocytosis (SM) is a neoplastic disease characterized by abnormal mast cell (MC) activation and proliferation. Accurate diagnosis often relies on flow cytometry to detect aberrant CD25, CD2, and CD30 expression on MCs in bone marrow (BM). However, the frequently low abundance of MCs in BM, lack of completely specific antigens, and strong and highly variable autofluorescence can cause misinterpretation and lead to diagnostic misclassifications. We investigated the potentially interfering cell populations in flow cytometric analysis of MCs based on literature and expert insights, focusing on CD117, CD45, CD203c, and FcεR1. Additionally, we determined the most appropriate approach to quantify aberrant CD25, CD2, and CD30 expression. Apoptotic granulocytes frequently cause misinterpretation by mimicking strong CD117 and aberrant CD25, CD2, and CD30 expression, and must be distinguished from MCs with a viability dye like DRAQ7. CD117-positive myeloblasts and promyelocytes overlap with CD117-reduced immature MCs in advanced SM disease and can be differentiated using CD203c. Quantifying CD25, CD2, and CD30 expression is skewed on log-transformed scales due to the strong and highly heterogeneous autofluorescence of MCs. Linear calculation of net expression levels of CD25, CD2, and CD30 yields the highest accuracies in predicting SM with a Youden index of 0.96, 0.93, and 0.88, respectively. Incorporating a viability dye like DRAQ7 and CD203c into the flow cytometric analysis for MC identification, along with the linear quantification of aberrant expression, significantly enhances the correct identification of MCs and increases the diagnostic accuracy of aberrant CD25, CD2, and CD30 expression for SM.
期刊介绍:
Cytometry Part A, the journal of quantitative single-cell analysis, features original research reports and reviews of innovative scientific studies employing quantitative single-cell measurement, separation, manipulation, and modeling techniques, as well as original articles on mechanisms of molecular and cellular functions obtained by cytometry techniques.
The journal welcomes submissions from multiple research fields that fully embrace the study of the cytome:
Biomedical Instrumentation Engineering
Biophotonics
Bioinformatics
Cell Biology
Computational Biology
Data Science
Immunology
Parasitology
Microbiology
Neuroscience
Cancer
Stem Cells
Tissue Regeneration.