Issue Highlights – Cytometry Part B March 2014 This issue of the Journal contains articles that address many important topics for those practicing clinical cytometry, including the selection of specific antigens for cell identification, documenting phenotypic variation in non‐neoplastic cells, distinguishing between neoplastic and non‐ neoplastic cells, identifying subtypes of disease, and reliably evaluating markers of prognosis. Which is the most sensitive and specific immunophenotypic marker of monocytes? CD14 is probably the most frequently used monocytic marker, and for many purposed is sufficient. However, CD14 is often negative on immature monocytes and is GPI‐linked and therefore absent in paroxysmal nocturnal hemoglobinuria (PNH). Bright intensity staining for CD33 is characteristic of monocytes, and has been utilized in PNH WBC assays1 but, as outlined by Hudig et al. in this issue of the Journal, CD33 expression varies significantly between individuals2. Two recently published articles illustrate the use of CD64 for identifying monocytes in PNH WBC assays3, 4, and more recently Sutherland et al. report using CD157 to detect both granulocytes and monocytes in a one tube 5‐color PNH WBC assay5. In this issue of the Journal, Hudig at al. propose that CD91 expression along with orthogonal light scatter is a more robust method for identifying non‐neoplastic monocytes than either CD14 or CD33. In their study, CD91 was restricted to monocytes and expressed at a consistent level among non‐neoplastic monocytes2. It will be of interest to further evaluate CD91 in the setting of immunophenotyping for leukemia and PNH. After confirming that CD91 is a useful marker for the identification of monocytes, Hudig et al. used it as a tool to evaluate variation in expression of other monocyte‐associated molecules, and report their findings in a second article in the same issue of the Journal6. It’s interesting to read about variation in the expression of markers routinely use in diagnostic practice. For example, monocyte expression of HLA‐Dr varied within, and among, individuals. Indeed, in a previous issue of the Journal, Demaret et al, reported using differences in monocyte HLA‐Dr expression as a marker of immune function7. Therefore, diminished expression of HLA‐Dr on monocytes should be interpreted with caution and not considered to represent phenotypic aberrancy. This is important information for those of us developing flow cytometric immunophenotyping panels for the detection of phenotypic aberrancy as a marker of disease. Some of you are probably saying “I told you we shouldn’t rely on detection of aberrant antigen expression to identify disease. Now, light chain monotypia, that’s something you can hang your hat on!” Well maybe not. In this issue of the Journal, Vafaii and DiGiuseppe describe three patients with multiple sclerosis who had monotypic light chain restricted B‐cell populations identified in CSF specimens, but no other evidence of lymphoma8. Flow cytometric immunophenotyping has well established utility in the detection of CSF involvement by previously diagnosed lymphoma and has also been advocated as a primary diagnostic tool9, 10_ENREF_8. However, the article by Vafaii and DiGiuseppe is a good reminder that it is important for all clinical flow cytometric data to be interpreted in the context of the clinical and other information. In addition, it might be prudent to evaluate for both light chain restriction and phenotypic aberrancy. Those of you, like me, who plan to continue offering flow cytometric CSF evaluation for lymphoma, will also be interested in the brief communication by Greig and Stetler‐ Stevenson describing increased cell yields and flow cytometric immunophenotyping results from CSF specimens after addition of RPMI without fetal calf serum11.
This article has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process which may lead to differences between this version and the Version of Record. Please cite this article as an ‘Accepted Article’, doi: 10.1002/cytob.21161
Imagine you overcome all these challenges and detect a mature B‐cell neoplasm. What prognosis can the patient anticipate? Although flow cytometric immunophenotyping provides information useful for the classification of small B‐cell lymphoid neoplasms, the distinction between chronic lymphocytic leukemia (CLL) and mantle cell lymphoma remains difficult, but is important for predicting outcome. CD200 has recently been proposed to assist in the diagnosis of CLL, hairy cell leukemia and plasma cell myeloma12‐14. In this issue of the Journal, Sandes et al, report their experience with CD200, including evaluation of cases of atypical CLL, and propose an algorithm for the classification of CD5+ mature B‐cell neoplasms15. Once a diagnosis of CLL has been established, there remains interest in evaluating for indicators of prognosis. Should clinical flow cytometry laboratories be offering testing for ZAP‐70 expression? Flow cytometric evaluation of ZAP‐70 expression has been fraught with problems, and several alternate procedures have been published previously in the Journal16, 17. In this issue, Adams et al. evaluate three different flow cytometric methods for calculating ZAP‐70 expression by flow cytometry in comparison with IgVH mutational status, quantitative PCR for ZAP‐70, and time to first treatment 18. The most promising method identified in this study is quantitative flow cytometric assessment for ZAP‐70 using a corrected mean fluorescence intensity algorithm (MFI ZAP‐70 B‐cells – MFI isotype B‐cells/MFI ZAP‐70 T‐cells – MFI isotype T‐cells). This result is interesting given the ongoing controversy about the use of isotypic control antibodies and the recent report in the Journal by Rizzo et al, that the T/B ratio does not accurately reflect levels of ZAP‐70 expression in CLL due to T‐cell over‐ expression19, 20. However, the study by Adams at al. does have the advantage over many previous studies of incorporating clinical data18. Serum soluble CD23 (sCD23) is another prognostic marker in CLL. In this issue of the Journal Grelier et al. describe a flow cytometric bead array‐based assay for sCD23 and suggest that this assay might be a more convenient alternative to RIA and ELISA‐based assays21. In addition, flow cytometric bead‐based prognostic assays might be easier to standardize than cell‐based fluorescence prognostic assays, since they probably conform to many of the established validation guidelines for soluble analytes. However, the need for similar guidelines for the validation of cell‐based assays has recently been addressed, as outlined in pivotal publications in the recent special issue of the Journal22‐26. Fiona Craig, Pittsburgh, PA, USA. E‐mail: [email protected]
References: 1. Borowitz MJ, Craig FE, Digiuseppe JA, Illingworth AJ, Rosse W, Sutherland DR, et al. Guidelines for the diagnosis and monitoring of paroxysmal nocturnal hemoglobinuria and related disorders by flow cytometry. Cytometry Part B, Clinical cytometry. 2010; 78B(4): 211‐230. 2. Hudig D, Hunter KW, Diamond WJ, Redelman D. Properties of Human Blood Monocytes. I. CD91 expression and log orthogonal light scatter provide a robust method to identify monocytes that is more acurate than CD14 expression. Cytometry Part B, Clinical cytometry. 2014; 86B(B2). 3. Dalal BI, Khare NS. Flow cytometric testing for paroxysmal nocturnal hemoglobinuria: CD64 is better for gating monocytes than CD33. Cytometry Part B, Clinical cytometry. 2013; 84B(1): 33‐36.
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20. Rizzo D, Bouvier G, Youlyouz‐Marfak I, Guerin E, Trimoreau F, Bordessoule D, et al. T/B ratio does not reflect levels of ZAP70 expression in clonal CLL B‐cells due to ZAP70 overexpression in patient T‐cells. Cytometry Part B, Clinical cytometry. 2013; 84B(2): 125‐32. 21. Grelier A, Garff‐Tavernier ML, Nauwelaers F, Sarfati M, Merle‐Beral H. Soluble CD23 measurement by CBA: A convenient and reliable quantification method in chronic lymphocytic leukemia. Cytometry Part B, Clinical cytometry. 2013. 22. Wood B, Jevremovic D, Bene MC, Yan M, Jacobs P, Litwin V. Validation of cell‐based fluorescence assays: practice guidelines from the ICSH and ICCS ‐ part V ‐ assay performance criteria. Cytometry Part B, Clinical cytometry. 2013; 84B(5): 315‐323. 23. Barnett D, Louzao R, Gambell P, De J, Oldaker T, Hanson CA. Validation of cell‐based fluorescence assays: practice guidelines from the ICSH and ICCS ‐ part IV ‐ postanalytic considerations. Cytometry Part B, Clinical cytometry. 2013; 84B(5): 309‐314. 24. Tanqri S, Vall H, Kaplan D, Hoffman B, Purvis N, Porwit A, et al. Validation of cell‐based fluorescence assays: practice guidelines from the ICSH and ICCS ‐ part III ‐ analytical issues. Cytometry Part B, Clinical cytometry. 2013; 84B(5): 291‐308. 25. Davis BH, Dasgupta A, Kussick S, Han JY, Estrellado A. Validation of cell‐based fluorescence assays: practice guidelines from the ICSH and ICCS ‐ part II ‐ preanalytical issues. Cytometry Part B, Clinical cytometry. 2013; 8B(5): 286‐290. 26. Davis BH, Wood B, Oldaker T, Barnett D. Validation of cell‐based fluorescence assays: practice guidelines from the ICSH and ICCS ‐ part I ‐ rationale and aims. Cytometry Part B, Clinical cytometry. 2013; 84B(5): 282‐285.