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 purposes is sufficient. However, CD14 is often negative on immature monocytes and is glycophosphatidylinositol (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 assays [1] but, as outlined by Hudig et al. in this issue of the Journal, CD33 expression varies significantly between individuals [2]. Two recently published articles illustrate the use of CD64 for identifying monocytes in PNH WBC assays [3, 4], and more recently Sutherland et al. reported using CD157 to detect both granulocytes and monocytes in a one tube 5-color PNH WBC assay [5]. 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 monocytes [2]. 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 Journal [6]. 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 function [7]. 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 cerebrospinal fluid (CSF) specimens, but no other evidence of lymphoma [8]. 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 tool [9, 10]. 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 et al. describing increased cell yields and flow cytometric immunophenotyping results from CSF specimens after addition of RPMI without fetal calf serum [11].

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 myeloma [12-14]. 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 neoplasms [15]. 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 Journal [16, 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-expression [19, 20]. However, the study by Adams at al. does have the advantage over many previous studies of incorporating clinical data [18].

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 assays [21]. 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 Journal [22-26].

  • Fiona Craig*

  • Division of Hematopathology, Department of Pathology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania


  1. Top of page
  • 1
    Borowitz MJ, Craig FE, Digiuseppe JA, Illingworth AJ, Rosse W, Sutherland DR, Wittwer CT, Richards SJ. Guidelines for the diagnosis and monitoring of paroxysmal nocturnal hemoglobinuria and related disorders by flow cytometry. Cytometry B Clin Cytom 2010;78B:211230.
  • 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 accurate than CD14 expression. Cytometry B Clin Cytom 2014;86B:111120.
  • 3
    Dalal BI, Khare NS. Flow cytometric testing for paroxysmal nocturnal hemoglobinuria: CD64 is better for gating monocytes than CD33. Cytometry B Clin Cytom 2013;84B:3336.
  • 4
    Sutherland DR, Keeney M, Illingworth A. Practical guidelines for the high-sensitivity detection and monitoring of paroxysmal nocturnal hemoglobinuria clones by flow cytometry. Cytometry B Clin Cytom 2012;82B:195208.
  • 5
    Sutherland DR, Acton E, Keeney M, Davis BH, Illingworth A. Use of CD157 in FLAER-based assays for high-sensitivity PNH granulocyte and PNH monocyte detection. Cytometry B Clin Cytom 2014;86B:4455.
  • 6
    Hudig D, Hunter KW, Diamond WJ, Redelman D. Properties of human blood monocytes. II. Monocytes from healthy adults are highly heterogeneous within and among individuals. Cytometry B Clin Cytom 2014;86B:121134.
  • 7
    Demaret J, Walencik A, Jacob MC, Timsit JF, Venet F, Lepape A, Monneret G. Inter-laboratory assessment of flow cytometric monocyte HLA-DR expression in clinical samples. Cytometry B Clin Cytom 2013;84B:5962.
  • 8
    Vafaii P, Digiuseppe JA. Detection of B-cell populations with monotypic light chain expression in cerebrospinal fluid specimens from patients with multiple sclerosis by polychromatic flow cytometry. Cytometry B Clin Cytom 2014;86B:106110.
  • 9
    Stacchini A, Aliberti S, Demurtas A, Benevolo G, Godio L. Ten antibodies, six colors, twelve parameters: A multiparameter flow cytometric approach to evaluate leptomeningeal disease in B-cell non-Hodgkin's lymphomas. Cytometry B Clin Cytom 2012;82B:139144.
  • 10
    de Graaf MT, de Jongste AH, Kraan J, Boonstra JG, Sillevis Smitt PA, Gratama JW. Flow cytometric characterization of cerebrospinal fluid cells. Cytometry B Clin Cytom 2011; 80B:271281.
  • 11
    Greig B, Stetler-Stevenson M, Lea J. Stabilization media increases recovery in paucicellular cerebrospinal fluid specimens submitted for flow cytometry testing. Cytometry B Clin Cytom 2014; 86B:135138.
  • 12
    Cannizzo E, Bellio E, Sohani AR, Hasserjian RP, Ferry JA, Dorn ME, Sadowski C, Bucci JJ, Carulli G, Preffer F. Multiparameter immunophenotyping by flow cytometry in multiple myeloma: The diagnostic utility of defining ranges of normal antigenic expression in comparison to histology. Cytometry B Clin Cytom 2010;78B:231238.
  • 13
    Demurtas A, Stacchini A, Aliberti S, Chiusa L, Chiarle R, Novero D. Tissue flow cytometry immunophenotyping in the diagnosis and classification of non-Hodgkin's lymphomas: A retrospective evaluation of 1,792 cases. Cytometry B Clin Cytom 2013;84B:8295.
  • 14
    Alapat D, Coviello-Malle J, Owens R, Qu P, Barlogie B, Shaughnessy JD, Lorsbach RB. Diagnostic usefulness and prognostic impact of CD200 expression in lymphoid malignancies and plasma cell myeloma. Am J Clin Pathol 2012;137:93100.
  • 15
    Sandes AF, Chauffaille MD, Oliveira CR, Maekawa Y, Tamashiro N, Takao TT, Ritter EC, Rizzatti EG. CD200 has an important role in the differential diagnosis of mature B-cell neoplasms by multiparameter flow cytometry. Cytometry B Clin Cytom 2014;86B:98105.
  • 16
    Preobrazhensky SN, Szankasi P, Bahler DW. Improved flow cytometric detection of ZAP-70 in chronic lymphocytic leukemia using experimentally optimized isotypic control antibodies. Cytometry B Clin Cytom 2012;82B:7884.
  • 17
    Preobrazhensky SN, Bahler DW. Optimization of flow cytometric measurement of ZAP-70 in chronic lymphocytic leukemia. Cytometry B Clin Cytom 2008;74:118127.
  • 18
    Adams RL, Cheung C, Banh R, Saal R, Cross D, Gill D, Self M, Klein K, Mollee P. Prognostic value of ZAP-70 expression in chronic lymphocytic leukaemia as assessed by quantitative polymerase chain reaction and flow cytometry. Cytometry B Clin Cytom 2014;86B:8090.
  • 19
    O'Gorman MR, Thomas J. Isotype controls—Time to let go? Cytometry 1999;38:7880.
  • 20
    Rizzo D, Bouvier G, Youlyouz-Marfak I, Guerin E, Trimoreau F, Bordessoule D, Jaccard A, Gachard N, Feuillard J. T/B ratio does not reflect levels of ZAP70 expression in clonal CLL B-cells due to ZAP70 overexpression in patient T-cells. Cytometry B Clin Cytom 2013;84B:125132.
  • 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 B Clin Cytom 2014;86B:9197.
  • 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. V. Assay performance criteria. Cytometry B Clin Cytom 2013;84B:315323.
  • 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. IV. Postanalytic considerations. Cytometry B Clin Cytom 2013;84B:309314.
  • 24
    Tanqri S, Vall H, Kaplan D, Hoffman B, Purvis N, Porwit A, Hunsberger B, Shankey TV. Validation of cell-based fluorescence assays: Practice guidelines from the ICSH and ICCS. III. Analytical issues. Cytometry B Clin Cytom 2013;84B:291308.
  • 25
    Davis BH, Dasgupta A, Kussick S, Han JY, Estrellado A. Validation of cell-based fluorescence assays: Practice guidelines from the ICSH and ICCS. II. Preanalytical issues. Cytometry B Clin Cytom 2013;84B:286290.
  • 26
    Davis BH, Wood B, Oldaker T, Barnett D. Validation of cell-based fluorescence assays: Practice guidelines from the ICSH and ICCS. I. Rationale and aims. Cytometry B Clin Cytom 2013;84B:282285.