Quantitative Flow Cytometry In The Clinical Laboratory

Clinical and Applied Immunology Reviews 5 (2005) 353–372

Quantitative flow cytometry in the clinical laboratory Kevin J. Maher, PhDa,b,*, Mary Ann Fletcher, PhDa a

Department of Medicine, University of Miami School of Medicine, 1600 NW 10th Avenue, RMSB 8172A, Miami, FL 33136, USA b Laboratory Corporation of America, Burlington, NC, USA Received 11 January 2005; received in revised form 10 October 2005; accepted 13 October 2005

Abstract Flow cytometry is most often used in the clinical laboratory for the purpose of immunophenotyping. Here, fluorescently labeled antibodies are bound to cell surface receptors, and their presence on the cell is most often defined in bivariate terms of positive or negative, with a cutoff set relative to a nonstaining control population. It has long been recognized that the intensity of the fluorescent signal is proportional to the amount of antibody bound per cell and therefore related to the number of antigen sites expressed. This relationship makes flow cytometers, at least theoretically, capable of quantifying antigen expression in terms of molecules per cell. There were numerous obstacles to the development of such methods and clinical utilization of fluorescence intensity measures by flow cytometry has in the past been largely overlooked. The first widespread recognition of the clinical utility for fluorescence intensity measures came from laboratories where malignant phenotypes were defined by aberrant intensity of staining due to over or under expression of various cellular proteins. These semiquantitative measures were relative in nature and described staining as bright or dim compared to that normally seen in healthy individuals. Recent advances within the past decade have resulted in the development of flow cytometric methods and materials that now permit one to conduct measures of quantitative fluorescence with improved levels of control and interlaboratory precision. With these advances have come increasing interest in quantitative flow cytometry as a method to quantify the expression and activities

Abbreviations: ABC, antibody binding capacity; ALL, acute lymphocytic leukemia; CLL, chronic lymphocytic leukemia; MFI, mean fluorescence intensity; FITC, fluorescein isothiocyanate; FIS, fluorescence intensity standards; F:P, fluorochrome to protein ratio; GVHD, graft versus host disease; MESF, molecules of equivalent soluble fluorochrome; NIST, National Institutes of Standards and Technology; MRD, minimal residual disease; NK, natural killer cell; QFCM, quantitative flow cytometry; RFI, relative fluorescence intensity; rMol, relative number of molecules; VEGF, vascular endothelial growth factor. * Corresponding author. Cell Immunology, 1447 York Court, Burlington, NC 27215, USA. Tel.: C1 800 222 7505; fax: C1 305 243 4674. E-mail address: [email protected] (K.J. Maher). 1529-1049/05/$ – see front matter Ó 2005 Elsevier Inc. All rights reserved. doi: 10.1016/j.cair.2005.10.001

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of a variety of proteins and enzymes for diagnostic, prognostic, and therapeutic purposes. This article discusses the background and theoretical and practical considerations, as well as the current use of quantitative flow cytometry measures in the clinical laboratory. Ó 2005 Elsevier Inc. All rights reserved.

1. What is QFCM? Flow cytometry is a technology whose limits are constantly challenged by researchers and laboratorians. Although, as a clinical method, its principal role has been for immunophenotyping, new challenges have been placed on flow cytometry with an expanded clinical need for quantitative flow cytometry (QFCM). QFCM refers to flow cytometric methodologies that use additional standardization techniques (i.e., spectrally matched calibration standards) in an effort to generate accurate assessments of fluorescence intensity of the labeled cells that are consistent between instruments and laboratories. This technique has the potential to yield unique information that is complementary to that produced by conventional methods. Whereas conventional immunophenotyping measures the proportion of cells that have bound a fluorescently conjugated antibody, QFCM, through the definition of a calibrated scale, aims to quantify the number of bound molecules (e.g., antibodies) so as to make inferences about the cellular concentration of the target antigen. In the context of phenotypically defined subsets, this information on cellular concentrations of defined antigens is proving to be a powerful technique that will have far reaching applications throughout biology. Already, this technique has demonstrated utility in numerous clinical arenas, some of which are described below. 1.1. Early development of QFCM The goal of QFCM grew logically from the serologic nature of immunophenotyping and the recognition that fluorescence intensity of antibody stained cells is proportional to the bound conjugate. This relationship was demonstrated in studies combining radioimmunoassays and flow cytometric analysis of indirect immunofluorescence [1]. Several years later, Poncelet and Caryon [2] used radiolabeled antibodies to quantify cell surface p67 (CD5) expression on several different cell lines. From these determinations, a quantitative indirect immunofluorescence standardization assay was developed wherein the cell lines, with known numbers of antigenic sites were saturated with unlabeled anti-p67 followed by fluorescein isothiocyanate (FITC)-labeled antimouse IgG. These cells then functioned as fluorescently labeled standards from which a standard curve could be drawn. However, over the years, it has become apparent that numerous obstacles have made the goals of QFCM more easily attained in principle than in practice [2–7]. Many of the early attempts to quantify antigen expression used relative fluorescence intensity (RFI) values. RFI is a measure of the brightness of staining that is usually defined relative to control samples. RFI, however, does not define the number of antigen molecules per cell [8]. Some of the early clinical attempts at quantifying protein expression by flow cytometry came from investigators who wanted to describe the aberrant expression of antigens on

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malignant cells [9]. These descriptions of cell staining in terms of instrument channel number or as relative ‘‘brightness’’ have remained an important component in the flow cytometric assessment of leukemias and lymphomas [10–12]. However, the absolute distinction between the relative descriptors was ill defined and valid comparison of channel numbers across instruments and time has been problematic. Accurate interpretation of the data requires the judgment of individuals with considerable experience in assessing antigen expression by flow cytometry. In their article on instrument standardization, Purvis and Stelzer [13] noted that one reason for the difficulty in interpreting results was that cytometers report RFI values as unitless histogram channel numbers, which are entirely dependent on the cytometer’s design and configuration at the time of measurement. As a result, it has been suggested that mean fluorescence intensity (MFI) should not be used as a unit to report fluorescence intensity measures [14]. Among the instrument variables that affect fluorescence intensity measurement are gain settings and filter setup. Noninstrument variables that affect fluorescence intensity measures include the choice of fluorochrome, antibody, and the ratio of fluorochrome to protein (F:P) on the conjugated antibody. The absence of well-defined materials that could be used as standards and lack of a consensus regarding the appropriate method have also been major barriers to the development of QFCM methods in the clinical laboratory. Despite these limitations, over the years, fluorescence intensity measures have been increasingly used and recognized as an important parameter in appropriately designed analytical systems. The growing importance of QFCM can be found by noting the increase in the number of articles devoted to the subject. The dramatic increase in the number of publications whose abstracts referred directly to the use of quantitative fluorescence intensity measures by flow cytometry rose from 2 in 1981 to an average of 46 per year for the years 2000–2004. As QFCM increased in popularity, in 1998, an entire issue of Cytometry was devoted to the subject with the title Quantitative Fluorescence Cytometry; an Emerging Consensus. This collection was noteworthy in the articles, which served to identify the breadth of variables that affect accurate assessment of fluorescence intensity measures as well as identify various approaches to control these variables. The issue noted the state of the science and underscored the need for standardization of the instruments, procedures, and reagents. As the difficulties of performing QFCM became evident in the literature, so did the conclusion that for QFCM, a more stringent and standardized approach to instrument quality control and quality assurance is required. This was noted to be particularly true for the development of clinical assays using QFCM, such as in the assessment of hematologic malignancy [13,15]. As such, the emerging consensus has highlighted those variables that impact QFCM measurements. 2. Requirements In order to maximize the quality of the QFCM data that are generated, it is essential that the design phase of protocol development defines those variables that affect QFCM measures as well as the best method to control them. This includes the establishment of a quality control and assurance program that monitors these on a regular basis. Early on in the design phase, the particular antigens of interest and labeled antibodies are identified. This must be done so as to consider not just the biologic question to be answered, but also the effects

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of processing and the method of analysis. The selection of the fluorescent-labeled antibody for use in a QFCM study is of paramount importance. The antibody, in addition to having biologic relevance, needs to have an affinity for the epitope that is robust enough so as to be minimally affected by processing. The antibody must be titered so as to define a concentration that permits saturation binding with a minimum of nonspecific staining. This requirement for sufficient concentration is necessary so that all epitopes are bound by antibody in a stoichiometric fashion. If commercially packaged antibodies are not available in saturating concentrations, it will be necessary to work with vendors who will custom package antibodies at higher concentration for QFCM analysis. Defining the choice of fluorescent tag that is bound to the antibody is equally important in the early stages of design because the reporter molecule of the analytic system must yield a signal that is also stoichiometrically related to the presence of bound antigen. Numerous factors need to be considered here due to the distinct physical characteristics of individual fluorochromes. For instance, the fluorescence emission of FITC is affected by pH with fluorescence decreasing with decreasing pH [16]. As a result, any QFCM study using this fluorochrome must control for pH across sites and time. In addition, FITC has the capacity to self-quench because its excitation and emission spectra overlap [17]. The stoichiometry of binding of the fluorescent tag to the antibody is also variable, and the amount of tag bound per antibody molecule (F:P ratio) should be consistent over the course of the study. Furthermore, within a particular choice of fluorochrome, differences may exist related to its source. For example, the spectral characteristics of different phycoerythrin molecules from different suppliers may differ depending upon the organism that produced them. Spectral characteristics of the fluorochrome are also important when considering confounding factors such as autofluorescence, because there is a greater spectral overlap between the autofluorescence of cells and the emission from FITC than there is with other fluorochromes. As a result, any analyses utilizing FITC staining may require subtraction of the corresponding autofluorescence value from each of the fluorescence intensity measures. Finally, the choice of fluorochrome conjugate must be made in conjunction with the choice of fluorescence intensity standards, because they need to be spectrally matched to ensure instrument-independent calibration [18,19]. Once the selection of antibody conjugate is made, sufficient quantities from the same lot should be purchased so that all sites will have identical reagents for the duration of the study. Selection of sample type and anticoagulant and use of whole blood analysis vs. separated mononuclear fraction of blood need to be established because they will dictate the subsequent processing steps. The choice of sample type is important because processing methods are important determinants of the quality of the QFCM data that are generated. Separation of mononuclear cells by density gradient centrifugation may result in the cell loss and has rendered whole blood analysis the preferred method for immunophenotyping [20]. Although immunophenotyping for major subsets is not affected by lysing agent and fixative, QFCM is [21]. Because fixation effects are epitope and antibody clone specific, processing methods must be chosen that are optimal for the particular application. Instrument condition, age, setup, model, and manufacturer all affect the overall instrument performance and quantitative characteristics. Because QFCM measures are so dependent upon instrument setup, a more stringent and standardized approach to instrument quality control and quality assurance is required than is used with standard phenotyping

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[15]. This degree of standardization is needed to ensure accurate, reproducible cytometric analyses when conducting clinical diagnostics and research studies in a multiple site, multiple platform environment [13]. Daily verification of instrument alignment, voltage setting, and compensation are required so that the optimal parameters are identified and set each time the QFCM data are collected. In addition, to make comparisons across instruments, sites, and time, it is necessary to use a method of standardization that is specific for QFCM. The standardization process is necessarily designed in tandem with all other aspects of the protocol because all methods and materials must be complementary. The main requirement for a calibration standard for flow cytometry is that its excitation and emission spectra will match those of samples to be analyzed [18]. Matching the spectra of the calibrators and those of the samples will normalize the responses between instruments that have different barrier filters [18]. Once achieved, this standardization process should improve the QFCM analysis by minimizing the effects of minor daily fluctuations in instrument settings and condition as well as providing a way of transforming the data from instrument channel numbers to a standard unit of measure. This standardization is necessary to permit interlaboratory comparability of fluorescent measurements [15] as well as to meet the regulatory requirements and recommendations for clinical testing as established by the CLIA (Clinical Laboratory Improvement Amendments 1988) 88, CDC (Centers for Disease Control and Prevention), and NCCLS (National Committee for Clinical Laboratory Standardization) [20,22,23]. Although numerous methods have been developed for standardizing QFCM measurements, the easiest have been those that use bead-based standards. Quantitative calibration beads provide the means to move from arbitrary relative intensity units to standard quantitative fluorescence units for reporting quantitative molecules of equivalent soluble fluorochrome (MESF) intensities and even numbers of antibodies bound to the cell [16]. Four approaches are presented here. 2.1. Biologic calibrators As mentioned earlier, Poncelet and Caryon [2] used a radioimmunobinding assay to quantify CD5 antigen levels on cell lines. These cell lines, with different numbers of CD5 expression then functioned as biologic standards with assigned antigen values. The cell lines were then stained with unlabeled anti-CD5 antibody, followed by FITC-labeled antimouse IgG. This permitted the generation of a calibration curve that linked fluorescence intensity to absolute numbers of binding sites per cell. Janis Giorgi’s [24] group used the uniform expression of CD4 on healthy lymphocytes and a published value of 50 000 CD4 molecules per T-helper lymphocyte to define a single point calibration system. Here, the authors stained healthy lymphocytes with anti-CD4-PE antibodies and divided the value of 50 000 by the MFI for the CD4 to estimate the number of PE molecules per channel for their cytometers. This method was used to demonstrate the prognostic utility of measuring CD38 intensity in HIV infection (see below). 2.2. Molecules of equivalent soluble fluorochrome Another method for standardizing fluorescence intensity has been to use calibrators based upon solutions having a known number of fluorescent molecules (MESF). These standard

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solutions are then used as references to assign values to fluorescent beads. An FITC bead with an assigned value of 10 000 MESF has the same fluorescence intensity as a solution containing 10 000 molecules of FITC [18]. Using beads with known MESF values permits the calibration and the conversion of channel number to MESF as a unit of fluorescence intensity. Standards that have been assigned values in MESF establish an instrument-independent scale that accurately depicts the molar quantity of fluorochromes on stained particles. The FITC–MESF calibration system has been widely applied in a variety of studies within and between laboratories [13,25–27]. In 1999, the National Institute of Standards and Technology initiated the fluorescence intensity standards program [28] and developed two reference materials, a fluorescein solution and a calibrated set of microspheres, thereby permitting the generation of traceable standards for fluorescein based assays [29]. The MESF system has been used most extensively with fluorescein, however, MESF calibrated beads have also been developed for PE, although an established standard has not been set [13]. 2.3. QuantiBRITE A similar approach to the standardization of quantitative fluorescence measures uses phycoerythrin-labeled beads that have assigned values of known numbers of molecules of PE per bead. These beads can be used as calibrators to generate a curve of fluorescence intensity (MFI) vs. numbers of molecules PE per bead. Interpolation of this curve can be performed using the MFI value obtained by analyzing PE-Ab labeled cells to determine the number of PE molecules bound per cell. If the antibodies used to stain the cells have a known ratio of PE:IgG molecule of 1:1, then the number of PE molecules per cell equals the number of antibody molecules bound per cell. The system bypasses the need for MESF determination by using unimolar PE-fluorescent conjugate and assuming that the PE molecules on the microsphere standards have the same fluorescence yield as PE molecules on antibody bound to stained cells [29]. This method is simple in principle and practice but is limited by the need to use PE-labeled conjugates with a known F:P of 1:1. A variation of this method is demonstrated in Fig. 1, in which histograms from 2 separate analyses are overlaid with the QuantiBRITE calibration curve. Here the units are presented as relative (r) number of perforin molecules to reflect the unknown F:Pratio of the antibody. In this example, an individual with chronic fatigue syndrome is seen to have lower antiperforin fluorescence intensity associated with the natural killer (NK) cell subset than that for the healthy control. The CFS subject had a median fluorescence intensity of perforin-PE staining of 3.21 and an NK perforin content of 2809 rMol perforin/NK cell compared to an MFI of 14.9 and a perforin content of 12 129 rMol perforin/NK cell for the healthy control. Whereas this relative designation precludes the designation of absolute concentrations, it permits precise measures across instruments and time providing that all reagents and methods are consistent. 2.4. Antibody binding capacity The final system to be described here is that using type IIIc microsphere standards [30] that are coated with antimouse-immunoglobulin. Here, a series of beads with defined

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100000

Molecules PE

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Slope = 799 Y- Intercept = 244

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PE Intensity(channel #) Fig. 1. QFCM calibration composite of 2 histograms from the analysis of NK cell perforin content and the Quantibrite calibration curve. The peak on the left was derived from the analysis of a subject diagnosed with chronic fatigue syndrome whereas the peak on the right was from that of a healthy control.

binding capacity are incubated with the same lot of antibody used for staining the cells. A standard curve of antibody binding capacity (ABC) vs. RFI is constructed. ABC equals the number of antibody molecules bound by a particle when specific binding sites are saturated. Because the measurement is made near saturation, the ABC value is taken as a measure of the overall expression of the receptor, even though the relationship may not be one-to-one. As such, this unit (like those mentioned above) is not a direct measurement of cell receptors, but rather a measurement of the ABC of the cell for the labeled reagent [18]. Standards that have been assigned binding capacity units provide an instrument-independent molar quantification scale [23]. One advantage of ABC is that the effective fluorochrome to protein ratio does not need to be taken into consideration, because both the cells and the standards are being labeled with the same fluorescently labeled conjugated antibody [18]. This system provides direct, quantitative ABC calibration for the specific conjugated antibody being stained and permits the calibration of a wider range of fluorochromes [13].

3. The clinical utility of QFCM Because antigen expression can range along a scale from no expression to varying degrees of expression, the bivariate distinction of positive and negative, as determined with convention flow cytometry, may or may not correlate well with the results obtained with QFCM. An illustration of the potential advantages of QFCM can be demonstrated with the comparison of 2 analyses of perforin expression from healthy individuals and 2 individuals with genetic mutations in the perforin gene [31]. In Fig. 2, conventional flow cytometric analysis shows that the individual with a homozygous deficiency of perforin (0 functional perforin genes) has a negligible proportion of NK cells that express perforin at levels above the isotype control. In contrast, the mother of the perforin deficient subject, who was heterozygous for the

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Conventional Flow Cytometry

Proportion of NK Expressing Perforin

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Number Perforin Genes Fig. 2. Conventional methodology. Proportion of NK cells expressing perforin in 20 healthy controls (2 perforin genes), an individual with heterozygous deficiency of perforin (1 perforin gene), and an individual with homozygous deficiency of perforin (0 perforin genes).

deficient gene (1 functional perforin gene), had a proportion of NK cells expressing perforin that was comparable to those of the healthy controls. When these same individuals were analyzed by QFCM (Fig. 3), the heterozygous condition was associated with a level of perforin binding that was half that of the controls (2 functional perforin genes) and below the 15th percentile for healthy individuals. These results suggest that QFCM has a greater diagnostic sensitivity to detect quantitative deficiencies compared to conventional flow cytometric methods. Quantitative Fluorescence Flow Cytometry

r Mol Perforin / NK cell

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Number Perforin Genes Fig. 3. Quantitative method. Quantitative flow cytometric methods were used to calculate the median relative (r) number of perforin molecules expressed per NK cell in 2 subjects with perforin gene defects and healthy controls as described in Fig. 2.

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The ability to quantify cell-associated antigen expression has steadily increased over time and with the improved standardization, has been making an increased presence in clinical studies. The ability to quantify the cell-associated levels of proteins is a natural extension of the flow cytometry technique that has broad clinical applicability. To demonstrate the value of this technique, the following examples are presented as areas of clinical study that have used QFCM measures. 3.1. Malignancy Malignant cells often express antigens that are not typically expressed by mature cells of the same lineage [32–37]. This aberrant expression is often a hallmark of malignancy and such inappropriate expression of antigens can be diagnostic [35,38]. Furthermore, leukemic cells may express antigens at densities distinct from those presented by their normal counterparts [39,40]. Examples include CD20 in chronic lymphocytic leukemia [41], abnormally bright CD20 on hairy cell leukemia [42], decreased CD3 in Mycosis fungoides [43], and dim CD5 on large granular lymphoproliferative disorder [12]. Because fluorescence intensity measures are important determinants in the analysis of leukemia and lymphoma [12], reliable measurement of intensity of antigen expression is critical to the proper interpretation of data and precise classification of some hematologic malignancies. Therefore, although descriptive terms such as ‘‘dim’’ and ‘‘bright’’ are still useful, it has been suggested that quantitative terms such as ‘‘binding capacity’’ should be used with an understanding of their exact meanings [30]. As such, QFCM has been used by a number of investigators to differentiate malignant cells from their normal counterparts in a variety of settings for a number of purposes. The distinction between normal and leukemic bone marrow B-precursors is essential for the diagnosis and treatment monitoring of acute lymphoblastic leukemia. In one example, Rego et al. [44] used QFCM to demonstrate that the distinction between normal and leukemic cells by QFCM was possible in 38 out of 40 CD10C acute lymphoblastic leukemia cases. In a similar fashion, other investigators have used QFCM to better distinguish malignant cells from their healthy counterparts and to identify new prognostic indicators [45–49]. QFCM may also play a role in monitoring treatment effects as fluorescence intensity measures normalize following therapy in B-cell chronic lymphocytic leukemia [50]. 3.2. Bcl-2 Bcl-2 is an integral membrane protein that functions as a prosurvival apoptosis regulator. Overexpression of Bcl-2 has been reported in a wide variety of cancers and is associated with resistance to apoptotic stimuli such as chemotherapy [51–55]. Several studies have used antisense oligonucleotides to investigate the therapeutic benefits associated with Bcl-2 down regulation [56,57]. These studies prompted the investigators to longitudinally measure the levels of Bcl-2 in vivo and in vitro using QFCM so as to permit correlation of Bcl-2 expression levels with staging and specific treatment responses [36,56,57]. Compared to the western blot method, the quantitation range using flow cytometry had a higher resolution and greater sensitivity [57]. Using QFCM, the mean Bcl-2 expression by lymphoblasts in 10 cases of B-precursor acute lymphoblastic leukemia was significantly higher than that seen in normal B-precursors [36].

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In other studies, it was also demonstrated that cases of AML with M1 and M2 features showed significantly higher mean Bcl-2 levels than leukemias with promyelocytic (M3) or myelomonocytic (M4/M5) features [56]. Relatively high levels of Bcl-2 expression have also been associated with lower rates of complete remission and overall survival in patients with AML [58,59]. Because high Bcl-2 levels are clearly related to a resistance to apoptosis that can be induced by cytotoxic drugs [60], QFCM can be a valuable tool to demonstrate that a Bcl-2 mediated form of drug resistance might exist. In a similar fashion, estrogen receptor and progesterone receptor quantitation can be very useful in patients with breast cancer as their role in diagnosis and prognosis is well established [61]. A QFCM method has been developed for the detection and quantification of estrogen and progesterone receptors in several human cell lines and in clinical samples obtained from breast cancer tumors [61]. These receptors can be quantified reliably in terms of MESF without the limitations of competition with serum estradiol molecules [61].

4. Minimal residual disease detection The detection of leukemic cells at concentrations below the resolution by morphological analysis (!1%, minimal residual disease) may allow a better estimate of the leukemic burden and may be correlated with clinical outcome [32,33,46,62–67]. The ability of flow cytometry to analyze large numbers of cells with great sensitivity combined with the ability to distinguish leukemic cells from their normal counterparts by QFCM has prompted the use of this method in the detection of minimal residual disease [39,67–69]. QFCM was more informative than conventional morphology to assess remission status and showed a strong correlation with clinical outcome [39,67]. 4.1. Monoclonal antibody and immunotoxin therapy In addition to its role in diagnosis and prognosis as described above, QFCM has been demonstrating a valuable role in the selection of patients and determination of efficacy in the therapeutic use of immunotoxins in cancer treatment. In this treatment approach, toxins are linked to an antibody or ligand and infused into the patient to specifically kill tumor cells bearing the specific receptor. Because antigen density is directly related to the cells susceptibility to killing with these agents, QFCM is necessary to evaluate the appropriateness of these therapies for each patient. A number of therapeutic agents of this type have been developed and currently used in treatment. These include Rituximab, a chimeric anti-CD20 monoclonal antibody therapy for relapsed indolent lymphoma as the CD20 antigen is expressed on more than 90% of B-cell lymphomas. Herceptin (Trastuzumab) is a recombinant humanized monoclonal antibody that selectively binds human epidermal growth factor receptor 2 protein, HER2.1,2. Herceptin is indicated for the treatment of patients with metastatic breast cancer whose tumors overexpress the HER2 protein. Erbitux, which is used in the treatment of colorectal cancer, is a humanized mouse antibody that binds and functionally blocks the epidermal growth factor receptor. Another therapeutic antibody used in the treatment of colorectal cancers is Avastin, which functions as an antiangiogenic agent by binding and inhibiting vascular endothelial growth factor. ONTAK is a diphtheria toxin

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conjugated antibody directed against the receptor for IL-2. Its use is indicated for the treatment of patients with persistent or recurrent cutaneous T-cell lymphoma whose malignant cells express the CD25 component of the IL-2 receptor. Campath (Alemtuzumab) is a humanized monoclonal antibody that binds to CD52, which is present on the surface of essentially all B and T lymphocytes, a majority of monocytes, macrophages, and NK cells, and a subpopulation of granulocytes. Its use is indicated for the treatment of B-cell chronic lymphocytic leukemia where it purportedly mediates antibody-dependent lysis of leukemic cells following cell surface binding. A similar approach was recently applied by Smith et al. [70] to measure the cell surface density of CD51 to assess the efficiency of adenovirus targeted gene delivery. 4.2. HIV prognosis CD38 is a protein whose expression increases upon activation [71–74] and in HIVinfected individuals. Using CD4 fluorescence intensity as a biologic calibrator, Liu et al. [75] demonstrated the utility of QFCM analysis of CD38 as a prognostic marker in HIV infection. This study used 1:1 conjugates of PE:CD4 and PE:CD38 and determined the number of PE molecules detected per channel on the flow cytometer by measuring the fluorescence intensity of CD4 and setting this equal to 50 000 molecules of CD4. Using this calibration factor, the median CD38 RFI on each sample was converted to number of molecules CD38 per CD8 cell. This system allowed standardization of CD38 on CD8 measurements across instruments and laboratories. The prognostic power of elevated CD38 antigen expression on CD8C cells was reported to be greater than that of any other activation marker and greater than that of CD4C cell number and percent. Cox proportional hazard models indicated that elevated CD38 on CD8 cells was the most predictive marker of those studied for the development of a clinical AIDS diagnosis and death. Compared with the reference group, (who had CD38 of !2470 molecules per CD8C cell and in whom 4 of 99 developed clinical AIDS within 3 years), participants with CD38 on CD8 between 2470 and 3899, 3900 and 7250, and O7250 had relative risks (and numbers developing clinical AIDS within 3 years) of 5.0 (15 of 81), 12.3 (24 of 60), and 41.4 (36 of 49), respectively. This system was later simplified using PE calibration standards. In a multisite study [76], the CD38PE binding on CD8 T-cells measured using PE microsphere calibrators was comparable to that measured by the CD4 biologic calibrator method. 4.3. Sepsis During acute inflammation, a variety of changes occur in the immune system. In addition to the acute phase response, numerous changes in protein expression occur on the surface of leukocytes. CD69 is one marker that is modulated early in the course of cellular activation. Flow cytometric evaluation of bacterial sepsis has demonstrated the decrease in HLA-DR expression on monocytes [77] and elevation of CD11b [78] and CD64 on neutrophils [79]. Quantitation of CD64 on neutrophils has been developed as an indicator of systemic acute inflammatory response to infection, sepsis, or tissue injury [80] and has been marketed as a diagnostic assay (Trillium Diagnostics).

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5. Enzymatic deficiencies In a related but different approach, a study of intracellular enzymatic activity has been done with the use of flow cytometry and fluorescent substrates that are taken up by cells and rendered fluorescent following enzymatic cleavage. Because these fluorescent products are produced in proportion to the level of enzymatic activity, the fluorescent intensity of the product-laden cell can be used as a measure of enzyme content. This approach was used in the development of a clinical flow cytometric assay for the diagnosis of chronic granulomatous disease where genetic mutations in the gene for NADPH oxidase preclude the development of an oxidative burst [81–83]. In an analogous fashion, QFCM techniques were incorporated in the development of a flow cytometric-based diagnostic tool for measuring B-glucocerebrosidase activity in Gauchers disease [84]. Although such methods are not ligand binding in nature, the quantification of fluorescence intensity requires standardization analogous to the methods already described. 6. Genetic disease and carriage As alluded to earlier in the description of the perforin analysis, QFCM can be useful in discriminating heterozygous gene mutations from normal phenotypes. Other genetic deficiencies may be studied in a similar fashion. The intensity of expression of the CD11/ CD18 complex in suspected cases leukocyte adhesion deficiency has been demonstrated as a useful flow cytometry technique [85], and such analyses may be amenable to QFCM. QFCM may also be of value in identifying heterozygous family members who are carriers of a mutation for the purposes of genetic counseling. In the field of transplantation, QFCM has been used to decrease the likelihood of graft versus host disease by allowing improved matching of donor and recipients. The assessment of compatibility in donor/recipient pairs by routine serologic typing methods sometimes yields ‘‘blanks’’ in a number of cases that are presumed to be homozygous. Transfusion of cellular components with such a mismatch can lead to graft versus host disease [86– 93]. Because a true homozygous expression of an allele will result in twice the cellular concentration of a heterozygous expressing cell, Carreno et al., [94] used QFCM to identify situations where one allele was missed in the matching process as a clinical aid in therapy of such transplant recipients. 7. Advances Over the years, and in response to the expanding interest in QFCM, numerous committees have been formed, guidelines written, and articles published marking the development of QFCM as a discipline. In 1998, the journal Cytometry devoted an entire issue to QFCM. Here, a number of articles highlighted the technical aspects and presented what was considered an emerging consensus [13,19,24,26,27,30,95–110]. In addition to procedural aspects, several articles defined nomenclature for this field in an attempt to clarify the literature [30,97]. In 1999, the National Institute of Standards and Technology initiated the fluorescence intensity standards program, which led to the development of two reference

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materials: a fluorescein solution (SRM 1932) and a calibrated set of microspheres (RM 8640). Since then, the NCCLS has convened a subcommittee to propose consensus guidelines for quantitative fluorescence calibration [30], which were most recently published as the approved guidelines for fluorescence calibration and quantitative measurement of fluorescence intensity [29]. The development of a formal theory for quantitative fluorescence analysis and the development of standardized materials represent major advances in the field of quantitative fluorescence cytometry 8. Limitations The ultimate goal of QFCM is the accurate determination of number of molecules of protein expressed per cell. At the present time however, numerous limitations remain that prevent making such determinations with absolute certainty. The development of multiple QFCM calibrators has permitted the determination of binding in terms of antibodies bound per cell, but each approach to standardization has been developed independently of the other and as such each yields different results. Within a single lab, a comparison of 2 different commercially available methods (Quantum Simply Cellular and Quantibrite) yielded a 3fold difference in number of antibodies bound [19]. In 2 studies of CD4 binding on T-cells in which capture microsphere standards were used with direct conjugates, results differed over a 6-fold range (30 000–180 000) of antibody-fluorochrome conjugate bound per cell [107,108]. It has been reported that commercially available beads with a known number of antimouse capture antibodies are problematic because they lack distinct saturation and because they have varying binding capacities, which depend on factors such as clone, fluorochrome, and conjugation chemistry [95,111,112]. A lack of standardization between these laboratories also likely contributed to the variability. So, from the standpoint of available calibrators, additional work is needed to determine which, if any, is truly accurate. An additional obstacle includes being able to reliably monitor the characteristics of reagents over time. Useful here, would be the demonstration of a control material stable for extended periods of time and suitable for monitoring the binding and fluorescence characteristics of an antibody preparation. Several reports considered one or more commercially available control products (FluoroTrol, StatusFlow, and CD-Chex) with regard to fluorescence intensity, but none was found suitable [19,113]. Among the issues cited were decreased binding relative to fresh cells, interlot variability, and limited shelf life. As calibrators based upon a traceable standard are developed, additional obstacles will continue to limit the determination of absolute values with certainty. Chief among these is the fact that the number of antibodies bound to the surface of a cell is not necessarily equivalent to the number of antigen molecules expressed on that cell due to nonspecific binding, undefined valency of binding, steric hindrance, and hidden or incomplete binding sites [18,19]. 9. Conclusions Numerous variables exist in the quantitative determination of fluorescence intensity as a measure of antigen expression. Some were already mentioned and involve instrument

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(manufacturer, age, and setup) [13], antibody (specificity, affinity, F:P ratio, steric hindrance, valency), sample (type, anticoagulant, autofluorescence [15], polarization [114], interfering medications [115,116]), processing (incubation time, fixation [19]), standardization method, analysis (postanalysis compensation, gating), report (units of measure), and interpretation. Careful attention to these variables during the design phase of establishing QFCM analyses is therefore critical and can limit the effect of most of these variables. The use of a single standardization material and protocol will limit instrument-specific biases across sites and time whereas the use of a standardized reagent protocol (single lots, defined titers) will limit the variance due to affinity, fluorochrome, fixation, etc. Additional efforts will need to be made to determine which of the available methods is most accurate because differences between them have been noted. Therefore, even with these controls, there will, at least for the present time, be inherent assumptions that will need to be made regarding the data generated in highly controlled experiments. Issues such as long-term reagent stability will be addressed with the availability of control materials for the purpose whereas those relating to valency and saturation will likely limit the absolute determination of antigen expression for sometime. The units of measure will therefore be relative to the conditions under which the data were collected and should be acknowledged as such (e.g., rMolecules). The utility of and interest in the use of QFCM in the clinical setting are well documented in the literature and underscore the necessity for continued development of control procedures and materials for this purpose. Great strides have already been taken, and the field has been developing in a rapid pace. Although the goal of absolute molecular quantitation by flow cytometry has yet to be realized, the advances permit the analysis of cellular concentrations of antigen that are relative to the specific method chosen and if controlled appropriately should permit the comparison of values across instruments, sites, and time. Given the demonstrated value of this approach, QFCM will likely continue to have a greater presence in the clinical laboratory.

Acknowledgments This work was funded by support from the NIH Center Grant 1UD 1-AI 45940; the Miami Veterans Affairs Research and Education Foundation; and the CFIDS Association of America.

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