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1 9-Color and 10-Color Flow Cytometry in the Clinical Laboratory Brent Wood, MD, PhD Context. The development of commercial flow cytometers capable of detecting more than 10 simultaneous fluorescent signals presents opportunities for improved diagnosis and monitoring of patients with leukemia and lymphoma. Objective. To describe instrument and reagent characteristics necessary for successful 9-color and 10-color flow cytometry in a clinical setting. Design. Systematic review of issues related to instrument settings, reagent performance, and general principles of panel construction. Results. Nine-color and 10-color flow cytometry offers the possibility for increased accuracy in population identification, the ability to obtain detailed information from paucicellular specimens, improved laboratory efficiency, and the means to consistently detect abnormal populations at low levels. Careful attention to details of instrument and reagent performance allows for the development of panels suitable for screening of samples for leukemia and lymphoma in a clinical setting. Conclusions. The characteristics of this technique are particularly well suited to the analysis of leukemia and lymphoma and have the potential to revolutionize and standardize this type of analysis in the clinical laboratory. (Arch Pathol Lab Med. 2006;130: ) Flow cytometry has become an increasingly important tool in the clinical laboratory for the diagnosis and monitoring of a variety of disease states. 1 4 The ability to simultaneously and rapidly detect multiple cellular characteristics at the single-cell level, coupled with the ability to expeditiously prepare and process clinical material, yields a rapid multiparametric analysis with a high degree of informational content. As a result, the technique is ideal for the identification and immunophenotyping of cellular subpopulations in complex samples such as bone marrow and peripheral blood. In addition to the identification and quantification of normal cellular populations, recent publications have validated the concept that neoplastic cells exhibit patterns of antigenic expression that differ sufficiently from those of normal cells to allow for the diagnosis of neoplasia. 5 9 The success of this approach in a clinical setting is demonstrated by the increasing reliance on flow cytometry as a primary tool in the diagnosis and monitoring of hematopoietic neoplasms. In most clinical laboratories, flow cytometric immunophenotyping is performed using 2 to 4 simultaneous fluorochrome-conjugated antibodies, with each fluorochrome having different excitation or emission spectra and euphe- Accepted for publication December 2, From the Department of Laboratory Medicine, University of Washington School of Medicine, Seattle. The author has no relevant financial interest in the products or companies described in this article. Presented at William Beaumont Hospital s 13th Annual Symposium on DNA Technology in the Clinical Laboratory, Troy, Mich, October 7 9, Reprints: Brent Wood, MD, PhD, Department of Laboratory Medicine, University of Washington School of Medicine, Campus Box , 1959 NE Pacific St, Seattle, WA ( woodbl@u. washington.edu). mistically referred to as a color. This methodology has proved to be adequate to address many of the clinical questions that have arisen in the past decade. However, within the past few years, instrument manufacturers have begun to produce benchtop instruments capable of the simultaneous detection of 10 or more fluorochromes, and with the advent of an increasing variety of fluorochromes suitable for immunophenotyping, the possibility of highlevel multicolor flow cytometry is rapidly becoming a reality This technology offers the potential for exciting new advances in the diagnosis and monitoring of hematopoietic neoplasms, and the practical issues surrounding the implementation of this technology in a clinical laboratory setting are the subject of this article. WHY HIGH-LEVEL MULTICOLOR FLOW CYTOMETRY? Clinical flow cytometry laboratories are increasingly asked to evaluate smaller amounts of material, such as fine-needle aspirates and body fluids, in which the number of cells for evaluation is often the factor limiting analysis. In addition, there is growing interest in the ability to identify small populations of abnormal cells before or after therapy as markers of impending relapse or persistent disease, a task that requires the evaluation of larger numbers of cells with a high degree of reproducibility and specificity. Finally, many clinical laboratories are under more pressure to minimize their use of technical staff and reagents in the face of increasing workloads, a situation in which increased laboratory efficiency is needed. High-level multicolor flow cytometry is well suited to address many of these issues and offers several potential advantages over current 3-color and 4-color flow cytometric techniques. These include the following: 680 Arch Pathol Lab Med Vol 130, May Color and 10-Color Flow Cytometry Wood

2 Increased Accuracy of Population Identification The use of greater numbers of informative antibodies results in a geometric increase in the informational content of the data generated. This provides the ability to more precisely characterize any single event or cell within a complex mixture of cells, an increase in specificity. Increased informational content should also make it easier to identify the presence of abnormal populations of cells at lower levels, an increase in sensitivity. These issues are of particular importance in the identification of small abnormal populations (eg, minimal residual disease detection). Making Better Use of Small Specimens The ability to gain more information from a smaller amount of clinical material should reduce the number of marginal or inadequate results of studies performed on specimens in which the number of cells is a limiting factor. Specimens such as cerebrospinal fluid and fine-needle aspirates fall into this category. This should also improve diagnostic capabilities by providing the possibility for a more complete characterization of the cells that are present. Processing of Fewer Tubes The use of increased numbers of antibodies or reagents in a single tube results in fewer tubes needing to be processed, with resultant savings in specimen volume, instrument time for acquisition, and technologist time to process and acquire the specimen. In addition, through the use of more reagents per tube, redundancies of reagents within panels are reduced, resulting in savings in the volume of reagent consumed. Providing More Efficient Collection of Larger Numbers of Events The processing of fewer tubes and the use of smaller specimens would provide the ability to routinely collect larger numbers of events. This is an issue of increasing importance, particularly with regard to minimal residual disease detection. Standardization Current squabbles regarding the best 3-reagent or 4- reagent combination to identify a particular leukemia or lymphoma might be rendered irrelevant through the use of larger panels that include many of the most popular combinations. As a result, there is the possibility of providing a standardized approach to this type of analysis that is currently lacking. The disadvantages of high-level multicolor flow cytometry are predominantly related to a higher cost for instrumentation, the use of more specialized reagents with associated marginally higher costs, the greater expertise needed to understand a variety of technical issues, and more complex data analysis. The cost issues are likely to improve as the technology matures and becomes used more widely, and the technical issues will be discussed herein. HOW MANY COLORS ARE ENOUGH? With the ability to detect larger numbers of fluorochromes, the question arises as to how many fluorochromes are optimal for use in a clinical laboratory setting. As one might expect, the answer to this question is directly related to the objective of the evaluation. For some assays in which a homogeneous population of cells is being evaluated or a simple question is being asked, 1-color flow cytometry may be sufficient. In other more complex applications in which the sample consists of complex mixtures of cells, one is evaluating coordinate expression of multiple antigens or identifying and further immunophenotyping small abnormal subpopulations, and an increased number of fluorochromes is desirable. In principle, it would be ideal to incorporate all the reagents necessary to answer a single question into a single tube, but this may not be possible depending on the complexity of the question being addressed. For many common flow cytometric assays in the clinical laboratory (eg, lymphocyte subset analysis, immunodeficiency evaluation, and diagnosis of paroxysmal nocturnal hemoglobinuria), the question being asked is simple: how much of a given population having a known immunophenotype is present? For this purpose, 1 to 4 colors appears to be adequate, depending on the assay. However, in the case of leukemia and lymphoma diagnosis and monitoring, the evaluation of a specimen typically involves a series of interrelated questions as to whether an abnormal population of cells is present, what the lineage of the abnormal cells might be, and, if present, how the abnormality fits into current classification schemes. The problem is made more acute by the large number of types of hematopoietic neoplasms, the variability of immunophenotypic findings for a given disease category, and the need to identify the abnormal population in a complex cellular background. In particular, one feature that distinguishes this type of analysis is that the immunophenotype of the population of interest, if present, is largely unknown, and the analysis relies on the identification of deviation from immunophenotypic patterns of normal maturation. Consequently, to address the myriad of questions that surround this type of evaluation, a large number of colors would be ideally required. Therefore, leukemia and lymphoma analysis serves as a useful model for evaluating the application of high-level multicolor flow cytometry in the clinical laboratory. To determine the optimal number of colors required for leukemia and lymphoma analysis, one must first realize that it is not possible even with 10-color flow cytometry to incorporate all the reagents necessary to answer all of the relevant questions for even a subset of these disorders into a single tube. This necessitates refining the question that each combination of reagents is expected to address, with the following possible strategies: Disease Specific In this method, a tube of reagents is specifically constructed to identify 1 or perhaps a few closely related disease states. An example might be chronic lymphocytic leukemia, in which ideally one might like to include at least CD19, CD20, CD5, and light chains, CD23, and the prognostic markers CD38 and ZAP-70, with perhaps the addition of CD79b, CD45, FMC7, and others. In this example, we are already at a minimum of 8 colors, and probably 10 or more would be ideal. Although this approach would be good to identify, classify, and generate prognostic information for that neoplasm with a high level of sensitivity, it would perform less well for the identification and characterization of other B-cell neoplasms such as precursor B-cell leukemia/lymphoma or hairy cell leukemia, Arch Pathol Lab Med Vol 130, May Color and 10-Color Flow Cytometry Wood 681

3 and additional combinations of reagents specific for each neoplasm would be needed. Given the large number of hematopoietic neoplasms, this approach would require many disease-specific combinations and would prove impractical to implement as a screening tool when the diagnosis is unknown. However, for residual disease detection following therapy, this approach has potential advantages in efficiency and reagent use. Single-Tube Screening The ideal would be to create a single tube to simply identify the presence of any abnormal population of hematopoietic cells, with further characterization of the population requiring subsequent additional reagent combinations. Given the diversity of lineages and immunophenotypes for hematopoietic neoplasms, it is unlikely that a single combination could accomplish this with a high degree of sensitivity without the use of many more colors than are technically possible at this time. In addition, this approach would be inefficient in that for virtually every case in which an abnormal population was identified 1 or more additional tubes would need to be run. Consequently, if the incidence of positive cases was moderately frequent, the work flow in the laboratory would become recursive and inefficient. Lineage-Specific Screening This approach attempts to combine the benefits of disease-specific screening (ie, high-sensitivity detection with complete characterization of abnormal populations) with single-tube screening (ie, the ability to identify a variety of hematopoietic neoplasms simultaneously). The reagent combination ideally should be able to identify the presence of an abnormal population for all categories of neoplastic disease within a given lineage. Additional studies to further define the immunophenotype or to identify prognostic features could then be performed in separate assays using a reduced number of colors as appropriate for the question being asked. For instance, a generic evaluation of B cells might include CD45, CD19, CD20, CD10, CD5, CD38, CD34, and and light chains, a total of 9 colors, well within the capabilities of current technology. Although some recursive work flow is inevitable, the more complete nature of the screening should minimize the number of subsequent reagents used, as well as the need for additional tubes in many cases. The ability to incorporate yet-to-be-identified disease-specific prognostic features is also easily accomplished in this scheme. Using this approach, our initial evaluations suggest that it is possible to construct such reagent combinations using 10 or fewer colors that focus on identifying abnormal B-cell, T/NKcell, plasma cell, progenitor or blast, or maturing myelomonocytic hematopoietic neoplasms. This approach will be the focus of the subsequent discussion. With fewer than 8 or 9 colors, none of the approaches already outlined are feasible using a single tube, and multiple tubes will be required for any evaluation, each focusing on a subset of the features that need to be identified, resulting in a fragmented analysis strategy. The exact number of colors used per tube below the threshold of 8 or 9 is less critical, provided it is more than the recommended minimum of 3 colors. 13 Consequently, there is minimal benefit to moving from the current standard of 3-color and 4-color flow cytometry to 5-color and 6-color Table 1. Fluorochromes and Optical Filters Suitable for 11-Color Flow Cytometry* Laser Wavelength Fluorochrome Filter Violet (407 nm) Blue (488 nm) Yellow (594 nm) Red (635 nm) Pacific Blue DAPI Am-Cyan FITC PE PE Texas Red PE-Cy5 PE-Cy5.5 PerCP-Cy5.5 PE-Cy7 Alexa 594 APC Alexa 700 APC Alexa 700 APC-Cy7 682 Arch Pathol Lab Med Vol 130, May Color and 10-Color Flow Cytometry Wood 450/50 525/50 530/30 575/26 610/20 695/40 780/60 618/25 670/30 730/40 780/60 * DAPI indicates 4,6-diamidino-2-phenylindole, dihydrochlorine; FITC, fluorescein isothiocyanate; PE, phycoerythrin; Cy, cyanine; PerCP, peridinin chlorophyll protein; and APC, allophycocyanin. flow cytometry, as is available with the latest generation of clinical analyzers. INSTRUMENTATION The ability to perform high-level multicolor flow cytometry is a consequence of the combined development of multilaser benchtop instruments having sophisticated collection optics with the synthesis of a large number of simple and tandem fluorochromes having widely varying emission and excitation spectra. As already described, for leukemia and lymphoma analysis there is the need for a benchtop analyzer capable of detecting 9 to 10 colors and suitably configured for use in the clinical laboratory. Given the absence of such a production instrument, my laboratory had 2 instruments custom built by Becton Dickinson (San Jose, Calif) based on the LSRII platform. These instruments contain 4 lasers having excitation maxima at 407, 488, 594, and 635 nm, with spatially separated stream intersection points. Fluorochrome emissions from the stream are carried via optic fibers to detector arrays, allowing for the simultaneous detection of the fluorochromes listed in Table 1. In their present configuration, these instruments are capable of 11-color flow cytometry. The optimization of the performance of these systems illustrates some basic principles required for the successful conduct of multicolor flow cytometry, whether using 2-color or 10-color flow cytometry. Philosophy In general, my approach to instrument setup has been to identify conditions that provide optimal instrument performance (ie, maximal signal-to-noise ratio for each fluorochrome) and quality control of the instrument to achieve that performance on a daily basis. If done properly, there should be no need to deviate from these conditions because this will only result in a degradation of instrument performance. It also allows for consistency in the day-to-day operation of the laboratory that permits standardized and reproducible assay performance. Filters A great variety of optic filters is available for use in narrowing the portion of the electromagnetic spectrum seen by any particular detector. In most clinical instru-

4 Figure 1. Optimization of photomultiplier tube (PMT) voltage. A mixture of fluorescent beads having 8 discrete levels of fluorescence was evaluated across a range of PMT voltages, and the difference of the log mean values between each positive bead and the dimmest bead was calculated. Both detectors show an increase in separation between the positive and dim beads with a plateau, with the plateau voltage being higher for the longer wavelength fluorochrome phycoerythrin cyanine 7 (B) than for fluorescein isothiocyanate (A). The voltage giving the greatest signal-to-noise ratio is the optimal voltage. The decline in the values for the brightest beads at the higher voltages is due to the peaks being pushed off scale. ments, the filters are supplied with the instrument and are rarely changed. However, as one begins to use more esoteric fluorochromes, the question of filter selection takes on greater importance, and filter performance must be optimized. In general, the task of an optic filter is to exclude any residual light from any of the lasers in the system, minimize emission from other fluorochromes being used, and maximize the number of photons collected for the fluorochrome of interest. Although it is essential that the first of these objectives be achieved with a high level of efficiency to provide low background, the other 2 objectives often require a compromise because of the overlapping emission spectra of the fluorochromes. Filter selection can give rise to increased compensation requirements and compromised sensitivity if too much of the overlapping fluorochrome emission is permitted or may lead to decreased intensity for the fluorochrome of interest if insufficient photons are collected. However, although the compensation requirements may change dramatically with filter selection, the actual visual appearance of the compensated data is minimally affected. Consequently, it is probably better to use a slightly wider filter and to err on the side of acquiring more photons than to minimize compensation values and to compromise intensity. Detector Voltages One of the key elements to optimizing fluorescence detection (ie, good signal-to-noise ratio) is properly setting the voltages for the photomultiplier tubes or detectors. It is important to set the detector voltage at a high enough level to bring the autofluorescence of negative cell or bead populations above the noise threshold of the instrument; otherwise, low-level sensitivity and the signal-to-noise ratio are compromised. One way to determine appropriate settings is to run multipeak fluorescent beads at a variety of detector voltages and to plot the difference in the log of the mean between each positive bead and the negative bead peak (Figure 1). As the detector voltage increases, the fluorescence of the negative population will eventually exceed the noise threshold of the instrument, and the difference between each pair of beads will plateau. Further increases in detector voltage will not result in an improved signal-to-noise ratio, although positive signals will be progressively driven off scale. Another way to view this effect is by superimposing the single-parameter histograms for each of the detector voltages (Figure 2) and by noting the improved separation between the negative and first low-positive bead peaks until the plateau voltage is reached. Also, the separation between the more brightly positive bead peaks does not change with detector voltage. The optimal voltage for each detector is in the area at which the intensity difference plateaus. Sample Acquisition Rate Every instrument has a limit to the rate at which it can electronically process events as they are acquired. Exceeding that rate can result in a variety of artifacts, including the loss of data when events occur while another event is being processed (dead time). On some digital instruments, the dead time can be somewhat controlled by varying the time window during which each event is processed, which is termed the window extension on the LSRII platform. The use of a smaller event-processing window can significantly increase the sample acquisition rate and minimize data loss. Area Versus Height Most modern flow cytometers have the ability to process event pulses and to obtain area, width, or height measurements. In the case of digital instruments, each of these measurements can often be obtained simultaneously for all parameters, resulting in the question as to whether area or height measurements should be preferred for routine use. Although area theoretically provides a more accurate representation of the total signal, issues related to baseline determination and stability result in difficulties in accurately representing low-level signals. In addition, changes in instrument fluidics can shift the appropriate event-processing window for each laser because of changes in laser delay times and give rise to errors in area computation. For particles in the size range of hematopoietic cells, there is generally a linear relationship between pulse Arch Pathol Lab Med Vol 130, May Color and 10-Color Flow Cytometry Wood 683

5 Figure 2. Effect of photomultiplier tube voltage on dim signals. The data from Figure 1 for fluorescein isothiocyanate are displayed with the curves put in register so as to align the brightest peak that is on scale, peak 7. Note the improved separation of the dimmest peak from the first positive peak as the detector voltage is increased until the plateau voltage is reached. Green indicates 400 V; blue, 450 V; red, 500 V; and violet, 550 V. Figure 3. Doublet discrimination. Peripheral blood containing acute myeloid leukemia was labeled with 10 antibodies and was prepared using a standard ammonium chloride erythrocyte lysis technique. Examination of forward scatter (FSC) peak height versus peak area reveals a highly correlated population of singlets (colored) and a smaller population of doublets or cell aggregates (arrow). The aggregates may be excluded by initial gating on the singlet population before further analysis. Figure 4. Relative fluorescence intensities of fluorochromes. A series of peripheral blood samples was individually labeled with CD4 conjugated to representative fluorochromes used in 10-color flow cytom- area and height. Because baseline or fluidic stability issues minimally affect the determination of pulse height, the use of height measurements coupled with a moderate eventprocessing window allows for improved stability in instrument performance, acceptable low-level sensitivity detection, and rapid event processing. Coincidence Detection As particles or cells pass through the flow cytometer, there is a statistical probability that the laser will illuminate more than 1 particle simultaneously, a situation termed coincidence. The frequency of this occurrence is related to the rate at which the particles pass through the instrument or, more accurately, is related to increases in the diameter of the sample core stream due to increases in the sample aspiration pressure and in the concentration of the particles in solution, with increases in either resulting in an increase in coincidence. In addition, aggregation of particles due to processing or reagent artifacts will appear as coincidence. The presence of coincident particles gives rise to the appearance of events that have the composite properties of the particles in the aggregate and can result in significant problems in data interpretation. The combined simultaneous use of area, height, and width measurements for 1 or more parameters can allow for the removal of aggregate events during analysis (see Figure 3). Provided that the aggregates occur randomly (ie, are not due to specific reagent or cellular interactions), removal of these aggregates during analysis (doublet discrimination) greatly improves the quality of data and prevents errors in data interpretation. Compensation The proper setting of instrument compensation is critical to the success of multicolor flow cytometry. 14 Software compensation, on the instrument (if available) or off-line, is the only viable option for dealing with compensation in high-level multicolor flow cytometry. A series of samples singly stained with each fluorochrome of interest should be used to set compensation, with the positive population as bright as the brightest signal that one plans to evaluate for each fluorochrome. However, one should avoid setting compensation on the component of extremely bright signals that lie near the extreme end of the scale, as the actual intensities are near or off scale and the compensation settings obtained will be incorrect. When tandem fluorochromes are used, it is important to separately compensate for each reagent containing a tandem fluorochrome, as the spectral emission properties commonly vary among lots, between manufacturers, and over time (eg, if phycoerythrin [PE] Texas Red is attached to 3 different antibodies in a panel, compensation settings for each must be individually determined). This often results in the need for individual compensation settings for each separate reagent combination (ie, tube-specific compensation), a process easily implemented using software compensation. etry. The lymphocyte population was evaluated, and each of the resulting histograms was put in register to align the right edge of the negative population. Green indicates fluorescein isothiocyanate (FITC); dark blue, phycoerythrin (PE); light blue, PE Texas Red; magenta, peridinin chlorophyll protein cyanine 5.5 (PerCP-Cy5.5); orange, PE-Cy7; red, Pacific Blue; yellow green, Alexa 594; light green, allophycocyanin (APC); blue, Alexa 700; and purple, APC-Cy Arch Pathol Lab Med Vol 130, May Color and 10-Color Flow Cytometry Wood

6 REAGENTS Most reagents for high-level multicolor immunophenotyping consist of monoclonal antibodies coupled to a wide range of fluorochromes. Each of these reagents has particular performance and stability characteristics that must be evaluated first individually and then in combination to assure adequate signal intensity across the range to be detected. Relative Fluorochrome Intensity A prerequisite to the construction of reagent panels is knowledge of the relative intensities of each of the fluorochromes to be used, with a representative selection of those suitable for clinical use being depicted in Figure 4. In general, PE and the PE tandem fluorochromes PE Texas Red, PE cyanine 5 (PE-Cy5), PE-Cy5.5, and PE-Cy7 are the brightest, followed by allophycocyanin (APC) and the APC tandems APC Alexa 700 and APC-Cy7. The remaining small molecule fluorochromes, including fluorescein isothiocyanate (FITC), peridinin chlorophyll protein (PerCP), Pacific Blue, and the Alexa series of dyes, exhibit fluorescence approximately 1 log dimmer. Differences in background cellular autofluorescence occur throughout the visible spectrum, being greater at lower wavelengths, and significantly impair the apparent signal-to-noise ratio for fluorochromes such as Pacific Blue and FITC. Nonspecific Binding Each antibody and fluorochrome have the propensity for some degree of binding to cells via mechanisms unrelated to the epitope being detected (ie, nonspecific binding). Such increased background may be unique to the formulation of any particular reagent and requires evaluation for each reagent to be used. In particular, certain fluorochromes show increased binding to compromised or dying cells and debris, giving rise to significantly increased background on some samples. This is particularly true of reagents containing the cyanine dyes Cy5, Cy5.5, or Cy7, as well as Texas Red, and is less true of the fluorochromes Pacific Blue, FITC, PE, Alexa 594, and APC. The occurrence of nonspecific binding is often identifiable by the presence of a correlation between 2 or more fluorescent signals (ie, diagonal line) and can often be excluded during analysis. The exclusion of compromised cells and debris by the removal of low forward scatter events during analysis often greatly improves the quality of data. Preincubation with excess unlabeled immunoglobulin or serum from the same species as the reagents being tested is a common method to minimize nonspecific binding; however, such procedures may introduce additional antibody interaction problems and should be used with caution. Tandem Stability Several of the fluorochromes used for multicolor analysis consist of a primary fluorochrome covalently linked to 1 or more secondary fluorochromes (ie, tandem fluorochromes). Although these fluorochromes primarily emit via the secondary fluorochrome at the desired wavelength, a variable smaller proportion of the emission occurs at the emission wavelength of the primary fluorochrome. Under certain conditions, the efficiency of the coupling between the primary and secondary fluorochromes may be reduced, resulting in an increased emission for the primary fluorochrome. This may not occur in a consistent manner, resulting in a reagent that cannot be appropriately com- Figure 5. Tandem fluorochrome degradation. Peripheral blood was labeled with CD45 allophycocyanin (APC) cyanine 7 (Cy 7) by 1 of 2 methods: (1) Antibody was added to whole blood, followed by erythrocyte lysis with ammonium chloride containing 0.25% formaldehyde (left). (2) Whole blood was lysed with ammonium chloride, washed, and allowed to sit for 1 hour before antibody addition (right). The whole blood method shows the expected APC emission following compensation (left), while the prelyse method (right) shows a variable increase in APC emission due to a variable degree of tandem fluorochrome breakdown. A single compensation value no longer adequately describes compensation settings for this population. Figure 6. Demonstration of antibody interaction. Bone marrow was labeled with CD38 Alexa 594 or with CD13 phycoerythrin cyanine 7 (PE-Cy7) using 2 different CD13 clones. The combination of the 2 reagents shows apparent positivity for CD13 (left) that disappears when a different clone of CD13 PE-Cy7 is used (right), indicating artifact. pensated. The fluorochrome APC-Cy7 is particularly susceptible to such breakdown, as can be observed following increased light exposure, extended fixation during specimen processing, and elevated temperature. An example of this effect is given in Figure 5. Careful attention to reagent handling and to conditions of specimen processing is needed to prevent such occurrences. Steric Hindrance The addition of multiple reagents to the same tube raises the potential for 1 reagent interfering with the binding of 1 or more other reagents. This is particularly of concern if multiple reagents target the same macromolecular complex. Excluding such interactions is important in the validation of reagent performance and should be specifically sought. A simple way of performing this evaluation is to compare the intensities of positive populations from a sample prepared with all the reagents of interest with a series of samples prepared with each reagent individually. A decrease in intensity indicates probable steric hindrance. In my experience, the occurrence of this problem is rare. Arch Pathol Lab Med Vol 130, May Color and 10-Color Flow Cytometry Wood 685

7 Figure 7. Effect of overlapping fluorescence emission on sensitivity. Lymphocytes labeled with CD8 phycoerythrin (PE) show marked emission into the PE Texas Red detector (A). Because of errors in fluorescence measurement, the positive population has width (A, arrows) that, while appearing small at the upper end of the log scale, becomes more noticeable when the population is displayed at the lower end of the scale following compensation (B). The result is a difference in the level of background fluorescence for PE Texas Red that is dependent on the intensity of PE (B, solid line). It also indicates that the ability to detect low-level PE Texas Red fluorescence is impaired in the presence of bright PE compared with the negative PE population (B, dotted line and arrow). The shaded area should be avoided during panel design. Antibody Interactions Reagent interactions other than steric hindrance may occur and alter reagent performance. Often, these interactions take the form of a coordinate increase in fluorescence intensity for both reagents that often mimics improper compensation. An easy way to evaluate for such interactions is to compare the appearance of positive populations on a 2-parameter dot plot in the presence and in the absence of 1 or both of the reagents (Figure 6). This can be efficiently accomplished by comparing a sample prepared with all reagents of interest with a series of preparations in which each lacks 1 of the component reagents (fluorescence-minus-1 control samples). If significant reagent interactions exist, one will see alterations in signal intensity or in the pattern visualized on 2-parameter dot plots as individual reagents are subtracted or included. Such a process is also useful for confirming appropriate compensation. The few antibody interactions that I have observed appear to be antibody clone or fluorochrome specific and often are mediated by complement in plasma, such that only a subset of samples demonstrates the problem. A good working knowledge of the performance characteristics of the individual reagents and the reagent cocktail is the single best defense to detect and correct errors of this type. CONSTRUCTING REAGENT PANELS The selection of reagents and pairing with appropriate fluorochromes is a key factor in assuring appropriate signal intensity and detection sensitivity. In most cases, it is the outcome of this process that determines the success or the failure of an experiment. It is useful to follow these 4 steps in the construction of reagent panels. Determine the Objective for Each Potential Combination of Reagents Each reagent combination should be constructed to address 1 or more clearly stated objectives. If the combination is to be used as part of a larger panel, it is particularly important to identify and to prioritize potential conflicting objectives. Select a Group of Cellular Targets An ideal group of cellular targets should be identified for each reagent combination, which if evaluated simultaneously will successfully address the objective for the reagent combination. The focus should be on successfully addressing the question being asked, and the selection of targets should be largely independent of fluorochrome or whether these reagents are commercially available. In addition, reagents that simultaneously target the same macromolecular complex should be avoided unless compatibility has been previously demonstrated. The group of targets should represent a minimum that is needed to answer the question being posed. The inclusion of unnecessary reagents not only adds cost but also can compromise the performance of the entire panel. Assign a Fluorochrome to Each Target Using the known relative intensities of each fluorochrome, a fluorochrome should be associated with each target. The basic principle to be used is that highly expressed antigens should be coupled with dim fluorochromes and that dimly expressed antigens should be coupled with bright fluorochromes. This principle generally provides reasonable signal intensities and avoids compensation problems due to excessively bright fluorescence. 686 Arch Pathol Lab Med Vol 130, May Color and 10-Color Flow Cytometry Wood

8 Figure 8. Nine-color flow cytometry showing all the unique combinations of the 11 parameters, resulting in 55 dot plots, emphasizing the high level of informational content provided by this approach. Major populations are colored for emphasis. SSC indicates side scatter; FSC, forward scatter. Other abbreviations are explained in the footnote to Table 2. Neoplasm B cells T cells Blasts Myeloid Plasma cells Table 2. Immunophenotyping Panel for the Demonstration of Leukemia and Lymphoma* Pacific Blue FITC PE HLA-DR HLA-DR DAPI c c Fluorochrome PE Texas Red PCX PE-Cy7 Alexa 594 APC A700 APC-Cy * These combinations require a 4-laser flow cytometer having excitations at 407 nm (Pacific Blue), 488 nm (FITC, PE, PE Texas Red [TR], PCX, and PE-Cy7), 594 nm (Alexa 594), and 635 nm (APC, A700, and APC-Cy7). The numbers indicate cluster designations (ie, CD antigens). FITC indicates fluorescein isothiocyanate; PE, phycoerythrin; PCX, PE-Cy5 [cyanine 5] or PE-Cy5.5 or peridinin-chlorophyll protein [PCP] Cy5.5; APC, allophycocyanin; A700, Alexa 700 or APC Alexa 700; and c, cytoplasmic The second important component of fluorochrome assignment is understanding the effect of overlapping spectral emission on detection sensitivity and minimizing its contribution. The presence of spectral emission from fluorochromes other than the one of interest adds background noise to the signal that one is trying to detect but, unlike other forms of noise, is dependent on the intensities of the other fluorochromes in the sample. This effect is most extreme for fluorochrome pairs that have significant spectral emission overlap or in which the total number of photons detected is lower, as is typical of fluorochromes having longer wavelength emissions. This effect is illustrated in Figure 7. As a result, sensitivity is compromised when one attempts to detect a dimly fluorescent signal in the presence of other brightly fluorescent signals that are present on the same particle. During fluorochrome assignment, a determined effort must be made to minimize this effect for reagent pairs that exhibit significant compensation by using 1 of 3 basic strategies. The first is to use reagents that are expressed on different populations of cells, with the populations being of different lineages, maturational stages, or functional subpopulations. The second is to limit the intensity of the fluorochrome causing a compromise in sensitivity to a lower intensity, by careful antigen selection or by dilution of labeled reagent with unlabeled reagent. The third is to use reagent pairs in which the expected result is dual positive or dual negative, avoiding situations in which either reagent alone is positive. During fluorochrome assignment, one can also consider the commercial availability of fluorochrome-conjugated reagents. However, with the advent of custom conjugation Arch Pathol Lab Med Vol 130, May Color and 10-Color Flow Cytometry Wood 687

9 Figure 9. Detection of minimal residual disease. Peripheral blood from a patient recently treated for acute monocytic leukemia shows the presence of a residual abnormal immature monocyte population (light blue, emphasized), indicating persistent leukemia. Abbreviations are explained in the footnote to Table 2. Figure 10. Chronic myeloid leukemia in the chronic phase. The blast population identified by CD45 versus side scatter shows abnormal myeloid blasts (red) and abnormal immature B cells (light blue), indicative of the stem cell nature of the disorder. Note the expanded basophil population (gray) that is typical of myeloproliferative disorders. Abbreviations are explained in the footnote to Table 2. services, this consideration should not be allowed to compromise the quality of the panel. Test Reagent Combinations Once the desired reagents have been assembled, they must be empirically tested to assure that signal intensities are as expected, that low-level sensitivity is appropriate (if important), and that unexpected interactions between reagents do not occur. As already outlined, a sample prepared with all reagents of interest should be compared with the same sample prepared with a series of preparations in which each lacks 1 of the component reagents (fluorescence-minus-1 controls) and with a second series containing each single reagent independently (singlestained controls). If significant reagent interactions exist, one will see alterations in signal intensity or in the pattern visualized on 2-parameter dot plots as individual reagents are subtracted or included. 688 Arch Pathol Lab Med Vol 130, May Color and 10-Color Flow Cytometry Wood

10 Figure 11. Identification of a small abnormal population in cerebrospinal fluid. A small clonal B-cell population (light blue, emphasized) expressing bright CD20 with light-chain restriction is identified at a level of 0.7% of the white blood cells in this paucicellular specimen, indicative of involvement by B-cell lymphoma. Abbreviations are explained in the footnote to Table 2. Figure 12. Detection of an abnormal plasma cell population. A very small abnormal plasma cell population (blue) is identified that represents 0.05% of the white blood cells. The abnormal population expresses decreased CD45 and CD19, positivity for CD56, and cytoplasmic lightchain restriction. In addition, the population has an increased DNA content (DAPI), indicating aneuploidy. Abbreviations are explained in the footnote to Table 2. Arch Pathol Lab Med Vol 130, May Color and 10-Color Flow Cytometry Wood 689

11 Cocktail Reagents After a suitable combination of reagents has been identified, cocktails may be created to provide the delivery of all reagents to a given tube in a single pipetting step. In addition to simplifying pipetting, the use of cocktails minimizes errors in reagent delivery and aids in standardizing sample preparation, significantly improving the consistency of the technique. Before creating cocktails, each reagent must be individually titrated using the final total volume of the cocktail (eg, a 100- L total volume generally works well for 9-10 antibodies). DATA ANALYSIS The visualization and the analysis of high-level flow cytometric data are complex, and improved software tools are needed to accomplish this effectively. Using current software, the most general data representation is a series of 2-parameter dot plots that includes all unique combinations of parameters. However, often only a subset of the total possible 2-parameter combinations is informative, and a reduced number of dot plots may be displayed depending on the reagents used. Discrete populations can be identified and their events gated and colored to permit visualization in each of the other dot plots. This process is one way of incorporating information from other parameters into the 2-parameter display of a single dot plot, creating a higher-level multiparametric analysis. The inclusion of a density display further increases the informational content and in combination with multicolor gating provides a marked improvement in data visualization. For a 9-color experiment, this yields 55 unique dot plots, as illustrated in Figure 8. For the diagnosis of leukemia and lymphoma, the process becomes one of pattern recognition, observing differences between normal and abnormal population distributions as indications of neoplasia. PROPOSED SCREENING PANEL FOR LEUKEMIA AND LYMPHOMA A panel of reagents prepared by this process that is suitable for the demonstration of normal hematopoietic maturation and for the clinical diagnosis of hematopoietic neoplasms is presented in Table 2. The use of this panel on clinical material is provided in a series of examples that demonstrate the power of this approach. Identification of abnormal populations following therapy is an important application of multicolor flow cytometry. The demonstration of an abnormal immature monocyte population following therapy for acute monocytic leukemia is easily accomplished using the proposed panel (Figure 9). The multilineage differentiation of hematopoietic stem cell neoplasms is demonstrated in a patient during the chronic phase of chronic myeloid leukemia in Figure 10. The blast population not only exhibits abnormal myeloid differentiation, as indicated by the aberrant expression of CD7, increased CD117, and decreased CD13 on the CD34- positive blast population, but also shows aberrant immature B-cell differentiation, with decreased expression of CD38 and increased expression of CD10. The panel enables the demonstration of aberrant multilineage differentiation that confirms the diagnosis of a stem cell disorder. In Figure 11, a small clonal B-cell population is identified in cerebrospinal fluid of a patient with a history of lymphoma. Paucicellular specimens of this type are often difficult to evaluate, but the use of high-level multicolor flow cytometry with a single reagent combination allows for the detection of involvement by lymphoma at a low level. Finally, the ability to simultaneously examine surface antigen expression, cytoplasmic antigen expression, and DNA content is illustrated in Figure 12. An abnormal plasma cell population is distinguished from the coexistent normal plasma cells by the decreased expression of CD45 and CD19, the aberrant expression of CD56, and the presence of cytoplasmic light chain restriction. In addition, the use of the DNA-binding dye 4,6-diamidino-2-phenylindole, dihydrochloride (DAPI) shows an abnormal increase in DNA content, suggesting aneuploidy, a finding of potential prognostic significance. The entire analysis was accomplished using a single 100- L aliquot of sample and identified the abnormal population at a level of 0.05% of the white blood cells, a tangible demonstration of the power of high-level multicolor flow cytometry. CONCLUSIONS Compared with current methods, high-level multicolor flow cytometry offers the possibility for increased accuracy in population identification, the ability to obtain detailed information from paucicellular specimens, increased laboratory efficiency, and the means to consistently detect abnormal populations at low levels. These characteristics are particularly well suited to the analysis of leukemia and lymphoma. Through the use of consistent panels in which performance is systematically validated, high-level multicolor flow cytometry has the potential to revolutionize and to standardize this type of analysis in the clinical laboratory. I thank the technical staff of the University of Washington Medical Center Hematopathology Laboratory, in particular Shin-Hui Lee, for their invaluable efforts in the development and validation of this methodology. I also thank Larry Duckett of Becton Dickenson, who was responsible for the construction of our custom LSRII platform instruments and has been a constant and enthusiastic supporter of this project. References 1. Nicholson JKA, Mandy FF. Immunophenotyping in HIV infection. In: Stewart C, Nicholson JKA, eds. Immunophenotyping. New York, NY: Wiley-Liss; 2000: Braylan RC. Impact of flow cytometry on the diagnosis and characterization of lymphomas, chronic lymphoproliferative disorders and plasma cell neoplasias. Cytometry A. 2004;58: Orfao A, Ortuno F, de Santiago M, Lopez A, San Miguel J. Immunophenotyping of acute leukemias and myelodysplastic syndromes. Cytometry A. 2004;58: Richards SJ, Rawstron AC, Hillmen P. Application of flow cytometry to the diagnosis of paroxysmal nocturnal hemoglobinuria. Cytometry. 2000;42: Wood BL. Multicolor immunophenotyping: human immune system hematopoiesis. Methods Cell Biol. 2004;75: Loken MR, Wells DA. Normal antigen expression in hematopoiesis: basis for interpreting leukemia phenotypes. In: Stewart C, Nicholson JKA, eds. Immunophenotyping. New York, NY: Wiley-Liss; 2000: Kussick SJ, Wood BL. Using 4-color flow cytometry to identify abnormal myeloid populations. Arch Pathol Lab Med. 2003;127: Stetler-Stevenson M, Braylan RC. Flow cytometric analysis of lymphomas and lymphoproliferative disorders. Semin Hematol. 2001;38: Weir EG, Borowitz MJ. Flow cytometry in the diagnosis of acute leukemia. Semin Hematol. 2001;38: Baumgarth N, Roederer M. A practical approach to multicolor flow cytometry for immunophenotyping. J Immunol Methods. 2000;243: De Rosa SC, Brenchley JM, Roederer M. Beyond six colors: a new era in flow cytometry. Nat Med. 2003;9: Perfetto SP, Chattopadhyay PK, Roederer M. Seventeen-colour flow cytometry: unravelling the immune system. Nat Rev Immunol. 2004;4: U.S.-Canadian Consensus Recommendations on the Immunophenotypic Analysis of Hematologic Neoplasia by Cytometry: Bethesda, Maryland, November 16 17, Cytometry. 1997;30: Roederer M. Spectral compensation for flow cytometry: visualization artifacts, limitations, and caveats. Cytometry. 2001;45: Arch Pathol Lab Med Vol 130, May Color and 10-Color Flow Cytometry Wood

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