Clinica Chimica Acta, 21 I (1992) S13-S27 Elsevier Science Publishers B.V. 0009-8981/92/$05.00
s13
CCA 05406
INTERNATIONAL
FEDERATION
OF CLINICAL CHEMISTRY
Flow cytometry in the clinical laboratory. Principles, applications and problems A. Ruiz-Arguelles Scientific
Division, International
Key words: Flow cytometry;
Federation
Cytofluorography;
of Clinical Chemistry
Clinical
flow cytometry
Introduction Flow cytometry is a method of measuring cell characteristics as they ‘flow’ through special detectors while being illuminated by intense - usually laser - light. Cells to be analyzed in this system need to be prepared into single cell suspensions; hence, they might be forced to flow within a fluid sheath where they are interrogated by the laser beam. Every cell entering the beam will scatter light in all directions; the light scattered in the forward direction will be proportional to the size of the cell; that scattered at a 90” angle will provide information of its intracytoplasmic granularity. If the cell has been stained with one or more fluorochromes, special detectors will selectively register information about the presence or absence of such dyes in a given cell. After recording all 4 or 5 parameters of each cell, instruments will electronically place that cell in a category of size, granularity and the presence, and intensity, of green, red or orange fluorescence. In the early development of flow cytometry, instruments were confined to research laboratories and clinical applications of this technique were, if any, very scant. Progressive advances in availability of monoclonal antibodies specific for a very wide range of cell antigens, along with the development of small although powerful instruments and user friendly data analysis systems, are rapidly moving flow cytometry from the experimental to the clinical laboratories [l-4]. Correspondence to: A. Ruiz-Arguelles, Blvd. Diaz Ordaz 808, Cal. Anzures, The copyright
is vested with IFCC.
Laboratorios Clinicos de Puebla. 72530 Puebla, Pue., Mexico. 92, SD-PPI4
Departamento
de Inmunologia,
This paper WIII revtew some general aspects of the methodology and comment on the most widely used applications in the clinical laboratory. The rapidly developing experimental applications of flow cytometry are beyond the scope of this review. Principles of Flow Cytometr? The Bow cytometry instruments can be divided into three functional compartments: fluidics. optics and data analysis. The fluidics compartment is designed to create a sheath of fluid that will drive the cells in a suspension to flow into a detection chamber in a sequential array. The possibility of changing the pressure of the fluid sheath enables the user to increase or decrease the diameter of the flow stream, according to the mean size of the cells to be analyzed. The user is also able to change the flow rate according IO the number of cells to be analyzed in a given time. The optics compartment consists of a light source that will interrogate each cell flowing in the chamber and several detectors to record the cell’s responses. Early instruments were equipped with very powerful laser beams which required water-cooling systems and special facilities. Recent instruments employ small air-cooled lasers but more powerful detection systems and are assembled as benchtop machines. As the laser beam meet> a cell. the latter will scatter light in all directions. A detector positioned in the forward direction will detect the ‘forward angle scatter’ whose magnitude is proportional to the cell size: therefore. small cells will yield less ‘forward scatter’ than large ones (Fig. I). A photomultiplier positioned at 90” to the laser direction will register the so called ‘side scatter‘ which provides information on the intracellular texture of the cell. Thence. cells with granules will yield more side scatter than cells with few or no rntracytoplasmic inclusions. If the cells have been stained with fluorochromes. these will be excited by the same, or an additional, light source. Early flow cytometers had lasers whose wavelength could be modified, or were equipped with Inore than one hser. Benchtop instruments employ single wavelength (488 nm) laser beams. bur due to the dcvclopment of new fluorochromes [5] a wide variety of them can be used to lag antibodies or other molecules, thus making single
FL1 fa
FL2
Fig.
I Opcal system of a tlow cyt~mete~ in the chamber
yielda 4 parrtmerers
I‘he cl’fects of the laser heam interrogating the cells flowing of information about the characteristics of each cell.
s15
wavelength instruments very powerful. Up to three (or more) fluorochromes in a single cell can be excited at the same time and, by means of the appropriate filtering systems and dichroic mirrors, the emission of such dye is led to a different photomultiplier. All the signals registered from each cell (forward and side scatter and the presence and intensity of the fluorochromes) are converted into digital signals to be analyzed by a microprocessor. According to the users’ needs, one, or two parameter histograms may be built by the processor. One parameter histograms will yield information on the proportion of cells bearing, or not, a given characteristic, for example, the proportion of cells in the given sample that binds a fluorescein-conjugated antibody. Two parameter histograms will electronically group cells having certain features, for example, a forward/side scatter histogram of whole blood leukocytes will plot small non-granular cells (lymphocytes) as a group, large granular cells (polymorphonuclear leukocytes) as another group, while a third group will result from cells having an intermediate size and granularity (monocytes)(Fig. 2) By the use of either built-in or computer-
pm..
z DOUBLE STAINED
ss
I
FL2
% STAINED
I
% STAINED I
FL1
I
FL2
Fig. 2. Example of histograms in the analysis of lymphocyte subpopulations. The cytogram (top left) of forward and side scatter (FS, SS) enables the identification of three subpopulations of cells according to their size and texture. After gating the lymphocytes, histograms (bottom) of cells bearing or not a given fluorochrome (GF, green fluorescence: RF, red fluorescence) yields information on the proportion of cells that express an antigen. Cells co-expressing antigens, can be detected by the construction of double fluorescence
histograms
(top right).
Sl6
assisted software, the user is able to define electronic gates or windows and focus the analysis of a given characteristic in a special group of cells, for example, the cells plotted as lymphocytes in a forward/side scatter histogram can be ‘gated’ (i.e. electronically isolated) from the other cells in the histogram, to ensure that the detection of fluorescent dyes is limited to the lymphoid cells. As a result of this capability, the need for preparation of isolated lymphoid cells for immunophenotyping can be easily circumvented. Newly developed software capabilities, such as ‘color gating’ and multi-dimensional projections of histograms, are increasingly allowing flow cytometer users to achieve more accurate and complete cell analysis. Many of these new software programs are being designed for the clinical laboratory, reflecting the rapid move of this methodology to medical practice. Applications
The enumeration of peripheral blood lymphocyte subsets used to be of interest for scientists dealing with the study of primary immunodeficiency diseases or for those involved in the study of autoimmune diseases. However, in the past decade, the worldwide spread of human immunodeficiency virus (HIV) infection has made immunophenotyping of peripheral blood lymphocytes a routine test in many clinical laboratories. A gross estimation of subpopulations of lymphoid cells used to be accomplished by rosetting techniques or by cytochemical procedures. In the early 1980s. several monoclonal antibodies capable of defining lymphoid cell subsets with certain functional properties were developed [6-lo] and rapidly became commercially available. This major development permitted a more precise definition and enumeration of lymphocyte subsets. however, the use of either immunochemical or immunofluorescence microscopy methods to demonstrate the binding of monoclonal antibodies, made their detection subjective and cumbersome. After the development of more monoclonal antibodies (see Table I) specific for sub-subsets of lymphocyte populations and the discovery that certain cell populations cannot be defined but through the demonstration of a ‘phenotype’ (i.e., the simultaneous presence of more than one surface antigen in the same cell), microscopic techniques became impractical. By means of flow cytometry. extended panels, usually, made of mixed antibodies labeled with different fluorescent dyes, can be used to define, objectively and rapidly, the lymphocyte subset profile of a given individual. The establishment of these profiles has proved to be clinically useful in patients infected by the human immunodeficiency virus, since the numbers of CD!+ cells tends to decrease with progression of the disease and becomes the prognostic cornerstone in overt acquired immunodeficiency syndrome (AIDS). Similarly, the number of these cells (CD4) is considered as an indicator of response to therapy in several clinical trials of antiviral drugs. The numbers of CD3+ cells arc also decreased in these patients, while those bearing the CD8 or the CD20 antigens increase as the infection progresses. The CD4+ subset defined by the CD45R antigen usually decreases as a prediction of the appearance of autoimmune phenomena that frequently occurs in AIDS patients. The number of NK cells. in turn. decreases at very late stages of the infectious process [l l-131.
s17 TABLE Cluster
I designation
(CD) antigens
and their distribution
CD design
Main cellular
CDla CDlb CDlc CD2 CD2R CD3 CD4 CD5 CD6 CD7 CD8 CD9 CD10
Thy, DC, B subset Thy, DC, B subset Thy, DC, B subset T Activated T T T subset T, B subset T, B subset T T subset Pre-B, M, Plt Lymph. Prog., CALL, Germ Ctr. B, G Leukocytes M, G, NK M, G, NK, B sub M, G, Plt
CDlla CDllb CD1 Ic CDwl2 CD13 CD14 CD15 CD16 cDw17 CD18 CD19 CD20 CD21 CD22 CD23 CD24 CD25 CD26 CD27 CD28 CD29 CD30 CD31 CDw32 CD33 CD34 CD35 CD36 CD37 CD38
reactivity
M, G M, (G) G, (M) NK, G, Mac. G, M, Plt Leukocytes B B B subset Cytopl. B/surface B subset B subset, act. M, Eo
CD design
B subset, (M) B, carcinomas
CD41 CD42a CD42b CD43 CD44 CD45 CD45RA CD45RO CD46 CD47 CD48 CDw49b CDw49d CDw49f CDw50 CD51 CDw52 CD53 CD54 CD55 CD56 CD57 CD58 CD59 CDw60 CD61 CD62 CD63
Ph Ph Ph T, G, M, brain T, G, M, brain, RBC Leukocytes T subset, B, G, M T subset, B, G, M Leukocytes Broad Leukocytes Pit, cultured T
CD64 CDw65 CD66 CD67 CD68 CD69 CDw70
PLt, M, G, B, (T) M, G, B, Plt M. Prog. Prog
CD71 CD72 CD73 CD74 CDw75 CD76 CD77 CDw78
act. T
reactivity
CD39 CD40
B, G Activated T, B, M Activated T T subset T subset Broad Activated T, B, Sternberg-Reed
G, M, B M, Ph. (B) By (T, M) Lymph. Prog.,
Main cellular
M, T, B, Thy Pft, (T) Leukocytes (Pit) (B) Leukocytes Leukocytes Broad, Activ. Broad NK, activ. Lymphocytes NK, T, B sub, Brain Leukocytes, Epithel Broad T sub Pit Plt activ. Plt activ., M, (G, T, B) M G, M G G Macrophages Activated B, T Activated B, -T Sternberg-Reed cells Proliferating cells, Mac. B B subset, T subset B, M Mature B, (T subset) Mature B, T subset Restr. B B, (M)
Abbreviations: Thy, thymocytes; DC, dendritic cells; M, monocyte; Pit, platelets or their precursors; Prog, progenitors, CALL, common acute lymphoblastic leukemia; G, granulocytes; NK, natural killer cells, Mac, macrophages; act., activated; Eo, eosinophils; RBC, red blood cells; Epithel, epithelial cells; Restr., restricted; T, thymus derived lymphocytes; B, bursa (or equivalent) derived lymphocytes. Source: Knapp W, Darken B, Rieber P, Schmidt RE, Stein H. (Kr. von Demborne AEG). CD Antigens. Blood 1989:74:1448-1450.
SIX
The evaluation of these changes, in either direction, can be reliable, when using microscopic methods, only if their magnitude is very important, since the visual count of 200-300 cells yields considerable errors. With the use of flow cytometers, percentages of cell subpopulations are derived from the analysis of 5,000-10,000 cells. hence yielding very small intra- and inter-assay coefficients of variation. Lymphocyte immunophenotyping is very useful in the classification of primary or congenital deficiencies of the immune system. The DiGeorge syndrome, which involves ontogenic abnormalities of the structures derived from the third and fourth pharyngeal pouches, presents with T cell defects. Two color flow cytometric analysis with monoclonal antibodies to T cell subsets has demonstrated an arrest at the common thymocyte (CD2) stage of differentiation, resulting in abnormally low numbers of mature CD3 and CD8 cells. Children with severe combined immunodeficiency presenting without adenosine deaminase deficiency represents a group composed of three phenotypically distinct subgroups: the first of them fails to express thymic specific antigens; the second does not show evidence of maturation beyond the prothymocyte (CD38); while the third shows evidence of late differentiation of thymocytes (C’D38. CD4. CDX, CD3). This distinction may have therapeutic implications Common variable hypogammaglobulinemia, in the majority of cases, results from an intrinsic defect of B cell maturation that may be established by flow cytometry along with monoclonal antibodies specific for maturation stages of the B cell lineage. such as CDIO. CD1 9. CD20 and PCA. In a minority of cases, B cells are intrinsically normal but there is an excess of activated suppressor cells (CD8 and HLA-DR) that render B cells unresponsive to antigenic stimulation [14-191. Multiparameter analysis of cells from patients with autoimmune diseases has also proved useful. Although controversial, several authors have reported that suppressor cells (CDB. CD3) arc diminished in systemic lupus erythematosus. It has also been shown that some patients present increased cells bearing the CD8/Leu7 phenotype and that these cells are responsible for suppressing IL-2 production, a defect that seems to be important in the pathogenesis of this disease. Also in systemic lupus erythcmatosus. a subgroup of patients, perhaps with different clinical features, has been identified by flow cytometry through the demonstration that their CD4 receptor on T cells lacks the T4 epitope. In patients with rheumatoid arthritis, the cells that are prone to the production of autoantibodies have been identified as those bearing a mature B cell antigen tCD20), in co-existence with a non-B cell restricted structure, the CD5 antigen. This subset of cells cannot be quantified by other than flow cytometric methods [Xl. In the diagnosis and follow-up of certain patients with aplastic anemia, lymphocyte immunophenotyping is clinically useful [21]. Some patients presenting with disorders of hematopoiesis appear to have immunological suppressor cells which are defined by the CD3. CD8 CD25 and HLA-DR phenotype. Those patients that respond to treatment with anti-thymocyte globulin will decrease the number of cells expressing the CD25 antigen (IL-2 receptor), and their CD4XD8 ratio will return to normal [22]. Another follow-up evaluation of response to therapy that may be performed by flow cytometry in these patients is the enumeration of nucleated erythrocyte precursors. In tissue transplantation. some authors have adopted flow cytometric methods to evaluate the response of cells in mixed lymphocyte cultures, by detecting cell-
s19
activation markers, such as CD25 and 4F2, instead of measuring DNA synthesis through the incorporation of radiolabeled thymidine [23]. (As will be discussed later, DNA synthesis can be also measured by flow cytometry). Post-operative monitoring of transplant recipients includes, in many instances, lymphocyte immunophenotyping. An elevated CD4ICD8 ratio has been shown to correlate with rejection [24]. Abnormally high counts of CD4 and CD8 cells distinguish cyclosporin nephrotoxicity from renal graft rejections; while inversion of the CD4iCD8 ratio correlates with opportunistic cytomegalovirus infection in cardiac allograft recipients [25]. The presence of activation antigens on CD8 cells predicts clinical symptoms or signs of rejection 2-6 days in advance. Demonstration of allo and autoantibodies to blood cells
The demonstration of serum antibodies in potential recipients of tissue grafts or blood products can be accomplished by flow cytometry by means of incubating the donor cells with the recipient’s serum in a first step, followed by the addition of a fluorescent antiserum to human immunoglobulins. By electronic gating or multiparameter analysis, the cells to which the recipient’s antibodies are directed can be identified. This approach has been extended to the investigation of serum antibodies to lymphocytes, granulocytes and platelets in patients with autoimmune diseases. In the particular case of red cell antibodies, not only screening for the specificity can be performed by flow cytometry, but the agglutinating titer correlates closely with the intensity of fluorescence in the cells [26]. Phenotyping of leukemia and lymphoma
Multiparameter analysis of leukemic cells by flow cytometry has proved to be particularly useful in infant acute lymphoblastic leukemia. Thus, the classification of patients as having T, B, ‘common’, or null lymphoblastic leukemia is of most importance to define their prognosis. Patients having T (CD3, CD2 and CDS) B (CD20) or pre-B (CD19) immunophenotypes have a poor prognosis despite the fact that more aggressive therapy is commonly used in these cases, while patients having the ‘common’ (CDlO) or null types of leukemia have a much better outcome and can be treated with less aggressive approaches [27,28]. The adult lymphoblastic leukemia phenotype has also been evaluated by flow cytometry. It has been recently shown that a subgroup of patients that express myeloid differentiation antigens in conjunction with B cell markers were found to have fewer complete remissions and shorter survival times than those without myeloid antigens. In the case of acute myeloid and monocytic leukemias, double staining phenotyping allows the classification of both, lineage and maturation stage as well. The prognostic importance of this classification is still controversial. Acute megakarioblastic leukemia represents a subtype of myeloid leukemia with a very poor response to treatment and hence, an extremely high mortality rate. Morphologically, it closely resembles a lymphoblastic leukemia and, therefore, ultrastructural or immunological methods are required for its identification. The demonstration of platelet-associated antigens on the blast cells by means of flow cytometry is the optimal choice for this purpose [29,30].
lmmunophenotyping of malignant lymphomas correlates with the morphological classification of these turnouts and therefore, it has not as much clinical importance as it does in lymphoblastic leukemia [31,32]. Hence, the small lymphocytic (diffuse, well differentiated) lymphomas. known to be of low-grade malignancy, are commonly found to bear the following antigens: low intensity surface immunoglobulin (sIg), receptors for C3d, receptors for the Fc portion of IgG, la (Class-II major histocompatibility complex antigens). CD20. CD21, CD19 and CD24. The diffuse, small cleaved cell and diffuse mixed small and large cell (poorly differentiated) lymphomas. is an intermediate prognostic group whose common phenotype is: bright (monoclonal) slg, Ia and CD19. The diffuse large cell and large cell immunoblastic, that are intermediate to high-grade malignancy tumours, respectively, have been subdivided according to their phenotype into the following subgroups: (1) CD19, CD20 and sIg positive; CD21 negative; (2) CD19, CD20, CD21 and sIg positive; (3) CD19 and CD20 positive; slg and CD21 negative; (4) CD20 and slg positive; CD19 and CD2 1 negative [33]. The clinical importance of this classification remains to be determined. A small ( < 10%) proportion of cases in this group are T cell derived neoplasia and . (‘h~ca~~~. I%+ McCoy JP, Lovett EJ. Basic principles in clinical Ilo\\ cytotneir! In: Kcrcn i)l cd,. i ien\ a‘, tlmcir ) in clinical diagnosis. Chicago: ASCP Press_ IOSU;I7 -30 Ballieux R, Heynen C. Immunoregulatory T cell atlbpopulailn\ III rn.~tk ~~I~s.~~:~I~~~~ I.\, nr~~rr~~cl~~r~ il antibodies and Fc-receptors. lmmunol RCL i9X3;74:5-‘3 Hsu S, Cossman J, Jafee E. Lymphocqrc \uhscts in nmnrC h:muu l~mph,;~i L~XSII~.- XIII : i‘!i~ Pathol 1983;80:21-30. Timens W, Poppema S Lymphocyte !.f~~v~n~~l!~~~~ tc ,i~fc~c~ tiation in primary and secondary Irnrnuuod~ficlen~~ d~sca~> .I imm~:n~~l i’)X’ I ?< I 3% i 7:/Z Durandy A, LeDeist F, Frscher A, Griscelll i’ lmpalretl TI; i>niphocyl:. ;xcd;atcd~ti,rpr~~~~~.~: ac:)j ity in patients with partial DiGeorgc a\ndronlc 1 (‘Iill immunol 1 of p~t~rtnt\ x\li!t/ :tpla\!‘c ,tnem!.t ~~l~~~trlieti microflourometry. N Enpl J Med l9k5:3 I? 101 S Kurki P, Ogata K. Tan Ehl. Monoclonal ,tntibodle\ 1~1 prollter;iIing i,cli inu(.li‘;ti ,tn!igrri I in(PCNA)/cyclin as probes 101 prnllfctatjnp t,c!l \. h\, Irnrnuni~fl~rore~~cri~~~ ,inti t?rw ~\lwncrr;,’ munol Methods 1988:IO9:49 Cosimi AB, Calvin RR. Burton R( l’w ~)i~rr~or~i)(.l~~rli~idnlih;ldic\ II>‘f ill \Uhi?l\ 1111inl!llLlr!~ll\~t!i~ monitoring and treatment in rccipienl\ o!‘ rcndi dlogralts. Y tfngi J Mcd 1W W \I!3 O’Tolle CM, Maber P. Spiegrlhalter 1)J. Fnplish ThH. ‘Ke)wtion oi i;il’c~r;:: flralic:i\:, \.L!L!I. 3: T-cell subset ratio, before and after heari ~ransplantaliorr iieart T~.in>pl i’)&” -1 $! i Shaw S. Characterization ,)f human leukocyte diffentiation :intigcnh i!nmun\G 1 INLI> i9S ;. II): ; rrnxi III! Chan LC, Pegram SM, Grabes MI: C ontrlhution of~n~rnun~~phen~~t~ir~ :,I ‘he .!;~\s~~‘~~.~t~~w ferential diagnosis of acute leukemia. Ldncci 19x5: 1.37i Ruiz-Arguelles GJ, Marin-1.6pez A. Ruiz-A1guellcs A Immunologic i.l;tra~l’~c,i:lc~r~,)I lhc .liult fizis .cnd pl-~~~no~i\ Rrs\ i!i\c>i Clin (Mex) 1987;39:143-147. Ruiz-Arguelles GJ, Marin-Loper ‘2. i_~,harc)-Mcndirahai E. Ru;1-4rgucll?~ A ‘\ilchoi\ M i.. K.I~J 4 prospectiw study or it? idcntitication and !ren.tmrnr man JA. Acute megacarioblastic leukemra
Br J Haematol 1986;6?:55--63 30
Sobal RE, Mick R, Royston I. C linlcal importance ol‘mqcl~~;d antlgtn phoblastic leukemia. N Engl J Med 19X7:3)6 I1 I I
c*prcss!on
:n ;itlult a~uii’ i\ni-
s27
31
32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48
49
50
National Cancer Institute. The non-Hodgkin’s lymphoma pathologic classification project. Sponsored study of the classification of non-Hodgkin’s lymphoma survey and description of a working formalization for clinical usage. Cancer 1982;49:2112. Barlogie B. Raher MN. Schuman J. Flow cytometry in clinical cancer research. Cancer Res 1983;43:3982. Anderson KL, Bates MP, Slanherhopt D. Expression of human B cell associated antigens on leukemia and lymphomas: a model of human B cell differentiation. Blood 1984;63:1424. Reynolds CW, Foon KA. T y lymphoproliferative disease and related disorders in man and experimental animals: a review of the clinical cellular and functional characterization. Blood 1984;64: 1146. Kung PC, Berger CL, Goldstein G. Cutaneous T cell lymphoma: characterization by monoclonal antibodies. Blood 1981;57:261. Foon KA, Billing RJ, Ferasi PI. Dual B and T markers in acute and chronic lymphotropic leukemia. Blood 1980;55: 16. Ligler SF, Kettman JR, Smith G. Immunoglobulin phenotype on B cells correlates with clinical stage of chronic lymphocyte leukemia. Blood 1983;62:256. Koginer B. Kempin S, Passe G. Characterization of B cell leukemia: a tentative immumomorphological scheme. Blood 1980;56:8 15. Korsmeyer SJ, Greene MC, Cossman J. Rearrangement and expression of immunoglobulin gene and expressin of TAC antigen in hairy cell leukemia. Proc Nat1 Acad Sci USA 1983;80:4522. Bibbo M, Dytch HE, Puls JH. Clinical application for an inexpensive, microcomputer-based-DNAcytometry system. Acta Cytol 1985;30(4):372. Coon JS. Landay AL, Weinstein RS. Advances in flow cytometry for diagnostic pathology. Lab Invest 1987;57:453-479. Headley DW, Friedlander ML, Taylor IW. Method for analysis ofcellular DNA content of paraffinembedded pathological material using flow cytometry. J Histochem Cytochem 1983;3 1: 1333- 1335. Wolley RC. Chreiber K, Koss LG. DNA distribution in human colon carcinomas and its relationship to clinical behavior. J Nat1 Cancer Inst 1982;69:15. Kokal W, Sheibani K, Terz J. Tumor DNA content in the prognosis of colorectal carcinoma. J Am Med Assoc 1986;255:3 123. Murphy WM. DNA flow cytometry in diagnostic pathology of the urinary tract. Human Pathol 1987;13:317. Badalament RA, Kimmel M, Gay H. The sensitivity of flow cytometry compared with conventional cytology in the detectin of superficial bladder carcinoma. Cancer 1987;59:2078. Von Roenn J, Kheir S, Wolter J. Significance of DNA abnormalities in primary malignant melanoma and nevi. a restrospective flow cytometry study. Cancer Res 1986;46:3192. Bejar-Lozano C, Ruiz-Arguelles GJ, Ruiz-Arguelles A, Deschamps E. The pretreatment DNA labelling index of the blast cells of patients with acute lymphoblastic leukemia as a prognostic factor of the outcome of treatment: the concept of ‘G-O’ acute leukemia. Clin Lab Haematol 1989; Il:339-348. Ruiz-Arguelles A, Llorente L. Diaz-Jouanen E, Alarcon-Segovia D. Optimal conditions in 13H]thymidine uptake studies to prevent radiation damage to cells. A scintimetric and cytofluorographic analysis. Immunology I98 1;44:8 1 l-8 15. NCCLS. Clinical applications of flow cytometry: quality assurance and immunophenotyping of peripheral blood lymphocytes. NCCLS Document H42-P 1989:9( 13).
s13
CCA 05406
INTERNATIONAL
FEDERATION
OF CLINICAL CHEMISTRY
Flow cytometry in the clinical laboratory. Principles, applications and problems A. Ruiz-Arguelles Scientific
Division, International
Key words: Flow cytometry;
Federation
Cytofluorography;
of Clinical Chemistry
Clinical
flow cytometry
Introduction Flow cytometry is a method of measuring cell characteristics as they ‘flow’ through special detectors while being illuminated by intense - usually laser - light. Cells to be analyzed in this system need to be prepared into single cell suspensions; hence, they might be forced to flow within a fluid sheath where they are interrogated by the laser beam. Every cell entering the beam will scatter light in all directions; the light scattered in the forward direction will be proportional to the size of the cell; that scattered at a 90” angle will provide information of its intracytoplasmic granularity. If the cell has been stained with one or more fluorochromes, special detectors will selectively register information about the presence or absence of such dyes in a given cell. After recording all 4 or 5 parameters of each cell, instruments will electronically place that cell in a category of size, granularity and the presence, and intensity, of green, red or orange fluorescence. In the early development of flow cytometry, instruments were confined to research laboratories and clinical applications of this technique were, if any, very scant. Progressive advances in availability of monoclonal antibodies specific for a very wide range of cell antigens, along with the development of small although powerful instruments and user friendly data analysis systems, are rapidly moving flow cytometry from the experimental to the clinical laboratories [l-4]. Correspondence to: A. Ruiz-Arguelles, Blvd. Diaz Ordaz 808, Cal. Anzures, The copyright
is vested with IFCC.
Laboratorios Clinicos de Puebla. 72530 Puebla, Pue., Mexico. 92, SD-PPI4
Departamento
de Inmunologia,
This paper WIII revtew some general aspects of the methodology and comment on the most widely used applications in the clinical laboratory. The rapidly developing experimental applications of flow cytometry are beyond the scope of this review. Principles of Flow Cytometr? The Bow cytometry instruments can be divided into three functional compartments: fluidics. optics and data analysis. The fluidics compartment is designed to create a sheath of fluid that will drive the cells in a suspension to flow into a detection chamber in a sequential array. The possibility of changing the pressure of the fluid sheath enables the user to increase or decrease the diameter of the flow stream, according to the mean size of the cells to be analyzed. The user is also able to change the flow rate according IO the number of cells to be analyzed in a given time. The optics compartment consists of a light source that will interrogate each cell flowing in the chamber and several detectors to record the cell’s responses. Early instruments were equipped with very powerful laser beams which required water-cooling systems and special facilities. Recent instruments employ small air-cooled lasers but more powerful detection systems and are assembled as benchtop machines. As the laser beam meet> a cell. the latter will scatter light in all directions. A detector positioned in the forward direction will detect the ‘forward angle scatter’ whose magnitude is proportional to the cell size: therefore. small cells will yield less ‘forward scatter’ than large ones (Fig. I). A photomultiplier positioned at 90” to the laser direction will register the so called ‘side scatter‘ which provides information on the intracellular texture of the cell. Thence. cells with granules will yield more side scatter than cells with few or no rntracytoplasmic inclusions. If the cells have been stained with fluorochromes. these will be excited by the same, or an additional, light source. Early flow cytometers had lasers whose wavelength could be modified, or were equipped with Inore than one hser. Benchtop instruments employ single wavelength (488 nm) laser beams. bur due to the dcvclopment of new fluorochromes [5] a wide variety of them can be used to lag antibodies or other molecules, thus making single
FL1 fa
FL2
Fig.
I Opcal system of a tlow cyt~mete~ in the chamber
yielda 4 parrtmerers
I‘he cl’fects of the laser heam interrogating the cells flowing of information about the characteristics of each cell.
s15
wavelength instruments very powerful. Up to three (or more) fluorochromes in a single cell can be excited at the same time and, by means of the appropriate filtering systems and dichroic mirrors, the emission of such dye is led to a different photomultiplier. All the signals registered from each cell (forward and side scatter and the presence and intensity of the fluorochromes) are converted into digital signals to be analyzed by a microprocessor. According to the users’ needs, one, or two parameter histograms may be built by the processor. One parameter histograms will yield information on the proportion of cells bearing, or not, a given characteristic, for example, the proportion of cells in the given sample that binds a fluorescein-conjugated antibody. Two parameter histograms will electronically group cells having certain features, for example, a forward/side scatter histogram of whole blood leukocytes will plot small non-granular cells (lymphocytes) as a group, large granular cells (polymorphonuclear leukocytes) as another group, while a third group will result from cells having an intermediate size and granularity (monocytes)(Fig. 2) By the use of either built-in or computer-
pm..
z DOUBLE STAINED
ss
I
FL2
% STAINED
I
% STAINED I
FL1
I
FL2
Fig. 2. Example of histograms in the analysis of lymphocyte subpopulations. The cytogram (top left) of forward and side scatter (FS, SS) enables the identification of three subpopulations of cells according to their size and texture. After gating the lymphocytes, histograms (bottom) of cells bearing or not a given fluorochrome (GF, green fluorescence: RF, red fluorescence) yields information on the proportion of cells that express an antigen. Cells co-expressing antigens, can be detected by the construction of double fluorescence
histograms
(top right).
Sl6
assisted software, the user is able to define electronic gates or windows and focus the analysis of a given characteristic in a special group of cells, for example, the cells plotted as lymphocytes in a forward/side scatter histogram can be ‘gated’ (i.e. electronically isolated) from the other cells in the histogram, to ensure that the detection of fluorescent dyes is limited to the lymphoid cells. As a result of this capability, the need for preparation of isolated lymphoid cells for immunophenotyping can be easily circumvented. Newly developed software capabilities, such as ‘color gating’ and multi-dimensional projections of histograms, are increasingly allowing flow cytometer users to achieve more accurate and complete cell analysis. Many of these new software programs are being designed for the clinical laboratory, reflecting the rapid move of this methodology to medical practice. Applications
The enumeration of peripheral blood lymphocyte subsets used to be of interest for scientists dealing with the study of primary immunodeficiency diseases or for those involved in the study of autoimmune diseases. However, in the past decade, the worldwide spread of human immunodeficiency virus (HIV) infection has made immunophenotyping of peripheral blood lymphocytes a routine test in many clinical laboratories. A gross estimation of subpopulations of lymphoid cells used to be accomplished by rosetting techniques or by cytochemical procedures. In the early 1980s. several monoclonal antibodies capable of defining lymphoid cell subsets with certain functional properties were developed [6-lo] and rapidly became commercially available. This major development permitted a more precise definition and enumeration of lymphocyte subsets. however, the use of either immunochemical or immunofluorescence microscopy methods to demonstrate the binding of monoclonal antibodies, made their detection subjective and cumbersome. After the development of more monoclonal antibodies (see Table I) specific for sub-subsets of lymphocyte populations and the discovery that certain cell populations cannot be defined but through the demonstration of a ‘phenotype’ (i.e., the simultaneous presence of more than one surface antigen in the same cell), microscopic techniques became impractical. By means of flow cytometry. extended panels, usually, made of mixed antibodies labeled with different fluorescent dyes, can be used to define, objectively and rapidly, the lymphocyte subset profile of a given individual. The establishment of these profiles has proved to be clinically useful in patients infected by the human immunodeficiency virus, since the numbers of CD!+ cells tends to decrease with progression of the disease and becomes the prognostic cornerstone in overt acquired immunodeficiency syndrome (AIDS). Similarly, the number of these cells (CD4) is considered as an indicator of response to therapy in several clinical trials of antiviral drugs. The numbers of CD3+ cells arc also decreased in these patients, while those bearing the CD8 or the CD20 antigens increase as the infection progresses. The CD4+ subset defined by the CD45R antigen usually decreases as a prediction of the appearance of autoimmune phenomena that frequently occurs in AIDS patients. The number of NK cells. in turn. decreases at very late stages of the infectious process [l l-131.
s17 TABLE Cluster
I designation
(CD) antigens
and their distribution
CD design
Main cellular
CDla CDlb CDlc CD2 CD2R CD3 CD4 CD5 CD6 CD7 CD8 CD9 CD10
Thy, DC, B subset Thy, DC, B subset Thy, DC, B subset T Activated T T T subset T, B subset T, B subset T T subset Pre-B, M, Plt Lymph. Prog., CALL, Germ Ctr. B, G Leukocytes M, G, NK M, G, NK, B sub M, G, Plt
CDlla CDllb CD1 Ic CDwl2 CD13 CD14 CD15 CD16 cDw17 CD18 CD19 CD20 CD21 CD22 CD23 CD24 CD25 CD26 CD27 CD28 CD29 CD30 CD31 CDw32 CD33 CD34 CD35 CD36 CD37 CD38
reactivity
M, G M, (G) G, (M) NK, G, Mac. G, M, Plt Leukocytes B B B subset Cytopl. B/surface B subset B subset, act. M, Eo
CD design
B subset, (M) B, carcinomas
CD41 CD42a CD42b CD43 CD44 CD45 CD45RA CD45RO CD46 CD47 CD48 CDw49b CDw49d CDw49f CDw50 CD51 CDw52 CD53 CD54 CD55 CD56 CD57 CD58 CD59 CDw60 CD61 CD62 CD63
Ph Ph Ph T, G, M, brain T, G, M, brain, RBC Leukocytes T subset, B, G, M T subset, B, G, M Leukocytes Broad Leukocytes Pit, cultured T
CD64 CDw65 CD66 CD67 CD68 CD69 CDw70
PLt, M, G, B, (T) M, G, B, Plt M. Prog. Prog
CD71 CD72 CD73 CD74 CDw75 CD76 CD77 CDw78
act. T
reactivity
CD39 CD40
B, G Activated T, B, M Activated T T subset T subset Broad Activated T, B, Sternberg-Reed
G, M, B M, Ph. (B) By (T, M) Lymph. Prog.,
Main cellular
M, T, B, Thy Pft, (T) Leukocytes (Pit) (B) Leukocytes Leukocytes Broad, Activ. Broad NK, activ. Lymphocytes NK, T, B sub, Brain Leukocytes, Epithel Broad T sub Pit Plt activ. Plt activ., M, (G, T, B) M G, M G G Macrophages Activated B, T Activated B, -T Sternberg-Reed cells Proliferating cells, Mac. B B subset, T subset B, M Mature B, (T subset) Mature B, T subset Restr. B B, (M)
Abbreviations: Thy, thymocytes; DC, dendritic cells; M, monocyte; Pit, platelets or their precursors; Prog, progenitors, CALL, common acute lymphoblastic leukemia; G, granulocytes; NK, natural killer cells, Mac, macrophages; act., activated; Eo, eosinophils; RBC, red blood cells; Epithel, epithelial cells; Restr., restricted; T, thymus derived lymphocytes; B, bursa (or equivalent) derived lymphocytes. Source: Knapp W, Darken B, Rieber P, Schmidt RE, Stein H. (Kr. von Demborne AEG). CD Antigens. Blood 1989:74:1448-1450.
SIX
The evaluation of these changes, in either direction, can be reliable, when using microscopic methods, only if their magnitude is very important, since the visual count of 200-300 cells yields considerable errors. With the use of flow cytometers, percentages of cell subpopulations are derived from the analysis of 5,000-10,000 cells. hence yielding very small intra- and inter-assay coefficients of variation. Lymphocyte immunophenotyping is very useful in the classification of primary or congenital deficiencies of the immune system. The DiGeorge syndrome, which involves ontogenic abnormalities of the structures derived from the third and fourth pharyngeal pouches, presents with T cell defects. Two color flow cytometric analysis with monoclonal antibodies to T cell subsets has demonstrated an arrest at the common thymocyte (CD2) stage of differentiation, resulting in abnormally low numbers of mature CD3 and CD8 cells. Children with severe combined immunodeficiency presenting without adenosine deaminase deficiency represents a group composed of three phenotypically distinct subgroups: the first of them fails to express thymic specific antigens; the second does not show evidence of maturation beyond the prothymocyte (CD38); while the third shows evidence of late differentiation of thymocytes (C’D38. CD4. CDX, CD3). This distinction may have therapeutic implications Common variable hypogammaglobulinemia, in the majority of cases, results from an intrinsic defect of B cell maturation that may be established by flow cytometry along with monoclonal antibodies specific for maturation stages of the B cell lineage. such as CDIO. CD1 9. CD20 and PCA. In a minority of cases, B cells are intrinsically normal but there is an excess of activated suppressor cells (CD8 and HLA-DR) that render B cells unresponsive to antigenic stimulation [14-191. Multiparameter analysis of cells from patients with autoimmune diseases has also proved useful. Although controversial, several authors have reported that suppressor cells (CDB. CD3) arc diminished in systemic lupus erythematosus. It has also been shown that some patients present increased cells bearing the CD8/Leu7 phenotype and that these cells are responsible for suppressing IL-2 production, a defect that seems to be important in the pathogenesis of this disease. Also in systemic lupus erythcmatosus. a subgroup of patients, perhaps with different clinical features, has been identified by flow cytometry through the demonstration that their CD4 receptor on T cells lacks the T4 epitope. In patients with rheumatoid arthritis, the cells that are prone to the production of autoantibodies have been identified as those bearing a mature B cell antigen tCD20), in co-existence with a non-B cell restricted structure, the CD5 antigen. This subset of cells cannot be quantified by other than flow cytometric methods [Xl. In the diagnosis and follow-up of certain patients with aplastic anemia, lymphocyte immunophenotyping is clinically useful [21]. Some patients presenting with disorders of hematopoiesis appear to have immunological suppressor cells which are defined by the CD3. CD8 CD25 and HLA-DR phenotype. Those patients that respond to treatment with anti-thymocyte globulin will decrease the number of cells expressing the CD25 antigen (IL-2 receptor), and their CD4XD8 ratio will return to normal [22]. Another follow-up evaluation of response to therapy that may be performed by flow cytometry in these patients is the enumeration of nucleated erythrocyte precursors. In tissue transplantation. some authors have adopted flow cytometric methods to evaluate the response of cells in mixed lymphocyte cultures, by detecting cell-
s19
activation markers, such as CD25 and 4F2, instead of measuring DNA synthesis through the incorporation of radiolabeled thymidine [23]. (As will be discussed later, DNA synthesis can be also measured by flow cytometry). Post-operative monitoring of transplant recipients includes, in many instances, lymphocyte immunophenotyping. An elevated CD4ICD8 ratio has been shown to correlate with rejection [24]. Abnormally high counts of CD4 and CD8 cells distinguish cyclosporin nephrotoxicity from renal graft rejections; while inversion of the CD4iCD8 ratio correlates with opportunistic cytomegalovirus infection in cardiac allograft recipients [25]. The presence of activation antigens on CD8 cells predicts clinical symptoms or signs of rejection 2-6 days in advance. Demonstration of allo and autoantibodies to blood cells
The demonstration of serum antibodies in potential recipients of tissue grafts or blood products can be accomplished by flow cytometry by means of incubating the donor cells with the recipient’s serum in a first step, followed by the addition of a fluorescent antiserum to human immunoglobulins. By electronic gating or multiparameter analysis, the cells to which the recipient’s antibodies are directed can be identified. This approach has been extended to the investigation of serum antibodies to lymphocytes, granulocytes and platelets in patients with autoimmune diseases. In the particular case of red cell antibodies, not only screening for the specificity can be performed by flow cytometry, but the agglutinating titer correlates closely with the intensity of fluorescence in the cells [26]. Phenotyping of leukemia and lymphoma
Multiparameter analysis of leukemic cells by flow cytometry has proved to be particularly useful in infant acute lymphoblastic leukemia. Thus, the classification of patients as having T, B, ‘common’, or null lymphoblastic leukemia is of most importance to define their prognosis. Patients having T (CD3, CD2 and CDS) B (CD20) or pre-B (CD19) immunophenotypes have a poor prognosis despite the fact that more aggressive therapy is commonly used in these cases, while patients having the ‘common’ (CDlO) or null types of leukemia have a much better outcome and can be treated with less aggressive approaches [27,28]. The adult lymphoblastic leukemia phenotype has also been evaluated by flow cytometry. It has been recently shown that a subgroup of patients that express myeloid differentiation antigens in conjunction with B cell markers were found to have fewer complete remissions and shorter survival times than those without myeloid antigens. In the case of acute myeloid and monocytic leukemias, double staining phenotyping allows the classification of both, lineage and maturation stage as well. The prognostic importance of this classification is still controversial. Acute megakarioblastic leukemia represents a subtype of myeloid leukemia with a very poor response to treatment and hence, an extremely high mortality rate. Morphologically, it closely resembles a lymphoblastic leukemia and, therefore, ultrastructural or immunological methods are required for its identification. The demonstration of platelet-associated antigens on the blast cells by means of flow cytometry is the optimal choice for this purpose [29,30].
lmmunophenotyping of malignant lymphomas correlates with the morphological classification of these turnouts and therefore, it has not as much clinical importance as it does in lymphoblastic leukemia [31,32]. Hence, the small lymphocytic (diffuse, well differentiated) lymphomas. known to be of low-grade malignancy, are commonly found to bear the following antigens: low intensity surface immunoglobulin (sIg), receptors for C3d, receptors for the Fc portion of IgG, la (Class-II major histocompatibility complex antigens). CD20. CD21, CD19 and CD24. The diffuse, small cleaved cell and diffuse mixed small and large cell (poorly differentiated) lymphomas. is an intermediate prognostic group whose common phenotype is: bright (monoclonal) slg, Ia and CD19. The diffuse large cell and large cell immunoblastic, that are intermediate to high-grade malignancy tumours, respectively, have been subdivided according to their phenotype into the following subgroups: (1) CD19, CD20 and sIg positive; CD21 negative; (2) CD19, CD20, CD21 and sIg positive; (3) CD19 and CD20 positive; slg and CD21 negative; (4) CD20 and slg positive; CD19 and CD2 1 negative [33]. The clinical importance of this classification remains to be determined. A small ( < 10%) proportion of cases in this group are T cell derived neoplasia and . (‘h~ca~~~. I%+ McCoy JP, Lovett EJ. Basic principles in clinical Ilo\\ cytotneir! In: Kcrcn i)l cd,. i ien\ a‘, tlmcir ) in clinical diagnosis. Chicago: ASCP Press_ IOSU;I7 -30 Ballieux R, Heynen C. Immunoregulatory T cell atlbpopulailn\ III rn.~tk ~~I~s.~~:~I~~~~ I.\, nr~~rr~~cl~~r~ il antibodies and Fc-receptors. lmmunol RCL i9X3;74:5-‘3 Hsu S, Cossman J, Jafee E. Lymphocqrc \uhscts in nmnrC h:muu l~mph,;~i L~XSII~.- XIII : i‘!i~ Pathol 1983;80:21-30. Timens W, Poppema S Lymphocyte !.f~~v~n~~l!~~~~ tc ,i~fc~c~ tiation in primary and secondary Irnrnuuod~ficlen~~ d~sca~> .I imm~:n~~l i’)X’ I ?< I 3% i 7:/Z Durandy A, LeDeist F, Frscher A, Griscelll i’ lmpalretl TI; i>niphocyl:. ;xcd;atcd~ti,rpr~~~~~.~: ac:)j ity in patients with partial DiGeorgc a\ndronlc 1 (‘Iill immunol 1 of p~t~rtnt\ x\li!t/ :tpla\!‘c ,tnem!.t ~~l~~~trlieti microflourometry. N Enpl J Med l9k5:3 I? 101 S Kurki P, Ogata K. Tan Ehl. Monoclonal ,tntibodle\ 1~1 prollter;iIing i,cli inu(.li‘;ti ,tn!igrri I in(PCNA)/cyclin as probes 101 prnllfctatjnp t,c!l \. h\, Irnrnuni~fl~rore~~cri~~~ ,inti t?rw ~\lwncrr;,’ munol Methods 1988:IO9:49 Cosimi AB, Calvin RR. Burton R( l’w ~)i~rr~or~i)(.l~~rli~idnlih;ldic\ II>‘f ill \Uhi?l\ 1111inl!llLlr!~ll\~t!i~ monitoring and treatment in rccipienl\ o!‘ rcndi dlogralts. Y tfngi J Mcd 1W W \I!3 O’Tolle CM, Maber P. Spiegrlhalter 1)J. Fnplish ThH. ‘Ke)wtion oi i;il’c~r;:: flralic:i\:, \.L!L!I. 3: T-cell subset ratio, before and after heari ~ransplantaliorr iieart T~.in>pl i’)&” -1 $! i Shaw S. Characterization ,)f human leukocyte diffentiation :intigcnh i!nmun\G 1 INLI> i9S ;. II): ; rrnxi III! Chan LC, Pegram SM, Grabes MI: C ontrlhution of~n~rnun~~phen~~t~ir~ :,I ‘he .!;~\s~~‘~~.~t~~w ferential diagnosis of acute leukemia. Ldncci 19x5: 1.37i Ruiz-Arguelles GJ, Marin-1.6pez A. Ruiz-A1guellcs A Immunologic i.l;tra~l’~c,i:lc~r~,)I lhc .liult fizis .cnd pl-~~~no~i\ Rrs\ i!i\c>i Clin (Mex) 1987;39:143-147. Ruiz-Arguelles GJ, Marin-Loper ‘2. i_~,harc)-Mcndirahai E. Ru;1-4rgucll?~ A ‘\ilchoi\ M i.. K.I~J 4 prospectiw study or it? idcntitication and !ren.tmrnr man JA. Acute megacarioblastic leukemra
Br J Haematol 1986;6?:55--63 30
Sobal RE, Mick R, Royston I. C linlcal importance ol‘mqcl~~;d antlgtn phoblastic leukemia. N Engl J Med 19X7:3)6 I1 I I
c*prcss!on
:n ;itlult a~uii’ i\ni-
s27
31
32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48
49
50
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