Routine use of immunophenotype by flow ... - Wiley Online Library

Cytometry Part B (Clinical Cytometry) 56B:8 –15 (2003)

Routine Use of Immunophenotype by Flow Cytometry in Tissues With Suspected Hematological Malignancies Antoni Martıńez, Marta Aymerich, Mireia Castillo, Dolors Colomer, Beatriz Bellosillo, Elias Campo, and Neus Villamor* Hematopathology Unit, Departments of Pathology and Hematology, Hospital Clinic, University of Barcelona, Institut d’Investigacions Biome`diques August Pi i Sunyer (IDIBAPS), Barcelona, Spain

Background: Immunophenotype is an essential parameter in the diagnosis of hematological malignancies. Flow cytometry (FCM) is used in the analysis of bone marrow or peripheral blood samples but is less frequently used in the evaluation of tissue biopsies with suspected hematological malignancies. The aim of this study was to analyze the role of FCM in the diagnosis of biopsies from patients with a suspected hematological disorder. Methods: A total of 422 consecutive biopsies were studied using standard morphology, immunohistochemistry (IHC), and FCM. Results of FCM were obtained in less than 3 h and were interpreted independently from morphology and IHC. Results: A strong correlation between malignant disease and abnormal pattern of FCM was observed (218 of 250) with the exception of Hodgkin disease (P < 0.001). Overall, negative predictive value was 0.52 and positive predictive value was 1. Light chain restriction was observed in 182 of 201 B-cell lymphoma and in 0 of 142 non–B-cell disorders by FCM. In contrast, light chain pattern could only be evaluated in 38 of 91 cases by IHC. FCM allowed a rapid diagnosis of infrequent or high-grade malignancies such as histiocytic sarcoma or T-lymphoblastic lymphoma. The addition of FCM in the routine study of tissue biopsies facilitates the diagnosis of double pathology in five (1%) patients. Conclusions: FCM is a fast and reliable methodology for phenotyping tissue samples, which easily detects infrequent hematological malignancies, disease-specific phenotypes and clonality in B-cell lymphomas. Moreover, the simultaneous recognition of different cell populations allows the diagnosis of composite cell lymphomas, or double pathologies. Cytometry Part B (Clin. Cytometry) 56B:8 –15, 2003. © 2003 Wiley-Liss, Inc.

Key terms: lymphoma; leukemia; flow cytometry; immunohistochemistry; composite lymphoma; hematopathology

The recent classification system of the World Health Organisation (WHO) for neoplastic diseases of the hematopoietic and lymphoid tissues recognizes clinicopathological entities, some of them bearing specific phenotypic and molecular profiles (1). Therefore, ancillary technologies such as immunological markers and molecular techniques are necessary for the correct diagnosis of lymphomas and other hematological malignancies. In lymph node biopsies and other tissues, immunophenotype is usually analyzed on histological sections of frozen or fixed tissues by immunohistochemistry (IHC). The application of specific monoclonal antibodies for B, T, myeloid, or epithelial lineage allows the assignment of the cell origin of the neoplasm. Moreover, the development of monoclonal antibodies against proteins involved in specific translocations, such as ALK-1 or cyclin D1, is very helpful in the differential diagnosis of specific lymphoma types (2,3). Despite maintaining the histological architec-

© 2003 Wiley-Liss, Inc.

ture and morphology of the cells, IHC has some limitations related to the MoAb availability, mainly for natural killer (NK) and myeloid lineages, or the technique itself. The number of monoclonal antibodies working on fixed tissues is increasing, but the number of available reagents is still limited. On the other hand, immunohistochemical results are not immediately available for diagnostic purposes, and some may be difficult to interpret (e.g., surface light chain restriction) (4). Finally, it is not easy to perform

*Correspondence to: Neus Villamor, Unitat d’Hematopatologia Hospital Clinic, Villarroel 170, 08036-Barcelona, Spain. E-mail: [email protected] Supported by research grant from Fondo de Investigaciones Sanitarias (FIS) 01/1581, Madrid (Spain). Received 8 August 2002; Accepted 8 April 2003 Published online in Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002/cyto.b.10044

9

CYTOMETRY IN HEMOPATHOLOGY

double or triple labeling in the same section, which is sometimes necessary to identify subpopulations with abnormal phenotype admixed within normal lymphocytes. Direct immunofluorescence followed by flow cytometry (FCM) analysis is extensively used in immunology and hematology to assess the presence of different cellular populations within a heterogeneous cell suspension (5,6). The number of monoclonal antibodies available for FCM is very large, and they are coupled to different fluorochromes, allowing an easy multiple antigen staining. Nevertheless, immunophenotype by FCM needs to be done in cellular suspensions of viable cells, and the disaggregation of tissue leads to loss of histological architecture. This disadvantage could be overcome in part by the detailed information obtained using multiparametric phenotypical analysis and the capability to select cellular subsets during the acquisition or analysis. Thus, the recognition of phenotypical patterns associated with a disease is easily, specifically, and rapidly performed even when the abnormal population is present at low frequencies (6). Therefore, FCM is a rapid technique that may contribute to the diagnosis of lymph node biopsy or other tissues. The aim of the study was to analyze the contribution of FCM in the routine study of lymph node biopsies and other tissues obtained with the suspected diagnosis of lymphoproliferative disorder. MATERIAL AND METHODS Case Selection Four hundred and 22 consecutive biopsies of lymphoid nodes or extranodal tissues suspicious of having a hematological malignancy were obtained from 403 patients. The specimens corresponded to lymph node (380), spleen (25), skin (5), mediastinum (5), tonsil (3), abdominal mass (2), parotid gland (1), and brain (1). The biopsy specimens were included in the study when the size of the sample allowed us to obtain at least three fragments. One fragment was embedded in paraffin to perform histopathological and immunohistochemical studies, the second fragment was stored frozen for possible further additional studies, and the third fragment was submitted to FCM. Histopathological Studies and IHC Lymph nodes were fixed in 10% neutral buffered formalin and embedded in paraffin by routine methods. Immunophenotypic studies were performed in an automated immunostaining system (TechMate, DAKO, Glostrup, Denmark) using antigen retrieval and Envision System (DAKO). Antibodies were applied to tissue sections based on morphological suspicion and extended according to the phenotype obtained. The panel included T-cell antigens (CD3, CD5, CD7, CD4, CD8), B-cell antigens (CD20, CD79b, CD10, kappa, lambda, IgD), NK-cell antigens (CD56, CD57), myeloid antigens (myeloperoxidase, CD68, lyzozyme, CD15), and other antigens (CD23, CD30, CD34, CD43, CD138, cyclin D1, bcl-2, bcl-6, TIA-1, granzime B, cytokeratins).

Immunofluorescence and Flow Cytometry Cellular suspension was obtained after repetitive squirting with culture medium using a fine needle. The number of cells was adjusted to 5 ⫻ 106 cells/ml, and 100 ␮l of suspension were used for each test. Directly fluorochrome-labeled antibodies were used in triple combination. The panel applied included T-cell antigens (CD8/ CD4/CD3, CD7/CD5/CD2), B-cell antigens (CD20/CD5/ CD19, CD22/CD23/CD10, CD10/CD43/CD19, FMC7/ CD79b/CD45, k/CD19), and non–lineage-specific antigens (CD30/CD19/CD45). Briefly, each monoclonal antibody combination was added to the cellular suspension, mixed, and incubated for 15 min at room temperature in the dark. Cells to be stained with k/CD19 were previously washed three times with 5 ml of phosphate buffered saline (PBS; Biomerieux, Marseille, France). Lysis of erythrocytes was performed, when necessary, using FACS™ lysing solution (Becton Dickinson, San Jose, CA). Two washes with PBS were performed before acquisition in a FACScan flow cytometer (Becton Dickinson). When the number of cells obtained was low, a reduction in the number of cells per tube or a reduction in the number of monoclonal antibody combinations applied was performed. For each monoclonal antibody combination 104 cells were acquired and, in some cases, a specific acquisition of CD19 or CD3 cells was performed. Samples were analyzed using Paint-a-gate software (Becton Dickinson). The results were ready in 3h after arrival at the laboratory. In certain cases, the study was expanded with cytokeratins, myeloid, T-, NK, or immature-cell antigens in accordance with the initial results. The criteria for an FCM pathological pattern were the presence of cells with leukemia/lymphoma phenotype, epithelial phenotype, clonal light chain restriction in B cells, and abnormalities on forward scatter (FSC) and side scatter (SSC) characteristics. A subcategorization of flow cytometric patterns reflecting the most frequent B-cell proliferations was performed. These cases were classified as chronic lymphocytic leukemia (CLL) phenotype (CD19⫹CD5⫹ CD23⫹, with CD20dim, or CD22dim, or CD79bdim), mantle cell lymphoma (MCL) phenotype (CD19⫹CD5⫹CD23-, CD20⫹, CD79b⫹, FMC7⫹), follicular lymphoma (FL) phenotype (CD19⫹CD5-CD43CD10⫹) and B-cell non-Hodgkin’s lymphoma (B-NHL) (any other clonal B phenotype). Statistical Methods The statistical package SPSS 10.0 (SPSS, Inc., IL) was used to evaluate differences in the values of continuous variables by means of Student’s t-test for independent samples grouping according to the final diagnostic categories, and Chi-square test to compare categorical variables. Correlation between final diagnosis and phenotypical pattern in B-cell lymphoproliferative disorders was calculated using Spearman test. RESULTS The final histopathological diagnosis of the 422 biopsies is described in Table 1. Globally, a malignant disease was

10

MARTIŃEZ ET AL.

Table 1 Final pathological diagnosis in the 422 biopsies included in the studya Number Malignant hematological neoplasms Lymphoproliferative Chronic lymphocytic leukemia Mantle cell lymphoma Follicular lymphoma Diffuse large B-cell lymphoma Lymphoplasmacytic lymphoma Marginal zone lymphoma/MALT B-cell lymphoma, NOS Burkitt lymphoma T-cell lymphomac Hairy cell leukemia Hodgkin lymphoma Myeloid or histiocytic proliferations Chronic lymphocytic leukemia ⫹ metastasis Malignant nonhematological neoplasms Metastasis/thymoma Kaposi’s sarcoma Benign and reactive pathology Reactive follicular hyperplasia Granulomatous lymphadenitis Others Dermatopathic lymphadenopathy Amyloidosis Necrosis Normal and other reactive situations

224 54b 17 39 69 4 8 11 2 19 1 50 4 3

N 9 1 6 2

44 1

Phenotype P I 199 53 17 36 54 4 6 10 2 16 1

6

A 10 1 2 4

5

1 1

2 6

3 3

30 3

11 2

6

2

11 1

53 31 24 4 1 1 18

47 23 18 3

1

5 8 4 0 1 1 2

2 1

15

1

a

Phenotype: N, normal; P, pathological, I, inconclusive; A, acellular; NOS, not otherwise specified. b Two cases of composite lymphoma B-CLL and T-NHL. c 5 peripheral T-cell lymphoma, 3 T-cell lymphoblastic lymphoma, 2 anaplastic large cell lymphoma, 2 mycosis fungoides, 2 angioimmunoblastic lymphadenopathy, 1 large granular leukemia, and 1 T/NK nasal type NHL.

observed in 314 biopsies (278 hematological neoplasms, 30 epithelial tumors, 3 Kaposi’s sarcomas, and 3 cases of coexistence of chronic lymphocytic leukemia and metastasis of carcinoma), and benign, reactive, or absence of pathology was observed in 108. Enough cellularity to perform the FCM studies was obtained in 377 samples (89%), with a higher success rate in biopsies with hematological diseases (94%) compared with nonmalignant processes (84%) or metastatic infiltration (64%; P ⫽ 0.0001). The immunophenotype was considered normal in 155 cases, abnormal in 211 cases, and inconclusive in 11 cases. The phenotypical distribution of abnormal cases was as follows: B-cell origin in 184 samples; T-cell in 16; myeloid or monocytic in 3; epithelial in 6; B-cell and T-cell in 2. A strong correlation between abnormal FCM pattern and malignant disease and between normal pattern and nonmalignant disease was obtained, except for Hodgkin’s disease (HD; Table 2). The sensitivity of the test was 0.72 (0.9 excluding HD), and the accuracy was 1, having a predictive positive value of 1 and a predictive negative value of 0.52 (0.79 excluding HD). Assessment of Clonal Light Chain Restriction Assessable results for light chain expression were obtained in 324 cases. A polyclonal pattern of light chain was

obtained in all non–B-cell disorders studied (n ⫽ 142). Overall, the distribution of kappa and lambda chain could be analyzed in 182 of 201 cases of B-lymphoproliferative disorders with enough cellularity. Only 9 of 182 B-cell disorders showed polyclonal light chain, corresponding to three T-cell–rich B-cell lymphomas, three marginal zone lymphomas (MZL) infiltrating the lymph node partially, two diffuse large cell lymphoma (DLCL) and one follicular lymphoma (FL). In 12 cases, all corresponding to DLCL, Table 2 Correlation between immunophenotypical profile by FCM and final diagnosisa Final diagnosis Nonmalignant Nonhematological B-NHL T-NHL Myeloid/monocytic Hodgkin lymphoma

Concordant 87 6 183 16 3 0

Flow cytometry Discordant Inconclusive 0 13 10 0 1 44

3 2 5 1 0 0

a Concordant means normal flow cytometry in nonmalignant final diagnosis and abnormal phenotype of the same cell lineage than the final diagnosis in all the other situations. Inconclusive means no definite diagnosis of pathology or normality. NHL, non-Hodgkin’s lymphoma.

11


FIG. 1. Absence of light chain expression in a case of diffuse large cell lymphoma (DLCL). Left: Biparametric dot plot showing side scatter (SSC) and CD19 expression in a cellular suspension from a lymph node infiltrated by a DLCL. CD19-positive cells spans from low SSC (red dots) to high SSC (black dots). Right: biparametric dot plot showing kappa and lambda chain expression. The polyclonal pattern was restricted to small B lymphocytes (red dots), whereas large B cells (black dots) showed no light chain expression. [Color figure can be viewed in the online issue, which is available at www.interscience.wiley.com.]

no surface light chain was detected in the lymphoma cells, whereas it was present in the normal residual B lymphocytes (see Fig. 1). Light chain expression was analyzed by both IHC and FCM in 91 cases (16 CLL, 6 MCL, 14 FL, 31 DLCL, 2 lymphoplasmacytic lymphoma [LpL], 1 Burkitt lymphoma, 6 MZL, 4 B-NHL, and 11 reactive follicular hyperplasia [RFH]). Light chain pattern could be assessed by FCM in all cases compared with 38 (42%) cases by IHC (light chain restriction in 27 cases: 5 CLL, 3 MCL, 2 FL, 11 DLCL, 2 LpL, 3 MZL, and 1 B-NHL; and polyclonal light chain expression in 11 cases of RFH). A concordance in the light chain restriction was obtained between both methodologies. Immunophenotypical Flow Cytometry Patterns and Final Diagnosis in B-Cell Malignancies To analyze the contribution added by FCM to IHC in the diagnosis of lymph node biopsies or extranodal tissues, special analysis focusing in gray zones was performed. In this sense, the differential diagnosis between FL and RFH,

and the role of FCM in the subclassification of B cell malignancies and in the diagnosis of less frequent hematological diseases (T and NK lymphomas, and myeloid proliferations) were studied. FL (36 cases) had a lower percentage of T cells than RFH (53 cases; 32.3% ⫾ 12.3 vs 59.3% ⫾ 14.0; P ⬍0.001), and a higher CD10 expression on B lymphocytes (38.8% ⫾ 29.1) than RFH (1.8% ⫾ 3.9; P ⬍ 0.001). In fact, none of the RFH cases was CD10 positive (CD10 ⬎ 20% of total B cells), whereas 25 of 33 (76%) FL were CD10 positive. Nevertheless, light chain analysis was the most powerful to diagnose both entities, because no RHF showed light chain clonality, and only one case of FL showed no light chain restriction, corresponding to the previously mentioned false-negative result (see text above). We analyzed the value of multiparametric phenotype in the diagnosis of specific lymphoma entities (Table 3). According to the immunophenotype classification described in the Materials and Methods section, a CLL phenotype was observed in 58 cases (56 CLL and 2 DLCL arising in patients with CLL), FL phenotype was observed in 41 cases (25 FL, 13 DLCL, 2 DLCL after FL, and 1 Burkitt), MCL phenotype was observed in 17 cases (all MCL), and B-NHL phenotype was observed in 67 cases (36 DLCL, 11 FL, 5 MZL, 4 LpL, 1 Burkitt, and 10 nonclassified). A significant correlation was found between the FCM classification and the final diagnosis (P ⬍ 0.001). Thus, MCL, CLL, and most FL are specifically detected by FCM, whereas this technique is less useful in the subclassification of lymphomas lacking specific phenotype. Immunophenotypical Flow Cytometry Patterns and Final Diagnosis in Non–B-Cell Malignancies FCM was very useful in recognizing T-cell malignancies (see Table 4). In all cases, an abnormal FCM was observed due to changes in FSC and SSC pattern (56% of cases) or phenotypical anomalies (100%). The most frequent anomalies were loss or dim expression of pan T-cell antigen (94% of cases; CD7, 67% of cases; CD3, 62%; CD5, 44%; CD2, 21%) or other cellular antigens (CD43, 50%; CD45, 20%; CD4, 6%), followed by ectopic expression (56%;

Table 3 Correspondence between final diagnosis of B-cell malignancies and phenotypical pattern assessed by FCMa

FCM pattern CLL phenotype MCL phenotype FL phenotype B-cell NHL

CLL (n ⫽ 56)

MCL (n ⫽ 17)

Final diagnosis FL (n ⫽ 37)

DLCL (n ⫽ 65)

Other B (n ⫽ 26)

2b

56 17 25 11

15c 36

1 20d

a B-cell phenotype not allowing a further subclassification (see Materials and Methods section). FCM, flow cytometry; CLL, chronic lymphocytic leukemia; MCL, mantle cell lymphoma; FL, follicular lymphoma; DLCL, diffuse large cell lymphoma. b Cases corresponding to Richter’s transformation from a previous CLL. c Two cases of transformation from previous FL. d Including a case of hairy cell leukemia with a typical phenotype.

12

MARTIŃEZ ET AL.

Table 4 Abnormalities detected by flow cytometry in T-cell disordersa Diagnosis Immature T-ALL (T-IV) T-ALL (T-III) T-ALL (T-III) Mature T/NK AIL AIL M. fungoides M. fungoides LGL ALCL ALCL TCL TCL TCL TCL TCL

FSC/SSC pattern

CD4/CD8 ratio

N N Abn

0.3 1.2 0.8

Abn N Abn N Abn N N Abn Abn Abn Abn Abn N

7.0 8.4 99.0 27.0 8.1 0.8 0.3 0.4 47.5 6.6 12.3 1.1 5.0

Phenotypical abnormalities Overexpressed Ectopic/cross-lineage

Negative or dim CD45, CD43 CD45, CD3, CD5 CD45, CD3, CD5, CD2 CD3m, CD5, CD7 CD3, CD7, TCR␣␤

CD7

CD34, Tdt, CD10 CD1a, CD34, Tdt, CD4⫹CD8⫹ CD1a, CD34, Tdt, CD33, CD4-CD8-

CD3c,CD45

CD56, CD4-CD8CD20

CD3, CD3, CD3, CD3, CD5 CD3, CD7, CD2, CD3, CD7

CD7 CD7, CD2, CD43 CD4, CD5, CD7 CD5

CD5 CD43

CD7, TCR␣␤, CD43 CD43 CD7, CD43 CD5, CD7, CD43

CD45 CD5

CD57 CD57 CD30 CD30, CD20 CD20, CD10 CD30 CD20, CD10

a T-ALL, T-cell lymphoblastic lymphoma; T/NK, T/NK lymphoma nasal type; AIL, angioimmunoblastic lymphadenopathy; LGL, large granular leukemia; ALCL, anaplastic large cell lymphoma; TCL, peripheral T-cell lymphoma; N, normal; Abn, abnormal; CDm, membrane antigen; CDc, cytoplasmic antigen.

immature phenotype,19%; CD30, 19%; CD57, 12%; CD56, 6%), antigen overexpression (37%; CD45, 12%; CD5, 12%; CD43, 8%; CD7, 7%), and cross-lineage expression (25%; CD20, 25%; CD10,19%). Dim expression of CD45 was only observed in immature T-cell proliferations, whereas CD45 overexpression was only observed in mature T-cell lymphomas. Aberrant phenotypes were observed in both mature and immature lymphoproliferative disorders. Mature T-cell disorders express NK-related antigens (CD57, CD56), activation antigens (CD30), or B-related antigens (CD10, CD20). Immature T-cell disorders coexpressed myeloid-related antigens (CD33), B-related antigens (CD10), and immature cell antigens (CD34, TdT, and CD1a). When analyzing upper mediastinal biopsies, a normal cortical thymocyte phenotype alone in absence of aberrances (e.g., coexpression of myeloid antigens) is not indicative of hematological malignancy. In fact, the two patients with thymoma showed a phenotype of normal cortical thymocyte. In HD, a high percentage of CD3 cells was detected without phenotypical abnormalities. Only a predominance of the CD4 subset was observed in comparison with reactive lymph nodes (50.4% ⫾ 16.7 versus 37.6 ⫾ 15.8; P ⫽ 0.001), thus being insufficient for differential diagnosis. Finally, FCM was very useful in the rapid diagnosis of high grade lymphomas (for instance, T-cell lymphoblastic lymphomas), extramedullary infiltration of acute myeloid leukemias, and in the diagnosis of infrequent types of lymphoma, such as T/NK cell lymphoma or histiocytic sarcoma. The routine application of a panel of monoclonal antibodies also allowed the detection of phenotypical aberrances: dim CD10 expression in one case of MCL; CD8 positivity in a B-cell DLCL, IgM-, IgD⫹ lymphoma cells in

3 of 12 cases of FL; and the absence of light chain expression in 12 cases of 47 DLCL (25.5%). Composite Pathology and Immunophenotype by FCM In this study, we identified two different malignant processes located in the same biopsy in five patients (1.2%). Three cases were metastases of carcinoma and CLL (see Fig. 2). Two of these patients had a previous diagnosis of CLL, and the lymph node biopsy was performed for a suspected Richter’s transformation. In the third patient, both the CLL and the carcinoma were initially diagnosed in the lymph node biopsy. The other two cases were composite B–CLL and peripheral T-cell lymphoma. One of the patients showed two morphologically different areas of infiltration, corresponding to CLL and mycosis fungoides (Fig. 3). In the second case, no morphological distinction between both lymphomas was observed. More interestingly, by IHC only the abnormal B-cell population could be detected, whereas both abnormal populations were detected by multiparametric flow cytometry, as abnormal T-cells were membrane CD3- but cytoplasmic CD3⫹. DISCUSSION The diagnosis of malignant lymphomas and other hematological malignant disorders is mainly based on morphology, but diagnostic accuracy and reproducibility are highly increased by the use of ancillary techniques such as immunophenotyping and molecular analysis. This multiparametric approach is recommended by the recent WHO classification for tumors of hematopoietic and lymphoid tissues (1,7,8). In diagnostic hematopathology, IHC is widely used to assess cellular phenotype in tissue sections. The main advantage of this approach is the possi-


13

FIG. 2. Concurrence of two different malignancies. A: Hematoxylin and eosin (original magnification, 10⫻) staining of a lymph node infiltrated by carcinoma and chronic lymphocytic leukemia (CLL). A minimal peripheral lymphoid tissue is observed. B: Flow cytometry of cell suspension obtained from the same case showing lymphoid cells with B–CLL phenotype (CD19⫹, CD5⫹, CD22 dim, CD23⫹, and kappa light chain restriction). [Color figure can be viewed in the online issue, which is available at www.interscience.wiley.com.]

bility to correlate antigen expression with cell morphology and tissue architecture (8,9). In addition, some nuclear antigens are more easily detected by IHC than FCM techniques. However, although rapid IHC protocols have been designed, immunohistochemical results are usually available only 1 or 2 days after the tissue has been routinely processed and examined. Moreover, the evaluation by IHC of crucial antigens, such as immunoglobulin light chain restriction, is difficult. The relative limited number of monoclonal antibodies available for IHC, particularly for NK and myelomonocytic lineage, may hamper a correct characterization of these disorders. Finally, simultaneous detection of several antigens in the same subset of cells by IHC is impractical for routine purposes and usually is limited to detection of two antigens (4,10). Flow cytometry is an alternative immunophenotyping method that provides flexibility, rapidity, and multiparametric analysis of cells (6). Compared with diagnostic hematopathology in bone marrow and peripheral blood specimens, FCM is much less frequently used in phenotyping tissue samples, probably due to the requirement of fresh material and the loss of a morphological perspective. The main application of FCM in tissues has been as a complementary technique in the cytological diagnosis of lymphoproliferative disorders by fine-needle aspiration (FNA) (10 –21). However, one major disadvantage of this approach is that FNA plus FCM does not usually preclude the need of tissue biopsy to obtain a definite diagnosis in a significant number of patients (22). Therefore, lymph node biopsy remains the criterion standard for lymph node pathology (7,22). In our study, at least three fragments from each lymph node biopsy or extranodal tissues were obtained for standard histological examination, frozen storage, and to obtain a suspension of fresh cells. In that way, all the benefits from the different technologies are gathered in one medical action. Very few authors have applied a similar strategy (23–25) with similar overall results as far as obtaining cells (24) and false negative results (23) are concerned. In this study, we have confirmed that FCM is a very useful complementary technique in the diagnosis of NHL in tissue specimens. In B-cell NHL lymphoma, the most powerful information provided by FCM was the recogni-

tion of specific patterns and the detection of clonal light chain expression. Flow cytometry was superior to IHQ analysis in assessment of light chain expression. Absence of clonal chain expression was observed in 25% of DLCL, a phenotype previously noticed (14) and related to B-cell malignancy (26). The level of identification of light chain restriction in B-cell lymphomas in the present study (90%) is higher than in a previous one (47%), with no other explanation than the use of different reagents (24). T-cell– rich B-cell lymphoma, MZL, and cases with partial infiltration of lymph node concentrate the false-negative results of FCM in our series and others, and are mainly related to scarcity and fragility of malignant cells, analysis of an uninvolved area, or fibrosis in the tumoral zone causing low cell yield (16,23,24). All T-cell NHL lymphomas detected in this study showed two or more flow abnormalities regarding FSC/SSC pattern or abnormal T-cell phenotype. In non–T-cell malignancies only low expression of CD7 has been reported (27), then the detection of multiple cell abnormalities by flow cytometry is indicative of T-cell malignancy. Standard FCM only detects membrane antigens, this being different from the membrane and cytoplasmic staining provided by IHC. In several T-cell NHL and myeloid proliferations, the information of antigen density (underexpression or overexpression) given by FCM was used to direct the diagnosis. In fact, one of the two composite Band T-cell lymphomas was diagnosed by FCM because FCM detected an abnormal T-cell population (membrane CD3- but cytoplasmic CD3⫹) that was not revealed by IHC (as it was cytoplasmic CD3⫹). Other authors have used the quantitative information of antigen density provided by FCM, which has also been used in the differential diagnosis of FL and RFH (28). The wide range of myeloid and monocytic antigens available by FCM is a great advantage for the diagnosis of this type of malignancies when compared with IHC. The characteristics of myeloid cells in FSC and SSC and the pattern of reactivity using the basic panel used in this series were very helpful to rapidly suggest this diagnosis and to expand the study with other myeloid markers. Compared with NHL and myeloid or monocytic proliferations, the value of FCM in the diagnosis of metastatic

14

MARTIŃEZ ET AL.

FIG. 3. Composite B-cell lymphoma (chronic lymphocytic leukemia [CLL]) and peripheral T-cell lymphoma (mycosis fungoides). A: Hematoxylin and eosin (H&E; original magnification, 20⫻) of a lymph node infiltrated by B–CLL and mycosis fungoides. The subcapsular area of larger lymphocytes with irregular nucleus corresponds to CD4⫹ T cells, whereas a central diffuse infiltration by smaller lymphocytes corresponds to CD79a⫹ cells. B: Flow cytometry showing a minority of T lymphocytes with an abnormal phenotype (CD3 dim, CD7- and CD4⫹) and a massive infiltration by abnormal B cells (CD5⫹ CD20 dim). [Color figure can be viewed in the online issue, which is available at www.interscience.wiley.com.]

infiltration and Hodgkin disease is lower. FCM was normal or no cells were obtained from the fragment in 75% of cases with metastatic infiltration, and no diagnostic abnormalities were detected in HD. The analysis of DNA content by FCM could improve the detection rate in HD in samples with normal phenotype (23,24,29). In both metastasis and HD, cytology of touch imprints of the tissue is helpful to suggest these diagnosis (17,19). Although we routinely perform touch imprints in all cases, this parameter was not evaluated in this study because the purpose was to analyze the applicability of immunophenotype using FCM in lymph node biopsy rather than a reproduction of FNA plus FCM studies. Finally, in this study, FCM as an ancillary technique in hematopathology was a method to detect double pathol-

ogy by highlighting a small abnormal population from another more abundant pathology. This finding was observed in five (1%) patients, in some of them as initial presentation for both pathologies. Also, the routine use of FCM could allow a better characterization of NHL, especially of those without peripheral blood involvement, to enlarge the number of antigens studied, or to obtain new prognostic factors (30 –32). In conclusion, immunophenotype by FCM of cellular suspensions obtained from fresh lymph nodes and other tissues is an applicable technique as a diagnostic methodology in hematopathology. Our approach, consisting in obtaining three different fragments from every biopsy, retains all the benefits of tissue examination of classic pathology and IHC and adds the advantages of FCM, such


as multiparametric analysis, wide range of monoclonal antibodies, and rapidity of the study, thus increasing the diagnostic capability in tissue biopsies. LITERATURE CITED 1. Jaffe ES, Harris NL, Stein H, Vardiman JWE. World Health Organization classification of tumours. Pathology and genetics of tumours of haematopoietic and lymphoid tissues. Lyon: IARC Press; 2001. 2. Nakamura S, Seto M, Banno S, et al. Immunohistochemical analysis of cyclin D1 protein in hematopoietic neoplasms with special reference to mantle cell lymphoma. Jpn J Cancer Res 1994;85:1270 –1279. 3. Pittaluga S, Wiodarska I, Pulford K, et al. The monoclonal antibody ALK1 identifies a distinct morphological subtype of anaplastic large cell lymphoma associated with 2p23/ALK rearrangements. Am J Pathol 1997;151:343–351. 4. Leers MP, Theunissen PH, Ramaekers FC, et al. Clonality assessment of lymphoproliferative disorders by multiparameter flow cytometry of paraffin-embedded tissue: an additional diagnostic tool in surgical pathology. Hum Pathol 2000;31:422– 427. 5. Jennings CD, Foon KA. Recent advances in flow cytometry: application to the diagnosis of hematologic malignancy. Blood 1997;90: 2863–2892. 6. Orfao A, Schmitz G, Brando B, et al. Clinically useful information provided by the flow cytometric immunophenotyping of hematological malignancies: current status and future directions. Clin Chem 1999;45:1708 –1717. 7. Harris NL, Jaffe ES, Diebold J, et al. World Health Organization classification of neoplastic diseases of the hematopoietic and lymphoid tissues: report of the clinical advisory committee meeting-Airlie House, Virginia, November 1997. J Clin Oncol 1999;17:3835–3849. 8. Jaffe ES. Hematopathology: integration of morphologic features and biologic markers for diagnosis. Mod Pathol 1999;12:109 –115. 9. Chen CC, Raikow RB, Sonmez-Alpan E, et al. Classification of small B-cell lymphoid neoplasms using a paraffin section immunohistochemical panel. Appl Immunohistochem Mol Morphol 2000;8:1–11. 10. Siebert JD, Weeks LM, List LW, et al. Utility of flow cytometry immunophenotyping for the diagnosis and classification of lymphoma in community hospital clinical needle aspiration/biopsies. Arch Pathol Lab Med 2000;124:1792–1799. 11. Nicol TL, Silberman M, Rosenthal DL, et al. The accuracy of combined cytopathologic and flow cytometric analysis of fine-needle aspirates of lymph nodes. Am J Clin Pathol 2000;114:18 –28. 12. Liu K, Stern RC, Rogers RT, et al. Diagnosis of hematopoietic processes by fine-needle aspiration in conjunction with flow cytometry: a review of 127 cases. Diagn Cytopathol 2001;24:1–10. 13. Wakely PJ, Frable WJ, Kneisl JS. Soft tissue aspiration cytopathology of malignant lymphoma and leukemia. Cancer 2001;93:35–39. 14. Young NA, Al-Saleem TI, Ehya H, et al. Utilization of fine-needle aspiration cytology and flow cytometry in the diagnosis and subclassification of primary and recurrent lymphoma. Cancer 1998;84:252– 261. 15. Rassidakis GZ, Tani E, Svedmyr E, et al. Diagnosis and subclassification of follicle center and mantle cell lymphomas on fine-needle aspirates: a cytologic and immunocytochemical approach based on the Revised European-American Lymphoma (REAL) classification. Cancer 1999;87:216 –223.

15

16. Zardawi IM, Jain S, Bennett G. Flow-cytometric algorithm on fineneedle aspirates for the clinical workup of patients with lymphadenopathy. Diagn Cytopathol 1998;19:274 –278. 17. Prasad RR, Narasimhan R, Sankaran V, et al. Fine-needle aspiration cytology in the diagnosis of superficial lymphadenopathy: an analysis of 2,418 cases. Diagn Cytopathol 1996;15:382–386. 18. Horii A, Yoshida J, Hattori K, et al. DNA ploidy, proliferative activities, and immunophenotype of malignant lymphoma: application of flow cytometry. Head Neck 1998;20:392–398. 19. Tarantino DR, McHenry CR, Strickland T, et al. The role of fine-needle aspiration biopsy and flow cytometry in the evaluation of persistent neck adenopathy. Am J Surg 1998;176:413– 417. 20. Dong HY, Harris NL, Preffer FI, et al. Fine-needle aspiration biopsy in the diagnosis and classification of primary and recurrent lymphoma: a retrospective analysis of the utility of cytomorphology and flow cytometry. Mod Pathol 2001;14:472– 481. 21. Meda BA, Buss DH, Woodruff RD, et al. Diagnosis and subclassification of primary and recurrent lymphoma. The usefulness and limitations of combined fine-needle aspiration cytomorphology and flow cytometry. Am J Clin Pathol 2000;113:688 – 699. 22. Sandhaus LM. Fine-needle aspiration cytology in the diagnosis of lymphoma. The next step. Am J Clin Pathol 2000;113:623– 627. 23. Dunphy CH. Contribution of flow cytometric immunophenotyping to the evaluation of tissues with suspected lymphoma?. Cytometry 2000;42:296 –306. 24. Ichinohasama R, DeCoteau JF, Myers J, et al. Three-color flow cytometry in the diagnosis of malignant lymphoma based on the comparative cell morphology of lymphoma cells and reactive lymphocytes. Leukemia 1997;11:1891–1903. 25. Morse EE, Yamase HT, Greenberg BR, et al. The role of flow cytometry in the diagnosis of lymphoma: a critical analysis. Ann Clin Lab Sci 1994;24:6 –11. 26. Li S, Eshleman JR, Borowitz MJ. Lack of surface immunoglobulin light chain expression by flow cytometric immunophenotyping can help diagnose peripheral B-cell lymphoma. Am J Clin Pathol 2002;118: 229 –234. 27. Gorczyca W, Weisberger J, Liu Z, et al. An approach to diagnosis of T-cell lymphoproliferative disorders by flow cytometry. Cytometry 2002;50:177–190. 28. Cornfield DB, Mitchell DM, Almasri NM, et al. Follicular lymphoma can be distinguished from benign follicular hyperplasia by flow cytometry using simultaneous staining of cytoplasmic bcl-2 and cell surface CD20. Am J Clin Pathol 2000;114:258 –263. 29. Sanchez J, Serrano J, Garcia JM, et al. Flow cytometry of cell suspensions from lymph nodes: immunophenotype, DNA content and proliferative rate are strongly correlated with histopathology diagnosis. Haematologica 1999;84:762–763. 30. Xu Y, Kroft SH, McKenna RW, et al. Prognostic significance of tumour-infiltrating T lymphocytes and T-cell subsets in de novo diffuse large B-cell lymphoma: a multiparameter flow cytometry study. Br J Haematol 2001;112:945–949. 31. ten Berge RL, Oudejans JJ, Dukers DF, et al. Percentage of activated cytotoxic T-lymphocytes in anaplastic large cell lymphoma and Hodgkin’s disease: an independent biological prognostic marker. Leukemia 2001;15:458 – 464. 32. Drillenburg P, Wielenga VJ, Kramer MH, et al. CD44 expression predicts disease outcome in localized large B cell lymphoma. Leukemia 1999;13:1448 –1455.