Classification of Acute Myeloid Leukemias

Immunological classification of acute myeloblastic leukemias: relevance to patient outcome

Abstract

Immunophenotyping is a major tool to assign acute leukemia blast cells to the myeloid lineage. However, because of the large heterogeneity of myeloid-related lineages, no clinically relevant immunological classification of acute myeloblastic leukemia (AML) has been devised so far. To attempt at formulating such a classification, we analyzed the pattern of expression of selected antigens, on blast cells collected at AML diagnosis. Patients were eligible if they had a first diagnosis of de novo AML and a sufficient number of blast cells for proper immunophenotyping. The relative expression of CD7, CD13, CD14, CD15, CD33, CD34, CD35, CD36, CD65, CD117, and HLA-DR were analyzed by cytometry in a test series of 176 consecutive AML cases. Statistical tools of clusterization allowed to remove antigens with overlapping distribution, leading us to propose an AML classification that was validated in a second AML cohort of 733 patients. We identified five AML subsets (MA to ME) based on the expression of seven antigens within four groups (CD13/CD33/CD117, CD7, CD35/CD36, CD15).-MA and MB-AML have exclusively myeloid features with seldom extramedullary disease and rare expression of lymphoid antigens. No cases of acute promyelocytic leukemia (APL) were observed within MB AML. MC AML have either myeloid or erythroblastic features. MD AML have more frequently high WBC counts than other subsets, which were related to the expression of CD35/CD36 and CD14 and to monoblastic differentiation. ME AML lack CD13, CD33, and CD117 but display signs of terminal myeloid differentiation. Specific independent prognostic factors were related to poor overall survival in each immunological subset: CD34+ (P<3 × 10−4) in MA AML, CD7+ in MB AML, non-APL cases (P<0.03) in MC AML, CD34+ (P<0.002) and CD14+ (P<0.03) in MD AML, CD14+ in ME AML (P<0.01). The inclusion of seven key markers in the immunophenotyping of AML allows a stratification into clinically relevant subsets with individual prognostic factors, which should be considered to define high-risk AML populations.

Introduction

The immunological analysis of a limited panel of surface or intra cellular antigens allows to assign most cases of acute leukemia to a specific lineage. Immunophenotyping of blast cells has thus become an elective and useful tool to characterize the myeloid or lymphoid origin of blast cell populations. The use of more extensive panels further allows us to identify either undifferentiated acute leukemias(1,2) or acute leukemia entities expressing simultaneously several lineage antigens, defining multiphenotypic acute leukemia.(1,3)

In lymphoid lineage-derived acute leukemia, extended immunophenotyping, moreover, allows to stratify distinct clinical and biological subsets, based on the hierarchy of antigen expression during the maturation of the normal cell counterparts of blast cells.(4,5) In acute non-lymphoblastic leukemia, several antigens (myeloperoxidase, CD13, CD33, CD117) have also been defined as hallmarks of myeloid differentiation and are specifically useful for the identification of morphologically undifferentiated AML cases or the detection of blasts of either erythroid (Glycophorin, CD36) or megakaryoblastic lineage (CD41, CD42, CD61). However, although the coexpression of numerous antigens provides insights in to the myeloid lineage commitment of blast cells at various levels of maturation, because of the wide heterogeneity of myeloid-related lineages and the numerous stages of differentiation in each of them, no relevant immunological classification of AML has been devised so far.

Here we report how we were able to define an immunological classification of AML, based on the pattern of expression of selected antigens, which does not overlap with the FAB classification and defines specific clinical and outcome patterns.

Patients and methods

The study was initiated in 1993 by the Groupe d'Etude Immunologique des Leucémies (GEIL), a multicenter group that collects data from over 40 hospitals in France and Belgium. Ten teams participated in this study. Patients eligible for the study had to meet the following criteria: established first diagnosis of de novo AML, excluding therapy-related AML and AML secondary to a previous diagnosis of myelodysplastic or myeloproliferative disease. The collection of a sufficient number of blast cells for proper immunophenotyping was also mandatory, the latter allowing lineage assignment and exclusion of BAL, and also the analysis of each of the following antigens: CD7, CD13, CD15, CD33, CD35, CD36, and CD117. FAB, clinical, and outcome data were also collected for each patient. The end point of the present analysis for patient outcome was January 1st, 2001.

Test and training series

The first 176 consecutively recruited patients eligible were analyzed to establish the immunological classification of AML and were considered as a test series. In a second part of the study, this classification was applied to an independent population of 733 AML patients, defined as the training series. The final description of the immunological subgroups identified and analysis of the response to therapy were performed on the whole series of 909 patients.

Treatment

Most patients received intravenous standard induction treatment including a combination of anthracyclin (daunorubicine 45–60 mg/m2/day for 3 days or idarubicine 8 mg/m2/day for 5 days) and cytosine arabinoside(100–200 mg/m2/day for 7 days) adapted according to age.

Patients who achieved a complete remission (CR) received a consolidation treatment including either an allograft transplantation if they were less than 45 years old and had an HLA-matched sibling donor, or two courses of chemotherapy including the same induction anthracyclin if they had no sibling donor or were older than 45 years of age. Patients older than 70 years received, after the first course of consolidation, a maintenance therapy during 24 months.

Patients with acute promyelocytic leukemia (APL) received, during induction treatment, oral all-trans-retinoic acid (ATRA) 45 mg/m2/day until they reached CR. The consolidation treatment was followed by an oral maintenance therapy during 2 years consisting of methotrexate 15 mg/m2/week associated to 6-mercaptopurine 90 mg/m2/day and ATRA 45 mg/m2/day 15 days every 3 months.

Some patients, because of their advanced age or their bad performance status, received only supportive care.

Immunological phenotyping

The immunophenotype was performed as previously described(6) on bone marrow blast cells collected at AML diagnosis. Flow cytometry was used in all centers on blast cells gated on their light scatter characteristics, using directly conjugated monoclonal antibodies for the following antigens: CD7, CD13, CD15, CD33, CD34, CD35, CD36, CD65, and CD117. Monoclonal antibodies against CD34 (HPCA2), CD35 (J3D3), CD36 (FA6152), CD65 (VIM2), and CD117 (95C3) were aliquoted and distributed by the GEIL to each of the participating laboratories. Monoclonal antibodies against CD7, CD15, CD13, and CD33 were those routinely used by each participating laboratory. Additional antigens were also analyzed when sufficient blast cells were collected, identifying lymphoid (CD2, CD4, CD5, CD10, CD19, CD20, CD24), or myeloid (CD11b, CD14, CD16, CD18, CD41, CD42, glycophorin A) antigens or with no lineage specificity (HLA DR, TdT).

Negative controls included omission and/or substitution of the monoclonal antibody by a mouse isotype matched nonrelevant immunoglobulin. A case was considered as positive when more than 20% of blast cells reacted with the monoclonal antibody, except for TdT (10% cutoff) according to the EGIL criteria.(1) The interlaboratory reproducibility of the group, tested on five different coded samples distributed to all laboratories reached 94%.

Statistical analysis

The relation between variables were analyzed by the Fisher exact test or Pearson's χ2 test for categorical variables and by the Mann–Witney U-test or the Student's T-test for continuous variables, depending on the sample size.

Cluster analysis was performed to determine which antigens among CD7, CD13, CD14, CD15, CD33, CD34, CD35, CD36, CD65, CD117, and HLA-DR best discriminated between the immunophenotypic groups of AML patients observed. The distance measured between each antigen was computed using the percentage of disagreement.(7) The linkage rule used the weighted pair group average in which the distances between clusters were calculated as the average distance between all pairs of antigens in two different clusters, weighted by the size of respective clusters.(8) The hierarchical tree of clusters was plotted using a standardized scale (distance of linkage/maximal distance × 100). The closest antigens, exhibiting a distance linkage less than 70%, were merged or removed according to their myeloid lineage weight to produce a final classification with four clusters.

Overall survival (OS) was calculated from the date of AML diagnosis to the date of death, the observations of patients alive at the last visit being censored. Disease-free survival (DFS) was measured from the date of CR achievement to the date of relapse or death of any cause. The observation of patients free of disease and alive were censored. OS and DFS were estimated by the Kaplan-Meier method and compared by the logrank test. Analysis of the relative value of the prognostic factors for treatment outcome were based on Cox's proportional hazards regression models for DFS and OS. The median follow-up duration for censored patients was 3.6 years in the test series and 2.1 years in the training series.

The statistical analysis was performed using the Statistica software, version 6.0 (Tulsa, OK, USA).

Results

Characteristics of patients in the test series and development of the classification

The characteristics of the first series of 176 patients are detailed in Table 1. The classification was established by a cluster analysis procedure according to the differential expression by the blast cells of myeloid or undifferentiated lineage antigens, respecting whenever possible, the known features of physiological myeloid differentiation from immature to mature myeloid lineage. The antigens tested were thus chosen according to their diagnosis value among pan-myeloid markers such as CD13, CD33, CD117 or according to their value at identifying myeloid differentiation subsets, such as CD15 and CD65 for granulocytic differentiation, CD14, CD35, and CD36 for the monocytic lineage and CD36 for the erythroid lineage. Three nonlineage antigens, CD7, CD34, and HLA-DR were also tested.

Table 1 Characteristics of patients in the test and training series

The distance between the distribution of each pair or group of antigens was assessed and the classification was progressively simplified by a forward stepwise elimination of overlapping antigens (Figure 1). The pan-myeloid antigens CD13, CD33, and CD117 had a closely similar distribution and a wide expression since more than 95% of tested AML were positive for at least one of them. Because of their specific myeloid lineage diagnosis value,(1,9) they were finally analyzed simultaneously. The linkage of CD35 and CD36 was strong enough to amalgamate them in the same cluster, and CD14 was eliminated because of its too narrow expression. Among the granulocytic differentiation antigens studied, CD15 (86 positive cases) was preferred to CD65 (62 positive cases) because of its broader expression. Among nonlineage antigens, CD7 had the widest distance linkage with respect to myeloid antigens, compared to CD34 and HLA-DR. The definitive classification was finally based on the expression of 7 antigens clustered into four categories identifying five subsets of AML, namely MA, MB, MC, MD, and ME (Figures 1 and 2).

Figure 1
figure1

Distance linkage between 11 (a) and 7 (b) antigens expressed in 176 AML cases (test series).

Figure 2
figure2

Immunological classification of AML.

MA is defined by the sole positivity of at least one of the pan-myeloid antigens (CD13, CD33, CD117). MB is related to the additional positivity of CD7. MC is associated to the co-expression of pan-myeloid antigens and either CD35 or CD36 on blast cells whatever the CD7 expression. MD is characterized by the additional expression of CD15. Finally, ME includes AML, which express none of the pan-myeloid antigens.

Characteristics of the AML classification subsets

The clinical, cytologic, and immunophenotypic features of the five AML immunological classification subsets within the test and the training series were compared in order to assess the reproducibility of the classification.

The characteristics of the whole AML population regarding clinical and hematological parameters were very similar in the training and test series (Table 1). The frequency of antigens expression on AML blast cells of the training and the test series was very close as well, and the clustering method was applied to the training series population. The segregation of the various antigens was similar to those observed in the test series (Figure 3). The main differences appeared in the linkage distances observed either among pan-myeloid antigens or between CD15 and the CD35/CD36 cluster, which were shorter in the test than in the training series, thus strengthening and validating the choice of clusters used for the classification.

Figure 3
figure3

Distance linkage between the seven antigens of the AML classification in the 733 cases of the training series.

The main characteristics of MA to ME AML subsets were first established on the test series and confirmed on the larger training series. Since we did not observe any difference between the features of the immunological subsets analyzed of both series, we will report the AML subsets characteristics on the overall population of 909 patients (Table 2).

Table 2 Characteristics of AML patients of the whole population of 909 patients according to the immunological classification subsets

Hematological parameters are similar in the different subsets except for WBC, which are significantly higher in MB and MD AML patients than in patients belonging to other AML subgroups (P<0.004). Conversely, both MA and MB AML have significantly less frequent extramedullary disease (P<0.05).

MA subset:

The blasts of most of MA AML patients have a myeloid morphology (72%) and were predominantly classified as M1 in the FAB classification. With regard to differentiation antigens not involved in the immunological classification, MA AML have a significantly lower frequency expression of the myeloid antigens CD14 (P<10−5), CD16 (P=0.0002) and CD65 (P<10−5), also of the nonlineage antigens HLA-DR (P<10−5) and CD34 (P<0.05), than the other AML subsets (Table 2). Lymphoid lineage antigens were also seldom expressed in this subset.

MB subset:

MB AML represent the smallest group of AML expressing pan-myeloid antigens. Despite CD7 coexpression, MB AML do not usually express other T lymphoid lineage antigens such as CD2,-CD3, or CD5. Only four of the 23 MB AML cases (17%), compared to 36% in other AML subsets, were positive for CD4 (P=0.05). B lineage antigens were also usually absent. Although most of MB AML had myeloid cytological features, no APL was observed in this subset.

MC subset:

The cytological features of this group are mainly those of M1 and M2 AML (47%). Nine M6 AML also belonged to this immunophenotypic subgroup. CD7 was detected in 33% of MC AML without any difference between the clinical or hematological parameters of CD7-negative and -positive groups. Conversely, different biological AML properties were observed between the two groups since APL were only observed in the CD7- subgroup, and the expression of CD7 was related to a significantly more frequent expression of B lineage antigens (33% in CD7+ MC AML vs 12% in CD7- MC AML: P<0.004). No individual B lineage antigen was found to be specifically expressed in CD7+ MC AML.

MD subset:

MD AML represent 48% of the whole population. Their cytological features are heterogeneous, but M4 and M5 AML are significantly more frequent in the MD group than in the other subsets (41 vs 17%; P<10−5). Ten of the 24 (42%) acute erythroblastic leukemias (AEL) observed also belonged to this immunological subgroup. Significantly higher (P<0.03) median WBC counts are observed in MD AML patients compared to other AML subsets. High WBC count appears to be related to a more frequent organomegaly at presentation (P=0.01) and to CD35 or CD36 blast cell expression (P<0.007).

MD AML display a significantly more frequent expression of CD14 and CD65 than other subgroups (Table 2). Both antigens are preferentially detected in CD35+ or CD36+ AML cases since CD14 and CD65 were positive in 51 and 71% of cases, respectively, in the CD35+ or CD36+ subset, compared to 21% (P<10−5) and 55% (P<0.002), respectively, in the CD35-/CD36- MD AML population. CD14 positivity was also strongly related to the expression of CD11b, with 71% CD14+ MD AML cases expressing CD11b, compared to 41% in the CD14- MD AML subgroup (P<10−5). The expression of both CD14 and CD11b was related to high WBC counts, since 56% CD14+ and 62% CD11b+ MD AML patients had WBC >30 G/L at diagnosis compared to 36% CD14- (P=0.00007) and 44% CD11b- MD AML cases (P<0.002). In all, 88% of the CD35- or CD36- positive MD AML coexpressing CD14 and CD11b had monoblastic cytologic features.

AEL were also related in most cases (70%) to the expression of CD35 or CD36. However, although all the AEL were found to express CD36, within MC or ME subsets, four of 10 (40%) AEL did not express CD36 in the MD subset (P<0.03). CD71 and glycophorin A expression was detected in 83 and 70% of cases, respectively, the proportions being similar in MC and ME subsets.

CD35 - and CD36- negative MD AML expressed CD34 more frequently than MD AML expressing either CD35 or CD36 or both (51 vs 41%; P=0.03).

ME subset:

ME AML displayed heterogeneous cytological features (Table 2). The more frequently expressed antigen was myeloperoxidase (61%), and most of ME AML had an EGIL myeloid score higher than 2 (72%). Lymphoid lineage antigens were infrequently expressed. Two M7 AML expressed exclusively platelet-related antigens including CD41 and CD36. M6 AML expressed only glycophorin A and CD36. Five AML with monocytic differentiation expressed only CD15,-CD35, or CD36. All APL were positive for CD15 but did not express CD65. Three remaining ME AML with poor antigen myeloid differentiation had myeloperoxidase cytochemical positivity.

Clinical course of treated patients

The relevance of the immunological classification on outcome was assessed on the overall population of patients who received a curative treatment. In all, 165 patients (18%) who received only supportive care were excluded from this analysis. The proportion of cases excluded from the survival analysis was similar in the different immunological AML subsets. Patients who received as consolidation treatment either chemotherapy or allogenic transplantation were also well balanced in the various immunological AML subtypes.

Among the treated patients, 496 (66.7%) achieved CR and 218 (44%) had already relapsed. A total of 435 patients had died (58%) at a median time from diagnosis of 189 days. The median follow-up for alive patients was 28 months. The initial response to treatment and the probability of OS were not significantly different between the training and the test series.

In univariate analysis, age>60, WBC>30 G/L, non-APL, blast cell expression of CD7 or CD34 were shown to display adverse prognostic significance on both the response to treatment and the OS (Table 3). CD14 detection on blast cells did not influence achievement of CR, but was related to lower OS. The immunological classification had no direct impact on CR and OS probability. Conversely, the response duration estimated by the DFS was significantly shorter in MB AML compared to remaining AML subsets (P<0.04) (Table 4). DFS was also influenced by the age of the patient and the cytological AML subgroup (Table 3).

Table 3 Response to treatment according to six prognostic factors
Table 4 Response to treatment according to the immunological classification

In Cox multivariate analysis, the parameters influencing survival duration remained age>60 (P<10−6), CD34+ (P<0.00003), WBC>30 G/L (P<0.0003), non-APL (P<0.01), and age>60 (P<10−5), MB AML (P<0.04), and non-APL (P<0.04) were independent pejorative factors for DFS duration.

Immunophenotypic classification-dependent prognostic factors

The prognostic factors shown to influence outcome in the overall patients population had obviously not the same weight in each immunological AML subset, since, for instance, APL were not observed in MB AML, and MA AML never expressed CD7. We therefore examined the impact of these prognostic factors in each immunological AML subset (Table 5).

Table 5 Response to treatment and outcome of patients in each immunological AML subset according to identified prognostics factors

In univariate analysis, the response to treatment and probability of OS were related to the age of patients, and the cytological AML subtype in MA, MC, and MD AML (Table 5). WBC counts >30 G/L influenced also the achievement of CR in MC and MD AML and the probability of OS in MA, MC, and MD AML. In addition, CD34 expression on blast cells was related to a lower response rate, and shorter OS in MA and MD subsets (Figures 4a and 5b). CD34 expression influenced also the response duration in MA AML but not in MD AML (Figure 4b and Figure 5b). CD7 positivity was associated to poor response (P<0.002) and survival (P<0.02) in MD AML. CD14 expression was related to a lower CR rate in ME AML and a shorter survival duration in MD and ME AML (Figures 6 and 7). MB AML patients had a poor outcome with a 9% probability of 3 years OS. No factor was found to influence patient outcome in this subset.

Figure 4
figure4

OS (a) and DFS (b) of patients with MA AML according to the expression of CD34.

Figure 5
figure5

OS (a) and DFS (b) of patients with MD AML according to the expression of CD34.

Figure 6
figure6

OS of patients with MD AML according to the expression of CD14.

Figure 7
figure7

OS of patients with ME AML according to the expression of CD14.

Multivariate analysis was performed in MA, MC, and MD AML to determine the relative value of the several prognostic parameters associated with shorter OS in each of these subgroups.

In MA AML, the Cox model indicated that old age (P<3 × 10−5), CD34+ (P<3 × 10−4), and WBC>30 G/L (P=0.002) were independent factors pejoratively influencing the probability of OS.

In MC AML, old age (P<2 × 10−5) and non-APL (P<0.03) were independent pejorative predictive factors for survival.

In MD AML, multivariate analysis (p<10−6) showed that only age>60 (P<10−6), CD34+ (P<0.002), CD14+ (P<0.03), and WBC>30 G/L (P<0.05) remained independent prognosis factors for OS.

Altogether, these results show that the value on patient outcome of both immunophenotypic and nonimmunophenotypic prognosis criteria depends on the immunological differentiation of blast cells and therefore on the proposed immunological AML classification. Thus, we combined these classification-dependent prognostic factors to define, in each classification subgroup, a specific pattern of clinically relevant prognosis factors influencing the probability of OS (Figure 8).

Figure 8
figure8

Immunophenotypic classification-dependent prognostic parameters influencing pejoratively the overall survival duration.

Discussion

The present report demonstrates that the analysis of seven differentiation antigens, namely CD13,-CD33,-CD117,-CD7,-CD35,-CD36,-CD15, on AML blast cells allows to stratify AML with a high reproducibility, in five immunological subtypes, each related to specific myeloid differentiation stages and prognostic factors.

The antigens chosen for this classification are sufficient since all AML cases expressed at least one of them. The expression of the pan-myeloid antigens CD13,-CD33, and CD117 had a very close distribution in the population studied. The combination of these three markers is highly sensitive for AML diagnosis, 95% of cases being positive for at least one of them, and appears to be slightly higher than the unique detection of the cytoplasmic myeloperoxidase antigen.(10) Moreover, adding the search for MPO antigen positivity as a lineage assignment marker, more than 98% of the cases reported here could be identified as AML. Conversely, the negativity of CD13,-CD33, and CD117 defined a small group of acute leukemia that remain of myeloid origin in most cases with expression of MPO (61%) or CD65 (35%). This AML group does not usually display immaturity features, since it has a low frequency of CD7 and CD34 positivity and few cytologically undifferentiated cases were observed among ME. These AML cases rather appear to be derived from committed progenitors. Interestingly, AML cases that did not express any of the major myeloid antigens, including MPO and CD65, were all derived from the erythroblastic or megakaryoblastic lineage.

According to the proposed immunological classification, AML blast cells, regardless of the FAB classification,(11) can be usefully and simply characterized by the expression of surface antigens and subsequently by their immunological differentiation. The combined analysis of CD35, CD36, and CD15 was able to provide insights about the myeloid sublineage of most differentiated AML cases. CD35 and CD36 are usually detected on many normal myeloid lineage cells including erythroid precursors and monocytes.(12,13) CD36 analysis was sensitive to detect erythroblastic lineage-derived AML (82%), and the only four M6 cases that did not express CD36 belonged to the MD subset. The coexpression of CD35-or-CD36 with CD15 identifies most of the AML with a monocytic component, which also usually express CD14 and CD11b. Therefore, CD15, which has been reported to be a late differentiation antigen,(14) is also strongly expressed in monoblastic AML populations. Conversely, CD15-positive AML lacking CD35 and CD36 appeared to be mainly of granulocytic lineage.

In all, 53% of AML cytologically defined as myeloid (M1–M3) were characterized by early myeloid differentiation (CD13,-CD33, or CD117 positivity), minimal terminal granulocytic differentiation without expression of CD15,-CD35, or CD36. They were classified as MA or MB according to the expression of CD7. The distance linkage between CD7 and the cluster CD13/CD33/CD117 was larger than that observed between CD34 and the pan-myeloid antigens. Moreover, the frequency of CD7 expression decreased along granulomonocytic AML maturation from MB to ME (2), while the frequency of CD34 positivity was quite similar in all these AML subsets. This indicates that, as in normal myeloid differentiation,(15,16) CD7 is likely to be expressed in a small compartment of immature cells, while CD34 is expressed on a larger population of both immature and committed myeloid cells. Altogether these data led us to select CD7 rather than CD34 as an immaturity marker to establish the classification. They also suggest that MB AML cases, coexpressing CD7 and only immature pan-myeloid antigens, without evidence of granulomonocytic terminal differentiation, could be derived from an immature myeloid precursor found in a subset of bone marrow and fetal liver myeloid progenitors.(15,16,17) Consistent with this hypothesis, the percentage of CD7+ AML blast cells was significantly higher in the MB AML subset compared to other AML subsets (P<0.05; data not shown).

It has been suggested that the immunophenotype of the blastic cell population may depend on the differentiation ability of the leukemia-initiating cell.(18) Subsequently, the biological significance of the expression of a given differentiation antigen will vary depending on the AML immunological subset considered, yielding variable prognostic values. This has important bearings as the presence of a given marker on blast cells should no longer be considered individually, but should be replaced in the context of myeloid differentiation according to the immunological classification of AML proposed here. This report highlights specifically the fact that the prognostic value of an individual antigen's expression depends on the immunological differentiation stage of the leukemic cells. The present study demonstrated that antigens whose expression had already been shown as a potential prognostic factor (CD34,-CD7,-CD14)(19,20,21,22,23,24,25,26,27,28) were indeed related to outcome in the overall population. More interestingly, their prognostic value, which could be marginal in the overall population, became strongly significant in specific immunological AML subsets while it retained no significance in other subsets. The prognostic influence of CD7 positivity thus appears to be restricted to the MB subset. This had already been pointed out indirectly by reports analyzing infrequent AML cases expressing either CD13 or CD33 and CD7 without other T or myeloid lineage antigen.(19,29) Conversely, the influence of CD7 expression on CR achievement in the overall AML population was not related, in multivariate analysis, to a shorter DFS or OS of CD7+ AML patients probably because of the overlapping prognostic influence of APL. The CD7 negativity of APL(6) had not previously been accounted for in studies reporting a poor survival of CD7+AML.(20,25) Yet antigens never expressed by some specific progenitor-derived AML blast cells could obviously not have any prognostic value in these AML subsets. CD34 expression was related to poor outcome in 70% of AML of the MA and MD AML subsets. The frequency of CD34 expression was similar in these two subsets as compared to other immunological AML subsets, and was not related to specific FAB subgroups, which indicates that MA and MD indeed define specific entities. Conversely, CD14, more frequently expressed in AML with a monocytic component,(21,22,23,30) appeared related to a poor outcome only in MD and ME subsets. The prognostic value of CD14 expression was independent of the FAB classification in the MD subset and had already been reported in such FAB subsets as M3(22) or M0.(2) The imbalanced prognostic weight of CD7,-CD14, or CD34 expression in different immunological settings could explain the discrepancies previously observed when analyzing individually the prognostic value of these antigens expression.(19,20,21,24,25,26,27,28,30,31,32,33,34,35,36,37,38,39)

The relation between the proposed immunological classification of AML and cytogenetic subsets remain to be determined. We previously demonstrated that the expression of a single given antigen on blast cells was poorly related to karyotype, and whether some immunophenotypic patterns were strongly predictive of cytogenetic entities, numerous immunophenotypic variants were observed among AML subtypes with recurrent cytogenetic anomalies.(6) This AML classification could help to identify some of these clinically relevant variants. It is particularly interesting to note that APL cases displaying an immature phenotype (MA) have a poorer clinical outcome than that of patients with more mature APL (MC to ME): MA APL patients achieve less frequently CR (82 vs than 97%) (P=0.04) and have a worse 3-year OS probability (54 vs 68% although statistical significance was not reached at the time of testing, P=0.09), compared to mature APL patients (data not shown). Further analyses will be needed to confirm these data on a larger number of APL cases and to determine the value of this immunophenotypic classification to stratify AML populations with either other recurrent cytogenetic anomalies or normal karyotypes.

From a practical point of view, the seven markers allowing to apply this classification should be completed by the investigation of the MPO antigen, in order to confirm in all cases that blast cells belong to the myeloid lineage, and by that of CD14-and-CD34 for prognostic purposes. Megakaryocytic markers such as CD41 or CD61 should also be incorporated into the immunophenotyping panel, as well as CD65-and-CD11b for a more complete identification of the differentiation stage.

In summary, the immunological classification of AML that we propose, validated on a large cohort of patients, allows to easily identify five clinically relevant AML subsets with specific differentiation characteristics. In each classification subset, high-risk AML patients can be identified, which should be eligible for alternative therapeutic strategies.

References

  1. 1

    Bene MC, Castoldi G, Knapp W, Ludwig WD, Matutes E, Orfao A et al. Proposals for the immunological classification of acute leukemias. European Group for the Immunological Characterization of Leukemias (EGIL). Leukemia 1995; 9: 1783–1786.

    CAS  Google Scholar 

  2. 2

    Bene MC, Bernier M, Casasnovas RO, Castoldi G, Doekharan D, van der Holt B et al. Acute myeloid leukaemia M0: haematological, immunophenotypic and cytogenetic characteristics and their prognostic significance: an analysis in 241 patients. Br J Haematol 2001; 113: 737–745.

    CAS  Article  Google Scholar 

  3. 3

    Matutes E, Morilla R, Farahat N, Carbonell F, Swansbury J, Dyer M et al. Definition of acute biphenotypic leukemia. Haematologica 1997; 82: 64–66.

    CAS  PubMed  Google Scholar 

  4. 4

    Garand R, Vannier JP, Bene MC, Faure G, Favre M, Bernard A . Comparison of outcome, clinical, laboratory, and immunological features in 164 children and adults with T-ALL. The Groupe d'Etude Immunologique des Leucemies. Leukemia 1990; 4: 739–744.

    CAS  PubMed  Google Scholar 

  5. 5

    Garand R, Voisin S, Papin S, Praloran V, Lenormand B, Favre M et al. Characteristics of pro-T ALL subgroups: comparison with late T-ALL. The Groupe d'Etude Immunologique des Leucémies. Leukemia 1993; 7: 161–167.

    CAS  PubMed  Google Scholar 

  6. 6

    Casasnovas RO, Campos L, Mugneret F, Charrin C, Béné MC, Garand R et al. Immunophenotypic patterns and cytogenetic anomalies in acute non-lymphoblastic leukemia subtypes: a prospective study of 432 patients. Leukemia 1998; 12: 34–43.

    CAS  Article  Google Scholar 

  7. 7

    Hartigan JA . Clustering algorithms. New York: Wiley, 1975.

    Google Scholar 

  8. 8

    Sneath PHA, Sokal RR . Numerical Taxonomy. San Francisco: WH Freeman & Co., 1973.

    Google Scholar 

  9. 9

    Bene MC, Bernier M, Casasnovas RO, Castoldi G, Knapp W, Lanza F et al. The reliability and specificity of c-kit for the diagnosis of acute myeloid leukemias and undifferentiated leukemias. The European Group for the Immunological Classification of Leukemias (EGIL). Blood 1998; 92: 596–599.

    CAS  PubMed  Google Scholar 

  10. 10

    Buccheri V, Shetty V, Yoshida N, Morilla R, Matutes E, Catovsky D . The role of an anti-myeloperoxidase antibody in the diagnosis and classification of acute leukaemia: a comparison with light and electron microscopy cytochemistry. Br J Haematol 1992; 80: 62–68.

    CAS  Article  Google Scholar 

  11. 11

    Bennett JM, Catovsky D, Daniel MT, Flandrin G, Galton DA, Gralnick HR et al. Proposals for the classification of the acute leukaemias. French-American-British (FAB) co-operative group. Br J Haematol 1976; 33: 451–458.

    CAS  Article  Google Scholar 

  12. 12

    Huh HY, Pearce SF, Yesner LM, Schindler JL, Silverstein RL . Regulated expression of CD36 during monocyte-to-macrophage differentiation: potential role of CD36 in foam cell formation. Blood 1996; 87: 2020–2028.

    CAS  Google Scholar 

  13. 13

    van Schravendijk MR, Handunnetti SM, Barnwell JW, Howard RJ . Normal human erythrocytes express CD36, an adhesion molecule of monocytes, platelets, and endothelial cells. Blood 1992; 80: 2105–2114.

    CAS  PubMed  Google Scholar 

  14. 14

    Lo SK, Golenbock DT, Sass PM, Maskati A, Xu H, Silverstein RL . Engagement of the Lewis X antigen (CD15) results in monocyte activation. Blood 1997; 89: 307–314.

    CAS  PubMed  Google Scholar 

  15. 15

    Tien HF, Chou CC, Wang CH, Chang CH, Hsing CC . Putative normal counterparts of leukaemic cells from CD7-positive acute myeloid leukaemia can be demonstrated in human haemopoietic tissues. Br J Haematol 1996; 94: 501–506.

    CAS  PubMed  Google Scholar 

  16. 16

    Chabannon C, Wood P, Torok-Storb B . Expression of CD7 on normal human myeloid progenitors. J Immunol 1992; 149: 2110–2113.

    CAS  PubMed  Google Scholar 

  17. 17

    Barcena A, Muench MO, Galy AH, Cupp J, Roncarolo MG, Phillips JH et al. Phenotypic and functional analysis of T-cell precursors in the human fetal liver and thymus: CD7 expression in the early stages of T- and myeloid-cell development. Blood 1993; 82: 3401–3414.

    CAS  PubMed  Google Scholar 

  18. 18

    Bonnet D, Dick JE . Human acute myeloid leukemia is organized as a hierarchy that originates from a primitive hematopoietic cell. Nat Med 1997; 3: 730–737.

    CAS  Article  Google Scholar 

  19. 19

    Jensen AW, Hokland M, Jorgensen H, Justesen J, Ellegaard J, Hokland P . Solitary expression of CD7 among T-cell antigens in acute myeloid leukemia: identification of a group of patients with similar T-cell receptor beta and delta rearrangements and course of disease suggestive of poor prognosis. Blood 1991; 78: 1292–1300.

    CAS  PubMed  Google Scholar 

  20. 20

    Venditti A, Del Poeta G, Buccisano F, Tamburini A, Cox-Froncillo MC, Aronica G et al. Prognostic relevance of the expression of Tdt and CD7 in 335 cases of acute myeloid leukemia. Leukemia 1998; 12: 1056–1063.

    CAS  Article  Google Scholar 

  21. 21

    Solary E, Casasnovas RO, Campos L, Bene MC, Faure G, Maingon P et al. Surface markers in adult acute myeloblastic leukemia: correlation of CD19+, CD34+ and CD14+/DR--phenotypes with shorter survival. Groupe d'Etude Immunologique des Leucemies (GEIL). Leukemia 1992; 6: 393–399.

    CAS  PubMed  Google Scholar 

  22. 22

    Fergedal M, Astrom M, Tidefelt U, Karlsson MG . Differences in CD14 and alpha-naphthyl acetate esterase positivity and relation to prognosis in AML. Leuk Res 1998; 22: 25–30.

    CAS  Article  Google Scholar 

  23. 23

    Campos L, Guyotat D, Archimbaud E, Devaux Y, Treille D, Larese A et al. Surface marker expression in adult acute myeloid leukaemia: correlations with initial characteristics, morphology and response to therapy. Br J Haematol 1989; 72: 161–166.

    CAS  Article  Google Scholar 

  24. 24

    Bradstock K, Matthews J, Benson E, Page F, Bishop J . Prognostic value of immunophenotyping in acute myeloid leukemia. Australian Leukaemia Study Group. Blood 1994; 84: 1220–1225.

    CAS  PubMed  Google Scholar 

  25. 25

    Del Poeta G, Stasi R, Venditti A, Cox C, Aronica G, Masi M et al. CD7 expression in acute myeloid leukemia. Leuk Lymphoma 1995; 17: 111–119.

    CAS  Article  Google Scholar 

  26. 26

    Del Poeta G, Stasi R, Venditti A, Suppo G, Aronica G, Bruno A et al. Prognostic value of cell marker analysis in de novo acute myeloid leukemia. Leukemia 1994; 8: 388–394.

    CAS  Google Scholar 

  27. 27

    Lee EJ, Yang J, Leavitt RD, Testa JR, Civin CI, Forrest A et al. The significance of CD34 and TdT determinations in patients with untreated de novo acute myeloid leukemia. Leukemia 1992; 6: 1203–1209.

    CAS  PubMed  Google Scholar 

  28. 28

    Geller RB, Zahurak M, Hurwitz CA, Burke PJ, Karp JE, Piantadosi S et al. Prognostic importance of immunophenotyping in adults with acute myelocytic leukaemia: the significance of the stem-cell glycoprotein CD34 (My10). Br J Haematol 1990; 76: 340–347.

    CAS  Article  Google Scholar 

  29. 29

    Bassan R, Biondi A, Benvestito S, Tini ML, Abbate M, Viero P, Barbui T et al. Acute undifferentiated leukemia with CD7+ and CD13+ immunophenotype. Lack of molecular lineage commitment and association with poor prognostic features. Cancer 1992; 69: 396–404.

    CAS  Article  Google Scholar 

  30. 30

    Merle-Beral H, Nguyen Cong Duc L, Leblond V, Boucheix C, Michel A et al. Diagnostic and prognostic significance of myelomonocytic cell surface antigens in acute myeloid leukaemia. Br J Haematol 1989; 73: 323–330.

    CAS  Article  Google Scholar 

  31. 31

    Schwarzinger I, Valent P, Koller U, Marosi C, Schneider B, Haas O Prognostic significance of surface marker expression on blasts of patients with de novo acute myeloblastic leukemia. J Clin Oncol 1990; 8: 423–430.

    CAS  Article  Google Scholar 

  32. 32

    Miwa H, Nakase K, Kita K . Biological characteristics of CD7(+) acute leukemia. Leuk Lymphoma 1996; 21: 239–244.

    CAS  PubMed  Google Scholar 

  33. 33

    Saxena A, Sheridan DP, Card RT, McPeek AM, Mewdell CC, Skinnider LF . Biologic and clinical significance of CD7 expression in acute myeloid leukemia. Am J Hematol 1998; 58: 278–284.

    CAS  Article  Google Scholar 

  34. 34

    Kornblau SM, Thall P, Huh YO, Estey E, Andreeff M . Analysis of CD7 expression in acute myelogenous leukemia: martingale residual plots combined with ‘optimal’ cutpoint analysis reveals absence of prognostic significance. Leukemia 1995; 9: 1735–1741.

    CAS  PubMed  Google Scholar 

  35. 35

    Reuss Borst MA, Bühring HJ, Schmidt H, Müller CA . AML: immunophenotypic heterogeneity and prognostic significance of c-kit expression. Leukemia 1994; 8: 258–263.

    CAS  PubMed  Google Scholar 

  36. 36

    Kanda Y, Hamaki T, Yamamoto R, Chizuka A, Suguro M, Matsuyama T et al. The clinical significance of CD34 expression in response to therapy of patients with acute myeloid leukemia: an overview of 2483 patients from 22 studies. Cancer 2000; 88: 2529–2533.

    CAS  Article  Google Scholar 

  37. 37

    Kyoda K, Nakamura S, Hattori N, Takeshima M, Nakamura K, Kaya H et al. Lack of prognostic significance of CD34 expression in adult AML when FAB M0 and M3 are excluded. Am J Hematol 1998; 57: 265–266.

    CAS  Article  Google Scholar 

  38. 38

    Lanza F, Rigolin GM, Moretti S, Latorraca A, Castoldi G . Prognostic value of immunophenotypic characteristics of blast cells in acute myeloid leukemia. Leuk Lymphoma 1994; 13(Suppl 1): 81–85.

    Article  Google Scholar 

  39. 39

    Ciolli S, Leoni F, Caporale R, Pascarella A, Salti F, Rossi-Ferrini P . CD34 expression fails to predict the outcome in adult acute myeloid leukemia. Haematologica 1993; 78: 151–155.

    CAS  PubMed  Google Scholar 

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Correspondence to R O Casasnovas.

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This work was supported by a grant from the CHU of Dijon and by the GOELAMS

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Casasnovas, R., Slimane, F., Garand, R. et al. Immunological classification of acute myeloblastic leukemias: relevance to patient outcome. Leukemia 17, 515–527 (2003). https://doi.org/10.1038/sj.leu.2402821

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Keywords

  • AML
  • immunophenotyping
  • classification
  • prognosis

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