SEARCH

SEARCH BY CITATION

Keywords:

  • flow cytometry;
  • aberrant antigen expression;
  • acute myeloid leukaemia;
  • myelodysplastic syndromes;
  • minimal residual disease

Summary

  1. Top of page
  2. Summary
  3. Aberrancies at diagnosis in AML
  4. Acute leukaemias of ambiguous lineage
  5. Aberrancies and prognosis in AML
  6. Minimal Residual Disease (MRD) detection
  7. Clinical aspects of MRD detection in AML
  8. Current status and future improvements of MRD assessment
  9. Immunopenotypical aberrancies in MDS
  10. Aberrancies in the immature and mature myeloid/granulocytic lineage
  11. Aberrancies in the monocytic lineage
  12. Erythroid and megakaryocytic lineage
  13. FCM in MDS: role in diagnosis
  14. FCM in MDS: role in prognosis
  15. Prediction of response to therapy by FCM in low risk MDS
  16. Conclusions
  17. References

This article reviews the use of aberrant antigen expression detected by flow cytometry in the diagnosis and clinical handling of acute myeloid leukaemia (AML) and the myelodysplastic syndromes (MDS). Such aberrancies offer a valuable tool for the proper classification of these myeloid malignancies according the World Health Organization 2008 classification. Aberrant antigen expression by flow cytometry is also important for prognostification. This review supports the view, that minimal residual disease detection methods that make use of such aberrancies should be part of the routine management of AML patients to guide therapy, but also suggests the introduction of flow cytometry in MDS for diagnosis and treatment decisions in the near future.

The use of aberrant antigen expression detected by flow cytometry of acute myeloid leukaemia (AML) and myelodysplastic syndromes (MDS) is increasingly instrumental for diagnosis and clinical handling. Firstly, such aberrancies offer a valuable tool for the proper classification of these myeloid neoplasms according to the latest World Health Organization (WHO) classification (Swerdlow et al, 2008). This revised classification uses a combination of clinical, morphological, immunophenotypic and genetic features to define disease entities. Although still to be proven, the aberrant antigen expression by flow cytometry could also be of great clinical value in providing predictive biomarkers. This review supports the view that minimal residual disease (MRD) detection that makes use of such aberrancies should be part of the routine management of AML patients to guide therapy. Although for MDS the value of aberrant antigen expression is less well-established, its role in the near future in both for proper diagnosis and as a guide for treatment decisions seems obvious. The present article reviews the literature on aberrant antigen expression in AML and MDS with respect to diagnosis and prognosis. In addition, in AML the role of aberrancies in MRD detection and its putative consequences for clinical decision-making will be emphasized.

Aberrancies at diagnosis in AML

  1. Top of page
  2. Summary
  3. Aberrancies at diagnosis in AML
  4. Acute leukaemias of ambiguous lineage
  5. Aberrancies and prognosis in AML
  6. Minimal Residual Disease (MRD) detection
  7. Clinical aspects of MRD detection in AML
  8. Current status and future improvements of MRD assessment
  9. Immunopenotypical aberrancies in MDS
  10. Aberrancies in the immature and mature myeloid/granulocytic lineage
  11. Aberrancies in the monocytic lineage
  12. Erythroid and megakaryocytic lineage
  13. FCM in MDS: role in diagnosis
  14. FCM in MDS: role in prognosis
  15. Prediction of response to therapy by FCM in low risk MDS
  16. Conclusions
  17. References

Flow cytometric immunophenotyping (FCM) is an indispensable tool for quantitative and qualitative evaluation of antigen expression of haematopoietic cells (Civin & Loken, 1987; Nakahata & Okumura, 1994; Elghetany, 2002). The WHO 2008 classification of myeloid neoplasms (Swerdlow et al, 2008) uses morphology, immunophenotype, genetics and clinical features to define clinically significant disease entities. From a diagnostic and therapeutic point of view, distinction between AML and acute lymphoblastic leukaemia (ALL) is extremely important and FCM is very instrumental in this. Malignant blasts often have an abnormal phenotype that allows distinction from normal immature cells (Al-Mawali et al, 2008). Abnormalities include expression on myeloid blasts of markers usually not present on cells of that particular lineage, e.g. lymphoid markers, such as CD7, CD19 and CD56, or deviations of the normal differentiation and maturation pathway (asynchronous expression: see also the section on MDS) (Campana, 2003; Craig & Foon, 2008). Aberrancies also include abnormal levels of expression of antigens normally present in a certain lineage.

Characteristic immunophenotypes have been associated with the presence of recurrent genetic abnormalities in AML (Bagg, 2007) (summarized in Table I):

Table I.   Correlation between genotype and immunophenotype.
AML typeCD34Aberrant expressionPositive/strong expressionWeak/absent expression
AML with t(8;21)+CD19, cCD79a, CD56HLA-DR, MPO, CD13CD33
AML inv(16) or t(16;16)+CD2CD117 
APL with t(15;17)CD56 HLA-DR, CD15, CD65
AML with mutated NPM1 CD13, CD117, CD123HLA-DR
AML with mutated CEBPA+CD7CD13, CD33, HLA-DR, CD15CD14
  • 1
    AML with t(8;21) shows strong expression of CD34, HLA-DR, MPO and CD13 and a weak expression of CD33. Aberrant expression of lymphoid markers CD19 and cCD79a is frequently observed as well as CD56, which is associated with poor prognosis in this otherwise good prognosis AML type (Khoury et al, 2003).
  • 2
    AML inv(16) or t(16;16) can be distinguished by the presence of different blast populations. On the one hand there are immature blasts with a high CD34 and CD117 expression and on the other hand populations with granulocytic and monocytic differentiation often accompanied by maturation asynchrony. Co-expression of CD2 is frequently observed, although not specific for this type of AML (Dunphy, 1999; Medeiros et al, 2010).
  • 3
    APL with t(15;17) is characterized by very low or absent expression of CD34 and HLA-DR. CD117 is mostly positive with a strong expression of CD33 and heterogeneous expression of CD13 while CD15 and CD65 (granulocytic markers) are usually not present. CD56 is present in roughly 20% of patients and is, as in AML t(8;21), associated with poor prognosis. (Paietta et al, 2004)
  • 4
    AML with mutated NPM1 accounts for approximately one-third of adult AML and, in absence of FLT3-internal tandem duplications (ITD), is associated with a good prognosis (Falini et al, 2005). Most NPM1+ AML are CD34 negative and have strong expression of CD33. In addition, these are CD13, CD117, CD123 and the stem cell marker CD110 positive, as well as HLA-DR negative in 50% of the cases (Nomdedeu et al, 2010). Recently, a subgroup of AML with NPM1 type A mutation were reported to have a characteristic pattern: most were AML with limited differentiation, lack of expression of CD34, CD133 and HLA-DR, strong expression of MPO and CD33 and weak expression of CD64 and CD117 (Kern et al, 2009).
  • 5
    AML with mutated CEBPA. In particular, the biallelically mutated CEBPA AML cases are associated with the immunophenotype CD34+, CD13+, CD33+, HLA-DR+, CD14, CD15+ and CD7+ and have a good prognosis (Haferlach et al, 2009).

Because the described immunophenotypes are characteristic, but not specific for the various AML types, they have to be considered of additional value.

Acute leukaemias of ambiguous lineage

  1. Top of page
  2. Summary
  3. Aberrancies at diagnosis in AML
  4. Acute leukaemias of ambiguous lineage
  5. Aberrancies and prognosis in AML
  6. Minimal Residual Disease (MRD) detection
  7. Clinical aspects of MRD detection in AML
  8. Current status and future improvements of MRD assessment
  9. Immunopenotypical aberrancies in MDS
  10. Aberrancies in the immature and mature myeloid/granulocytic lineage
  11. Aberrancies in the monocytic lineage
  12. Erythroid and megakaryocytic lineage
  13. FCM in MDS: role in diagnosis
  14. FCM in MDS: role in prognosis
  15. Prediction of response to therapy by FCM in low risk MDS
  16. Conclusions
  17. References

In <5% of acute leukaemias it is not clear whether the immature cells are derived from either myeloid or lymphoid precursors and therefore these are classified as acute leukaemia (AL) of ambiguous lineage. These include acute undifferentiated leukaemia (AUL), which shows no expression of lineage-specific antigens, and mixed phenotype acute leukaemia (MPAL) that expresses antigens of more than one lineage. MPAL can contain either distinct blast populations with expression of different lineage markers (previously referred to as bilineal AL) (Hanson et al, 1993) or blasts that co-express antigens of more than one lineage [previously referred to as biphenotypic acute leukaemias (BAL)] (Legrand et al, 1998). Single expression of cytoplasmic myeloperoxidase (cytMPO) or CD3 (surface or intracellular) is now regarded as sufficient to determine whether blasts belong to the myeloid, or T-cell lineage respectively: the B cell lineage is defined as being CD19+ and positive for either one or two of the markers cytCD79a, CD10 and cytCD22. Based on these criteria, which clearly differ from the European Group for the Immunological characterization of Leukaemias (EGIL; Bénéet al, 1995) and WHO2001 criteria, many cases that have previously been reported as BAL, in fact represent ALL or AML with aberrant cross-lineage expression (Vardiman et al, 2009). In a series of 517 AML patients, 5·8% were classified as BAL according to EGIL criteria, whereas in WHO2008 only 1·5% would have been classified as MPAL (van den Ancker et al, 2010). The majority of all AL with combined myeloid and B or T characteristics are thus reclassified as ALL or AML in the new WHO 2008 classification, which has a major impact on therapeutic decision-making.

Aberrancies and prognosis in AML

  1. Top of page
  2. Summary
  3. Aberrancies at diagnosis in AML
  4. Acute leukaemias of ambiguous lineage
  5. Aberrancies and prognosis in AML
  6. Minimal Residual Disease (MRD) detection
  7. Clinical aspects of MRD detection in AML
  8. Current status and future improvements of MRD assessment
  9. Immunopenotypical aberrancies in MDS
  10. Aberrancies in the immature and mature myeloid/granulocytic lineage
  11. Aberrancies in the monocytic lineage
  12. Erythroid and megakaryocytic lineage
  13. FCM in MDS: role in diagnosis
  14. FCM in MDS: role in prognosis
  15. Prediction of response to therapy by FCM in low risk MDS
  16. Conclusions
  17. References

Immunophenotypic aberrancies have been explored to predict treatment outcome in AML. The results are not unequivocal: some studies reported an adverse prognostic association with a multitude of markers (cytTdT, CD7, CD9, CD11b, CD13, CD14, CD33, CD34 and CD56), while others failed to show any association between immunophenotype and treatment outcome (Lee et al, 1992; Raspadori et al, 1997; Venditti et al, 1998; Ogata et al, 2001; Béné, 2005). Some antigens deserve further attention because their expression is related to survival.

CD34

CD34 expression has been associated with poor prognosis, although no conclusive evidence for this was obtained in a large meta-analysis of over 2000 patients (Kanda et al, 2000). Given that many NPM1 mutated AML cases have very low or absent CD34 expression (Falini et al, 2005; Taussig et al, 2010), while NPM1 mutated patients make up a substantial portion of diagnosed AML cases (Falini et al, 2005), we may define a CD34 negative subgroup with relatively good prognosis amongst a majority of normal prognosis CD34 positive patients. Given that the cut-off levels for positivity usually were rather high (10–20%)(Kanda et al, 2000) while NPM1 cases usually were <5% CD34, this has probably obscured the prognostic significance of CD34 expression.

CD56

Neural adhesion molecule CD56, which together with CD3 defines natural killer cells, is not present on normal myeloid cells. If expressed on myeloblasts it is a predictor of lower complete response rate and overall survival (OS) (Raspadori et al, 2001, 2002). CD56 expression in AML has been associated with extramedullary leukaemia and, when expressed in AML with t(8;21), correlates with reduced disease-free survival (DFS) and OS, including those patients who underwent transplantation (Yang et al, 2007). It thereby identifies a poor prognosis subgroup within an otherwise good prognostic patient population.

CD7

CD7 is often aberrantly expressed in AML and, in most publications, associated with adverse outcome. In 256 de novo adult AML cases, the proportion of CD7+ cases increased stepwise, from cases with favourable cytogenetics to cases with intermediate and unfavourable cytogenetics. CD7-positivity adversely affected survival only in the cases with unfavourable cytogenetics (P < 0·03). However in a recent study in normal karyotype AML, CD7 was expressed in 37% of cases, was associated with shorter DFS and, in multivariate analysis, it was an independent risk factor (Chang et al, 2007). In the particular case of CEBPA, this mutation is also found with CD7 expression and thus defines a sub-group of CD7 positive good prognosis patients in poor prognosis CD7+ AML.

CD7+ CD56+ AML is often referred to as ‘myeloid/NK cell precursor acute leukaemia’ and has distinct clinico-pathological features (Tiftik et al, 2004; Suzuki et al, 2010). They present most often as French-American-British subtype M0 with extramedullary involvement and lymphadenopathy with or without a mediastinal mass and have an extremely poor response on therapy. Although CD7+ CD56+ AML other than AML-M0 have a different clinical picture, the prognosis is as poor (Suzuki et al, 2010).

CD25

Interleukin-2 receptor alpha-chain expression was observed in 41 of 65 newly diagnosed AML (Terwijn et al, 2009). In a multivariate analysis CD25 expression proved to be an independent adverse predictor for OS and relapse-free survival (RFS). High CD25 expression combined with FLT3-ITD positivity resulted in the poorest OS and RFS. CD25 expression remained of prognostic value within the intermediate cytogenetic risk group. In addition, after the first cycle of chemotherapy, a significantly higher MRD frequency was found in patients with high CD25 expression at diagnosis (Terwijn et al, 2009). Interestingly, the markers discussed above are also present on AML stem cells (van Rhenen et al, 2007; Saito et al, 2010), which makes these markers of interest for targeting the leukaemia stem cell.

As shown, several aberrant immunophenotypes parallel the presence of genetic aberrations. Partly due to inconsistent and contradictory findings, but also due to their strong association with cytogenetics, none of these markers/aberrant combinations have been included in the standard set of prognostic factors at diagnosis (Basso et al, 2007). Nevertheless, such associations may now serve as a guide to search for unknown genetic changes in AML cases with known immunophenotype aberrancies. It is unknown whether the aberrant immunophenotypes are just bystander effect or offer a functional contribution to the observed poor or favourable prognosis.

In conclusion, FCM is an important and indispensable tool for the appropriate WHO2008 diagnosis. The value of aberrancies for prognosis is less apparent because numerous reports have appeared with often conflicting conclusions. Cytogenetic- and molecular-based risk classification have resulted in much more consistent predictors of treatment outcome and are now generally applied by all major AML trial groups, with minor differences only.

Minimal Residual Disease (MRD) detection

  1. Top of page
  2. Summary
  3. Aberrancies at diagnosis in AML
  4. Acute leukaemias of ambiguous lineage
  5. Aberrancies and prognosis in AML
  6. Minimal Residual Disease (MRD) detection
  7. Clinical aspects of MRD detection in AML
  8. Current status and future improvements of MRD assessment
  9. Immunopenotypical aberrancies in MDS
  10. Aberrancies in the immature and mature myeloid/granulocytic lineage
  11. Aberrancies in the monocytic lineage
  12. Erythroid and megakaryocytic lineage
  13. FCM in MDS: role in diagnosis
  14. FCM in MDS: role in prognosis
  15. Prediction of response to therapy by FCM in low risk MDS
  16. Conclusions
  17. References

In contrast with a role as a prognostic marker, immunophenotypical aberrancies have been convincingly shown to be useful for MRD detection and quantification with the aim of providing prognostic information (Kern et al, 2008; Buccisano et al, 2009). Immunophenotypical analysis of residual leukaemic cells using FCM is an attractive approach for MRD detection: it is sensitive, rapid, quantitative, relatively cheap and applicable in more than 80–94% of patients, much more than achieved by polymerase chain reaction (PCR)-based approaches (Grimwade et al, 2010a). Real time quantitative reverse transcription PCR (RQ-PCR) is the most sensitive (molecular) MRD detection method. It is based on genetic aberrations, such as mutations and fusion genes that occur in subgroups of AML. The clinical utility of RQ-PCR has been most convincingly demonstrated in acute promyelocytic leukaemia (APL) in which sequential monitoring of the PML-RARA fusion gene has been used to direct treatment (Grimwade et al, 2009). The PETHEMA (Program for the Study and Treatment of Haematological Malignancies) group clearly showed that early institution of salvage therapy at molecular failure, before onset of haematological relapse, is beneficial (Sanz et al, 2009). Molecular targets suitable for PCR-based MRD monitoring are the Core Binding Factor (CBF) leukaemias (Marcucci et al, 2001, Perea et al, 2006). Also mutations in FLT3, NPM1, MLL and CEBPA are potential leukaemia-specific targets (Grimwade et al, 2010b). For NPM1, Schnittger et al (2009) demonstrated a high prognostic value for MRD levels assessed by NPM1 mutation-specific RQ-PCR in 252 NPM1 mutated AML patients. The major hurdle in MRD detection by RT/RQ-PCR is the limited, although steadily increasing, percentage of AML cases with detectable genetic aberrancies for which standardized reliable assays are applicable. Other applications may include gene over-expression of WT1, MECOM (EVI1) and PRAME (Ommen et al, 2008; Grimwade et al, 2009).

Despite intrinsic problems with gene expression studies, these may turn out to be of value, as, for example in a study by Cilloni et al (2009), who recently showed that evaluation of WT1 after chemotherapy can distinguish patients in continuous remission from those who obtained an apparent complete response but relapsed within a few months). Since their introduction, immunophenotypic aberrancies have been categorized and many usable combinations of antigens have been described. As an example, Fig 1 shows aberrant absence of HLA-DR expression on CD34 positive cells at diagnosis (Fig 1A–D). The immunophenotype can be traced at follow-up (Fig 1E–H). Such aberrant immunophenotypes are nowadays referred to as Leukaemia Associated (Immune) Phenotype [LA(I)P] (reviewed in Béné & Kaeda, 2009). Although aberrancies as such are used to quantify MRD, in general these are part of the disturbed differentiation processes and can best be traced by comparing the leukaemic and normal bone marrow (NBM) differentiation process. Obviously, the latter asks for a vast experience of normal differentiation patterns, which may be a major drawback of immunophenotypical MRD analysis.

image

Figure 1.  Absence of HLA-DR expression at diagnosis and tracing residual aberrant cells at follow up. (A–D) gating strategy identifying CD34+ cells with absence of HLA-DR. LAP = HLA-DR-/CD33+/CD45dim/CD34+. Green: lymphocytes; yellow: monocytes; blue: blast cells; red: CD34+ cells. (E–H) residual aberrant cells at different time points after diagnosis. Red: MRD cells. E shows effectiveness of first course of chemotherapy, F (compared with E) shows effectiveness of second course, while G shows increase (compared to F) after consolidation with MRD% of >0·1%, known to result in relapse (Feller et al, 2004). These results are from a patient from the good prognosis group with a nevertheless low (<0·1%) MRD burden after second course, but who nevertheless had a (late) relapse (17 months after diagnosis). The forthcoming relapse can be predicted by an increase in MRD% (Feller et al, 2004), in this case from <0·01% to 0·11%, seen between 5 and 12 months after diagnosis (compare F with G).

Download figure to PowerPoint

One other drawback of the immunophenotypic MRD approach, partly related to the first one, is the ‘background’ expression of the particular markers or of particular marker combinations on the non-malignant cells (Kern et al, 2003). This lack of specificity hampers quantification of MRD at lower levels of detection (<0·01%). Above that, backgrounds in NBM and in stem cell products may significantly differ between individual LA(I)Ps (Kern et al, 2003; Feller et al, 2005). As a result, the minimal level of detection of specific aberrant events is different for different LA(I)Ps and may in part of the cases be as high as 0·1% (Feller et al, 2005). The sensitivity of the approach obviously depends on the number of LA(I)P positive events that can be measured. First, the amount of BM that can be obtained during follow-up may be limited and therefore decrease sensitivity. Secondly, in AML, immunophenotype aberrancies in many cases cover only part of the blast cells (Feller et al, 2004; Kern et al, 2004a). For these cases not all leukaemic cells can be traced, which results in low sensitivity. The major impact of these variances is that, when establishing cut-off levels of MRD that should discriminate good prognosis from poor prognosis patients (see next paragraph), these should be applicable to all patients. The limits are thus determined by those cases with the lowest specificity and sensitivity, which in turn depend on both diagnosis properties (specificity of LA(I)P and level of blast coverage) and follow up conditions (amount of BM obtainable). In other words, large benefits may be expected with increasing sensitivity and specificity.

Another drawback concerns immunophenotype shifts (Baer et al, 2001; Voskova et al, 2004). In general, investigators in AML immunophenotyping will agree that expression of markers may change during and/or after therapy. Immunophenotype changes occurred in 91% of the patients in one series (Baer et al, 2001), but these included changes in levels of expression not necessarily leading to false negativity. In fact, as more than one LAP is mostly present at diagnosis, the incidence of false negative results is low (Baer et al, 2001).

Changes leading to higher expression are not misleading, because aberrant marker expression usually is already defined as an easy-to-recognize expression. Provided marker expression is still recognizable, even decreases of marker expression do not necessarily lead to under-estimation of residual AML cells. Nevertheless, losses of marker expression have been reported (Voskova et al, 2004) and it is therefore strongly recommended to use as many independent LA(I)Ps as possible. Strikingly, immunophenotype shifts thus far are defined as changes related to the originally present aberrant immunophenotype. Recently, several institutes, including our group, have shown that new genotypically-defined leukaemic clones may emerge at relapse, at the cost of original clones. This suggests that these are formed either during therapy or, possibly more likely, were present at diagnosis as minor clones and selected upon treatment (Kottaridis et al, 2002; Cloos et al, 2006; Bachas et al, 2010). This may well result in more immature immunophenotypes, as reported in childhood AML by pair wise comparing diagnosis with relapse (Langebrake et al, 2005). Keeping in mind the relationships that may exist between genotype and immunophenotype, as discussed earlier, disappearance of particular aberrant immunophenotypes (defined as immunophenotypic shifts in MRD analysis) can be hypothesized to accompany disappearance of molecularly-defined clones. Inversely, the appearance of new, molecularly-defined clones, may be accompanied by new aberrant immunophenotypes, not established at diagnosis, and thus, by definition, not used for MRD detection at follow up. Such phenomena might thus account for cases when relapse could not be predicted due to the use of a disappearing aberrant immunophenotype. If minor molecular clones as well as accompanying aberrant immunophenotypes can be traced at diagnosis even at low frequencies, it may thus open the way for an even more reliable MRD approach.

So, with the still limited numbers of optimal antibody-fluorochrome combinations at present, five- to six-colour flowcytometry can successfully be used. Increases in specificity of aberrant immunophenotypes are seen with skilful choices of extra markers used in an aberrant immunophenotype. The definition of reliable numbers of aberrant cells varies amongst studies. Assuming that at least 20 LAP+ events are needed, reliable quantification of MRD cell frequency at a cut-off level of 0·01% will be possible using 200 000 cells. However, usually LAP does not cover the whole blast population and therefore more cells are needed (up to 1 million with 20% coverage). With often limitations in sample size, multicolour flowcytometry will therefore become of great value. However, even after inclusion of markers that increase specificity of LAPs as referred to above, not all LAPs are, or will be, highly specific. The most important cut-offs for positivity after second induction and consolidation used in different studies therefore range from 0·03 to 0·1% (Table II). These include the 250- to 270-fold reduction of aberrant blast cells reported by the German group (Kern et al, 2004b), as starting with <100% blast cells probably results in MRD cell frequencies close to 0·1%.

Table II.   Clinical studies on the prognostic value of minimal residual disease determination by flow cytometry. (modified and updated according: Kern et al 2008, Buccisano et al, 2009).
ReferenceNo of Pts% LAPMRD measurement following:Cut-off MRD levelUnivariate analysis significant for:Multivariate analysis significant for:Adult/Children
ICpostTx
  1. I, induction treatment; C, consolidation; Tx, transplantation; PBCST, peripheral blood stem cell transplantation; LAP, leukaemia associated phenotype; MRD, minimal residual disease; OS, overall survival; RFS, relapse-free survival; MRD, minimal residual disease; RR, relapse risk; ?, not known; A, adult; C, children.

  2. *Includes 56 patients previously reported by Venditti et al (2000).

San Miguel et al (1997)5346I, C<0·5%-0·2% RFS, OSRFSA
Nakamura et al (2000)1731% CD15/CD11710 months in CR<10% CD15/CD117 % blasts  RFSA
Venditti et al (2000)5670%I, C0·045%0·035% I:-, C: RFS, OSI:-, C: RFS, OSA
San Miguel et al (2001)12675%I<0·01, 0·01–0·1%, 0·1–1%, >1% RFS, OSRFSA
Coustan-Smith et al (2003)4685%I1, I20·1% I1: RR, OS I2: RR, OSI1: OS, I2: OSC
Venditti et al (2003)3179%Pre Tx0·035% RR after Tx A
Sievers et al (2003)178?I, C0·5%0·5% I: RFS, OSI: RFS, OS C: RFS, OSC
Kern et al (2004b)106100%Day 16Log difference median 2·11  CR, EFS, RFS, OSEFS, RFSA
Kern et al (2004a)62100%I, CLog difference median 2·7Log difference median 2·53 I: RFS C: RFS, OSI: RFS C: RFSA
Feller et al (2004)72?I1, I2, C, PBSCTI1, 1% I2: 0·14%0·11%0·13%I1, I2, C and PBSC: RFS, OSI1, I2, C and PBSC: RFS, OSA
Gianfaldoni et al (2006)30100%Day 14Log difference median 1·85  CRCRA
Buccisano et al (2006)*10089%I, C0·035%0·035% I and C: RR, RFS, OSI:-, C: RR, RFS, OSA
Laane et al (2006)4594%I, C0·05–0·1%0·05–0·1% I: RFS, C: RFSA
Langebrake et al (2006)150?Day 15, I, I2, C0·1–2%0·1–1·3% Day 15, and I: EFSC
Díez-Campelo et al (2009)41?Day 100 after Tx  10−3RFS, OSRFS, OSA
Maurillo et al (2008)142?I, C0·035%0·035% I and C: RFS, OSI and C: RFS, OSA
Al-Mawali et al (2009)5494%I0·15%0·15% I: RFS, OS C: RFS, OSI: RFS, OS C:-A
van der Velden et al (2010)94 (94%)?I1, I2, C and at end of treatment<0·1% 0·1–0·5% >0·5%  I1: RFS, OSI1: RFS, OSC

Although there is no essential difference between MRD assessment after whole BM lysis and staining or after ficoll separation followed by staining, it is known that cell losses occur with the latter procedure. To avoid the possibility that such losses are selective for particular sub-populations and to shorten the time period of the whole preparation and staining procedures, the first method is preferable.

Taking into account the advantages as well as disadvantages of the immunophenotypical MRD approach, the question arises how to apply in clinical studies. Quite a number of single centre studies have now been published (see next section). Obviously, for large international studies the involvement of a (limited) number of core centres, probably allocated according to specific regions, may be preferable. Efforts to standardize LA(I)P measurements in order to enable adequate multicentre studies are needed, as performed in the past for B- and T-ALL in a Biomed 1 study (Porwit-MacDonald et al, 2000; Lucio et al, 2001). To study the feasibility of such an approach, including design of LA(I)Ps, handling of material, transport and inter-centre variations in interpreting, validation studies have been initiated, e.g. for HOVON/SAKK (Stichting Hemato-Oncologie voor Volwassenen Nederland/Swiss Group for Clinical Cancer Research) AML studies. Results are awaited shortly. It is of utmost importance that RQ-PCR should be run in parallel in these studies.

Also, in the UK AML 16 and 17 trials, the National Cancer Research Institute (http://www.haematologyclinicaltrials.co.uk) is currently determining the clinical value of the MRD status either by molecular monitoring or by FCM monitoring. Once a validated method has been identified patients will be randomized to be monitored or not to be monitored with the aim of establishing whether MRD could serve as a predictive biomarker.

Clinical aspects of MRD detection in AML

  1. Top of page
  2. Summary
  3. Aberrancies at diagnosis in AML
  4. Acute leukaemias of ambiguous lineage
  5. Aberrancies and prognosis in AML
  6. Minimal Residual Disease (MRD) detection
  7. Clinical aspects of MRD detection in AML
  8. Current status and future improvements of MRD assessment
  9. Immunopenotypical aberrancies in MDS
  10. Aberrancies in the immature and mature myeloid/granulocytic lineage
  11. Aberrancies in the monocytic lineage
  12. Erythroid and megakaryocytic lineage
  13. FCM in MDS: role in diagnosis
  14. FCM in MDS: role in prognosis
  15. Prediction of response to therapy by FCM in low risk MDS
  16. Conclusions
  17. References

Patients with AML show a heterogeneous response to therapy. The current standard of care involves an intensive induction chemotherapy followed by post-remission consolidation treatment including additional chemotherapy cycles and/or allogeneic/autologous stem cell transplantation (Döhner et al, 2010). Treatment outcome varies from primary refractory disease to cure. Many patients experience a relapse. In addition to patient age, cytogenetic aberrancies and certain mutations are associated with outcome and divides AML patients in groups varying from a good prognosis [t(15;17), inv(16), t(16;16), t(8;21), NPM1+/FLT3-ITD−, CEBPA mutated] to poor prognosis [e.g. monosomal karyotype, 11q23 rearrangements resulting in MLL fusion proteins, chromosome 3 aberrancies, MECOM] (Breems et al, 2008; Grimwade et al, 2010b; Gröschel et al, 2010). This risk classification is currently used in decision making leading to custom tailored therapy (for example no allogeneic SCT in very good risk patients). Apart from these cytogenetic and molecular factors, several mechanisms not included in standard risk assessment at diagnosis have shown prognostic value. These include increased drug efflux by transporters of the ABC family and including P-glycoprotein and breast cancer resistance protein as well as apoptosis related mechanisms In addition, pharmacologic resistance as well as interaction of the leukaemic cell with the BM environment also may play a role. Constitutive activation of signal transduction pathways important for stem cell survival also contributes to chemotherapy resistance. It has been hypothesized that all these mechanisms favour the survival of leukaemia-initiating stem cells that, upon re-growth, leads to MRD and subsequently to relapse. MRD thus represents the sum of the effects of all relevant molecularly and functionally defined resistance factors, pharmacokinetic resistance and all other unknown factors determining the outcome of treatment. To provide evidence for that, a number of such risk factors were shown to correlate with MRD cell frequency (Feller et al, 2003; van der Pol et al, 2003; van Rhenen et al, 2005; van Stijn et al, 2005; Hess et al, 2009). In addition, the presence of FLT3-ITD was associated with MRD cell frequency (Hess et al, 2009). As, on the one hand relapses occur in very good risk patients and on the other hand, cures are possible in very poor prognosis AML patients, the prognosis of an individual cannot yet be estimated accurately. Fine-tuning by MRD measurement after chemotherapy could hypothetically be very instrumental for guiding treatment.

Methodologies for MRD detection after chemotherapy that are most widely used are: PCR of molecular aberrancies and flow cytometric detection of leukaemia-associated phenotypes LA(I)P. Despite the low sensitivity of BM morphology, early blast clearance determined by BM microscopy has been shown to be a major independent prognostic factor. Kern et al (2004b), showed that day-16 BM blast percentage as a continuous variable significantly predicted clinical outcome. A correlation was found between the slope of blast clearance during administration of chemotherapy and the probability of achieving and staying in complete remission (Lacombe et al, 2009).

Several studies in children as well as adults have shown that MRD detection by FCM provides strong prognostic information in AML after both induction and consolidation (Table II) (San Miguel et al, 1997; Nakamura et al, 2000; Venditti et al, 2000; San Miguel et al, 2001; Coustan-Smith et al, 2003; Venditti et al, 2003; Sievers et al, 2003; Kern et al, 2004a,b; Feller et al, 2004; Gianfaldoni et al, 2006; Buccisano et al, 2006; Laane et al, 2006; Langebrake et al, 2006; Diez-Campalo et al, 2009; Maurillo et al, 2008; Al-Mawali et al, 2009; van der Velden et al, 2010). Importantly, one has to realize that most of these studies were retrospective in a single institute setting, thus introducing well known potential bias. By identifying cut-off values in the order of 0·01–0·1% it has been possible in most of these studies to identify two patient groups with either poor or good prognosis. Determining the optimal cut-off is mostly done by empirically setting a threshold below or above which the outcome is statistically significant different.

Various statistical methods have been used, such as maximally selected log-rank statistics or receiver operating characteristic (ROC) analysis. Two examples of clinical studies will be discussed in more detail while the remaining studies are summarized in Table II.

Feller et al (2004) evaluated MRD after each of three cycles of chemotherapy and from peripheral blood stem cell (PBSC) harvests. The percentage of MRD in BM after each cycle of chemotherapy and in PBSC products correlated strongly with RFS. Many cut-off levels predicted for outcome: a cut-off threshold of 1% after the first cycle, 0·14% after cycle 2, 0·11% after the cycle 3 and 0·13% in the PBSC harvest were most significant in predicting predicted for a relative risk of relapse (RR): RR was 6·1-, 3·4-, 7·2- and 5·7-fold, higher respectively, in the high MRD group. Rising MRD levels after completion of therapy, measured at 3-month intervals, heralded impending relapse (Feller et al, 2004).

Maurillo et al, in a follow up of earlier work, demonstrated for 142 patients that persistence of ≥3·5 × 10−4 residual leukaemic cells after consolidation was associated with a 5-year RFS of 16% and OS of 23% as compared to 69% and 62% survival respectively in MRD low patients. Combining MRD status after induction and consolidation showed that patients achieving early MRD negativity and maintaining this after consolidation, had the best treatment outcome. In addition, MRD status was predictive for outcome after transplantation. Allogeneic transplantation had a higher likelihood of RFS (47% vs. 14%) (Maurillo et al, 2008). The exact time point at which MRD is most predictive differs among the studies and is probably therapy dependent. It could be an advantage to select, as early as possible, those patients who are doing very well. They then could be treated with a less intensive treatment schedule while those patients who, on basis of MRD, classify as poor prognosis patients could be directed towards an allogeneic transplant protocol.

Prospective HOVON/SAKK multicentre studies in young (n = 518) and elderly (n = 220) patients with AML, to validate the cut-off frequency points established in retrospective analysis, have recently closed accrual. In these studies, molecular MRD was also performed in subsets of patients. From such studies it has been realized that multicentre FCM studies require extensive validation and quality controls.

We are convinced that implementation of FCM for MRD detection resulting in a re definition of complete response will become part of a risk-adapted approach enabling the delivery of appropriate treatment i.e. proportional to the individual risk of relapse. Such a strategy has recently been investigated in 232 children with AML (Rubnitz et al, 2010). Risk classification was based on genetic abnormalities at diagnosis and MRD. Levels of MRD were used to allocate intensification of treatment with gemtuzumab-ozogamicin and the timing of induction cycle 2. The outcome of this study [3-year event-free survival (EFS) 63% and OS 71%] compares favourably with the previous St. Jude AML 97 trial (44% and 50%) and also with results reported by other childhood AML study groups (MRC: 48% and 56%, BFM: 49% and 56%) (Rubnitz et al, 2010). MRD of 1% or higher after induction 1 was the only significant adverse prognostic factor for both EFS and OS (Rubnitz et al, 2010).

Apart from MRD assessment to guide stratification of groups and to apply individual risk assessment, the strong correlation discussed earlier that exist sbetween diagnosis prognostic factors and MRD, especially after first course of therapy, strongly suggests that MRD assessment may also offer a short-term surrogate endpoint for determining effectiveness of new targeted therapies.

Current status and future improvements of MRD assessment

  1. Top of page
  2. Summary
  3. Aberrancies at diagnosis in AML
  4. Acute leukaemias of ambiguous lineage
  5. Aberrancies and prognosis in AML
  6. Minimal Residual Disease (MRD) detection
  7. Clinical aspects of MRD detection in AML
  8. Current status and future improvements of MRD assessment
  9. Immunopenotypical aberrancies in MDS
  10. Aberrancies in the immature and mature myeloid/granulocytic lineage
  11. Aberrancies in the monocytic lineage
  12. Erythroid and megakaryocytic lineage
  13. FCM in MDS: role in diagnosis
  14. FCM in MDS: role in prognosis
  15. Prediction of response to therapy by FCM in low risk MDS
  16. Conclusions
  17. References

The relative lack of specificity of particular LA(I)Ps has led to approaches that may improve or circumvent this. Whereas in the early days, three-colour flow cytometry analysis was performed, many of the large studies were performed with four-colour analysis. Increasing the number of fluorochromes improves specificity, as shown for the transition from four to five colours (Voskova et al, 2007), for example by using exclusion markers, i.e. markers that allow to exclude non- MRD cell populations that ‘pollute’ the MRD gate. Apart from that, multicolour flow cytometry enables restriction of the number of tubes and thereby the number of cells to be analyzed. This is an advantage in those cases where the amount of BM is limited. At present 8-colour approaches are in progress. One should realize that steadily increasing the number of colours is paralleled by increasing technical demands, such as the availability and stability of new antibody-fluorochrome combinations.

Moreover, interpreting immunophenotypically defined populations or differentiation patterns continues to be a rather subjective method. In order to overcome this, at least partly, a European consortium has recently set out to implement an approach that allows diagnostics to be performed in a more objective way. To that end, the Infinicyte program was developed that enables the comparison and interpretation of specific diagnostic cases (not AML restricted) against a background of many normal BM patterns (Pedreira et al, 2008). Recently an 8-colour protocol for the diagnosis of haematological malignancies in a multicentre fashion has been developed. The validation for MRD detection in AML, however, has not yet started. The additional advantage of the program is that it allows the merging of immunophenotypic files obtained with different tubes, provided both contain a number of overlapping parameters (scatter and a few of the same antibody-fluorochrome combinations). This results in a virtual tube describing an infinite number of markers, while using only a limited number of fluorochromes. Clearly it offers the advantage that the development of large numbers of fluorochromes can be avoided, but of course the amount of available BM can still be the limiting factor as the results are obtained using multiple tubes. Another way to decrease a-specificity is to use peripheral blood (PB): PB lacks immature normal populations that often interfere with the aberrant leukaemia-associated but not leukaemic-specific immunophenotypes. Moreover, it obviously offers advantages in terms of ease of sampling, as it is more convenient for both patient and physician, with subsequent opportunities for sampling at multiple time points. One immunophenotypic study thus far showed a strikingly good correlation between PB MRD and BM MRD (Maurillo et al, 2007). This is not necessarily the case in all cases of AL because, in contrast to T-ALL, in B-ALL no such good correlations were found (van der Velden et al, 2002).The disadvantage is that PB has lower MRD levels compared to BM (Maurillo et al, 2007).

Finally, detection of AML stem cells offers advantages in terms of specificity. Leukaemia stem cells are hypothesized to selectively survive chemotherapy, to subsequently grow out to what we term MRD, and in many cases are thus at the basis of outgrowth of MRD towards relapse. Their frequencies at diagnosis are directly related to MRD frequencies and poor clinical outcome, as shown for the CD34+ CD38 defined stem cell compartment (van Rhenen et al, 2005). Identification and quantification may therefore add a biologically important parameter and thereby contribute to the prognostic impact of MRD. Apart from newly characterized AML stem cell-specific markers, such as CD123, CLL-1, CD44, CD47 and CD96 (Krause & Van Etten, 2007; ten Cate et al, 2010), AML stem cells are characterized by the same lineage aberrantions, e.g. CD34+ CD56+ and CD34+ CD7+, as used for MRD assessment (van Rhenen et al, 2007). The strong prognostic impact of AML stem cell frequencies measured after different courses of therapy has been demonstrated in a small study (unpublished observations). The important observation is that the specificity of these aberrancies, i.e. concomitant absence on the normal counterpart (here the normal CD34+ CD38 haematopoietic stem cells), is higher than specificity on all blast cells as used for MRD. As a result, AML stem cell frequencies can be assessed with high specificity, without extensive experience in defining real aberrant populations, as was necessary for MRD assessment in BM. An important disadvantage is the median 2 log lower frequencies (van Rhenen et al, 2005).

Thus, immunophenotypic aberrancies, measured as MRD at follow up, as well as AML stem cell frequency, measured as ‘stem cell MRD’ at follow up, now offer new post-diagnosis prognostic factors. This adds to the few post-diagnosis prognostic factors known, i.e. complete response rate after first therapy course and BM or stem cell transplant CD34 percentage (Feller et al, 2003; Keating et al, 2003; Gorin et al, 2010). Such post-diagnosis prognostic factors may well become extremely important in risk stratification, assessment of the efficacy of new therapies and personalized medicine.

Immunopenotypical aberrancies in MDS

  1. Top of page
  2. Summary
  3. Aberrancies at diagnosis in AML
  4. Acute leukaemias of ambiguous lineage
  5. Aberrancies and prognosis in AML
  6. Minimal Residual Disease (MRD) detection
  7. Clinical aspects of MRD detection in AML
  8. Current status and future improvements of MRD assessment
  9. Immunopenotypical aberrancies in MDS
  10. Aberrancies in the immature and mature myeloid/granulocytic lineage
  11. Aberrancies in the monocytic lineage
  12. Erythroid and megakaryocytic lineage
  13. FCM in MDS: role in diagnosis
  14. FCM in MDS: role in prognosis
  15. Prediction of response to therapy by FCM in low risk MDS
  16. Conclusions
  17. References

Flow cytometric evaluation of dyspoiesis in MDS

Similar to AML, application of flow cytometry for the diagnosis of MDS requires knowledge of changes in antigen expression in normal haematopoietic cell differentiation. (van Lochem et al, 2004) Recently, minimal diagnostic criteria for MDS have been redefined, which include the presence of dysplasia in one or more cell lineages, an increase in blasts (5–19%) and cytogenetic abnormalities. (Valent et al, 2007).

Flow cytometry enables the detection of minimal aberrancies in the differentiation of myelo-monocytic cell populations by changes in antigen expression that are otherwise not detected by morphology (Stetler-Stevenson et al, 2001). In a consensus document from the European LeukaemiaNet (ELN) working group for standardization of flow cytometry in MDS, a minimal combination of antibodies for the analysis of dyspoiesis in the (im)mature myelo-monocytic cell compartments was proposed (Table III). (van de Loosdrecht et al, 2009). Aberrancies in haematopoiesis observed in MDS include expression of lymphoid antigens on myeloid cells, over- and under- expression of antigens and/or loss of antigen expression, expression of immature antigens on mature cells and vice versa and abnormal differentiation patterns between antigens. The accumulation of aberrancies might discern MDS from non-clonal cytopenias. (Malcovati et al, 2005a; Loken et al, 2008; Matarraz et al, 2010).

Table III.   Combination of markers as recommended by the ELN working group for the standardization of flow cytometry in MDS (van de Loosdrecht et al, 2009).
ErythroidCD71/CD235a/CD117 Optional: CD105, CD34/CD117, CD36
  1. A minimum panel for the diagnosis and/or prognosis of MDS. The common leucocyte antigen CD45 should be combined with the antigens that are listed in the table. The subpopulations in the BM should be gated based on CD45 and sideways scatter.

Myeloid progenitorsCD34 in combination with CD117/CD11b, HLA-DR/CD15 Lineage infidelity markers: CD5, CD7/CD13, CD19, CD56 Optional: CD123, TdT
Lymphoid progenitorsCD34/CD19 Optional: CD10/CD19/CD38, TdT, CD79a
Maturing myeloid cellsCD11b/CD13/CD16, CD11b/CD117/HLA-DR/CD10 CD34 in combination with CD5, CD7, CD15, CD19, CD56, CD33/CD14 Optional: CD65, CD123
MonocytesCD11b/HLA-DR, CD34 in combination with CD5, CD7 CD19, CD56, CD64/CD14, CD33/CD14, CD33/CD36 Optional: CD64/CD36

Aberrancies in the immature and mature myeloid/granulocytic lineage

  1. Top of page
  2. Summary
  3. Aberrancies at diagnosis in AML
  4. Acute leukaemias of ambiguous lineage
  5. Aberrancies and prognosis in AML
  6. Minimal Residual Disease (MRD) detection
  7. Clinical aspects of MRD detection in AML
  8. Current status and future improvements of MRD assessment
  9. Immunopenotypical aberrancies in MDS
  10. Aberrancies in the immature and mature myeloid/granulocytic lineage
  11. Aberrancies in the monocytic lineage
  12. Erythroid and megakaryocytic lineage
  13. FCM in MDS: role in diagnosis
  14. FCM in MDS: role in prognosis
  15. Prediction of response to therapy by FCM in low risk MDS
  16. Conclusions
  17. References

Flow cytometry can be used to identify distinct subpopulations of myeloid progenitor cells based on antigen expression levels. In order to identify myeloid progenitors, the ELN working group for the standardization of FCM in MDS recommends the use of scatter properties and CD45 in combination with CD34/CD117/HLA-DR and CD34/CD123/HLA-DR and CD11b/HLA-DR (Table II) (van de Loosdrecht et al, 2009). Quantification of immature myeloid progenitor cells by FCM may add in diagnosis and follow-up although no direct correlation is observed with conventional morphologic blast cell count.

Lymphoid antigens, such as CD2, CD5, CD7, CD19 and CD56, may be aberrantly expressed on myeloid progenitors and maturing myeloid cells in MDS. A common finding in MDS is the aberrant expression of antigens on immature myeloid cells that are normally expressed on mature myeloid cells, such as CD11b and/or CD15. Neutrophil maturation stages can be distinguished by different expression levels of CD11b, CD13 and CD16. Hypogranularity, which is reflected by a decreased sideways scatter (SSC), is a common finding in MDS (Stetler-Stevenson et al, 2001). Aberrancies that can be detected in the myeloid compartment are listed in Table IV (Maynadiéet al, 2002; Wells et al, 2003; Pirruccello et al, 2006; Loken et al, 2008; van de Loosdrecht et al, 2008; Satoh & Ogata, 2008; Stachurski et al, 2008).

Table IV.   Common immunophenotypic aberrancies in MDS.
  1. The table is compiled from a meeting report on definitions and standards in the diagnosis and treatment of MDS (Loken et al, 2008; van de Loosdrecht et al, 2009; Valent et al, 2007; Wells et al, 2003). The most relevant and commonly described aberrancies that can be detected in MDS are described.

Common phenotypic abnormalities detected by flow cytometry in MD
Myeloid progenitors
 Increased, decreased or absent CD45 expression
 Increased, decreased or absent and/or homogenous CD34 expression
 Homogenous CD117 expression
 Asynchronous expression of CD11b and/or CD15
 Decreased or absent HLA DR, CD13 and/or CD33 expression
 Expression of lymphoid associated antigens: CD2, CD5, CD7, CD19 and/or CD56
 Decreased CD38 expression
 Absolute and relative increase in the number of myeloid progenitors
B cell progenitors
 Absolute and relative (to myeloid progenitors) decrease in B cell progenitors
Maturing myeloid cells
 Decreased CD45 expression
 Abnormal relationship patterns of myeloid antigens CD11b, CD13 and CD16
 Hypogranularity characterized by decreased SSC
 Decreased or absent CD33 expression
 Asynchronous expression of CD34 and/or HLA-DR
 Expression of lymphoid associated antigens: CD5, CD7, CD19 and/or CD56
Maturing monocytes
 Decreased CD45 expression
 Abnormal relationship patterns of CD11b and HLA DR, CD13 and CD16, CD14 and CD33
 Increased, decreased or absent CD11b, CD13, CD14, CD16, CD33 and/or HLA-DR
 Expression of CD34
 Expression of lymphoid antigens: CD2, CD5, CD7, CD19 and/or CD56
 Absolute and relative increase in the number of monocytes
Maturing erythroid cells
 Abnormal expression of CD34 CD45 and/or CD117
 Decreased CD71 expression
 Absolute and relative increase in the number of immature erythroid cells
 Persistent low levels of CD71 expression on CD235a positive erythroid precursors

Aberrancies in the monocytic lineage

  1. Top of page
  2. Summary
  3. Aberrancies at diagnosis in AML
  4. Acute leukaemias of ambiguous lineage
  5. Aberrancies and prognosis in AML
  6. Minimal Residual Disease (MRD) detection
  7. Clinical aspects of MRD detection in AML
  8. Current status and future improvements of MRD assessment
  9. Immunopenotypical aberrancies in MDS
  10. Aberrancies in the immature and mature myeloid/granulocytic lineage
  11. Aberrancies in the monocytic lineage
  12. Erythroid and megakaryocytic lineage
  13. FCM in MDS: role in diagnosis
  14. FCM in MDS: role in prognosis
  15. Prediction of response to therapy by FCM in low risk MDS
  16. Conclusions
  17. References

The additional value of FCM in monocytic lineage analysis can be substantial given that dyspoiesis in the monocytic lineage on the BM level is difficult to identify by morphology. The combination of CD14, CD36 and CD64 (Matarraz et al, 2008) enables the detection of immature monocytes. Abnormalities in the expression patterns of HLA-DR, CD11b, CD13, CD14 and CD33 are common findings. Aberrant increases, decreases or even lack of expression of CD13, CD14, CD16 or CD33 are common in MDS (Table IV). Persistence of the immature marker CD34 on mature monocytes is an intriguing observation. Finally, also lymphoid antigens can be aberrantly expressed on monocytes in MDS. Overexpression of CD56, defined as 1-log increase above normal expression, is aberrant and associated with chronic myelomonocytic leukaemia (CMML). It can be of relevance for the differential diagnosis of MDS and MDS/myeloproliferative diseases, such as CMML.

Erythroid and megakaryocytic lineage

  1. Top of page
  2. Summary
  3. Aberrancies at diagnosis in AML
  4. Acute leukaemias of ambiguous lineage
  5. Aberrancies and prognosis in AML
  6. Minimal Residual Disease (MRD) detection
  7. Clinical aspects of MRD detection in AML
  8. Current status and future improvements of MRD assessment
  9. Immunopenotypical aberrancies in MDS
  10. Aberrancies in the immature and mature myeloid/granulocytic lineage
  11. Aberrancies in the monocytic lineage
  12. Erythroid and megakaryocytic lineage
  13. FCM in MDS: role in diagnosis
  14. FCM in MDS: role in prognosis
  15. Prediction of response to therapy by FCM in low risk MDS
  16. Conclusions
  17. References

The detection of erythroid dysplasia by FCM in MDS is limited due to lack of markers. Erythroid cells can be identified by the absence of CD45 and by low light scatter. The markers that are mainly investigated in the context of dyserythropoiesis in MDS are CD235a and CD71. Other markers that are associated with erythroid dysplasia in MDS are the intracellular ferritin subunits, H-ferritin and L-ferritin and mitochondrial ferritin (MtF). Analysis of dyspoiesis in the megakaryocytic lineage by FCM is limited due to technical aspects. The number of megakaryocytes is too low to be analyzed by FCM without extensive enrichment.

FCM in MDS: role in diagnosis

  1. Top of page
  2. Summary
  3. Aberrancies at diagnosis in AML
  4. Acute leukaemias of ambiguous lineage
  5. Aberrancies and prognosis in AML
  6. Minimal Residual Disease (MRD) detection
  7. Clinical aspects of MRD detection in AML
  8. Current status and future improvements of MRD assessment
  9. Immunopenotypical aberrancies in MDS
  10. Aberrancies in the immature and mature myeloid/granulocytic lineage
  11. Aberrancies in the monocytic lineage
  12. Erythroid and megakaryocytic lineage
  13. FCM in MDS: role in diagnosis
  14. FCM in MDS: role in prognosis
  15. Prediction of response to therapy by FCM in low risk MDS
  16. Conclusions
  17. References

The diagnostic utility of multi-parameter FCM of the myeloid, erythroid and megakaryocytic lineage in the BM is strongly supported by the correlations with established diagnostic classification systems, such as those defined by WHO (Stetler-Stevenson et al, 2001; Maynadiéet al, 2002; Wells et al, 2003; van de Loosdrecht et al, 2008). In order to develop a numerical display of FCM data, a flow cytometric scoring system (FCSS) was proposed (Wells et al, 2003). This FCSS showed a good correlation with WHO 2001 classification for MDS (van de Loosdrecht et al, 2008). Flow scores were heterogeneous within WHO subgroups. This indicates that FCM might even identify subgroups within existing classification systems, which in turn would offer a more refined classification with potential prognostic impact.

Interestingly, FCM identified patients with MDS refractory anaemia with ringed sideroblasts, who already had multi-lineage involvement according to FCM while morphology could only show erythroid dysplasia (Hokland et al, 1986; Malcovati et al, 2005a). In another series aberrancies in the myelo-monocytic lineage also could be detected in the majority of MDS patients with unilineage erythroid dysplasia (van de Loosdrecht et al, 2008). Based on four parameters e.g. the percentage of myeloid progenitors, B cell progenitors, CD45 expression of myeloid progenitors and neutrophil SSC (Ogata et al, 2009), lower risk MDS could be distinguished from normal, e.g. non-clonal, haematopoiesis with a relatively high sensitivity and specificity. CD38 expression on CD34 positive cells as a single marker might be of value for the diagnosis of MDS but this observation needs to be confirmed. (Goardon et al, 2009). The majority of FCM studies focussed on the enumeration of phenotypic abnormalities which might provide a measurement for the degree of dysregulation of haematopoiesis or difference from normal. However, some phenotypic aberrancies might be of more significance than others in detecting the dysregulation of haematopoiesis (Loken et al, 2008).

FCM in MDS: role in prognosis

  1. Top of page
  2. Summary
  3. Aberrancies at diagnosis in AML
  4. Acute leukaemias of ambiguous lineage
  5. Aberrancies and prognosis in AML
  6. Minimal Residual Disease (MRD) detection
  7. Clinical aspects of MRD detection in AML
  8. Current status and future improvements of MRD assessment
  9. Immunopenotypical aberrancies in MDS
  10. Aberrancies in the immature and mature myeloid/granulocytic lineage
  11. Aberrancies in the monocytic lineage
  12. Erythroid and megakaryocytic lineage
  13. FCM in MDS: role in diagnosis
  14. FCM in MDS: role in prognosis
  15. Prediction of response to therapy by FCM in low risk MDS
  16. Conclusions
  17. References

Within the low risk categories, multi-lineage dysplasia is of prognostic relevance in MDS. The International Prognostic Scoring System (IPSS) and WHO-based Prognostic Scoring System (WPSS) provide a prognostic scoring system integrating not only morphological information but also karyotyping and transfusion need, respectively. Several studies show that flow cytometric aberrancies in BM of MDS patients correlate with the IPSS and WPSS (Maynadiéet al, 2002; Wells et al, 2003; Malcovati et al, 2005b; Pirruccello et al, 2006; van de Loosdrecht et al, 2008; Lorand-Metze et al, 2008). In studies that quantified the number of FCM aberrancies in BM of MDS patients, high numbers of aberrancies were associated with (high risk) MDS categories and an adverse clinical outcome (Del Cañizo et al, 2003; Wells et al, 2003; van de Loosdrecht et al, 2008). Univariate analysis showed that more than three aberrations had a significant negative influence on survival. In patients lacking cytogenetic information or patients with normal karyotype, FCM added significant prognostic information in multivariate analysis (Arroyo et al, 2004). Wells et al (2003) designed a flow cytometric scoring system (FCSS) based on aberrancies in the (im)mature myelo-monocytic compartment. In a group of 111 MDS patients that were treated with allogeneic haematopoietic stem cell transplantation, flow scores correlated with post-transplantation outcome independent of the IPSS score (Scott et al, 2008). Aberrancies in the (myeloid) progenitor compartment might be of more relevance for prognostication of MDS patients than aberrancies in the mature myelo-monocytic compartment(van de Loosdrecht et al, 2008; Matarraz et al, 2010; Westers et al, 2010). Low risk MDS patients with <5% blasts may have abnormal blasts by flow cytometry (Wells et al, 2003; Kussick et al, 2005; van de Loosdrecht et al, 2008; Scott et al, 2008; Westers et al, 2010). More importantly, the presence of aberrant myeloid progenitors in low risk MDS patients has an adverse clinical outcome with a higher risk for transfusion dependency and/or progressive disease, independent of existing and validated prognostic classification systems (van de Loosdrecht et al, 2008). Probably, MDS with myeloblasts with CD7 expression behave more aggressive than in MDS without CD7 expression (Satoh & Ogata 2008). The expression of lymphoid antigens by a significant proportion of myeloid or monocytic cells might carry more weight with respect to prognosis than altered expression of myeloid or monocytic antigens (Craig & Foon, 2008).

Quantification of CD34 positive cells in the PB of MDS patients by flow cytometry might be a relevant tool for the prognostication of MDS patients (Cesana et al, 2008). Low risk MDS patients with circulating blasts have a comparable prognosis to patients with refractory anaemia with excess blasts, type 1 (MDS RAEB-1) (Knipp et al, 2008). According to the WHO 2008 classification, a percentage of 2–4% circulating blasts, but <5% blasts in the BM defines a patient already as a MDS RAEB-1 (Swerdlow et al, 2008).

Prediction of response to therapy by FCM in low risk MDS

  1. Top of page
  2. Summary
  3. Aberrancies at diagnosis in AML
  4. Acute leukaemias of ambiguous lineage
  5. Aberrancies and prognosis in AML
  6. Minimal Residual Disease (MRD) detection
  7. Clinical aspects of MRD detection in AML
  8. Current status and future improvements of MRD assessment
  9. Immunopenotypical aberrancies in MDS
  10. Aberrancies in the immature and mature myeloid/granulocytic lineage
  11. Aberrancies in the monocytic lineage
  12. Erythroid and megakaryocytic lineage
  13. FCM in MDS: role in diagnosis
  14. FCM in MDS: role in prognosis
  15. Prediction of response to therapy by FCM in low risk MDS
  16. Conclusions
  17. References

The first line of treatment in IPSS low and intermediate-1 risk MDS patients is supportive therapy consisting of transfusions and growth factors such as erythropoietin (Epo) and human recombinant granulocyte colony-stimulating factor (G-CSF). Response to treatment can be predicted by a model that includes pre-treatment endogenous serum Epo levels and transfusion need (Hellström-Lindberg et al, 1997; Hellström-Lindberg et al, 2003). In a group of 46 IPSS low and intermediate-1 risk MDS patients who were treated with Epo and G-CSF and evaluated by flow cytometry, the presence of immunophenotypically aberrant myeloid progenitors was instrumental in predicting response to growth factor treatment (Westers et al, 2010). A new predictive model based on flow cytometry and endogenous serum Epo levels was proposed and identified three subgroups of MDS patients: patients with low serum Epo and normal myeloid progenitors by flow cytometry have a high probability to respond to growth factor treatment (94%) compared with patients with high serum Epo levels and aberrant myeloid progenitors with a low probability to respond to treatment (11%).

Conclusions

  1. Top of page
  2. Summary
  3. Aberrancies at diagnosis in AML
  4. Acute leukaemias of ambiguous lineage
  5. Aberrancies and prognosis in AML
  6. Minimal Residual Disease (MRD) detection
  7. Clinical aspects of MRD detection in AML
  8. Current status and future improvements of MRD assessment
  9. Immunopenotypical aberrancies in MDS
  10. Aberrancies in the immature and mature myeloid/granulocytic lineage
  11. Aberrancies in the monocytic lineage
  12. Erythroid and megakaryocytic lineage
  13. FCM in MDS: role in diagnosis
  14. FCM in MDS: role in prognosis
  15. Prediction of response to therapy by FCM in low risk MDS
  16. Conclusions
  17. References

Recent developments show that the detection of aberrancies in haematopoietic cells by flow cytometry in AML and MDS is of diagnostic, prognostic and predictive relevance. Detection of aberrant myeloid progenitors might be instrumental in treatment decisions, monitoring and facilitating patient-tailored and -adaptive treatment. It is certainly, next to morphology and cytogenetics, a valuable and indispensible part of the diagnostic and prognostic work-up of AML/MDS patients.

References

  1. Top of page
  2. Summary
  3. Aberrancies at diagnosis in AML
  4. Acute leukaemias of ambiguous lineage
  5. Aberrancies and prognosis in AML
  6. Minimal Residual Disease (MRD) detection
  7. Clinical aspects of MRD detection in AML
  8. Current status and future improvements of MRD assessment
  9. Immunopenotypical aberrancies in MDS
  10. Aberrancies in the immature and mature myeloid/granulocytic lineage
  11. Aberrancies in the monocytic lineage
  12. Erythroid and megakaryocytic lineage
  13. FCM in MDS: role in diagnosis
  14. FCM in MDS: role in prognosis
  15. Prediction of response to therapy by FCM in low risk MDS
  16. Conclusions
  17. References
  • Al-Mawali, A., Gillis, D., Hissaria, P. & Lewis, I. (2008) Incidence, sensitivity, and specificity of leukemia-associated phenotypes in acute myeloid leukemia using specific five-color multiparameter flow cytometry. American Journal of Clinical Pathology, 129, 934945.
  • Al-Mawali, A., Gillis, D. & Lewis, I. (2009) The use of receiver operating characteristic analysis for detection of minimal residual disease using five-color multiparameter flow cytometry in acute myeloid leukemia identifies patients with high risk of relapse. Cytometry. Part B, Clinical Cytometry, 76, 91101.
  • van den Ancker, W., Terwijn, M., Westers, T.M., Merle, P.A., van Beckhoven, E., Dräger, A.M., Ossenkoppele, G.J. & van de Loosdrecht, A.A. (2010) Acute leukemias of ambiguous lineage: diagnostic consequences of the WHO2008 classification. Leukemia, 24, 13921396.
  • Arroyo, J.L., Fernández, M.E., Hernández, J.M., Orfao, A., San Miguel, J.F. & del Cañizo, M.C. (2004) Impact of immunophenotype on prognosis of patients with myelodysplastic syndromes. Its value in patients without karyotypic abnormalitie. The Hematology Journal, 5, 227233.
  • Bachas, C., Schuurhuis, G.J., Hollink, I.H., Kwidama, Z.J., Goemans, B.F., Zwaan, C.M., van den Heuvel-Eibrink, M.M., de Bont, E.S., Reinhardt, D., Creutzig, U., de Haas, V., Assaraf, Y.G., Kaspers, G.J. & Cloos, J. (2010) High frequency type I/II mutational shifts between diagnosis and relapse are associated with outcome in pediatric AML: implications for personalized medicine. Blood, 116, 27522758.
  • Baer, M.R., Stewart, C.C., Dodge, R.K., Leget, G., Sulé, N., Mrózek, K., Schiffer, C.A., Powell, B.L., Kolitz, J.E., Moore, J.O., Stone, R.M., Davey, F.R., Carroll, A.J., Larson, R.A. & Bloomfield, C.D. (2001) High frequency of immunophenotype changes in acute myeloid leukemia at relapse: implication for residual disease detection. Blood, 97, 35743580.
  • Bagg, A. (2007) Lineage ambiguity, infidelity, and promiscuity in immunophenotypically complex acute leukemias genetic and morphologic correlates. The American Journal of Pathology, 128, 545548.
  • Basso, G., Case, C. & Dell’Orto, M.C. (2007) Diagnosis and genetic subtypes of leukemia combining gene expression and flow cytometry. Blood Cells, Molecules, and Diseases, 39, 164168.
  • Béné, M.C. (2005) Immunophenotyping of acute leukaemias. Immunology Letters, 98, 921.
  • Béné, M.C. & Kaeda, J.S. (2009) How and why minimal residual disease studies are necessary in leukemia: a review from WP10 and WP12 of the European LeukaemiaNet. Haematologica, 94, 11351150.
  • Béné, M.C., Castoldi, G., Knapp, W., Ludwig, W.D., Matutes, E. & Orifao, A. (1995) Proposals for the immunological classification of acute leukemis. European Group for the immunological characterization of leukemias (EGIL). Leukemia, 9, 17831786.
  • Breems, D.A., Van Putten, W.L., De Greef, G.E., Van Zelderen-Bhola, S.L., Gerssen-Schoorl, K.B., Mellink, C.H., Nieuwint, A., Jotterand, M., Hagemeijer, A., Beverloo, H.B. & Löwenberg, B. (2008) Monosomal karyotype in acute myeloid leukemia: a better indicator of poor prognosis than a complex karyotype. Journal of Clinical Oncology, 26, 47914797.
  • Buccisano, F., Maurillo, L. & Gattei, V. (2006) The kinetics of reduction of minimal residual disease impacts on duration of response and survival of patients with acute myeloid leukemia. Leukemia, 20, 17831789.
  • Buccisano, F., Maurillo, L., Spagnoli, A., Del Principe, M.I., Ceresoli, E., Lo Coco, F., Arcese, W., Amadori, S. & Venditti, A. (2009) Monitoring of minimal residual disease in acute myeloid leukemia. Review. Current Opinion in Oncology, 21, 582588.
  • Campana, D. (2003) Determination of minimal residual disease in leukaemia patients. Review. British Journal of Haematology, 121, 823838.
  • ten Cate, B., de Bruyn, M., Wei, Y., Bremer, E. & Helfrich, W. (2010) Targeted elimination of leukemia stem cells; a new therapeutic approach in hemato-oncology. Current Drug Targets, 11, 95110. Review.
  • Cesana, C., Klersy, C., Brando, B., Nosari, A., Scarpati, B., Scampini, L., Molteni, A., Nador, G., Santoleri, L., Formenti, M., Valentini, M., Mazzone, A., Morra, E. & Cairoli, R. (2008) Prognostic value of circulating CD34+ cells in myelodysplastic syndromes. Leukemia Research, 32, 17151723.
  • Chang, H., Yeung, J., Brandwein, J. & Yi, Q. (2007) CD7 expression predicts poor disease free survival and post-remission survival in patients with acute myeloid leukemia and normal karyotype. Leukemia Research, 31, 157162.
  • Cilloni, D., Renneville, A., Hermitte, F., Hills, R.K., Daly, S., Jovanovic, J.V., Gottardi, E., Fava, M., Schnittger, S., Weiss, T., Izzo, B., Nomdedeu, J., van der Heijden, A., van der Reijden, B.A., Jansen, J.H., van der Velden, V.H., Ommen, H., Preudhomme, C., Saglio, G. & Grimwade, D. (2009) Real-time quantitative polymerase chain reaction detection of minimal residual disease by standardized WT1 assay to enhance risk stratification in acute myeloid leukemia: a European LeukemiaNet study. Journal of Clinical Oncology, 27, 51955201.
  • Civin, C.I. & Loken, M.R. (1987) Cell surface antigens on human marrow cells: dissection of hematopoietic development using monoclonal antibodies and multiparameter flow cytometry. International Journal of Cell Cloning, 5, 267288.
  • Cloos, J., Goemans, B.F., Hess, C.J., van Oostveen, J.W., Waisfisz, Q., Corthals, S., de Lange, D., Boeckx, N., Hählen, K., Reinhardt, D., Creutzig, U., Schuurhuis, G.J., Zwaan, Ch.M. & Kaspers, G.J. (2006) Stability and prognostic influence of FLT3 mutations in paired initial and relapsed AML samples. Leukemia, 20, 12171220.
  • Coustan-Smith, E., Ribeiro, R.C., Rubnitz, J.E., Razzouk, B.I., Pui, C.H., Pounds, S., Andreansky, M., Behm, F.G., Raimondi, S.C., Shurtleff, S.A., Downing, J.R. & Campana, D. (2003) Clinical significance of residual disease during treatment in childhood acute myeloid leukaemia. British Journal of Haematology, 123, 243252.
  • Craig, F.E. & Foon, K.A. (2008) Flow cytometric immunophenotyping for hematologic neoplasms. Blood, 111, 39413967.
  • Del Cañizo, M.C., Fernández, M.E., López, A., Vidriales, B., Villarón, E., Arroyo, J.L., Ortuño, F., Orfao, A. & San Miguel, J.F. (2003) Immunophenotypic analysis of myelodysplastic syndromes. Haematologica, 88, 402407.
  • Díez-Campelo, M., Pérez-Simón, J.A., Pérez, J., Alcoceba, M., Richtmon, J., Vidriales, B. & San Miguel, J. (2009) Minimal residual disease monitoring after allogeneic transplantation may help to individualize post-transplant therapeutic strategies in acute myeloid malignancies. American Journal of Hematology, 84, 149152.
  • Döhner, H., Estey, E.H., Amadori, S., Appelbaum, F.R., Büchner, T., Burnett, A.K., Dombret, H., Fenaux, P., Grimwade, D., Larson, R.A., Lo-Coco, F., Naoe, T., Niederwieser, D., Ossenkoppele, G.J., Sanz, M.A., Sierra, J., Tallman, M.S., Löwenberg, B. & Bloomfield, C.D. (2010) European Leukemianet diagnosis and management of acute myeloid leukemia in adults: recommendations from an international expert panel, on behalf of the European LeukemiaNet. Review. Blood, 115, 453474.
  • Dunphy, C.H. (1999) Comprehensive review of adult acute myelogenous leukemia: cytomorphological, enzyme cytochemical, flow cytometric immunophenotypic, and cytogenetic findings. Journal of Clinical Laboratory Analysis, 13, 1926.
  • Elghetany, M.T. (2002) Surface antigen changes during normal neutrophilic development: a critical review. Blood Cells, Molecules, and Diseases, 28, 260274.
  • Falini, B., Mecucci, C., Tiacci, E., Alcalay, M., Rosati, R., Pasqualucci, L., La Starza, R., Diverio, D., Colombo, E., Santucci, A., Bigerna, B., Pacini, R., Pucciarini, A., Liso, A., Vignetti, M., Fazi, P., Meani, N., Pettirossi, V., Saglio, G., Mandelli, F., Lo-Coco, F., Pelicci, P.G. & Martelli, M.F. (2005) Cytoplasmic nucleophosmin in acute myelogenous leukemia with a normal karyotype. New England Journal of Medicine, 352, 254256.
  • Feller, N., Schuurhuis, G.J., van der Pol, M.A., Westra, G., Weijers, G.W., van Stijn, A., Huijgens, P.C. & Ossenkoppele, G.J. (2003) High percentage of CD34-positive cells in autologous AML peripheral blood stem cell products reflects inadequate in vivo purging and low chemotherapeutic toxicity in a subgroup of patients with poor clinical outcome. Leukemia, 17, 6875.
  • Feller, N., van der Pol, M.A., van Stijn, A., Weijers, G.W., Westra, A.H., Evertse, B.W., Ossenkoppele, G.J. & Schuurhuis, G.J. (2004) MRD parameters using immunophenotypic detection methods are highly reliable in predicting survival in acute myeloid leukaemia. Leukemia, 18, 13801390.
  • Feller, N., Jansen-van der Weide, M.C., van der Pol, M.A., Westra, G.A., Ossenkoppele, G.J. & Schuurhuis, G.J. (2005) Purging of peripheral blood stem cell transplants in AML: a predictive model based on minimal residual disease burden. Experimental Hematology, 33, 120130.
  • Gianfaldoni, G., Mannelli, F., Baccini, M., Antonioli, E., Leoni, F. & Bosi, A. (2006) Clearance of leukaemic blasts from peripheral blood during standard induction treatment predicts the bone marrow response in acute myeloid leukaemia: a pilot study. British Journal of Haematology, 134, 5457.
  • Goardon, N., Nikolousis, E., Sternberg, A., Chu, W.K., Craddock, C., Richardson, P., Benson, R., Drayson, M., Standen, G., Vyas, P. & Freeman, S. (2009) Reduced CD38 expression on CD34+ cells as a diagnostic test in myelodysplastic syndromes. Haematologica, 94, 11601163.
  • Gorin, N.C., Labopin, M., Reiffers, J., Milpied, N., Blaise, D., Witz, F., de Witte, T., Meloni, G., Attal, M., Bernal, T. & Rocha, V. (2010) Higher incidence of relapse for acute myelocytic leukemia patients infused with higher doses of CD34+ cells from leukapheresis products autografted during the first remission. Blood, 116, 31573162.
  • Grimwade, D., Jovanovic, J.V., Hills, R.K., Nugent, E.A., Patel, Y., Flora, R., Diverio, D., Jones, K., Aslett, H., Batson, E., Rennie, K., Angell, R., Clark, R.E., Solomon, E., Lo-Coco, F., Wheatley, K. & Burnett, A.K. (2009) Prospective minimal residual disease monitoring to predict relapse of acute promyelocytic leukemia and to direct pre-emptive arsenic trioxide therapy. Journal of Clinical Oncology, 27, 36503658.
  • Grimwade, D., Vyas, P. & Freeman, S. (2010a) Assessment of minimal residual disease in acute myeloid leukemia. Current Opinion in Oncology, 22, 656663.
  • Grimwade, D., Hills, R.K., Moorman, A.V., Walker, H., Chatters, S., Goldstone, A.H., Wheatley, K., Harrison, C.J. & Burnett, A.K. (2010b) Refinement of cytogenetic classification in acute myeloid leukemia: determination of prognostic significance of rare recurring chromosomal abnormalities among 5876 younger adult patients treated in the United Kingdom Medical Research Council trials. Blood, 116, 354365.
  • Gröschel, S., Lugthart, S., Schlenk, R.F., Valk, P.J., Eiwen, K., Goudswaard, C., van Putten, W.J., Kayser, S., Verdonck, L.F., Lübbert, M., Ossenkoppele, G.J., Germing, U., Schmidt-Wolf, I., Schlegelberger, B., Krauter, J., Ganser, A., Döhner, H., Löwenberg, B., Döhner, K. & Delwel, R. (2010) High EVI1 expression predicts outcome in younger adult patients with acute myeloid leukemia and is associated with distinct cytogenetic abnormalities. Journal of Clinical Oncology, 28, 21012107.
  • Haferlach, C., Mecucci, C., Schnittger, S., Kohlmann, A., Mancini, M., Cuneo, A., Testoni, N., Rege-Cambrin, G., Santucci, A., Vignetti, M., Fazi, P., Martelli, M.P., Haferlach, T. & Falini, B. (2009) AML with mutated NPM1 carrying a normal or aberrant karyotype show overlapping biologic, pathologic, immunophenotypic, and prognostic features. Blood, 114, 30243032.
  • Hanson, C.A., Abaza, M., Sheldon, S., Ross, C.W., Schnitzer, B. & Stoolman, L.M. (1993) Acute biphenotypic leukaemia: immunophenotypic and cytogenetic analysis. British Journal of Haematology, 84, 4960.
  • Hellström-Lindberg, E., Gulbrandsen, N., Lindberg, G., Ahlgren, T., Dahl, I.M., Dybedal, I., Grimfors, G., Hesse-Sundin, E., Hjorth, M., Kanter-Lewensohn, L., Linder, O., Luthman, M., Löfvenberg, E., Oberg, G., Porwit-MacDonald, A., Rådlund, A., Samuelsson, J., Tangen, J.M., Winquist, I. & Wisloff, F.; Scandinavian MDS Group (1997) Erythroid response to treatment with G-CSF plus erythropoietin for the anaemia of patients with myelodyplastic syndromes: proposal for a predictive model. British Journal of Haematology, 99, 344351.
  • Hellström-Lindberg, E., Gulbrandsen, N., Lindberg, G., Ahlgren, T., Dahl, I.M., Dybedal, I., Grimfors, G., Hesse-Sundin, E., Hjorth, M., Kanter-Lewensohn, L., Linder, O., Luthman, M., Löfvenberg, E., Oberg, G., Porwit-MacDonald, A., Rådlund, A., Samuelsson, J., Tangen, J.M., Winquist, I. & Wisloff, F.A. (2003) A validated decision model for treating the anaemia of myelodysplastic syndromes with erythropoietin + granulocyte colony-stimulating factor: significant effects on quality of life. British Journal of Haematology, 120, 10371046.
  • Hess, C.J., Feller, N., Denkers, F., Kelder, A., Merle, P.A., Heinrich, M.C., Harlow, A., Berkhof, J., Ossenkoppele, G.J., Waisfisz, Q. & Schuurhuis, G.J. (2009) Correlation of minimal residual disease cell frequency with molecular genotype in patients with acute myeloid leukemia. Haematologica, 94, 4653.
  • Hokland, P., Kerndrup, G., Griffin, J.D. & Ellegaard, J. (1986) Analysis of leukocyte differentiation antigens in blood and bone marrow from preleukemia (refractory anemia) patients using monoclonal antibodies. Blood, 67, 898902.
  • Kanda, Y., Hamaki, T., Yamamoto, R., Chizuka, A., Suguro, M., Matsuyama, T., Takezako, N., Miwa, A., Kami, M., Hirai, H. & Togawa, A. (2000) 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, 88, 25292533.
  • Keating, S., Suciu, S., de Witte, T., Zittoun, R., Mandelli, F., Belhabri, A., Amadori, S., Fibbe, W., Gallo, E., Fillet, G., Varet, B., Meloni, G., Hagemeijer, A., Fazi, P., Solbu, G. & Willemze, R.; EORTC Leukemia Group; GIMEMA Leukemia Group (2003) The stem cell mobilizing capacity of patients with acute myeloid leukemia in complete remission correlates with relapse risk: results of the EORTC-GIMEMA AML-10 trial. Leukemia, 17, 6067.
  • Kern, W., Danhauser-Riedl, S., Ratei, R., Schnittger, S., Schoch, C., Kolb, H.J., Ludwig, W.D., Hiddemann, W. & Haferlach, T. (2003) Detection of minimal residual disease in unselected patients with acute myeloid leukemia using multiparameter flow cytometry for definition of leukemia-associated immunophenotypes and determination of their frequencies in normal bone marrow. Haematologica, 88, 646653.
  • Kern, W., Voskova, D., Schoch, C., Hiddeman, W., Schnittger, S. & Haferlach, T. (2004a) Determination of relapse risk based on assessment of minimal residual disease during complete remission by multiparameter flow cytometry in unselected patients with acute leukemia. Blood, 104, 30783085.
  • Kern, W., Voskova, D., Schoch, C., Schnittger, S., Hiddemann, W. & Haferlach, T. (2004b) Prognostic impact of early response to induction therapy as assessed by multiparameter flow cytometry in acute myeloid leukemia. Haematologica, 89, 528540.
  • Kern, W., Haferlach, C., Haferlach, T. & Schnittger, S. (2008) Monitoring of minimal residual disease in acute myeloid leukemia. Cancer, 112, 416.
  • Kern, W., Haferlach, C., Bacher, U., Haferlach, T. & Schnittger, S. (2009) Flow cytometric identification of acute myeloid leukemia with limited differentiation and NPM1 type A mutation: a new biologically defined entity. Leukemia, 23, 13611364.
  • Khoury, H., Dalal, B.I., Nevill, T.J., Horsman, D.E., Barnett, M.J., Shepherd, J.D., Toze, C.L., Conneally, E.A., Sutherland, H.J., Hogge, D.E. & Nantel, S.H. (2003) Acute myelogenous leukemia with t(8;21) – identification of a specific immunophenotype. Leukaemia & Lymphoma, 44, 17131718.
  • Knipp, S., Strupp, C., Gattermann, N., Hildebrandt, B., Schapira, M., Giagounidis, A., Aul, C., Haas, R. & Germing, U. (2008) Presence of peripheral blasts in refractory anemia and refractory cytopenia with multilineage dysplasia predicts an unfavourable outcome. Leukemia Research, 32, 3337.
  • Kottaridis, P.D., Gale, R.E., Langabeer, S.E., Frew, M.E., Bowen, D.T. & Linch, D.C. (2002) Studies of FLT3 mutations in paired presentation and relapse samples from patients with acute myeloid leukemia: implications for the role of FLT3 mutations in leukemogenesis, minimal residual disease detection, and possible therapy with FLT3 inhibitors. Blood, 100, 23932398.
  • Krause, D.S. & Van Etten, R.A. (2007) Right on target: eradicating leukemic stem cells. Trends in Molecular Medicine, 13, 470481.
  • Kussick, S.J., Fromm, J.R., Rossini, A., Li, Y., Chang, A., Norwood, T.H. & Wood, B.L. (2005) Four-color flow cytometry shows strong concordance with bone marrow morphology and cytogenetics in the evaluation for myelodysplasia. American Journal of Clinical Pathology, 124, 170181.
  • Laane, E., Derolf, A.R., Björklund, E., Mazur, J., Everaus, H., Söderhäll, S., Björkholm, M. & Porwit-MacDonald, A. (2006) The effect of allogeneic stem cell transplantation on outcome in younger acute myeloid leukemia patients with minimal residual disease detected by flow cytometry at the end of post-remission chemotherapy. Haematologica, 91, 833836.
  • Lacombe, F., Arnoulet, C., Maynadié, M., Lippert, E., Luquet, I., Pigneux, A., Vey, N., Casasnovas, O., Witz, F. & Béné, M.C. (2009) Early clearance of peripheral blasts measured by flow cytometry during the first week of AML induction therapy as a new independent prognostic factor: a GOELAMS study. Leukemia, 23, 350357.
  • Langebrake, C., Brinkmann, I., Teigler-Schlegel, A., Creutzig, U., Griesinger, F., Puhlmann, U. & Reinhardt, D. (2005) Immunophenotypic differences between diagnosis and relapse in childhood AML: implications for MRD monitoring. Cytometry. Part B, Clinical Cytometry, 63, 19.
  • Langebrake, C., Creutzig, U., Dworzak, M., Hrusak, O., Mejstrikova, E., Griesinger, F., Zimmermann, M. & Reinhardt, D. (2006) Residual disease monitoring in childhood acute myeloid leukemia by multiparameter flow cytometry: the MRD-AML-BFM Study Group. Journal of Clinical Oncology, 24, 36863692.
  • Lee, E.J., Yang, L., Leavitt, R.D., Testa, J.R., Civin, C.I. & Forrest, A. (1992) The significance of CD34 and TdT determinations in patients with untreated de novo acute myeloid leukemia. Leukemia, 6, 12031209.
  • Legrand, O., Perrot, J.Y., Simonin, G., Baudard, M., Cadiou, M., Blanc, C., Ramond, S., Viguié, F., Marie, J.P. & Zittoun, R. (1998) Adult biphenotypic acute leukaemia: an entity with poor prognosis which is related to unfavourable cytogenetics and P-glycoprotein over-expression. British Journal of Haematology, 100, 147155.
  • van Lochem, E.G., van der Velden, V.H., Wind, H.K., te Marvelde, J.G., Westerdaal, N.A. & van Dongen, J.J. (2004) Immunophenotypic differentiation patterns of normal hematopoiesis in human bone marrow: reference patterns for age-related and disease-induced shifts. Cytometry. Part B, Clinical Cytometry, 60, 113.
  • Loken, M.R., van de Loosdrecht, A., Ogata, K., Orfao, A. & Wells, D.A. (2008) Flow cytometry in myelodysplastic syndromes: report from a working conference. Leukemia Research, 32, 517.
  • van de Loosdrecht, A.A., Westers, T.M., Westra, A.H., Dräger, A.M., van der Velden, V.H. & Ossenkoppele, G.J. (2008) Identification of distinct prognostic subgroups in low and intermediate-1 risk myelodysplastic syndromes by flow cytometry. Blood, 111, 10671077.
  • van de Loosdrecht, A.A., Alhan, C., Béné, M.C., Della Porta, M.G., Dräger, A.M., Feuillard, J., Font, P., Germing, U., Haase, D., Homburg, C.H., Ireland, R., Jansen, J.H., Kern, W., Malcovati, L., Te Marvelde, J.G., Mufti, G.J., Ogata, K., Orfao, A., Ossenkoppele, G.J., Porwit, A., Preijers, F.W., Richards, S.J., Schuurhuis, G.J., Subirá, D., Valent, P., van der Velden, V.H., Vyas, P., Westra, A.H., de Witte, T.M., Wells, D.A., Loken, M.R. & Westers, T.M. (2009) Standardization of flow cytometry in myelodysplastic syndromes: report from the first European LeukemiaNet working conference on flow cytometry in myelodysplastic syndromes. Haematologica, 94, 11241134.
  • Lorand-Metze, I., Califani, S.M., Ribeiro, E., Lima, C.S. & Metze, K. (2008) The prognostic value of maturation-associated phenotypic abnormalities in myelodysplastic syndromes. Leukemia Research, 32, 211213.
  • Lucio, P., Gaipa, G., van Lochem, E.G., van Wering, E.R., Porwit-MacDonald, A., Faria, T., Bjorklund, E., Biondi, A., van den Beemd, M.W., Baars, E., Vidriales, B., Parreira, A., van Dongen, J.J., San Miguel, J.F. & Orfao, A.; BIOMED-I (2001) BIOMED-I concerted action report: flow cytometric immunophenotyping of precursor B-ALL with standardized triple-stainings. BIOMED-1 Concerted Action Investigation of Minimal Residual Disease in Acute Leukemia: International Standardization and Clinical Evaluation. Leukemia, 15, 11851192.
  • Malcovati, L., Della Porta, M.G., Lunghi, M., Pascutto, C., Vanelli, L., Travaglino, E., Maffioli, M., Bernasconi, P., Lazzarino, M., Invernizzi, R. & Cazzola, M. (2005a) Flow cytometry evaluation of erythroid and myeloid dysplasia in patients with myelodysplastic syndrome. Leukemia, 19, 776783.
  • Malcovati, L., Porta, M.G., Pascutto, C., Invernizzi, R., Boni, M., Travaglino, E., Passamonti, F., Arcaini, L., Maffioli, M., Bernasconi, P., Lazzarino, M. & Cazzola, M. (2005b) Prognostic factors and life expectancy in myelodysplastic syndromes classified according to WHO criteria: a basis for clinical decision making. Journal of Clinical Oncology, 23, 75947603.
  • Marcucci, G., Caligiuri, M.A., Döhner, H., Archer, K.J., Schlenk, R.F., Döhner, K., Maghraby, E.A. & Bloomfield, C.D. (2001) Quantification of CBFbeta/MYH11 fusion transcript by real time RT-PCR in patients with INV(16) acute myeloid leukemia. Leukemia, 15, 10721080.
  • Matarraz, S., López, A., Barrena, S., Fernandez, C., Jensen, E., Flores, J., Bárcena, P., Rasillo, A., Sayagues, J.M., Sánchez, M.L., Hernandez-Campo, P., Hernandez Rivas, J.M., Salvador, C., Fernandez-Mosteirín, N., Giralt, M., Perdiguer, L. & Orfao, A. (2008) The immunophenotype of different immature, myeloid and B-cell lineage-committed CD34+ hematopoietic cells allows discrimination between normal/reactive and myelodysplastic syndrome precursors. Leukemia, 22, 11751183.
  • Matarraz, S., López, A., Barrena, S., Fernandez, C., Jensen, E., Flores-Montero, J., Rasillo, A., Sayagues, J.M., Sánchez, M.L., Bárcena, P., Hernandez-Rivas, J.M., Salvador, C., Fernandez-Mosteirín, N., Giralt, M., Perdiguer, L., Laranjeira, P., Paiva, A. & Orfao, A. (2010) Bone marrow cells from myelodysplastic syndromes show altered immunophenotypic profiles that may contribute to the diagnosis and prognostic stratification of the disease: a pilot study on a series of 56 patients. Cytometry. Part B, Clinical Cytometry, 78, 154168.
  • Maurillo, L., Buccisano, F., Spagnoli, A., Del Poeta, G., Panetta, P., Neri, B., Del Principe, M.I., Mazzone, C., Consalvo, M.I., Tamburini, A., Ottaviani, L., Fraboni, D., Sarlo, C., De Fabritiis, P., Amadori, S. & Venditti, A. (2007) Monitoring of minimal residual disease in adult acute myeloid leukemia using peripheral blood as an alternative source to bone marrow. Haematologica, 92, 605611.
  • Maurillo, L., Buccisano, F., Del Principe, M.I., Del Poeta, G., Spagnoli, A., Panetta, P., Ammatuna, E., Neri, B., Ottaviani, L., Sarlo, C., Venditti, D., Quaresima, M., Cerretti, R., Rizzo, M., de Fabritiis, P., Lo Coco, F., Arcese, W., Amadori, S. & Venditti, A. (2008) Toward optimization of postremission therapy for residual disease-positive patients with acute myeloid leukemia. Journal of Clinical Oncology, 26, 49444951.
  • Maynadié, M., Picard, F., Husson, B., Chatelain, B., Cornet, Y., Le Roux, G., Campos, L., Dromelet, A., Lepelley, P., Jouault, H., Imbert, M., Rosenwadj, M., Vergé, V., Bissières, P., Raphaël, M., Béné, M.C. & Feuillard, J. (2002) Immunophenotypic clustering of myelodysplastic syndromes. Blood, 100, 23492356.
  • Medeiros, B.C., Kohrt, H.E., Arber, D.A., Bangs, C.D., Cherry, A.M., Majeti, R., Kogel, K.E., Azar, C.A., Patel, S. & Alizadeh, A.A. (2010) Immunophenotypic features of acute myeloid leukemia with inv(3)(q21q26.2)/t(3;3)(q21;q26.2). Leukemia Research, 34, 594597.
  • Nakahata, T. & Okumura, N. (1994) Cell surface antigen expression in human erythroid progenitors: erythroid and megakaryocytic markers. Leukaemia & Lymphoma, 13, 401409.
  • Nakamura, K., Ogata, K., An, E. & Dan, K. (2000) Flow cytometric assessment of CD15+ CD117+ cells for the detection of minimal residual disease in adult acute myeloid leukaemia. British Journal of Haematology, 108, 710716.
  • Nomdedeu, J., Bussaglia, E., Villamor, N., Martinez, C., Esteve, J., Tormo, M., Estivill, C., Queipo, M.P., Guardia, R., Carricondo, M., Hoyos, M., Llorente, A., Juncà, J., Gallart, M., Domingo, A., Bargay, J., Mascaró, M., Moraleda, J.M., Florensa, L., Ribera, J.M., Gallardo, D., Brunet, S., Aventin, A. & Sierra, J., on behalf of the Spanish CETLAM (2010) Immunophenotype of acute myeloid leukemia with NPM mutations: prognostic impact of the leukemic compartment size. Leukemia Research, 7, 7. [Epub ahead of print. doi: 10.1016/j.leukres.2010.05.015].
  • Ogata, K., Yokose, N., Shioi, Y., Ishida, Y., Tomiyama, J., Hamaguchi, H., Yagasaki, F., Bessyo, M., Sakamaki, H., Dan, K. & Kuriya, S. (2001) Reappraisal of the clinical significance of CD7 expression in association with cytogenetics in de novo acute myeloid leukaemia. British Journal of Haematology. 115, 612615.
  • Ogata, K., Della Porta, M.G., Malcovati, L., Picone, C., Yokose, N., Matsuda, A., Yamashita, T., Tamura, H., Tsukada, J. & Dan, K. (2009) Diagnostic utility of flow cytometry in low-grade myelodysplastic syndromes: a prospective validation study. Haematologica, 94, 10661074.
  • Ommen, H.B., Nyvold, C.G., Braendstrup, K., Andersen, B.L., Ommen, I.B., Hasle, H., Hokland, P. & Ostergaard, M. (2008) Relapse prediction in acute myeloid leukaemia patients in complete remission using WT1 as a molecular marker: development of a mathematical model to predict time from molecular to clinical relapse and define optimal sampling intervals. British Journal of Haematology, 141, 782791.
  • Paietta, E., Goloubeva, O., Neuberg, D., Bennett, J.M., Gallagher, R., Racevskis, J., Dewald, G., Wiernik, P.H. & Tallman, M.S. (2004) Eastern Cooperative Oncology Group. A surrogate marker profile for PML/RAR alpha expressing acute promyelocytic leukemia and the association of immunophenotypic markers with morphologic and molecular subtype. Cytometry. Part B, Clinical Cytometry, 59, 19.
  • Pedreira, C.E., Costa, E.S., Arroyo, M.E., Almeida, J. & Orfao, A.A. (2008) Multidimensional classification approach for the automated analysis of flow cytometry data. IEEE Transactions on Biomedical Engineering, 55, 11551162.
  • Perea, G., Lasa, A., Aventín, A., Domingo, A., Villamor, N., Queipo de Llano, M.P., Llorente, A., Juncà, J., Palacios, C., Fernández, C., Gallart, M., Font, L., Tormo, M., Florensa, L., Bargay, J., Martí, J.M., Vivancos, P., Torres, P., Berlanga, J.J., Badell, I., Brunet, S., Sierra, J. & Nomdedéu, J.F.; Grupo Cooperativo para el Estudio y Tratamiento de las Leucemias Agudas y Miel (2006) Prognostic value of minimal residual disease (MRD) in acute myeloid leukemia (AML) with favorable cytogenetics [t(8;21) and inv(16)]. Leukemia, 20, 8794.
  • Pirruccello, S.J., Young, K.H. & Aoun, P. (2006) Myeloblast phenotypic changes in myelodysplasia. CD34 and CD117 expression abnormalities are common. American Journal of Clinical Pathology, 125, 884894.
  • van der Pol, M.A., Broxterman, H.J., Pater, J.M., Feller, N., van der Maas, M., Weijers, G.W., Scheffer, G.L., Allen, J.D., Scheper, R.J., van Loevezijn, A., Ossenkoppele, G.J. & Schuurhuis, G.J. (2003) Function of the ABC transporters, P-glycoprotein, multidrug resistance protein and breast cancer resistance protein, in minimal residual disease in acute myeloid leukemia. Haematologica, 88, 134147.
  • Porwit-MacDonald, A., Björklund, E., Lucio, P., van Lochem, E.G., Mazur, J., Parreira, A., van den Beemd, M.W., van Wering, E.R., Baars, E., Gaipa, G., Biondi, A., Ciudad, J., van Dongen, J.J., San Miguel, J.F. & Orfao, A. (2000) BIOMED-1 concerted action report: flow cytometric characterization of CD7+ cell subsets in normal bone marrow as a basis for the diagnosis and follow-up of T cell acute lymphoblastic leukemia (T-ALL). Leukemia, 14, 8, 16125.
  • Raspadori, D.F., Lauria, M.A., Ventura, D., Rondelli, G., Visani de Vivo, A. & Tura, S. (1997) Incidence and prognostic relevance of CD34 expression in acute myeloid leukemia: analysis in 141 cases. Leukemia Research, 137, 966971.
  • Raspadori, D., Damiani, D., Lenoci, M., Rondelli, D., Testoni, N., Nardi, G., Sestigiani, C., Mariotti, C., Birtolo, S., Tozzi, M. & Lauria, F. (2001) CD56 antigenic expression in acute myeloid leukemia identifies patients with poor clinical prognosis. Leukemia, 15, 11611164.
  • Raspadori, D., Damiani, D., Michieli, M., Stocchi, R., Gentili, S., Gozzetti, A., Masolini, P., Michelutti, A., Geromin, A., Fanin, R. & Lauria, F. (2002) PGP expression in acute myeloid leukemia: impact on clinical outcome. Haematologica, 87, 11351140.
  • van Rhenen, A., Feller, N., Kelder, A., Westra, A.H., Rombouts, E., Zweegman, S., van der Pol, M.A., Waisfisz, Q., Ossenkoppele, G.J. & Schuurhuis, G.J. (2005) High stem cell frequency in acute myeloid leukemia at diagnosis predicts high minimal residual disease and poor survival. Clinical Cancer Research, 11, 65206527.
  • van Rhenen, A., van Dongen, G.A., Kelder, A., Rombouts, E.J., Feller, N., Moshaver, B., Stigter-van Walsum, M., Zweegman, S., Ossenkoppele, G.J. & Schuurhuis, G.J. (2007) The novel AML stem cell associated antigen CLL-1 aids in discrimination between normal and leukemic stem cells. Blood, 110, 26592666.
  • Rubnitz, J.E., Inaba, H., Dahl, G., Ribeiro, R.C., Bowman, W.P., Taub, J., Pounds, S., Razzouk, B.I., Lacayo, N.J., Cao, X., Meshinchi, S., Degar, B., Airewele, G., Raimondi, S.C., Onciu, M., Coustan-Smith, E., Downing, J.R., Leung, W., Pui, C.H. & Campana, D. (2010) Minimal residual disease-directed therapy for childhood acute myeloid leukaemia: results of the AML02 multicentre trial. The Lancet Oncology, 11, 543552.
  • Saito, Y., Kitamura, H., Hijikata, A., Tomizawa-Murasawa, M., Tanaka, S., Takagi, S., Uchida, N., Suzuki, N., Sone, A., Najima, Y., Ozawa, H., Wake, A., Taniguchi, S., Shultz, L.D., Ohara, O. & Ishikawa, F. (2010) Identification of therapeutic targets for quiescent, chemotherapy-resistant human leukemia stem cells. Science Translational Medicine, 3, 17ra9.
  • San Miguel, J.F., Martinez, A., Macedo, A., Vidriales, M.B., López-Berges, C., González, M., Caballero, D., García-Marcos, M.A., Ramos, F., Fernández-Calvo, J., Calmuntia, M.J., Diaz-Mediavilla, J. & Orfao, A. (1997) Immunophenotyping investigation of minimal residual disease is a useful approach for predicting relapse in acute myeloid leukemia patients. Blood, 90, 24652470.
  • San Miguel, J.F., Vidriales, M.B., Lopez Berges, C., Díaz-Mediavilla, J., Gutiérrez, N., Cañizo, C., Ramos, F., Calmuntia, M.J., Pérez, J.J., González, M. & Orfao, A. (2001) Early immunophenotypical evaluation of minimal residual disease in acute myeloid leukemia identifies different patient risk groups and may contribute to postinduction treatment stratification. Blood, 98, 17461751.
  • Sanz, M.A., Grimwade, D., Tallman, M.S., Lowenberg, B., Fenaux, P., Estey, E.H., Naoe, T., Lengfelder, E., Büchner, T., Döhner, H., Burnett, A.K. & Lo-Coco, F. (2009) Management of acute promyelocytic leukemia: recommendations from an expert panel on behalf of the European Leukemianet. Blood, 113, 18751891.
  • Satoh, C. & Ogata, K. (2008) Flow cytometric parameters with little interexaminer variability for diagnosing low-grade myelodysplastic syndromes. Leukemia Research, 32, 699707.
  • Schnittger, S., Kern, W., Tschulik, C., Weiss, T., Dicker, F., Falini, B., Haferlach, C. & Haferlach, T. (2009) Minimal residual disease levels assessed by NPM1 mutation-specific RQ-PCR provide important prognostic information in AML. Blood, 114, 22202231.
  • Scott, B.L., Wells, D.A., Loken, M.R., Myerson, D., Leisenring, W.M. & Deeg, H.J. (2008) Validation of a flow cytometric scoring system as a prognostic indicator for posttransplantation outcome in patients with myelodysplastic syndrome. Blood, 112, 26812686.
  • Sievers, E.L., Lange, B.J., Alonzo, T.A., Gerbing, R.B., Bernstein, I.D., Smith, F.O., Arceci, R.J., Woods, W.G. & Loken, M.R. (2003) Immunophenotypic evidence of leukemia after induction therapy predicts relapse: results from a prospective Children’s Cancer Group study of 252 patients with acute myeloid leukemia. Blood, 101, 33983406.
  • Stachurski, D., Smith, B.R., Pozdnyakova, O., Andersen, M., Xiao, Z., Raza, A., Woda, B.A. & Wang, S.A. (2008) Flow cytometric analysis of myelomonocytic cells by a pattern recognition approach is sensitive and specific in diagnosing myelodysplastic syndrome and related diseases: emphasis on a global evaluation and recognition of diagnostic pitfalls. Leukemia Research, 32, 215224.
  • Stetler-Stevenson, M., Arthur, D.C., Jabbour, N., Xie, X.Y., Molldrem, J., Barrett, A.J., Venzon, D. & Rick, M.E. (2001) Diagnostic utility of flow cytometric immunophenotyping in myelodysplastic syndrome. Blood, 98, 979987.
  • van Stijn, A., Feller, N., Kok, A., van der Pol, M.A., Ossenkoppele, G.J. & Schuurhuis, G.J. (2005) Minimal residual disease in acute myeloid leukemia is predicted by an apoptosis-resistant protein profile at diagnosis. Clinical Cancer Research, 11, 25402546.
  • Suzuki, R., Ohtake, S., Takeuchi, J., Nagai, M., Kodera, Y., Hamaguchi, M., Miyawaki, S., Karasuno, T., Shimodaira, S., Ohno, R., Nakamura, S. & Naoe, T. (2010) The clinical characteristics of CD7CD56+ acute myeloid leukemias other than M0. International Journal of Hematology, 91, 303309.
  • Swerdlow, S.H., Capo, E., Harris, N.L., Jaffe, E.S., Pileri, S.A., Stein, H., Thiele, J. & Vardiman, J.W. (eds) (2008) WHO Classification of Tumours of Haematopoietic and Lymphoid Tissues. IARC, Lyon.
  • Taussig, D.C., Vargaftig, J., Miraki-Moud, F., Griessinger, E., Sharrock, K., Luke, T., Lillington, D., Oakervee, H., Cavenagh, J., Agrawal, S.G., Lister, T.A., Gribben, J.G. & Bonnet, D. (2010) Leukemia-initiating cells from some acute myeloid leukemia patients with mutated nucleophosmin reside in the CD34(−) fraction. Blood, 115, 19761984.
  • Terwijn, M., Feller, N., van Rhenen, A., Kelder, A., Westra, A.H., Zweegman, S., Ossenkoppele, G. & Schuurhuis, G.J. (2009) Interleukin-2 receptor alpha-chain (CD25) expression on leukaemic blasts is predictive for outcome and level of residual disease in AML. European Journal of Cancer, 45, 16921699.
  • Tiftik, N.Z., Bolaman, S., Batun, O., Ayyildiz, A., Isikdogan, A., Kadikoylu, G. & Muftuoglu, E. (2004) The importance of CD7 and CD56 antigens in acute leukaemias. International Journal of Clinical Practice, 58, 149152.
  • Valent, P., Horny, H.P., Bennett, J.M., Fonatsch, C., Germing, U., Greenberg, P., Haferlach, T., Haase, D., Kolb, H.J., Krieger, O., Loken, M., van de Loosdrecht, A., Ogata, K., Orfao, A., Pfeilstöcker, M., Rüter, B., Sperr, W.R., Stauder, R. & Wells, D.A. (2007) Definitions and standards in the diagnosis and treatment of the myelodysplastic syndromes: consensus statements and report from a working conference. Leukemia Research, 31, 727736.
  • Vardiman, J.W., Thiele, J., Arber, D.A., Brunning, R.D., Borowitz, M.J., Porwit, A., Harris, N.L., Le Beau, M.M., Hellström-Lindberg, E., Tefferi, A. & Bloomfield, C.D. (2009) The 2008 revision of the World Health Organization (WHO) classification of myeloid neoplasms and acute leukemia: rationale and important changes. Blood, 114, 937951.
  • van der Velden, V.H., Jacobs, D.C., Wijkhuijs, A.J., Comans-Bitter, W.M., Willemse, M.J., Hählen, K., Kamps, W.A., van Wering, E.R. & van Dongen, J.J. (2002) Minimal residual disease levels in bone marrow and peripheral blood are comparable in children with T cell acute lymphoblastic leukemia (ALL), but not in precursor-B-ALL. Leukemia, 16, 14321436.
  • van der Velden, V.H., van der Sluijs-Geling, A., Gibson, B.E., te Marvelde, J.G., Hoogeveen, P.G., Hop, W.C., Wheatley, K., Bierings, M.B., Schuurhuis, G.J., de Graaf, S.S., van Wering, E.R. & van Dongen, J.J. (2010) Clinical significance of flowcytometric minimal residual disease detection in pediatric acute myeloid leukemia patients treated according to the DCOG ANLL97/MRC AML12 protocol. Leukemia, 24, 15991606.
  • Venditti, A.G., Del Poeta, F., Buccisano, A., Tamburini, M.C., Cox-Froncillo, MC., Aronica, G., Bruno, A., Del Moro, B., Epiceno, A.M., Battaglia, A., Forte, L., Postorino, M., Cordero, V. & Santinelli, S. (1998) Prognostic relevance of the expression of Tdt and CD7 in 335 cases of acute myeloid leukemia. Leukemia, 12, 10561063.
  • Venditti, A., Buccisano, F., Del Poeta, G., Maurillo, L., Tamburini, A., Cox, C., Battaglia, A., Catalano, G., Del Moro, B., Cudillo, L., Postorino, M., Masi, M. & Amadori, S. (2000) Level of minimal residual disease after consolidation therapy predicts outcome in acute myeloid leukemia. Blood, 96, 39483952.
  • Venditti, A., Maurillo, L., Buccisano, F., del Poeta, G., Mazzone, C., Tamburini, A., del Principe, M.I., Consalvo, M.I., de Fabritiis, P., Cudillo, L., Picardi, A., Franchi, A., Lo-Coco, F. & Amadori, S. (2003) Pretransplant minimal residual disease level predicts clinical outcome in patients with acute myeloid leukemia receiving high-dose chemotherapy and autologous stem cell transplantation. Leukemia, 17, 21782182.
  • Voskova, D., Schoch, C., Schnittger, S., Hiddemann, W., Haferlach, T. & Kern, W. (2004) Stability of leukemia associated aberrant immunophenotypes in patients with acute leukemia between diagnosis and relapse: comparison with cytomorphologic, cytogenetic and molecular genetic findings. Cytometry, 62b, 2538.
  • Voskova, D., Schnittger, S., Schoch, C., Haferlach, T. & Kern, W. (2007) Use of five-color staining improves the sensitivity of multiparameter flow cytomeric assessment of minimal residual disease in patients with acute myeloid leukemia. Leukaemia & Lymphoma, 48, 8088.
  • Wells, D.A., Benesch, M., Loken, M.R., Vallejo, C., Myerson, D., Leisenring, W.M. & Deeg, H.J. (2003) Myeloid and monocytic dyspoiesis as determined by flow cytometric scoring in myelodysplastic syndrome correlates with the IPSS and with outcome after hematopoietic stem cell transplantation. Blood, 102, 394403.
  • Westers, T.M., Alhan, C., Chamuleau, M.E., van der Vorst, M.J., Eeltink, C., Ossenkoppele, G.J. & van de Loosdrecht, A.A. (2010) Aberrant immunophenotype of blasts in myelodysplastic syndromes is a clinically relevant biomarker in predicting response to growth factor treatment. Blood, 115, 17791784.
  • Yang, D.H., Lee, J.J., Mun, Y.C., Shin, H.J., Kim, Y.K., Cho, S.H., Chung, I.J., Seong, C.M. & Kim, H.J. (2007) Predictable prognostic factor of CD56 expression in patients with acute myeloid leukemia with t(8:21) after high dose cytarabine or allogeneic hematopoietic stem cell transplantation. American Journal of Hematology, 82, 15.