Overview of studies in adult AML with cut-off values used for analyzing relapse free and overall survival.
1. Introduction
Acute myeloid leukemia (AML) is the most common type of acute leukemia in adults. With current treatment strategies, almost 80% of AML patients (18-60 years) will achieve complete remission (CR). However, approximately 50% of these patients will experience a relapse, resulting in a five-year survival rate of only 35%-40% [1]
2. Minimal residual disease and acute myeloid leukemia
In AML patients, morphologic assessment is performed to evaluate chemotherapy response and to define remission status. By definition, patients are in CR when less than 5% blast cells are present in the bone marrow (BM) concurrent with evidence of normal erythropoiesis, granulopoiesis and megakaryopoiesis. In addition, neutrophils and platelets in peripheral blood should be at least 1.0 x 109/l and 100 x 109/l, respectively [2]
2.1. Immunophenotypic MRD detection
2.1.1. Principles of immunophenotypic MRD detection
One of the most frequently used techniques to assess MRD in leukemia is based on assessment of immunophenotypic aberrant antigen expression using flow cytometry. For practical purposes, in most cases, this approach is restricted to cell surface antigen expression. At diagnosis, so-called leukemia associated (immuno)phenotypes (LA[I]Ps, further referred to as LAPs) are determined. Such a LAP consists of (an) aberrantly expressed cell surface marker(s), usually combined with a myeloid marker (CD13/CD33) and with a normal progenitor antigen, i.e. CD34, CD117 or CD133. LAPs are grouped into (1) cross-lineage antigen expression (e.g. expression of lymphoid markers in myeloid blasts), (2) asynchronous antigen expression (co-expression of antigens that are not concomitantly present during normal differentiation), (3) lack of antigen expression and (4) antigen overexpression [3]. Such aberrancies can subsequently be used to detect MRD (Figure 2).
Due to large heterogeneity of immunophenotypes in AML, determination of LAPs has to be performed for each individual patient. These LAPs are not, or only in very low frequencies, present on normal BM cells in remission BM. Sensitivities have been reported to be in a range of 10-3 down to 10-5 (1 leukemic cell in 1,000 to 100,000 normal cells) [4-9]. Besides these relatively high sensitivities, it is also a very rapid technique. Main advantage of flow cytometric MRD assessment is its broad applicability: in 80%-95% of all AML patients one or more LAPs can be defined. [4,5,9-11]. There are, however, potential pitfalls/disadvantages that should be taken into account.
2.1.2. Prognostic value of immunophenotypic MRD in bone marrow
The likelihood of achieving CR after therapy and the duration of CR depend on different factors. Important prognostic risk factors available at diagnosis are: history of previous leukemia or myelodysplastic syndrome, age, white blood cell (WBC) count, percentage of BM blast cells and the presence of particular cytogenetic and/or molecular aberrancies [14]. Besides these pre-treatment prognostic factors, it is suggested that MRD detection in BM shortly after treatment offers an important post-treatment prognostic factor. To evaluate the impact of MRD frequencies on relapse rate and overall survival (OS), MRD was related to outcome parameters using survival analyses such as Kaplan Meier curves. For these analyses, most studies set a threshold to define MRD negative (or low) and MRD positive (or high) patients. Different laboratories use different optimal cut-off values after both induction and consolidation therapy (Table 1). However, it should be emphasized that usually, it is not a single cut-off point, but a range of cut-off values that significantly predict clinical outcome.
Author | Patients (n) | Cut-off post- induction |
Cut-off post-consolidation |
Reference |
San Miguel |
126 | <0.01%, 0.01-0.1%, 0.1-1%, >/1% |
not available | [15] |
Feller |
52 | 0.14% | 0.11% | [6] |
Kern |
62 | Log difference 1.70 | Log difference 2.94 |
[5] |
Maurillo |
142 | 0.035% | 0.035% | [16] |
Al-Mawali |
54 | 0.15% | 0.15% | [10] |
San Miguel
MRD level | Patients (n) | Relapse rate ± standard error |
< 0.1 % | 16 | 9% ± 7% |
0.1% - 1% | 45 | 56% ± 9% |
"/1% | 21 | 83% ± 10% |
Al-Mawali
2.2. Molecular MRD detection
Although flow cytometry is an attractive technique for MRD detection, the limitations, including background staining, immunophenotypic switches, complexity of analysis and LAP expression on only part of the leukemic cells, give rise to alternative approaches for MRD detection, including molecular MRD monitoring using the Polymerase Chain Reaction (PCR) technique. This approach allows for the detection of mutations, translocations, inversions, deletions and polymorphisms. Real-time-(qRT-) PCR is the most sensitive technique for MRD detection: it allows detecting MRD with sensitivities that have been reported in a range of 10-4 to 10-6 [18-21]. QRT-PCR is now extensively being studied as approach for MRD detection. Common targets for molecular MRD monitoring, including fusion genes, overexpressed genes and gene mutations, will be reviewed in this section.
2.2.1. Fusion genes
Fusion genes are among the best potential targets for molecular MRD detection. In AML the most common chromosomal rearrangements, producing fusion genes, are t(8;21), t(15;17) and inv(16)/t(16;16). The corresponding fusion genes are
In t(8;21) rearrangement, the AML1 gene on chromosome 21 fuses with the MTG8(ETO) gene on chromosome 8 to produce the fusion gene
More research has been done on the
Mixed-lineage leukemia (
2.2.2. Overexpressed genes
Since in only a small fraction of patients, fusion transcripts are present, overexpressed genes might offer a potential alternative target for molecular MRD monitoring. Such overexpressed genes are either silenced or expressed at very low levels in normal hematopoietic cells. Commonly overexpressed genes are
Another potential marker is
The ecotropic virus integrations-1 (
2.2.3. Gene mutations
Since fusion genes are only present in 15%-45% of AML patients and overexpressed genes seem to be less specific MRD markers, gene mutations may offer another attractive group of targets for MRD monitoring.
A decade ago, fms-like tyrosine kinase 3 (
Mutations in the nucleophosmin (
CCAAT/enhancer binding protein alpha (
2.3. Clinical applications of MRD
As discussed above, MRD frequency assessment using immunophenotypic and molecular parameters in patients with AML in clinical remission has important prognostic value and can predict forthcoming relapses. Therefore, it would be of potential importance to monitor MRD cell frequency for risk stratification. Current AML risk stratification is based on a number of parameters determined at diagnosis, including origin of leukemia (secondary AML, AML after myelodysplastic syndrome), age, WBC count, and presence of certain cytogenetic and/or molecular aberrancies [14]. Novel AML risk stratification should not only be based on risk assessment at diagnosis, but also on MRD cell frequency as a “response to treatment” parameter. Including MRD in AML risk stratification could help identify CR patients after induction therapy with increased MRD levels and therefore high risk of relapse. For instance, good risk patients with high MRD levels after induction therapy may benefit from allogeneic stem cell transplantation, while on the other hand intermediate risk group patients with low MRD levels could be spared from an allogeneic transplantation and the accompanying toxicity. Especially in this intermediate risk group, MRD monitoring would be of great help, since the prognosis of these patients is difficult to estimate. Therefore, MRD based clinical decision making after induction therapy may contribute to better RFS and OS rates.
Also after consolidation therapy, MRD based clinical intervention is promising. Even after an allogeneic transplantation, still a proportion of 20%-40% of the patients will relapse [73-75]. Therapeutic options in the case of post-transplant relapse consist of withdrawal or decrease of dose of immune-suppressive drugs, or immunotherapeutic intervention with a donor lymphocyte infusion. As these approaches intend to boost the graft versus leukemia effect, they are most effective when the leukemic cell load is small. Therefore early detection of impending post-transplant relapses is essential and would allow immunotherapeutic intervention at a low leukemic burden. The current standard to guide post-transplant treatment is the level of donor chimerism. This refers to the percentage of donor cells in PB or BM and it can be determined using short tandem repeat (STR)-PCR. Although mixed chimerism (< 95% of donor cells) has been associated with a higher incidence of relapse [76,77], patients with full chimerism (> 95% donor cells) can still suffer from relapse [77]. Additional monitoring of MRD levels in these transplanted patients could improve successful prediction of relapse, since MRD analysis directly detects the neoplastic part of the patient cell population, while STR analysis reflects total donor and total patient populations. Multiple studies have shown that MRD monitoring after an allogeneic transplantation indeed correlates with clinical outcome and identifies patients who are likely to relapse [78-81]. Therefore, it can be suggested that MRD based pre-emptive immunotherapy after transplantation could reduce relapse and improve survival. Standardization of treatment, based on MRD and chimerism analysis in the post-transplant period, seems therefore warranted. In conclusion, since MRD frequency assessment gives important prognostic information after both induction and consolidation therapy, it seems likely that using MRD for therapeutic intervention in the post-remission phase might reduce relapse rates en prolong OS. To confirm this hypothesis, large prospective studies with MRD based clinical intervention in the post-remission phase are essential.
2.4. Improvement of and alternatives for bone marrow MRD detection
2.4.1. Improvements for immunophenotypic and molecular MRD detection
Although flow cytometric MRD monitoring has many advantages, one of the difficulties is the complexity of MRD analysis. Nowadays, more advanced data analysis programs, that aid to distinguish between normal and malignant cells, are available [82]. This might simplify the analysis and result in more objective results. Notwithstanding the high prognostic value of MRD monitoring, in almost all studies 20%-40% of the patients with immunophenotypic defined low MRD levels still suffer from a relapse [5-7,10,16]. There are several potential reasons for missing these MRD cells. Normal BM cells express LAPs at low frequencies. Counting these cells as leukemic might result in false-positivity. This background expression thus seriously hinders specific identification of leukemic cells. On the other hand, subtracting background levels might under-estimate MRD frequencies and this could result in false-negatives. High specificity and thereby high sensitivity can be achieved when only the most specific immunophenotypic aberrancies are used, i.e. with no expression in normal cells. Inclusion of markers/marker combinations that allow excluding non-specific events in a multi-color approach may increase specificity. This is already shown for the transition of a four to five-color flow cytometric approach [83]. Another explanation for MRD misclassification is low sensitivity of the aberrant immunophenotype. Marker expression may be highly heterogeneous in an AML sample: LAPs may thereby often not be expressed on the total population of blast cells, thereby, at follow up, preventing the identification of all leukemic cells. Improvements can only be expected with the discovery of new aberrancies that cover larger parts of diagnosis blast cells. At present, with the large differences in specificity and sensitivity of LAPs the level of detection of MRD varies between patients: 1:10,000 or even better may be reached in one patient, while in another patient 1:1,000 may be the best attainable. Besides misclassification, immunophenotype shifts can also contribute to false-negative observations. To reduce this, it is recommended to use multiple LAPs for MRD monitoring [6,12,13]. Recently, it has become clear that such shifts may occur through clonal selection: while major molecular clones may disappear upon therapy, minor diagnosis clones may survive chemotherapy treatment, and grow out to relapse [84]. This may be accompanied by immunophenotype changes [84]. More efforts towards recognition of minor clones at diagnosis, that potentially can expand to cause relapse, may identify emerging molecular clones and immunophenotypes instead of disappearing molecular clones and immunophenotypes only. For molecular MRD, in fact most of the pitfalls for immunophenotypic MRD hold here as well. Similar to MFC, multiple molecular MRD studies have reported patients with low molecular MRD levels that still suffer from relapse [25,26,37,38,42]. Underlying causes may include 1) as argued earlier for different LAPs, Q-PCRs for different mutations and fusion genes reach different sensitivities as well; 2) part of the blasts may only be characterized by the molecular aberrancy of interest; and 3) molecular clone shifts occur between diagnosis and relapse. To avoid these false-negative results different molecular markers, if present in the patient, could be quantified for MRD monitoring. There are no real solutions for these problems unless more generally applicable, specific and stable markers are discovered. Until then, combining as many molecular and immunophenotypic targets may contribute to accurate MRD based prediction of relapse. Another possible explanation for finding false-negative MRD results is the fact that it may not only be the number of leukemic blasts that determines the chance for relapse, but more specifically the number of leukemic stem cells (LSCs). These LSCs can cause tumor outgrowth, thereby leading to MRD and finally resulting into overt disease relapse [85]. Although these stem cells are much less frequent than whole blast MRD, LSC frequency assessment may offer an additional specific and biologically relevant determinant of risk on relapse. In section 3 the role of leukemic stem cells in acute myeloid leukemia will be further discussed.
2.4.2. Alternative parameters for risk stratification
Perhaps the conceptually simplest method to evaluate treatment response is calculating the decrease rate of peripheral blasts shortly after treatment
3. Leukemic stem cells and acute myeloid leukemia
3.1. Definition of leukemic stem cells
It was hypothesized that a small population of cells, distinct from the bulk of tumor cells, is responsible for tumor initiation and growth in various cancers, including AML [91,92]. These cells are referred to as leukemic stem cells (LSCs) or leukemia-initiating cells (LICs). It is assumed that similar to normal hematopoiesis, leukemia is hierarchically structured. In many respects LSCs resemble normal hematopoietic stem cells (HSCs). Similar to HSCs, LSCs are defined by their ability to undergo self-renewal and the capacity to differentiate to a limited, although highly variable, extent [93,94]. Furthermore, the immunophenotype of LSCs resembles the immunophenotype of normal HSCs. The majority of HSCs are present in the CD34+CD38- immunophenotypic compartment [95,96] and initial AML studies demonstrated leukemia initiating capacity also to be in the CD34+CD38- compartment [97]. This small subpopulation of CD34+CD38- cells was able to engraft and cause leukemia in non-obese diabetic/sever combined immune-deficient (NOD/SCID) mice. These cells were present at a frequency of only 0.2 to 100 cells per 106 mononuclear cells [97]. Nowadays it is known that AML LSCs can also reside within the CD34+CD38+ or the CD34- immunophenotypic compartment [98-102]. There is growing evidence that the transformation of a normal human cell into a LSC not only can occur in a normal HSC, but also in a normal progenitor cell [103]. Mutations in a normal progenitor cell may confer self-renewal properties to progenitors. A recent study demonstrated that CD34+CD38- LSCs, despite the immunophenotypic similarities with normal HSCs, are most related to normal progenitors instead of normal stem cells [102]. In addition, it has been demonstrated that within a patient, the pool of LSCs at diagnosis is often largely heterogeneous. This implies that different subpopulations of LSCs often coexist at diagnosis [84,101] (Figure 1). In CD34 positive patients often both CD34+CD38- cells, CD34+CD38+ and CD34- cells are present and all are able to show leukemic engraftment when infused separately in NOD/SCID mice. However, no information exists on possible competition between these compartments in leukemogenesis. Moreover, the CD34+CD38- compartment has been shown to be less immunogenic compared to the other compartments [104], which may explain why it was almost exclusively the CD34+CD38- compartment that engrafted in NOD/SCID mice with residual immunity [97], while in the severely immunocompromised later mouse models, the other compartments engrafted as well. In CD34 negative AML by definition, the CD34- compartment and in particular the CD34-CD38+ compartment contain LSCs [100]. For clinical treatment and patient survival it is important to know which putative LSC will survive therapy. In that respect it is important to realize that the CD34+CD38- compartment has been shown to be most therapy resistant
In the course of time other compartments enriched for LSCs have been identified. These are based on functional properties and include aldehyde dehydrogenase (ALDH) activity and drug efflux (Hoechst) capacity. ALDH is a group of cytosolic enzymes that catalyze the oxidation of aldehydes. It plays an important role in the retinoid metabolism, since it is required for the conversion of retinol (Vitamin A) to retinoic acids. For maturation, loss of quiescence and differentiation of HSCs, these retinoic acids are important [105,106]. Furthermore, ALDH activity is supposed to protect cells from the toxic effects of cyclophosphamide and therefore high ALDH expression in leukemic cells may play a role in chemotherapy resistance [107,108]. Recently it has been shown that leukemic cells and normal hematopoietic cells differ in ALDH activity. Normal stem- and progenitor cells have high ALDH expression [109-112]. It has to be emphasized that it has recently been demonstrated that the population of cells with intermediate ALDH activity appeared to be enriched for leukemic CD34+CD38- cells [113-115]. Several authors have confirmed the leukemia initiating capacity of these cells in NOD/SCID mice [116-118].
Another functional stem cell compartment is the so-called side population (SP). These SP cells are primarily defined by their capability of efficient Hoechst 33342 dye efflux and especially by the way in which fluorescence emission of Hoechst is recorded. In normal BM a population of CD34+CD38- cells was found in the SP [119,120]. In AML, it has been demonstrated that the SP compartment contains a heterogeneous population of cells, containing HSCs, LSCs, LSC progenitors and early lymphocytes [121]. AML SP cells have shown to be able to initiate acute leukemia in NOD/SCID mice [122,123]. All these immunophenotypic and functional findings are important for gaining insight in the process of leukemogenesis and especially for the development of new therapies aiming at eradication of LSCs.
Besides the ability of LSCs to initiate and sustain the initial AML, there is increasing evidence pointing towards the importance of LSCs in the occurrence of MRD and the emergence of a relapse. LSCs are thought to be more resistant to standard chemotherapy compared to the total population of malignant blast cells and therefore these LSCs are able to escape apoptosis. Other essential LSC features are their acquired capacity for self-renewal and proliferation. Such properties allow LSCs to survive chemotherapy treatment, to divide and to grow out and cause a relapse (Figure 1). Consequently, identification and characterization of LSCs is fundamental to gain insight in the mechanisms that underlie relapse and how to evade relapse.
3.2. Identification of leukemic stem cells
Since the assumed role of LSC in the emergence of an AML relapse, identification of these probably most malignant cells becomes imperative. The hypothesis would thus be that quantitation of LSCs in AML patients would give important information about treatment response and risk of relapse. Similar to MRD identified by flow cytometry, LSCs in BM can be identified using cell surface antigen expression. As mentioned before, LSCs can reside in different immunophenotypic compartments, but, as argued before, the CD34+CD38- defined LSCs may be most malignant/resistant [84,104]. Since both HSCs and LSCs reside within this compartment, discrimination between CD34+CD38- HSCs and LSCs is challenging. Immunophenotypic LSC detection is often possible making use of the fact that the lineage marker combinations used for MRD detection, are frequently aberrantly expressed on CD34+CD38- cells too [124]. These lineage markers include CD2, CD7, CD11b, CD13, CD15, CD19, CD22 CD33, CD56 and HLA-DR. Combinations of lineage markers could also be used, like CD33+CD13- and CD15+HLA-DR-. Besides these lineage markers, a growing number of other markers is now available to discriminate between LSCs and HSCs. These include CLL-1 CD25, CD32, CD33, CD44, CD47, CD96, CD123 and TIM-3 (Figure 3). An overview of LSC markers is given in Table 3.
It is important to realize that there is a large heterogeneity in marker expression. This implies that marker expression differs between AML patients and even within an individual patient different stem cell markers are often differentially expressed (Figure 4). Thus, none of the individual markers are expressed in all AML cases. For accurate LSC detection, high specificity of stem cell markers is essential. Both CLL-1 and lineage markers have proven to be highly specific, since these are present on leukemic CD34+CD38- cells in a substantial part of the AML patient population, but absent on normal CD34+CD38- cells, also after chemotherapy [124,125]. For the other stem cell markers high specificity and stability during treatment/disease still have to be confirmed. The established differences in ALDH activity between CD34+CD38- LSCs and CD34+CD38- HSCs were confirmed using this aberrant marker approach [114,115], thereby strengthening that the functional ALDH assay offers an alternative tool for CD34+CD38- LSC identification, which importantly, could be applied in absence of aberrant antigen expression. In contrast, the SP phenotype does not discriminate between HSCs and LSCs since both may be present in the SP compartment. Here the immunophenotypic marker approach is necessary to discriminate between LSCs and HSCs [121]. Both ALDH and SP assays not only identify leukemia initiating cells with the CD34+CD38- immunophenotype, but also other cell types, like CD34+CD38+ progenitors or CD34- cells [114,115,117].
Although functional assays, like ALDH and SP, are complex and time-consuming compared to standard immunophenotypic LSC detection, they may offer promising alternatives for CD34+ AML patients without detectable CD34+CD38- cells, as well as for AML patients who are defined as CD34 negative. The latter patients usually have less than 1% expression of CD34 on the leukemic blast cells which all are of non-neoplastic origin [133]
Antigen | Function | Reference |
CLL-1 | C-type lectin-like molecule-1 | [125] |
Lineage markers | Lymphoid lineage and myeloid lineage markers | [124] |
CD25 | Interleukin-2 receptor α-chain | [126] |
CD32 | Fc fragement of IgG, low affinity IIa receptor | [126] |
CD33 | Myeloid marker | [127] |
CD44 | Receptor for hyaluronan | [128] |
CD47 | Integrin associated protein | [129] |
CD96 | T cell-activated increased late expression protein | [130] |
CD123 | Interleukin 3 receptor alpha chain | [131] |
TIM-3 | T-cell Ig mucin-3 | [132] |
Seen the large clonal heterogeneity at diagnosis [84,101], and the possibility that not just the major clone at diagnosis, but often low-frequency CD34+CD38- clones may grow out [84]
CD34+CD38- population was analyzed for the expression of six aberrant markers: CD2 (A), CLL-1 (B), CD22 (C), CD96 (D), CD123 (E), CD11b (F). Expressions percentages for marker positive and marker negative CD34+CD38- cells are shown for each marker.
3.3. Prognostic value of LSC frequency
Since it has been hypothesized that the subpopulation of chemotherapy resistant LSCs is responsible for relapse, LSC frequency, similar to MRD frequency, should have direct prognostic impact.
Van Rhenen
Cut-off | Number of patients above cut-off | Relative risk of relapse | 95% C.I. | |
First cycle | 5 x 10-6 | 14 | 5.0 | 1.8-14.0 |
Second cycle | 5 x 10-6 | 18 | 4.7 | 2.2-10.1 |
Consolidation | 2 x 10-6 | 14 | 8.5 | 1.8-41.4 |
All together, several studies showed CD34+CD38- LSC frequency to be an independent prognostic risk factor. Important to emphasize, however, is that these studies focus on LSC detection and quantification at AML diagnosis. Because LSCs are hypothesized to be chemotherapy resistant and to grow out after treatment and then cause a relapse, it would be of utmost importance to study the frequency of these LSCs during follow-up. For the first time we also demonstrated that the frequencies of LSCs after different courses of therapy significantly correlated with clinical outcome [137]. More effort is needed to identify LSCs and their prognostic value in immunophenotypic compartments other than CD34+CD38-, like the CD34+CD38+ and CD34- compartment using the ALDH and SP assay. Ultimately, when the clinical importance of different stem cell compartments have been prospectively confirmed, this, together with MRD based strategies, should offer new diagnostic tools to guide clinical intervention and to monitor effectiveness of therapy and, moreover, to design new therapies that specifically target LSCs while leaving the normal HSCs intact.
3.4. Leukemic stem cell targeted therapy
Apart from the clinical application of LSCs, characterization of these malignant cells offers the design of new therapies that specifically target LSCs while leaving the normal HSCs intact. The most direct example of such therapy is the application of antibodies that are used to specifically discriminate between LSC and HSC. CD123 and CD33 are examples. It has been reported, using NOD/SCID mice, that treatment with the anti-CD123 antibody 7G3 improved mouse survival [138]. A humanized version of the anti-CD123 antibody (CLS360) has been studied in a phase 1 study in relapsed, refractory and high-risk AML patients. Interim analysis showed no treatment related toxicity, besides two mild infusion reactions and one infection possibly related to the treatment. Of eight patients treated with CLS360, one CR had been observed [139]
CD33 is expressed on leukemic blasts in 85%-90% of AML patients and therefore, already years ago, it had been suggested as a potential target for anti-AML therapy. The CD33 immunoconjugate gemtuzumab ozogamicin (Mylotarg) has been studied in several trials and, after initial disappointment relating to toxicity, new studies with altered treatment schedules suggest that Mylotarg is beneficial in certain subgroups of AML patients, including patients with favorable cytogenetics [140]
4. Conclusions and future perspectives
MRD frequency assessments by RQ-PCR and MFC in AML patients are more sensitive methods to define remission status compared to current morphologic assessment. Although RQ-PCR is in general the most sensitive technique, MFC is applicable in almost all AML patients. Since the importance of flow cytometric MRD detection has now been validated in a first prospective study, it is of utmost importance that, when these data are confirmed in other prospective studies, MRD status will be implemented in clinical decision-making. We have described that alternatives for BM MRD may include MRD assessment in peripheral blood and blast reduction, frequency of B-lymphocytes precursors and CD34+ myeloid/lymphoid ratios. It thus seems that development of algorithms including all such parameters may ultimately contribute to improved detection of residual therapy resistant cells and early and accurate prediction of relapses. Also, based on the observation of immunophenotypic and molecular shifts, occurring between diagnosis and relapse, a new issue in MRD research may be that not only disappearing phenotypes, but also emerging “new” phenotypes have to be monitored. An alternative, probably more specific method to predict clinical outcome is LSC frequency assessment. Results so far on the clinical importance of LSCs are limited, but very promising, especially since for the first time the correlation between the presence of LSCs after treatment and clinical outcome has been reported. When the value of LSC assessment is confirmed in other retrospective and eventually prospective studies, it may be hypothesized that in the future, not only MRD, but also LSC frequency assessment may be implemented in clinical decision-making.
Hopefully, using the suggested approaches in this chapter, it will become possible to significantly improve clinical outcome of acute myeloid leukemia patients.
Acknowledgments
We thank J. Cloos for reviewing the manuscript and A. Kelder for assistance in figure preparation.References
- 1.
Cornelissen J. J. van Putten W. L. J. Verdonck L. F. Theobald M. Jacky E. Daenen S. M. et al. 2007 Results of a HOVON/SAKK donor versus no-donor analysis of myeloablative HLA-identical sibling stem cell transplantation in first remission acute myeloid leukemia in young and middle-aged adults: benefits for whom? Blood 109 9 3658 66 - 2.
Cheson B. D. Bennett J. M. Kopecky K. J. Büchner T. Willman C. L. Estey E. H. et al. 2003 Revised recommendations of the International Working Group for Diagnosis, Standardization of Response Criteria, Treatment Outcomes, and Reporting Standards for Therapeutic Trials in Acute Myeloid Leukemia. J Clin Oncol 21 24 4642 9 - 3.
Kern W. Haferlach C. Haferlach T. Schnittger S. 2008 Monitoring of minimal residual disease in acute myeloid leukemia. Cancer 112 1 4 16 - 4.
San Miguel. J. F. Martinez A. Macedo A. Vidriales M. B. López-Berges C. González M. et al. 1997 Immunophenotyping investigation of minimal residual disease is a useful approach for predicting relapse in acute myeloid leukemia patients. Blood 90 6 2465 70 - 5.
Kern W. Voskova D. Schoch C. Hiddemann W. Schnittger S. Haferlach T. 2004 Determination of relapse risk based on assessment of minimal residual disease during complete remission by multiparameter flow cytometry in unselected patients with acute myeloid leukemia. Blood 104 10 3078 85 - 6.
Feller N. van der Pol M. A. van Stijn A. Weijers G. W. D. Westra A. H. Evertse B. W. 2004 MRD parameters using immunophenotypic detection methods are highly reliable in predicting survival in acute myeloid leukaemia. Leukemia 18 8 1380 90 - 7.
Venditti A. Buccisano F. Del Poeta G. Maurillo L. Tamburini A. Cox C. et al. 2000 Level of minimal residual disease after consolidation therapy predicts outcome in acute myeloid leukemia. Blood 96 12 3948 52 - 8.
Diez-Campelo M. 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. Am J Hematol 84 3 149 52 - 9.
Buccisano F. Maurillo L. Spagnoli A. Del Principe M. I. Ceresoli . E. Lo Coco. F. et al. 2009 Monitoring of minimal residual disease in acute myeloid leukemia. Curr Opin Oncol 21 6 582 8 - 10.
Al-Mawali A. Gillis D. Lewis I. 20 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 B Clin Cytom 76 2 91 101 - 11.
Vidriales M. B. San-Miguel J. F. Orfao A. Coustan-Smith E. Campana D. 2003 Minimal residual disease monitoring by flow cytometry. Best Pract Res Clin Haematol 16 4 599 612 - 12.
Baer M. R. Stewart C. C. Dodge R. K. Leget G. Sulé N. Mrózek K. et al. 2001 High frequency of immunophenotype changes in acute myeloid leukemia at relapse: implications for residual disease detection (Cancer and Leukemia Group B Study 8361). Blood 97 11 3574 80 - 13.
Macedo A. San Miguel. J. F. Vidriales M. B. López-Berges M. C. García-Marcos M. A. Gonzales M. et al. 1996 Phenotypic changes in acute myeloid leukaemia: implications in the detection of minimal residual disease. J Clin Pathol 49 1 15 8 - 14.
Grimwade D. Hills R. K. 2009 Independent prognostic factors for AML outcome. Hematology Am Soc Hematol Educ Program :385 95 - 15.
San Miguel. J. F. Vidriales M. B. López-Berges C. Diaz-Mediavilla J. Guttiérrez N. Cañizo C. et al. 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 6 1746 51 - 16.
Maurillo L. Buccisano F. Del Principe M. I. Del Poeta G. Spagnoli A. Panetta P. et al. 2008 Toward optimization of postremission therapy for residual disease-positive patients with acute myeloid leukemia. J Clin Oncol 26 30 4944 51 - 17.
Terwijn M. Kelder A. van Putten W. L. J. Snel A. N. van der Velden V. H. J. Brooimans R. A. 2010 High prognostic impact of flowcytometric minimal residual disease detection in acute myeloid leukemia: prospective data from the HOVON/SAKK 42a study. Blood (ASH Annual Meeting Abstracts)116:760. - 18.
Sugimoto T. Das H. Imoto S. Murayama T. Gomyo H. Chakraborty S. et al. 2000 Quantitation of minimal residual disease in t(821)-positive acute myelogenous leukemia patients using real-time quantitative RT-PCR. Am J Hematol 64 2 101 6 - 19.
Tobal K. Liu Yin J.A. 1996 Monitoring of minimal residual disease by quantitative reverse transcriptase-polymerase chain reaction for AML1-MTG8 transcripts in AML-M2 with t(821). Blood 88 10 3704 9 - 20.
Guerrasio A. Pilatrino C. De Micheli D. Cilloni D. Serra A. Gottardi E. et al. 2002 Assessment of minimal residual disease (MRD) in CBFbeta/MYH11-positive acute myeloid leukemias by qualitative and quantitative RT-PCR amplification of fusion transcripts. Leukemia 16 6 1176 81 - 21.
Mitterbauer G. Zimmer C. Pirc-Danoewinata H. Haas O. A. Hojas S. Schwarzinger I. et al. 2000 Monitoring of minimal residual disease in patients with MLL-AF6-positive acute myeloid leukaemia by reverse transcriptase polymerase chain reaction. Br J Haematol 109 3 622 8 - 22.
Grimwade D. Hills R. K. Moorman A. V. Walker H. Chatters S. Goldstone A. H. et al. 2010 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 3 354 65 - 23.
Erickson P. Gao J. Chang K. S. Look T. Whisenant E. Raimondi S. et al. 1992 Identification of breakpoints in t(821) acute myelogenous leukemia and isolation of a fusion transcript, AML1/ETO, with similarity to a drosophila segmentation gene, runt. Blood 80 7 1825 31 - 24.
Tobal K. Newton J. Macheta M. Chang J. Morgenstern G. Evans P. A. S. et al. 2000 Molecular quantitation of minimal residual disease in acute myeloid leukemia with t(821) can identify patients in durable remission and predict clinical relapse. Blood 95 3 815 9 - 25.
Krauter J. Görlich K. Ottmann O. Lübbert M. Döhner H. Heit W. et al. 2003 Prognostic value of minimal residual disease quantification by real-time reverse transcriptase polymerase chain reaction in patients with core binding factor leukemias. J Clin Oncol 21 23 4413 22 - 26.
Buonamici S. Ottaviani E. Testoni N. Montefusco V. Visani G. Bonifazi F. et al. 2002 Real-time quantitation of minimal residual disease in inv(16)-positive acute myeloid leukemia may indicate risk for clinical relapse and may identify patients in a curable state. Blood 99 2 443 9 - 27.
Grimwade D. Jovanovic J. V. Hills R. K. Nugent E. A. Patel Y. Flora R. et al. 2009 Prospective minimal residual disease monitoring to predict relapse of acute promyelocytic leukemia and to direct pre-emptive arsenic trioxide therapy. J Clin Oncol 27 22 3650 8 - 28.
Pui C. H. Relling M. V. Downing J. R. 2004 Acute lymphoblastic leukemia. N Engl J Med 350 15 1535 48 - 29.
Wetzler M. Dodge R. K. Mrozek K. Carroll A. J. Tantravahi R. Block A. W. et al. 1999 Prospective karyotype analysis in adult acute lymphoblastic leukemia: the cancer and leukemia Group B experience. Blood 93 11 3983 93 - 30.
Scholl C. Breitinger H. Schlenk R. F. Dohner H. Frohling S. Dohner K. 2003 Development of a real-time RT-PCR assay for the quantification of the most frequent MLL/AF9 fusion types resulting from translocation t(911)(22q23) in acute myeloid leukemia. Genes Chromosomes Cancer 38(3):274-80. - 31.
Yang L. Han Y. Suarez F. Minden M. D. 2007 A tumor suppressor and oncogene: The WT1 story. Leukemia 21 5 868 76 - 32.
Sugiyama H. 2001 Wilms’ tumor gene WT1: its oncogenic function and clinical application. Int J Hematol 73 2 177 87 - 33.
Inoue K. Ogawa H. Sonoda Y. Kimura T. Sakabe H. Oka Y. et al. 1997 Aberrant overexpression of the Wilms tumor gene (WT1) in human leukemia. Blood 89 4 1405 12 - 34.
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 Leukaemia Net. Haematologica 94 8 1135 50 - 35.
Jacobsohn D. A. Tse W. T. Chaleff S. Rademaker A. Duerst R. Olszewski M. et al. 2009 High WT1 gene expression before haematopoeitic stem cell transplant in children with acute myeloid leukaemia predicts poor event-free survival. B J Haematol 146 6 669 74 - 36.
Candoni A. Tiribelli M. Toffoletti E. Cilloni D. Chiarvesio A. Michelutti A. et al. 2008 Quantitative assessment of WT1 gene expression after allogeneic stem cell transplantation is a useful tool for monitoring minimal residual disease in acute myeloid leukemia. Eur J Haematol 82 1 61 8 - 37.
Cilloni D. Renneville A. Hermitte F. Hills R. K. Daly S. Jovanovic J. V. et al. 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. J Clin Oncol 27 31 5195 201 - 38.
Hämäläinen M. M. Kairisto V. Juvonen V. Johansson J. Aurén J. Kohonen K. et al. 2008 Wilms tumour gene 1 overexpression in bone marrow as a marker for minimal residual disease in acute myeloid leukaemia. Eur J Haematol 80 3 201 7 - 39.
Matsushita M. Ikeda H. Kizaki M. Okamoto S. Ogasawara M. Ikeda Y. et al. 2001 Quantitative monitoring of the PRAME gene for the detection of minimal residual disease in leukaemia. Br J Haematol 112 4 916 26 - 40.
Steinbach D. Hermann J. Viehmann S. Zintl F. Gruhn B. 2002 Clinical implications of PRAME gene expression in childhood acute myeloid leukemia. Cancer Genet Cytogenet 133 2 118 23 - 41.
Greiner J. Ringhoffer M. Taniguchi M. Li L. Schmitt A. Shiku H. et al. 2004 mRNA expression of leukemia-associated antigens in patients with acute myeloid leukemia for the development of specific immunotherapies. Int J Cancer 108 5 704 11 - 42.
Qin Y. Zhu H. Jiang B. Li J. Lu X. Li L. et al. 2009 Expression patterns of WT1 and PRAME in acute myeloid leukemia patients and their usefulness for monitoring minimal residual disease. Leuk Res 33 3 384 90 - 43.
Barjesteh van Waalwijk. van Doorn-Khosrovani S. Erpelinck C. van Putten W. L. J. Valk P. J. M. van der Poel-van de Luytgaarde. S. Hack R. 2003 High EVI1 expression predicts poor survival in acute myeloid leukemia: a study of 319 de novo AML patients. Blood 101 3 837 45 - 44.
Lugthart S. van Drunen E. van Norden Y. van Hoven A. Erpelinck C. A. J. Valk P. J. M. et al. 2008 High EVI1 levels predict adverse outcome in acute myeloid leukemia: prevalence of EVI1 overexpression and chromosome 3q26 abnormalities underestimated. Blood 111 8 4329 37 - 45.
Aytekin M. Vinatzer U. Musteanu M. Raynaud S. Wieser R. 2005 Regulation of the expression of the oncogene EVI1 through the use of alternative mRNA 5’-ends. Gene 356 160 8 - 46.
Schnittger S. Schoch C. Dugas M. Kern W. Staib P. Wuchter C. et al. 2002 Analysis of FLT3 length mutations in 1003 patients with acute myeloid leukemia: correlation to cytogenetics, FAB subtype, and prognosis in the AMLCG study and usefulness as a marker for the detection of minimal residual disease. Blood 100 1 59 66 - 47.
Small D. 2006 FLT3 mutations: biology and treatment. Hematology Am Soc Hematol Educ Program 178 84 - 48.
Wagner K. Damm F. Thol F. Göhring G. Görlich K. Heuser M. et al. 2011 FLT3-internal tandem duplication and age are the major prognostic factors in patients with relapsed acute myeloid leukemia with normal karyotype. Haematologica 96 5 681 6 - 49.
Chou W. C. Hou H. A. Liu C. Y. Chen C. Y. Lin L. I. Huang Y. N. et al. 2011 Sensitive measurement of quantity dynamics of FLT3 internal tandem duplication at early time points provides prognostic information. Ann Oncol 22 3 696 704 - 50.
Schnittger S. Kern W. Tschulik C. Weiss T. Dicker F. Falini B. et al. 2009 Minimal residual disease levels assessed by NPM1 mutation-specific RQ-PCR provide important prognostic information in AML. Blood 114 11 2220 31 - 51.
Schiller J. Praulich I. Krings Rocha. C. Kreuzer K. A. 2012 Patient-specific analysis of FLT3 internal tandem duplications for the prognostication and monitoring of acute myeloid leukemia. Eur J Haematol 89 1 53 62 - 52.
Abdelhamid E. Preudhomme C. Helevaut N. Nibourel O. Gardin C. Rousselot P. et al. 2012 Minimal residual disease monitoring based on FLT3 internal tandem duplication in adult acute myeloid leukemia. Leuk Res 36 3 316 23 - 53.
Cloos J. Goemans B. F. Hess C. J. van Oostveen J. W. Waisfisz Q. Corthals Q. et al. 2006 Stability and prognostic influence of FLT3 mutations in paired initial and relapsed AML samples. Leukemia 20 7 1217 20 - 54.
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 7 2393 98 - 55.
Bachas C. Schuurhuis G. J. Hollink I. H. Kwidama Z. J. Goemans B. F. Zwaan C. M. et al. 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 15 2752 8 - 56.
Beretta C. Gaipa G. Rossi V. Bernasconi S. Spinelli O. Dell’Oro M. G. et al. 2004 Development of a quantitative-PCR method for specific FLT3/ITD monitoring in acute myeloid leukemia. Leukemia 18 8 1441 44 - 57.
Fallini B. Bolli N. Shan J. Martelli M. P. Liso A. Pucciarini A. et al. 2006 Both carboxy-terminus NES motif and mutated tryptophan(s) are crucial for aberrant nuclear export of nucleophosmin leukemic mutants in NPMc+ AML. Blood 107 11 4514 23 - 58.
Falini B. Nicoletti I. Martelli M. F. Mecucci C. 2007 Acute myeloid leukemia carrying cytoplasmic/mutated nucleophosmin (NPMc(+)AML): biologic and clinical features. Blood 109 3 874 85 - 59.
Falini B. Mecucci C. Tiacci E. Alcalay M. Rosati R. Pasqualucci L. et al. 2005 Cytoplasmic nucleophosmin in acute myelogenous leukemia with a normal karyotype. N Engl J Med 352 3 254 66 - 60.
Dohner K. Schlenk R. F. Habdank M. Scholl C. Rücker F. G. Corbacioglu A. et al. 2005 Mutant nucleophosmin (NPM1) predicts favorable prognosis in younger adults with acute myeloid leukemia and normal cytogenetics: interaction with other gene mutations. Blood 106 12 3740 6 - 61.
Schneider F. Hoster E. Schneider S. Dufour A. Benthaus T. Kakadia P. M. et al. 2012 Age-dependent frequencies of NPM1 mutations and FLT3-ITD in patients with normal karyotype AML (NK-AML). Ann Hematol 91 1 9 18 - 62.
Dvorakova D. Racil Z. Jeziskova I. Palasek I. Protivankova M. Lengerova M. et al. 2010 Monitoring of minimal residual disease in acute myeloid leukemia with frequent and rare patient-specific NPM1 mutations. Am J Hematol 85 12 926 9 - 63.
Chou W. C. Tang J. L. Wu S. J. Tsay W. Yao M. Huang S. Y. et al. 2007 Clinical implications of minimal residual disease monitoring by quantitative polymerase chain reaction in acute myeloid leukemia patients bearing nucleophosmin (NPM1) mutations. Leukemia 21 5 998 1004 - 64.
Barragan E. Pajuelo J. C. Ballester S. Fuster O. Cervera J. Moscardo F. et al. 2008 Minimal residual disease detection in acute myeloid leukemia by mutant nucleophosmin (NPM1): comparison with WT1 gene expression. Clinica Chimica Acta 395(1-2):120-3. - 65.
Kristensen T. Møller M. B. Friis L. Bergmann O. J. Preiss B. 2011 NPM1 mutation is a stable marker for minimal residual disease monitoring in acute myeloid leukaemia patients with increased sensitivity compared to WT1 expression. Eur J Haematol 87 5 400 8 - 66.
Gorello P. Cazzaniga G. Alberti F. Dell’Oro M. G. Gottardi E. Specchia G. et al. 2006 Quantitative assessment of minimal residual disease in acute myeloid leukemia carrying nucleophosmin (NPM1) gene mutations. Leukemia 20 6 1103 8 - 67.
Papadaki C. Dufour A. Seibl M. Schneider S. Bohlander S. K. Zellmeier E. et al. 2009 Monitoring minimal residual disease in acute myeloid leukaemia with NPM1 mutations by quantitative PCR: clonal evolution is a limiting factor. Br J Haematol 144 4 517 23 - 68.
Suzuki T. Kiyoi H. Ozeki K. Tomita A. Yamaji S. Suzuki R. et al. 2005 Clinical characteristics and prognostic implications of NPM1 mutations in acute myeloid leukemia. Blood 106 8 2854 61 - 69.
Nerlov. 2004 C/EBPalpha mutations in acute myeloid leukemias. Nature Rev Cancer 4 5 394 400 - 70.
Schlenk R. F. Dohner K. Krauter J. Fröhling S. Corbacioglu A. Bullinger L. et al. 2008 Mutations and treatment outcome in cytogenetically normal acute myeloid leukemia. N Engl J Med 358 18 1909 18 - 71.
Benthaus T. Schneider F. Mellert G. Zellmeier E. Schneider S. Kakadia P. M. et al. 2008 Rapid and sensitive screening for CEBPA mutations in acute myeloid leukaemia. Br J Haematol 143 2 230 9 - 72.
Fröhling S. Schlenk R. F. Stolze I. Bihlmayr J. Benner A. Kreitmeier S. et al. 2004 CEBPA mutations in younger adults with acute myeloid leukemia and normal cytogenetics: prognostic relevance and analysis of cooperating mutations. J Clin Oncol 22 4 624 33 - 73.
Mohty M. Labopin M. Volin L. Gratwohl A. Socié G. Esteve J. et al. 2010 Reduced-intensity versus conventional myeloablative conditioning allogeneic stem cell transplantation for patients with acute lymphoblastic leukemia: a retrospective study from the European Group for Blood and Marrow Transplantation. Blood 116 22 4439 43 - 74.
Kröger N. Brand R. van Biezen A. Zander A. Dierlamm J. Niederwieser D. et al. 2009 Risk factors for therapy-related myelodysplastic syndrome and acute myeloid leukemia treated with allogeneic stem cell transplantation. Haematologica 94 4 542 9 - 75.
Klingebiel T. Cornish J. Labopin M. Locatelli F. Darbyshire P. Handgretinger R. et al. 2010 Results and factors influencing outcome after fully haploidentical hematopoietic stem cell transplantation in children with very high-risk acute lymphoblastic leukemia: impact of center size: an analysis on behalf of the Acute Leukemia and Pediatric Disease Working Parties of the European Blood and Marrow Transplant group. Blood 115 17 3437 46 - 76.
Bader P. Kreyenberg H. Hoelle W. Dueckers G. Handgretinger R. Lang P. et al. 2004 Increasing mixed chimerism is an important prognostic factor for unfavorable outcome in children with acute lymphoblastic leukemia after allogeneic stem-cell transplantation: possible role for pre-emptive immunotherapy? J Clin Oncol 22 9 1696 705 - 77.
Rettinger E. Willasch A. M. Kreyenberg H. Borkhardt A. Holter W. Kremens B. et al. 2011 Preemptive immunotherapy in childhood acute myeloid leukemia for patients showing evidence of mixed chimerism after allogeneic stem cell transplantation. Blood 118 20 5681 8 - 78.
Díez-Campelo M. Pérez-Simón J. A. Pérez J. Alcoceba M. Richtmon J. Vidriales B. et al. 2009 Minimal residual disease monitoring after allogeneic transplantation may help to individualize post-transplant therapeutic strategies in acute myeloid malignancies. Am J Hematol 84 3 149 52 - 79.
Rubnitz J. E. Inaba H. Dahl G. Ribeiro R. C. Bowman P. Taub J. et al. 2010 Minimal residual disease-directed therapy for childhood acute myeloid leukemia: results of the AML02 multicenter trial. Lancet Oncol 11 6 543 52 - 80.
Miyazaki T. Fujita H. Fujimaki K. Hosoyama T. Watanabe R. Tachibana T. et al. 2012 Clinical significance of minimal residual disease detected by multidimensional flow cytometry: Serial monitoring after allogeneic stem cell transplantation for acute leukemia. Leuk Res 36 8 998 1003 - 81.
Yan C. H. Liu D. H. Liu K. Y. Xu L. P. Liu Y. R. Chen H. et al. 2012 Risk stratification-directed donor lymphocyte infusion could reduce relapse of standard-risk acute leukemia patients after allogeneic hematopoietic stem cell transplantation. Blood 119 14 3256 62 - 82.
Pyne S. Hu X. Wang K. Rossin E. Lin T. I. Maier L. M. et al. 2009 Automated high-dimensional flow cytometric data analysis. Proc Natl Acad Sci U S A 106 21 8519 24 - 83.
Voskova D. Schnittger S. Schoch C. Haferlach T. Kern W. 2007 Use of five-color staining improves the sensitivity of multiparameter flow cytometric assessment of minimal residual disease in patients with acute myeloid leukemia. Leuk Lymphoma 48 1 80 8 - 84.
Bachas C. Schuurhuis G. J. Assaraf Y. G. Kwidama Z. J. Kelder A. Wouters F. et al. 2012 The role of minor subpopulations within the leukemic blast compartment of AML patients at initial diagnosis in the development of relapse. Leukemia 26 6 1313 20 - 85.
Becker M. W. Jordan C. T. 2011 Leukemia stem cells in 2010: Current understanding and future directions. Blood rev 25 2 75 81 - 86.
Panzer-Grümayer E. R. Schneider M. Panzer S. Fasching K. Gadner H. 2000 Rapid molecular response during early induction chemotherapy predicts a good outcome in childhood acute lymphoblastic leukemia. Blood 95 3 790 4 - 87.
Lacombe F. Arnoulet C. Maynadie M. Lippert E. Luquet I. Pigneux A. et al. 2009 Early clearance of peripheral blasts measured by flow cytometry during the first week of AML induction therapy as new independent prognostic factor: a GOELAMS study. Leukemia 23 2 350 7 - 88.
Maurillo L. Buccisano F. Spagnoli A. Del Poeta G. Panetta P. Neri B. et al. 2007 Monitoring of minimal residual disease in adult acute myeloid leukemia using peripheral blood as an alternative source to bone marrow. Haematologica 92 5 605 11 - 89.
Chantepie S. P. Salaün V. Parienti J. J. Truquet F. Macro M. Cheze S. et al. 2011 Hematogenes: a new prognostic factor for acute myeloblastic leukemia. Blood 117 4 1315 8 - 90.
Martinez A. San Miguel. J. F. Vidriales M. B. Ciudad J. Caballero M. D. López-Berges M. C. et al. 1999 An abnormal CD34+ myeloid/CD34+ lymphoid ratio at the end of chemotherapy predicts relapse in patients with acute myeloid leukemia. Cytometry 38 2 70 5 - 91.
McCulloch E.A. 1983 Stem cells in normal and leukemic hemopoiesis (Henry Stratton Lecture, 1982). Blood 62 1 1 13 - 92.
Griffin J. D. Löwenberg B. 1986 Clonogenic cells in acute myeloblastic leukemia. Blood 68 6 1185 95 - 93.
Luo L. Han Z. C. 2006 Leukemia stem cells. Int J Hematol 84 2 123 7 - 94.
Testa U. 2011 Leukemia stem cells. Ann Hematol 90 3 245 71 - 95.
Bhatia M. Wang J. C. Kapp U. Bonnet D. Dick J. E. 1997 Purification of primitive human hematopoietic cells capable of repopulating immune-deficient mice. Proc Natl Acad Sci U S A 94 10 5320 5 - 96.
Civin C. I. Almeida-Porada G. Lee M. J. Olweus J. Terstappen L. W. Zanjani E. D. 1996 Sustained, retransplantable, multilineage engraftment of highly purified adult human bone marrow stem cells in vivo. Blood 88 11 4102 9 - 97.
Bonnet D. Dick J. E. 1997 Human acute myeloid leukemia is organized as a hierachy that originates from a primitive hematopoeitic cell. Nat Med 3 7 730 7 - 98.
Hogan C. J. Shpall E. J. Keller G. 2002 Differential long-term and multilineage engraftment potential from subfractions of human CD34+ cord blood cells transplanted into NOD/SCID mice. Proc Natl Acad Sci U S A 99 1 413 8 - 99.
Taussig D. C. Miraki-Moud F. Anjos-Alsonso F. Pearce D. J. Allen K. Ridler C. et al. 2008 Anti-CD38 antibody-mediated clearance of human repopulating cells masks the heterogeneity of leukemia-initiating cells. Blood 112 3 568 75 - 100.
Taussig D. C. Vargaftig J. Miraki-Moud F. Griessinger E. Sharrock K. Luke T. et al. 2010 Leukemia-initiating cells from some acute myeloid leukemia patients with mutated nucleophosmin reside in the CD34− fraction. Blood 115 10 1976 84 - 101.
Sarry J. E. Murphy K. Perry R. Sanchez P. V. Secreto A. Keefer C. et al. 2011 Human acute myelogenous leukemia stem cells are rare and heterogeneous when assayed in NOD/SCID/IL2Rγc-deficient mice. J Clin Invest 121 1 384 95 - 102.
Goardon N. Marchi E. Atzberger A. Quek L. Schuh A. Soneji S. et al. 2011 Coexistence of LMPP-like and GMP-like leukemia stem cells in acute myeloid leukemia. Cancer cell 19 1 138 52 - 103.
Krivtsov A. V. Twomey D. Feng Z. Stubbs M. C. Wang Y. Faber J. et al. 2006 Transformation from committed progenitor to leukaemia stem cell initiated by MLL-AF9. Nature 442 7104 818 22 - 104.
Costello R. T. Mallet F. Gaugler B. Sainty D. Arnoulet C. Gastaut J. A. et al. 2000 Human acute myeloid leukemia CD34+/CD38- progenitor cells have decreased sensitivity to chemotherapy and Fas-induced apoptosis, reduced immunogenicity, and impaired dendritic cell transformation capacities. Cancer Res 60 16 4403 11 - 105.
Chute J. P. Muramoto G. G. Whitesides J. Colvin M. Safi R. Chao N. J. et al. 2006 Inhibition of aldehyde dehydrogenase and retinoid signaling induces the expansion of human hematopoietic stem cells. Proc Natl Acad Sci U S A 103 31 11707 12 - 106.
Duester G. 2000 Families of retinoid dehydrogenases regulating vitamin A function: production of visual pigment and retinoic acid. Eur J Biochem 267 14 4315 24 - 107.
Magni M. Shammah S. Schiró R. Mellado W. Dalla-Favera R. Gianni A. M. 1996 Induction of cyclophosphamide-resistance by aldehyde-dehydrogenase gene transfer. Blood 87 3 1097 1103 - 108.
Takebe N. Zhao S. C. Adhikari D. Mineishi S. Sadelain M. Hilton J. et al. 2001 Generation of dual resistance to 4-hydroperoxycyclophosphamide and methotrexate by retroviral transfer of the human aldehyde dehydrogenase class 1 gene and a mutated dihydrofolate reductase gene. Mol Ther 3 1 88 96 - 109.
Storms R. W. Trujillo A. P. Springer J. B. Shah L. Colvin O. M. Ludeman S. M. et al. 1999 Isolation of primitive human hematopoietic progenitors on the basis of aldehyde dehydrogenase activity. Proc Natl Acad Sci U S A 96 16 9118 23 - 110.
Armstrong L. Stojkovic M. Dimmick I. Ahmad S. Stojkovic P. Hole N. et al. 2004 Phenotypic characterization of murine primitive hematopoietic progenitor cells isolated on basis of aldehyde dehydrogenase activity. Stem Cells 22 7 1142 51 - 111.
Christ O. Lucke K. Imren S. Leung K. Hamilton M. Eaves A. et al. 2007 Improved purification of hematopoietic stem cells based on their elevated aldehyde dehydrogenase activity. Haematologica 92 9 1165 72 - 112.
Gentry T. Deibert E. Foster S. J. Haley R. Kurtzberg J. Balber A. E. 2007 Isolation of early hematopoietic cells, including megakaryocyte progenitors, in the ALDH-bright cell population of cryopreserved, banked UC blood. Cytotherapy 9 6 569 76 - 113.
Gerber J. M. Smith B. D. Ngwang B. Zhang H. Vala M. S. Morsberg L. et al. 2012 A clinically relevant population of leukemic CD34+CD38- cells in acute myeloid leukemia. Blood 119 15 3571 7 - 114.
Smit L. Min L. A. Terwijn M. Kelder A. Snel A. N. Ossenkoppele G. J. et al. 2009 High Aldehyde Dehydrogenase Activity (ALDH) is a general marker for normal hematopoietic stem cells but not leukemic stem cells in acute myeloid leukemia (AML). Blood (ASH Annual Meeting Abstracts)114:4035. - 115.
Schuurhuis G. J. Meel M. H. Min L. A. Wouters F. Terwijn M. Kelder A. et al. Consistently high aldehyde dehydrogenase (ALDH) activity is a feature of normal hematopoietic stem cells but not leukemic stem cells in Acute Myeloid Leukemia. Submitted - 116.
Cheung A. M. Wan T. S. Leung J. C. Chan L. Y. Huang H. Kwong Y. L. et al. 2007 Aldehyde dehydrogenase activity in leukemic blasts defines a subgroup of acute myeloid leukemia with adverse prognosis and superior NOD/SCID engrafting potential. Leukemia 21 7 1423 30 - 117.
Pearce D. J. Taussig D. Simpson C. Allen K. Rohatiner A. Z. Lister T. A. et al. 2005 Characterization of cells with a high aldehyde dehydrogenase activity from cord blood and acute myeloid leukemia samples. Stem Cells 23 6 752 60 - 118.
Ran D. Schubert M. Taubert I. Eckstein V. Bellos F. Jauch A. et al. 2012 Heterogeneity of leukemia stem cell candidates at diagnosis of acute myeloid leukemia and their clinical significance. Exp Hematol 40 2 155 65 - 119.
Goodell M. A. Brose K. Paradis G. Conner A. S. Mulligan R. C. 1996 Isolation and functional properties of murine hematopoietic stem cells that are replicating in vivo. J Exp Med 183 4 1797 806 - 120.
Goodell M. A. Rosenzweig M. Kim H. Marks D. F. De Maria M. Paradis G. et al. 1997 Dye efflux studies suggest that hematopoietic stem cells expressing low or undetectable levels of CD34 antigen exist in multiple species. Nat Med 3 12 1337 45 - 121.
Moshaver B. van Rhenen A. Kelder A. van der Pol M. Terwijn M. Bachas C. 2008 Identification of a small subpopulation of candidate leukemia-initiating cells in the side population of patients with acute myeloid leukemia. Stem Cells 26 12 3059 67 - 122.
Wulf G. G. Wang R. Y. Kuehnle I. Weidner D. Marini F. Brenner M. K. et al. 2001 A leukemic stem cell with intrinsic drug efflux capacity in acute myeloid leukemia. Blood 98 4 1166 73 - 123.
Feuring-Buske M. Hogge D. E. 2001 Hoechst 33342 efflux identifies a subpopulation of cytogenetically normal CD34(+)CD38(-) progenitor cells from patients with acute myeloid leukemia. Blood 97 12 3882 9 - 124.
van Rhenen A. Moshaver B. Kelder A. Feller N. Nieuwint A. W. M. Zweegman S. et al. 2007 Aberrant marker expression patterns on the CD34+CD38- stem cell compartment in acute myeloid leukemia allows to distinguish the malignant from the normal stem cell compartment both at diagnosis and in remission. Leukemia 21 8 1700 7 - 125.
Van Rhenen A. van Dongen G. A. M. S. Kelder A. Rombouts E. J. Feller N. Moshaver B. et al. 2007 The novel AML stem cell associated antigen CLL-1 aids in discrimination between normal and leukemic stem cells. Blood 110 7 2659 66 - 126.
Saito Y. Kitamura H. Hijikata A. Tomizawa-Murasawa M. Tanaka S. Takagi S. et al. 2010 Identification of therapeutic targets for quiescent, chemotherapy-resistant human leukemia stem cells, Sci Transl Med 2(17):17ra9. - 127.
Taussig D. C. Pearce D. J. Simpson C. Rohatiner A. Z. Lister T. A. Kelly G. et al. 2005 Hematopoietic stem cells express multiple myeloid markers: implications for the origin and targeted therapy of acute myeloid leukemia. Blood 106 13 4086 92 - 128.
Jin L. Hope K. J. Zhai Q. Smadja-Joffe F. Dick J. E. 2006 Targeting of CD44 eradicates human acute myeloid leukemic stem cells. Nat Med 12 10 1167 74 - 129.
Majeti R. Park C. Y. Weissman I. L. 2007 Identification of a hierarchy of multipotent hematopoietic progenitors in human cord blood. Cell Stem Cell 1 6 635 45 - 130.
Hosen N. Park C. Y. Tatsumi N. Oji Y. Sugiyama H. Gramatzki M. et al. 2007 CD96 is a leukemic stem cell-specific marker in human acute myeloid leukemia. Proc Natl Acad Sci U S A 104 26 11008 13 - 131.
Jordan C. T. Upchurch D. Szilvassy S. J. Guzman M. L. Howard D. S. Pettigrew A. L. et al. 2000 The interleukin-3 receptor alpha chain is a unique marker for human acute myelogenous leukemia stem cells. Leukemia 14 10 1777 84 - 132.
Jan M. Chao M. P. Cha A. C. Alizadeh A. A. Gentles A. J. Weissman I. L. et al. 2011 Prospective separation of normal and leukemic stem cells based on differential expression of TIM3, a human acute myeloid leukemia stem cell marker. Proc Natl Acad Sci U S A 108 12 5009 14 - 133.
van der Pol M. A. Feller N. Roseboom M. Moshaver B. Westra G. Broxterman H. J. et al. 2003 Assessment of the normal or leukemic nature of CD34+ cells in acute myeloid leukemia with low percentages of CD34 cells. Haematologica 88 9 983 93 - 134.
Van Rhenen A. Feller N. Kelder A. Westra A. H. Rombouts E. Zweegman S. et al. 2005 High stem cell frequency in acute myeloid leukemia at diagnosis predicts high minimal residual disease and poor survival. Clin Cancer Res 11 18 6520 7 - 135.
Witte K. E. Ahlers J. Schäfer I. André M. Kerst G. H. 2011 Scheel-Walter et al. High proportion of leukemic stem cells at diagnosis is correlated with unfavorable prognosis in childhood acute myeloid leukemia. Pediatr Hematol Oncol 28 2 91 9 - 136.
Hwang K. Park C. J. Jang S. Chi H. S. Kim D. Y. Lee J. H. et al. 2012 Flow cytometric quantification and immunophenotyping of leukemic stem cells in acute myeloid leukemia. Ann Hematol jun 6. - 137.
Terwijn M. Rutten A. P. Kelder A. Snel A. N. Scholten W. J. Zweegman S. et al. 2010 Accurate detection of residual leukemic stem cells in remission bone marrow predicts relapse in acute myeloid leukemia patients. Blood (ASH Annual Meeting Abstracts)116:759. - 138.
Jin L. Lee E. M. Ramshaw H. S. Busfield S. J. Peoppl A. G. Wilkinson L. et al. 2009 Monoclonal antibody-mediated targeting of CD123, IL-3 receptor α chain, eliminates human acute myeloid leukemic stem cells. Cell Stem Cell 5 1 31 42 - 139.
Roberts A. W. He S. Bradstock K. F. Hertzberg M. S. Durrant S. T. S. Ritchie D. et al. 2008 A Phase 1 and correlative biological study of CSL360 (anti-CD123 mAb) in AML. Blood (ASH Annual Meeting Abstracts)112:2956. - 140.
Walter R. B. Appelbaum F. R. Estey E. H. Bernstein I. D. 2012 Acute myeloid leukemia stem cells and CD33-targeted immunotherapy. Blood 119 26 6198 208