Next Article in Journal
Dendrobine Inhibits γ-Irradiation-Induced Cancer Cell Migration, Invasion and Metastasis in Non-Small Cell Lung Cancer Cells
Next Article in Special Issue
Hypomethylating Agents (HMAs) as Salvage Therapy in Relapsed or Refractory AML: An Italian Multicentric Retrospective Study
Previous Article in Journal
Mechanistic Illustration: How Newly-Formed Blood Vessels Stopped by the Mineral Blocks of Bone Substitutes Can Be Avoided by Using Innovative Combined Therapeutics
Previous Article in Special Issue
RSK Isoforms in Acute Myeloid Leukemia
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:

How to Improve Prognostication in Acute Myeloid Leukemia with CBFB-MYH11 Fusion Transcript: Focus on the Role of Molecular Measurable Residual Disease (MRD) Monitoring

by 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 3, 4, 1,*,†,‡ and 1,*,†
Section of Hematology, Department of Medical and Surgical Sciences, University of Modena and Reggio Emilia, Azienda Ospedaliero-Universitaria di Modena, 41124 Modena, Italy
Department of Laboratory Medicine and Pathology, Unità Sanitaria Locale, 41126 Modena, Italy
Center for Genome Research, Department of Medical and Surgical Sciences, University of Modena and Reggio Emilia, Azienda Ospedaliero-Universitaria di Modena, 41124 Modena, Italy
Pediatric Hematology/Oncology Unit and Cell Factory, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Policlinico San Matteo, 27100 Pavia, Italy
Authors to whom correspondence should be addressed.
M.L. and F.F. equally contributed to the review.
Additional corresponding author.
Biomedicines 2021, 9(8), 953;
Submission received: 31 May 2021 / Revised: 13 July 2021 / Accepted: 29 July 2021 / Published: 3 August 2021


Acute myeloid leukemia (AML) carrying inv(16)/t(16;16), resulting in fusion transcript CBFB-MYH11, belongs to the favorable-risk category. However, even if most patients obtain morphological complete remission after induction, approximately 30% of cases eventually relapse. While well-established clinical features and concomitant cytogenetic/molecular lesions have been recognized to be relevant to predict prognosis at disease onset, the independent prognostic impact of measurable residual disease (MRD) monitoring by quantitative real-time reverse transcriptase polymerase chain reaction (qRT-PCR), mainly in predicting relapse, actually supersedes other prognostic factors. Although the ELN Working Party recently indicated that patients affected with CBFB-MYH11 AML should have MRD assessment at informative clinical timepoints, at least after two cycles of intensive chemotherapy and after the end of treatment, several controversies could be raised, especially on the frequency of subsequent serial monitoring, the most significant MRD thresholds (most commonly 0.1%) and on the best source to be analyzed, namely, bone marrow or peripheral blood samples. Moreover, persisting low-level MRD positivity at the end of treatment is relatively common and not predictive of relapse, provided that transcript levels remain stably below specific thresholds. Rising MRD levels suggestive of molecular relapse/progression should thus be confirmed in subsequent samples. Further prospective studies would be required to optimize post-remission monitoring and to define effective MRD-based therapeutic strategies.

1. Introduction

The latest 2017 European Leukemia Net (ELN) recommendations for the diagnosis and management of acute myeloid leukemia (AML) in adults [1] confirm AML with inv(16)(p13.1q22) or t(16;16)(p13.1;q22) as a single entity in the category of AML with recurrent genetic abnormalities. Together with AML with t(8;21)(q22;q22.1), they are collectively referred to as core-binding factor (CBF) AML, cytogenetically and molecularly defined by abnormalities involving genes encoding subunits of core-binding factors. CBFs are a family of heterodimeric transcriptional elements implicated in the regulation of hematopoiesis [2,3], containing a common CBFB subunit associated, in lymphoid and myeloid tissues, with RUNX1, one of the three CBFA members. The translocation (8;21) results in the creation of a chimeric gene RUNX1/RUNX1T1, while inv(16), or with significantly lower incidence t(16;16), leads to the fusion of the CBFB gene with MYH11, the smooth muscle myosin heavy chain gene, resulting in the chimeric CBFB-MYH11 gene, which occurs in approximately 8% of adults with de novo AML [4].
According to 2017 ELN risk stratification [1], CBF AML are classified in the favorable risk category, with high CR rates after standard induction therapy and encouraging outcome, in particular after consolidation regimens containing a repetitive cycle of high-dose cytarabine [5]. Nevertheless, the 5-year overall survival (OS) rate in patients with CBF AML is about 50–60% [6], suggesting that it would be required to detect markers of more aggressive disease phenotypes, in order to optimize prognostic stratification-oriented treatments.
The effects on the long-term outcome of secondary cytogenetic abnormalities, detected in approximately 40% of inv(16) AML patients [7,8], and additional molecular lesions, which have been demonstrated to be required for leukemogenic transformations [9], remain controversial.
In the last decades, probably depending on the accessibility of increasingly sensitive biomolecular tools, the focus has shifted to disease evaluation in terms of the dynamic quantitative assessment of molecular measurable residual disease (MRD). Indeed, the changing of MRD levels throughout cycles of therapy, in particular the reduction at a specific timepoint compared to pre-treatment baseline levels, has proved to be the most useful independent prognostic variable for survival, allowing one to identify patients at high risk of relapse, as possible candidates for more intensive therapeutic approaches, including allogeneic hematopoietic stem cells transplantation (allo-SCT).
The purpose of this manuscript is to offer an overview on the most prognostic factors affecting the clinical outcomes of patients with AML harboring CBFB-MYH11, with a special focus on the role of MRD monitoring in risk stratification and treatment guidance.

2. Patient- and Disease-Related Features at Diagnosis

In general, AML with inv(16)(p13.1q22) or t(16;16)(p13.1;q22), hereafter referred as inv(16), exhibits some peculiarities, which also differentiate it when compared to AML with t(8;21)(q22;q22.1), abbreviated t(8;21) [6,7,8,10], such as presentation with acute myelomonocytic leukemia bone marrow morphology accompanied with abnormal/dysplastic eosinophils. Extramedullary disease, such as lymphadenopathy, hepatosplenomegaly, skin and gingival infiltrates, is often associated with inv(16) [6,8], whereas myeloid sarcoma in other extramedullary sites appears more frequently in t(8;21), and associated with worse prognosis [11].
Focusing on clinical variables (Table 1) [6,7,8,10,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33], age is recognized as a negative prognostic factor, not only for a lower response to induction therapy, but also with regard to survival. CBF AML is relatively more incident among younger patients, accounting for only 5–8% of all AML over 60 years [34,35]. However, among the entire population, the incidence of CBF AML increases with age, reflecting the rise of all AML cases in the general population [22]. While elderly patients with CBF AML retain better prognosis compared to those with other AML subtypes, in comparison to younger patients with CBF AML, they reveal significantly worse outcomes. First of all, comorbidities and poorer performance status might hamper management with a standard regimen of therapy. As a consequence, older patients show high therapy-related mortality [8] because of excessive toxicity from chemotherapy. Nonetheless, it is demonstrated that when patients who die early within the end of induction are excluded, trends of long-term survival are similar in younger and older subgroups [22]. In addition, elderly patients seem to fail to clear leukemic cells, suggesting a refractory attitude, due to modifications in pharmacokinetic and multidrug resistance phenotype [36,37,38]. It has also been proposed that in older patients AML results from a series of mutational events, leading to the development of multiple subclones potentially showing chemo-escape mechanisms. Of interest, when treated with intensive schedules, elderly CBF AML patients frequently obtain CR, also in the setting of rescue therapy after relapse [23]. However, regarding long-term survival, the reported negative impact of age on OS and RFS is attributable to more frequent additional chromosome abnormalities, a possible indicator of genetic instability, as well as to attenuated post-induction treatments [39]. As evidenced in Table 1, some studies identified statistically significant age cut-offs; when considering data collectively, patients over 40 years of age have a dismal outcome.
As reported in several studies, WBC counts and parallel bone marrow/peripheral blood (BM/PB) blast percentages are higher in inv(16) than t(8;21) AML, at diagnosis [6,7,8,40], proposing a somewhat different type of proliferation kinetics, perhaps related to additional genetic aberrations, such as receptor tyrosine kinase (RTK) mutations [19]. Several authors agree on granting a prognostic relevance to white blood cell (WBC) counts, by recognizing, in some cases, cut-off points for statistical significance [10,13,17,29]. Nevertheless, the negative impact of leukocytosis in terms of either response to therapy or of long-term remission has not so far definitely assessed. Indeed, while a correlation between induction failure and early death in inv(16) AML emerging with hyperleukocytosis [8,10] has been documented, on the other hand, prolonged CR could also be observed regardless of WBC counts at onset. Furthermore, even if an unfavorable effect of high WBCs in increasing relapse rate has been demonstrated [41], no influence on OS was observed, probably depending on deep responsiveness to alternative rescue strategies. Analogous observations could be provided about platelets (PLT) count: the French AML intergroup [10] identified an optimal PLT count threshold predictive of induction failure, without worsening the subsequent risk of relapse. Although a documented WBC threshold indicating high risk is not currently available [42], data recommend more prudent approaches in induction treatment for patients admitted with leukocytosis and/or thrombocytopenia.
Hoyos et al. [17] confirmed both age and WBC count as variables associated with decreased OS, when using these parameters to separate three groups with statistically significant difference of survival, namely, 80% at 5 years for patients without adverse factors versus 61% for patients with one factor and 36% for patients older than 50 years and with WBC > 20 × 109/L.
A marginal role is conferred to sex and ethnicity. In fact, only Marcucci et al. [6] and Paschka et al. [43] attributed a prognostic significance to sex. The former study showed that male patients could survive longer, and the latter study reported that female patients with inv(16), younger than 60 years, were more likely to maintain shorter remission. Fewer reports addressed the prognostic impact of ethnicity. Inv(16) AML is somewhat less frequent among non-whites compared to patients with t(8;21). Moreover, Black and Hispanic patients have worse survival rates compared to white Caucasian patients [22]. These findings are possibly related to different biological behavior of the disease, because the environmental disparities are not considered sufficient to justify an evident divergence among patients treated according to the same protocols.

2.1. Secondary Additional Genetic Abnormalities

According to the latest evidence [30] formulated on the theory of multistep outset of AML [3,44], CBF AML seems to result from the acquisition of a sequential order of mutations, affecting firstly transcription and differentiation (such as CBF) genes, followed by activating alterations that increase proliferation, such as class III RTKs. Additional lesions in this latter gene family are the most common in CBF AML [30], involving primarily the KIT gene (occurring in 17–38% of CBF AML [45]), whose significance on the prognosis of AML has been widely debated. KIT aberrations could affect either the tyrosine kinase domain, with substitution of a single amino acid at codon 816 or 822 within exon 17 (higher incidence among CBF AML [14,28]), or the extracellular domain, corresponding to insertions or deletions in exon 8; more rarely, internal tandem duplications in exon 11 could impair the juxtamembrane domain. Due to the debatable negative impact attributed to KIT mutation, CBF AML with KIT mutation was formerly assigned to the intermediate category, whereas more recent guidelines only stated that prognosis may be less favorable than CBF AML without such a mutation. When the two subtypes of CBF AML are considered, the majority of reports agree in conferring adverse prognosis in terms of relapse and sometimes [17,27] OS, mainly due to exon 17 mutation, in t(8:21) AML, as documented in some analyses restricted to D816 alteration, compared to other KIT mutations [14,26,32,41,46]. On the contrary, the impact of KIT mutations on inv(16) is less well concerted (Table 2). Different to t(8;21) AML, most recurrent alterations affect exon 8, in inv(16) AML [19,27,47]. Some authors recognize a correlation between KIT mutations and other biological features, such as higher WBCs and circulating blasts at onset [43], assisting the idea that RTK mutations lead to the enhancement of proliferation. Interestingly, the most consistent evidence concerning the unfavorable influence of KIT mutations is provided to influence the relapse rate [48,49], rather than the OS, probably owing to the higher sensitiveness to salvage therapy [8]. Schwind et al. [50] investigated the survival implication of non-type A fusion transcripts in inv(16) AML, documenting their association to longer EFS, maybe not strictly depending on the type of transcript, but because of the mutual exclusivity of non-type A and KIT mutations. In fact, in patients harboring the most frequent type A fusion transcript, better prognosis is achieved in those with wild-type KIT. The divergences among studies could be also related to allele burden, as demonstrated by Allen et al. [15] In the total cohort of CBF AML, outcomes are improved in KIT-mutated cases with a higher mutant level of 25%, in terms of relapse risk. Yoon et al. [20] illustrated poorer OS in CBFB-MYH11 AML with c-KIT mutation, by including this genetic alteration in a prognostic-risk scoring, combining age and additional chromosome abnormalities, and attributing an important weight on survival. Moreover, Ishikawa et al. [28] observed that c-KIT mutations correlated, statistically, to a lower reduction in fusion transcript levels, after the completion of consolidation chemotherapy, similar to what Qin et al. [47] documented after the first induction, despite neither impacting OS nor RFS. The importance of RTK mutations was related to the emerging possibility to target them by tyrosine kinase inhibitors, based on their activity on different mutations: first-generation TKIs (such as imatinib) work effectively against KIT variants of exon 8 and exon 17 mutants involving codon N822, but not against mutants involving codon D816, successfully targeted by other drugs, such as dasatinib and midostaurin [51]. However, the currently available data do not support the routine use of TKIs in association with chemotherapy outside of clinical trials [52]. Moreover, MRD status mainly outweighs the prognostic effects of additional signaling mutations, so that several authors do not take any clinical action based on KIT mutation status only. Overall, due to the lack of evidence about its impact on long-term prognosis in AML, the assessment of KIT mutational status is not recommended as part of the initial routine diagnostic workup, based on the international ELN recommendations [1].
In second place for incidence, mutations in the RAS genes, mainly NRAS, are observed in 17–53% of inv(16) AML, i.e., more frequently than in t(8;21) AML [12,15,16,19]. The prognostic role for these RTK mutations has been proposed in only a few studies, such as in the study by Ishikawa et al. [28], suggesting poor RFS for inv(16) patients with NRAS mutation. RAS variants, belonging to activating mutations, lead to uncontrolled proliferation, as shown by the correlation with higher WBC [15] and may potentially increase sensitivity to chemotherapy [56].
Likewise, FLT3 is a member of class III tyrosine kinase receptors, and its mutations are relatively rare in CBF AML. While internal tandem duplication (ITD) is the most frequent in cytogenetically normal AML, holding an unfavorable prognostic impact depending on allelic burden, FLT3 tyrosine kinase domain (TKD) point mutations represent the most common alteration, in inv(16) AML, being associated with BM blast percentage [16]. A clear-cut prognostic significance is not attributable to FLT3 mutations, because of their negative impact on relapse risk, according to some authors [16,19], whereas Allen et al. [15] showed a favorable role of FLT3-TKD high allelic variant on OS.
Remarkably, recent interest is growing about the mutational landscape associated with the rearrangements of the CBF transcriptional complex. Beside the founding mutation, cooperating molecular events contribute to define a distinct gene expression profile of the specific CBF subtype [30]. In inv(16) AML, significantly less co-mutations are detected [25], suggesting that CBFB-MYH11 promotes leukemogenesis without the need for increasing evolutionary advantage.

2.2. Secondary Additional Chromosomal Abnormalities

Secondary karyotypic aberrations are present in about 40–70% of inv(16) AML, with an incidence increasing with age [10]. In CBFB-MYH11 AML, most frequent additional chromosome alterations are trisomy of 22 and 21, followed by +8. Similar to other genetic mutations reported above, some authors correlate karyotype abnormalities to clinical manifestations of the disease, such as higher WBC counts at onset [8]. There is consensus about the prognostic favorable role of +22 [6,8] in conferring lower probability of relapse. In contrast, conflicting results had been shown about trisomy 8: some authors documented a negative impact on prognosis [7,19,30], while others reported association with longer survival [23,30]. The number of supplementary chromosome lesions, especially when they are more than 3, in line with other AML subgroups, is associated with a worse outcome [23], according to the prognostic risk scoring by Yoon et al. [20]. Recently, Han et al. [33] have retrospectively drawn up the largest cytogenetic dataset of CBF AML, therefore characterizing and differentiating the genomic features of the two AML subtypes. Trisomies of chromosomes 8, 21 or 22 recurred significantly more frequently in inv(16)-bearing patients, in line with previous studies [6,8,19], such as hyperdiploidy. On the other side, del(9q) and abnormalities in sex chromosomes were more common in t(8;21) AML. The survival analysis of the study revealed different prognostic patterns of cytogenetic factors among the CBF AML subgroups: in inv(16), chromosomal alterations other than +8 were associated with decreased OS, while trisomy 8 was associated with longer survival. Differently, in t(8;21), hypodiploidy was significant for DFS, whereas hyperdiploidy and del(9q) were associated with improved OS [33]. In the current molecular era, these results confirm the timeless relevance of conventional cytogenetic findings on CBF AML prognosis.

3. MRD Monitoring in CBFB-MYH11 AML

Traditionally, the determinant indicators of prognosis in AML have been identified in the pre-treatment features described above, related to either the patient or the disease features. Another relevant factor impacting on prognosis is represented by the response to cytoreductive therapies, which direct subsequent disease management. Over the last two decades, efforts have been made to improve the assessment of disease response and, especially, the monitoring over time, because although being classified as a favorable risk category, CBFB-MYH11 AML will experience relapse in nearly 30% of patients, with an estimated RFS rate of 42%, following standard care. The current definition of morphological response lacks sensitivity, and the purpose has been to more accurately detect the residual leukemic burden in BM, far below the 5% blast percentage detectable on microscopic examination [57,58], by detecting what is defined measurable (formerly minimal) residual disease (MRD). Persistent leukemic cells result from cellular resistance mechanisms [59]. Available qualitative molecular tools initially provided partial information about disease status. Firstly, because of low sensitivity techniques, MRD levels below the detection threshold could still be present, despite a negative qualitative reverse transcriptase polymerase chain reaction (RT-PCR) [60,61]. Furthermore, MRD-positive patients will not inevitably be destined to poor outcome, suggesting that monitoring trends of transcript during treatment and further remission phases might be more useful in predicting prognosis [62,63]. As widely applied in other acute and chronic hematologic malignancies, such as acute lymphoblastic or chronic myeloid leukemia [64,65], quantitative molecular methods have become mandatory in longitudinal disease monitoring [66]. Submicroscopic amounts of blast cells could be recognized from the distinct immunophenotypical pattern of lineage-specific antigen expression, identified by multiparametric flow cytometry (MFC), through a combined approach of stable leukemia-associated aberrant immunophenotype (LAIP) and different-from-normal, with a sensitivity of 10−3–10−5 [67]. Furthermore, with an accuracy up to 10−6, quantitative reverse transcriptase PCR (qRT-PCR) is currently considered the gold standard in detecting MRD, applicable in 50–60% of AML patients showing distinct molecular lesions. The ELN MRD working party afforded clinical issues in the application of MRD monitoring in AML by updating recommendations with concepts of complete molecular remission, molecular relapse, and molecular progression [68]. Interestingly, in the same international consensus, MRD status has been recognized to be a better predictor of relapse risk than the presence of cooperating mutations, such as KIT and FLT3-ITD in CBF AML [1], supporting the essential inclusion of molecular MRD detection into clinical management. Among newer molecular methods, targeted next-generation sequencing (NGS) could provide a complete test of all leukemia-specific genetic aberrations at once, with very high sensitivity. However, NGS data interpretation in MRD monitoring is actually complicated by incurring in some common mutations of any prognostic value but is associated with clonal hematopoiesis of indeterminate potential [69,70]. To note, recent studies have aimed to investigate the clinical relevance of NGS MRD detection, at different timepoints, finding the stronger prognostic impact of NGS MRD status after the first consolidation (2nd timepoint) than at first remission, which could help to identify patient candidates for more aggressive treatment, even when MRD is undetectable by MFC [71]. Indeed, MFC and NGS might be suggested to be used in combination in monitoring the disease, as also MFC and qRT-PCR, especially in the post-induction phase [72,73].
The above-mentioned ELN consensus document recommends timepoints and tools for MRD assessment in CBFB-MYH11 AML. Nevertheless, the lack of technique standardization and heterogeneity of available data results in non-firmly conclusive implications for clinicians, mainly regarding the indication to assign patients to intensive therapeutic approaches. In Table 3, we collected studies in which molecular MRD is found to play a role in impacting outcomes, both in terms of copies of transcript or in terms of logarithmic reduction/rise between different timepoints of detection.

4. ELN Recommendation for MRD Assessment

4.1. During the Treatment Phase, We Recommend Molecular MRD Assessment at Diagnosis

In all the studies reported in Table 3, CBFB-MYH11 fusion transcripts are detected by quantitative molecular methods and normalized to endogenous reference genes. In general, no significant differences in outcomes are observed, depending on the level of transcript at diagnosis [16,75,80,82], based on the great heterogeneity of the fusion gene expression [76]. Marcucci et al. [74], as well as Corbacioglu et al. [81], described only a correlation between copy number and high percentage of BM blasts at disease onset. No correlation was also found with the type of fusion transcript, the type A mutation being the most frequently observed [77,81]. Conversely, Schnittger et al. [77] brought out a strong prognostic impact of the level of transcript on both OS and EFS. A score based on the median expression ratio, after consolidation therapy, and the 75th percentile of the expression ratio at diagnosis was formulated, although it was not possible to identify an absolute threshold to define an early molecular response. However, even if no influence is demonstrated on prognosis, the molecular quantitative assessment of fusion transcript is recommended, at least to evaluate its subsequent modifications.

4.2. After Two Cycles of Standard Induction/Consolidation Chemotherapy

The earlier those patients at higher risk of disease relapse are identified, the better diversified therapeutic approaches may be engaged for them. Therefore, several groups have investigated which could be the most relevant timepoint for prognosis during treatment. Some studies proposed a threshold of copy number for discriminating subgroups with shorter remission (i.e., 100 copies in BM [17,73,75], 10 copies in PB [82]). Others, instead, concluded that early assessment of MRD did not predict the disease course [74,77,81], contrary to what is generally thought for early morphologic response, possibly due to the well-known good responsiveness of CBF AML to induction treatment, in addition to a rather slow decline in the disease burden. Interestingly, the prognostic impact of MRD after induction is mostly referred to relapse risk rather than to survival, emphasizing the efficacy of salvage treatment in this category of AML. Of note, Stentoft et al. [78] and Yoon et al. [20] attributed a prognostic relevance not to an absolute level of fusion transcript, but rather to transcript levels, referred to a number of copies at disease onset, namely, a qPCR reduction > or = 3 log, which was associated with longer OS.
Concerning consolidation therapy, the heterogeneity among studies renders highly difficult the comparison among them. In fact, while there is agreement on cytarabine-based consolidation therapy indication [5,78,86,87], controversial questions remain regarding the number of cycles, the most appropriate dose and schedule, as well as the role of combination with other agents. In most studies, two to four cycles have been administered after the attainment of CR and after each cycle MRD was assessed. Early consolidation cycles recur as relevant timepoints. Guièze et al. [80] reported poorer continuous CR (CCR) for values of MRD2 (after first consolidation) > 0.1%; at the same time, the decrease in MRD2 relative to transcript level at diagnosis (deltaMRD2) also strongly impacted the length of remission. Accordingly, the French AML Intergroup [16] demonstrated that a more than 3-log MRD reduction after first consolidation, such as an absolute MRD2 level < or =0.1%, could be used to differentiate low-risk from high-risk patients. Moreover, the threshold of 0.1% resulted to impact on survival also at the end of the second consolidation cycle, as reported by the studies of Duan et al. [31,32] Corbaciouglu et al. [81] underlined the importance of MRD detection in the time window of consolidation and early months after the end of treatment: this timing turns out to be the most informative, in accordance with the median time of relapse occurrence. An early prediction of prognosis allows the clinicians to propose alternative strategies of consolidation. Jourdan et al. [16] recognized in MRD2 the timepoint to evaluate patients for transplant options. Qin et al. [84] recommended allogeneic stem cell transplantation, if CBFB-MYH11 levels could not decrease to <0.2% after two courses of consolidation, improving RFS and OS [31,32] in these patients at high risk of relapse.

4.3. And after the End of Treatment

MRD assessment is recommended at the end of the last consolidation cycle, but its impact on outcome at this timepoint is not unequivocal [60]. If it could be assumed that the majority of long-term survivors maintain PCR-negativity [75,88], it has likewise been reported that a few of the patients in prolonged CR never clear MRD. On the contrary, 10–20% of PCR-negative patients would eventually relapse [89,90,91]. A molecular persistence at low transcript level in BM is common in CBF AML, in the first period after therapy as well as after stem cell transplantation. The possible presence of resistant leukemic clones or quiescent preleukemic cells, potentially responsible for relapse, could be supposed. The latter, called leukemic-initiating cells (LICs) [83] or leukemic stem cells (LSCs) [58,70], are defined as cells capable of initiating disease, self-renewing, with chemo-resistance properties. This subpopulation, usually CD34+/CD38-, may also contribute to subsequent relapse. A combined flow cytometry and fluorescence in situ hybridization examination could help in detecting LSC persistence, as reported by Wang et al. [83], given that the presence of FISH+CD34+CD38- cells predicted OS and RFS. Furthermore, the interpretation of residual rearranged copies is even more difficult because such molecular lesions carried by cells resulting from age-related clonal hematopoiesis of unknown potential [92,93] may not be indicative per se of disease recurrence. One possible explanation lies in biologic mechanisms of a somewhat immunosurveillance effect in preventing disease reappearance, similar to what is documented in the allotransplant setting, that might lead up to the clearance of leukemic compartment, as suggested by the progressive decline of MRD documented, in a timeframe up to 16 months, after consolidation, in some patients without further treatment [62,75,94]. Those findings reinforce the caveat that patients with low molecular burden of disease may need close monitoring, instead of urgent intervention [95]. The recent observation of CBFB-MYH11-specific T cells indicates that CBFB-MYH11 fusion neoantigen is naturally processed and presented on AML blasts and enables T cell recognition and the killing of leukemic cells, supporting the hypothesis of a potential contribution of specific cytotoxic cells in MRD control and CCR maintenance [96].
Hence, unlike other molecular rearrangements, the aim of treatment has to be the transcript reduction below a specific level at definite timepoints, rather than the obtainment of strict MRD negativity [97].

4.4. During Follow-Up of Patients with PML-RARA, RUNX1-RUNX1T1, CBFB-MYH11, Mutated NPM1, and Other Molecular Markers, We Recommend Molecular MRD Assessment Every 3 Months for 24 Months after the End of Treatment

Once treatments are completed, for patients not candidate to further therapy lines, it will be necessary to set up, on a medium-long-term basis, a reliable follow-up in tracking either an ongoing response or, promptly, an impeding relapse. Even at this stage, a consensus in monitoring MRD kinetics emerges from published studies. In fact, relapse could effectively be predicted by a comparison between longitudinal sampling, rather than by overcoming a definite threshold. ELN updated recommendations reflect such an awareness: molecular relapse, as well as molecular progression, is defined by a logarithmic increase in MRD levels between two consecutive samples, underlining the dynamic interpretation of a molecular parameter. In addition, this approach makes data more comparable, despite methodological and clinical differences among studies. The use of a logarithmic increase for defining relapse and progression is therefore operational in CBF AML, because of the predominantly slow pattern of regrowth, depending on biological factors, which allows one to observe evolutive trends before morphological relapse. Some concordance exists in the proposed patterns of molecular values: as a reduction of 2–3 log after induction/consolidation [75,78] is expected, a controlled disease is not supposed to show a 10-fold increasing of MRD, during follow-up. A monitoring schedule is pivotal for avoiding the missing herald of relapse, so that, at this point, a relevant interrogative matter is about frequency in sampling. International guidelines indicate to assess MRD every 3 months for at least the first 2 years after the end of treatments, because relapse occurs after 2 years of complete remission, more rarely [79,81,85]. This timeframe has been consistently derived from several studies that described that in patients monitored at 3-month intervals a clinical recurrence was predictable by rising MRD [70,77,80,83]. Krauter et al. [76], such as other authors earlier [74], recognized two patterns of relapse: some patients obtained molecular negativity directly after induction/consolidation, with a secondary transcript level increase, whereas others maintained a detectable disease at the end of treatment, but, in both instances, the median interval between increasing MRD and hematological relapse was beyond 3 months. When the kinetics of transcript levels rising was evaluated, a slower rate of MRD increasing for CBFB-MYH11 AML was observed, as compared to NPM1 or PML-RARA positive AML, with a BM doubling time of 36 days and the longest lag before morphological relapse (even 8 months) [98], suggesting the need for longer monitoring. However, these considerations may be challenged because the possibility of more rapid relapse kinetics cannot be excluded [79]. Relevant to this, Yin et al. [82] reported a median increment in transcript levels of about 0.5 log10/month, so that a 3-monthly assessment schedule might fail to identify a potential MRD increase up to 3 logs, impairing potential pre-emptive therapeutic strategies, including SCT [99]. Puckrin et al. [85] emphasized that the monitoring approach indicated by ELN could fail to detect, in a timely manner, relapsing patients, because the majority of clinical recurrences occurred within 100 days from molecular relapse. Reasons could be attributed to real-life limitations, such as difficulties in fulfilling sampling intervals, differences in either specimen quality or sensitivity of available molecular assays. This evidence warrants consideration about the informative value of MRD, in terms of treatment decision: if, on the one hand, clear recommendations have been formulated about timeframes of monitoring, no formal instructions are available to indicate either therapy changes or pre-emptive interventions, leaving the precautionary management of impending relapse at the single center’s discretion.

4.5. In BM and in PB. Alternatively, PB May Be Assessed Every 4–6 Weeks

Whether PB sampling can definitely succeed in replacing bone marrow sampling for MRD testing remains an open point. Sensitive and reliable blood-based assays would be an attractive possibility, given the less invasive nature compared to BM aspirations. The two sources have been studied as alternatives in several studies, albeit the most clinically relevant findings are derived from BM specimens. As detailed in Table 3, some authors, in the identification of significant thresholds of fusion transcripts for prognosis, included PB cut-offs about five times lower than in BM, taking into consideration the difference in sensitivity. This interest has grown from evidence in other AML subtypes, namely, NPM1-mutated AML, in which discrimination for survival was better by using PB rather than BM [100]. Boeckx et al. [101] reported preliminary data in support of a moderate correlation in PB-BM pairs, although generally higher levels are found in BM, suggesting that PM examinations could be performed every 2–3 months during follow-up, with further BM aspirations considered to be necessary only in the case of rising transcripts in PB. Encouraging results also emerged from Stentoft et al. [78], who demonstrated a convincing correlation between PB and BM, and from Ommen et al. [98], who provided preliminary data suggestive of equal usefulness of either BM or PB sources. Moreover, Guièze et al. [80] revealed a high degree of concordance for levels of MRD higher than 0.1%, whereas for lower levels, BM appeared more sensitive. Interestingly, Corbacioglu et al. [81] recommended to use BM samples during consolidation therapy, while, during follow-up, MRD could be measured on PB for evaluation of longitudinal rising levels during CCR. The UK MRC trial group [82] offered an optimal schedule for molecular monitoring and confirmed that both BM and PB were comparable for MRD detection after the end of treatment, even if in 10–15% of patients, negative PB showed discordance with MRD positivity detection in BM.
Recently, Skou et al. [99] reinforced the notion that an effective surveillance of imminent relapse could be achieved through frequent PB sampling. In fact, both the persistent molecular positivity in BM, despite continuous remission, and the relative absence of progenitors in peripheral blood should mean higher predictivity in detecting MRD in PB. A positive molecular finding from peripheral blood is more suggestive of imminent relapse. Doubts might arise about whether PB monitoring provides sufficient lead time to prevent clinical relapse. Despite earlier occurrence, no meaningful difference arose from comparisons between the rate of leukemic regrowth between PB and BM. In addition, it is possible to collect samples from peripheral blood with higher frequency [53] (possibly monthly, during the first year following the completion of therapy), which, in turn, are easily accessible and more acceptable by patients, outweighing the gap of molecular load about 0.5–1 log10 between BM and PB. Furthermore, additional information from PB with respect to BM could be provided, by gene expression assays and combined multiparameter flow cytometry, able to detect with more specificity, even though with less sensitivity, potential circulating leukemic cells, due to the background of less progenitor populations compared to bone marrow [58].
Hence, not only a comparable but also a better disease surveillance could be assured by monthly PB sampling, which allowed us to efficiently identify molecular relapse, as an increase by 1 log10 between two positive samples, confirmed by paired BM and PM assay, after 4 weeks [99].

4.6. MRD Should Be Assessed Pre Transplant. MRD Should Be Performed Post Transplant

Regarding the transplantation setting, although assessment is recommended before and after procedure, no specific indication is provided about the interpretation of MRD values. In consideration of the relatively satisfying long-term control of disease with repeated high or intermediate-dose cytarabine consolidation or alternatively autologous stem cell transplantation (auto-SCT), CBF AML are not usually candidated for allo-SCT in first CR, contemplating this procedure for patients in second remission [102], although data about post-remission therapy still remain debated. As reported in some studies [103,104,105], in first remission no differences have been found in terms of LFS and RI between auto-SCT and allo-SCT, to the detriment of the higher TRM (therapy-related mortality) of the non-autologous approach. On the other hand, some authors [20,106,107], comparing non-allogeneic and allo-SCT consolidation treatments, underlined favorable OS for the latter, encouraging the use of frontline transplantation for subgroups of CBF AML with adverse risk characteristics, including cases showing MRD positivity. The negative impact on the survival of residual disease prior to allogeneic SCT is demonstrated by several studies, as showed in a meta-analysis of Buckley et al. [108]. In case of indication of allogeneic transplantation in MRD-positive patients, haploidentical allograft seems to be superior to match sibling donor, suggesting strong anti-leukemia effects in eradicating pre-SCT residual disease [109,110,111]. Moreover, in this peri-transplant setting, rather than single timepoint positive or negative status, a significant role is attributed to the MRD dynamic trend among prior chemotherapy cycles. Interestingly, Qin et al. [84] identified as a sole independent adverse prognostic factor for CIR, DFS and OS a transcript level reduction less than 3 log after course 2 consolidation, and only in this poor MRD category of patients allo-SCT could significantly improve outcome, without any advantage for good MRD patients. When MRD trend after second consolidation indicates an SCT approach, several studies stress the negative impact of detectable MRD on the risk of post-transplant relapse [112,113], and achieving MRD negativity might result in improved transplantation outcome. However, it remains unclear whether patients with positive MRD should be straightly directed to SCT or should receive further chemotherapy. In fact, precisely in poor MRD responders, transplantation by exploiting intensive conditioning regimens, rather than reduced-intensity schemes, and utilizing alternative or mismatched donors, theoretically eliciting stronger GvL [114], could offer an advantage on outcome. Interestingly, among a series of 58 unselected AML patients receiving SCT, Zhang et al. [115] proved transplantation as a safe choice also for the treatment of refractory/relapsed (r/r) cases. In details, while the 5-year OS of r/r AML patients was 54.21% lower that documented in non-r/r patients (71.82%), the 5-year EFS was not statistically different between the two groups (53.54% versus 62.07%). Of note, the 5-year OS rates of r/r AML patients who had subsequently obtained CR and those with persistent disease before SCT were not different, 56.06% and 51.85%, respectively (p = 0.6408), due to the rapid and early tapering of immunosuppression therapy after transplantation and prophylactic donor lymphocyte infusion.
To reiterate the relative significance of positive MRD pre SCT, Zhao et al. [109] reported that instead of MRD before SCT, the unfavorable effect on prognosis in multivariate analysis is attributed to detectable MRD post haploidentical SCT, without the necessity of further intensive chemotherapy for MRD-positive patients prior to transplantation. Yalniz et al. [95] showed that there is no impact of the MRD level by qRT-PCR on the relapse incidence, even in the patients with the highest disease burden. In addition, in this study, two MRD checkpoints post SCT were identified: the presence of MRD on day +30 did not indicate impending relapse, whereas patients who had detectable disease on day +100 had a 3-year relapse incidence of 27.6% versus 9.7% for patients without residual disease, although not reaching statistical significance. Monitoring MRD after the first 3 months of transplantation rather than before could be more informative about the risk of relapse: lower LFS and higher CIR resulted for a decrease of less than 3 logs compared to pre-treatment levels [116]. Pre-emptive therapeutic strategies, including approaches selectively increasing GvL (graft versus leukemia), to target MRD persistence post allogeneic SCT in AML patients with inv(16)/t(16;16) are warranted.

5. Novel Therapies

In recent years, the approval of several novel agents for treating AML was obtained; the most remarkable for improving outcomes in inv(16) is the addition of the anti-CD33 monoclonal antibody gemtuzumab ozogamicin (GO) to the remission induction cycle [117,118,119]. To note, data have been published about the first steps toward specific T-cell immunotherapy in fusion gene-driven AML [96]. CBFB-MYH11 protein could act as neoantigen, giving rise to the potential development of a personalized adoptive TCR T-cell strategy. Because of the early and essential role in leukemogenesis and the specificity persistence in blast cells, CBFB-MYH11 should represent an optimal target, with minimal risk of off-tumor toxicity. Recent translational studies are providing the basis for future targeted therapeutic approaches. For example, advances in treatment would be warranted focusing on the molecular processes involved in leukemogenesis driven by fusion protein CBFB-SMMHC encoded by the CBFB-MYH11 founder gene, by the potential target of specific or indirect inhibitor [120], or exploring the disease mechanism of oncogene-induced chromatin remodeling [121].

6. Conclusions

In recent years, the advances in molecular diagnostic and monitoring, with the simultaneous incoming of new therapeutic agents, have led to significant improvements in clinical AML management. Awada et al. [122] recently integrated cytogenetic and gene sequencing data from a multicenter cohort of nearly 7000 AML patients that were analyzed using standard and machine learning methods to generate a novel AML molecular subclassification with biological correlates corresponding to underlying pathogenesis. Despite the heterogeneity of AML genomics, non-random genomic relationships were capable of identifying four novel unique genomic clusters with a distinct prognosis, regardless of the availability of pathomorphological or anamnestic information. MRD monitoring actually supersedes other well-recognized clinical features, with independent prognostic value, at least in some AML subgroups. European Leukemia Net has offered recommendations about quantitative and qualitative MRD monitoring, as part of the standard of care for AML patients. MRD threshold levels might prelude worse outcome, as clinical relapse could be accurately predicted by sequential sampling during follow-up in both BM and PB. Increasing MRD value or molecular relapse ensures a window of opportunity to adapt risk-directed interventions before overt progression. In CBF AML, the MRD-negative groups displayed more favorable RFS than those with MRD positivity, and OS was also superior in the MRD-negative group. Moreover, the CIR was statistically significantly lower in the MRD-negative group, when considering the most significant cut-off MRD level of 0.1% [123]. Nevertheless, the standardization of molecular tools, including the application of newer technologies, and timepoints of MRD investigations in CBF AML, in order to guide therapeutic decisions, is still controversial. It is argued whether patients in CR1 should be offered transplant, based only on early response, by considering an estimated transplant-related mortality of 10% to 15%, while at least half of these patients would not eventually relapse. Therefore, it is not actually confirmed that a pre-emptive approach would be beneficial, when considering the slower kinetics of leukemic growth, the real-life MRD monitoring limitations and the overall good responses achievable with salvage therapy, in case of a full-blown relapse.
Ultimately, further studies are needed to improve knowledge about the best employment of MRD information to improve the clinical outcomes of CBF AML patients.

Author Contributions

A.T. and F.F. designed the study, reviewed the literature and wrote the manuscript; F.B., V.P., D.G., A.G., C.C., L.G., R.G., H.C., F.D., R.M. (Rossana Maffei), S.M., P.B. and L.P. reviewed the literature and wrote the manuscript; R.M. (Roberto Marasca), T.T., E.T., P.C. and M.L. supervised the study, analyzed data and critically revised the manuscript. All authors have read and agreed to the published version of the manuscript.


This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.


This work was supported by grants from the Associazione Italiana per la Ricerca sul Cancro (AIRC), Milan, Italy (IG 20624-2018) (ML), the Progetto di Eccellenza Dipartimento MIUR 2017 (ML), and the “Charity Dinner initiative” in memory of Dr A. Fontana for Associazione Italiana Lotta alle Leucemie, Linfoma e Mieloma (AIL)—Sezione ‘Luciano Pavarotti’—Modena-ONLUS. This work was also supported by grants from the Fondazione Regionale per la Ricerca Biomedica (PC); Fondazione Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Policlinico San Matteo di Pavia [Ricerca Corrente 08069113 and 08069119 (PC)]; Fondazione Just Italia (PC).

Conflicts of Interest

F.F. served on advisory boards for Jannsen on the clinical use of decitabine for Novartis on the clinical use of midostaurin and eltrombopag and received travel grants from Jazz Pharmaceuticals. M.L. served on advisory boards for Novartis on the clinical use of midostaurin, for AbbVie, on the clinical use of venetoclax, for Jazz Pharmaceuticals, on the clinical use of Vyxeos, for Gilead Sci., on the clinical use of Ambisome, for MSD, on the clinical use of letermovir, for Sanofi, on the clinical use of caplacizumab, from Daiichi-Sankyo, for the clinical use of quizartinib and received travel grants from Gilead Sci and Sanofi. The other authors declare no potential conflicts of interest.


  1. Döhner, H.; Estey, E.; Grimwade, D.; Amadori, S.; Appelbaum, F.R.; Büchner, T.; Dombret, H.; Ebert, B.L.; Fenaux, P.; Larson, R.A.; et al. Diagnosis and Management of AML in Adults: 2017 ELN Recommendations from an International Expert Panel. Blood 2017, 129, 424–448. [Google Scholar] [CrossRef] [Green Version]
  2. De Bruijn, M.F.T.R.; Speck, N.A. Core-Binding Factors in Hematopoiesis and Immune Function. Oncogene 2004, 23, 4238–4248. [Google Scholar] [CrossRef] [Green Version]
  3. Speck, N.A.; Gilliland, D.G. Core-Binding Factors in Haematopoiesis and Leukaemia. Nat. Rev. Cancer 2002, 2, 502–513. [Google Scholar] [CrossRef]
  4. Byrd, J.; Mrózek, K.; Dodge, R.; Carroll, A. Pretreatment Cytogenetic Abnormalities Are Predictive Ofinduction Success, Cumulative Incidence Ofrelapse, and Overall Survival in Adult Patients with de Novo Acute Myeloid Leukemia: Results from Cancer and Leukemia Group B (CALGB 8461). Blood 2002, 100, 4325–4336. [Google Scholar] [CrossRef]
  5. Byrd, J.C.; Ruppert, A.S.; Mrózek, K.; Carroll, A.J.; Edwards, C.G.; Arthur, D.C.; Pettenati, M.J.; Stamberg, J.; Koduru, P.R.K.; Moore, J.O.; et al. Repetitive Cycles of High-Dose Cytarabine Benefit Patients with Acute Myeloid Leukemia and Inv(16)(P13q22) or t(16;16)(P13;Q22): Results from CALGB 8461. J. Clin. Oncol. 2004, 22, 1087–1094. [Google Scholar] [CrossRef] [PubMed]
  6. Marcucci, G.; Mrózek, K.; Ruppert, A.S.; Maharry, K.; Kolitz, J.E.; Moore, J.O.; Mayer, R.J.; Pettenati, M.J.; Powell, B.L.; Edwards, C.G.; et al. Prognostic Factors and Outcome of Core Binding Factor Acute Myeloid Leukemia Patients with t(8;21) Differ from Those of Patients with Inv(16): A Cancer and Leukemia Group B Study. J. Clin. Oncol. 2005, 23, 5705–5717. [Google Scholar] [CrossRef] [PubMed]
  7. Appelbaum, F.R.; Kopecky, K.J.; Tallman, M.S.; Slovak, M.L.; Gundacker, H.M.; Kim, H.T.; Dewald, G.W.; Kantarjian, H.M.; Pierce, S.R.; Estey, E.H. The Clinical Spectrum of Adult Acute Myeloid Leukaemia Associated with Core Binding Factor Translocations. Br. J. Haematol. 2006, 135, 165–173. [Google Scholar] [CrossRef] [PubMed]
  8. Schlenk, R.F.; Benner, A.; Krauter, J.; Büchner, T.; Sauerland, C.; Ehninger, G.; Schaich, M.; Mohr, B.; Niedenwieser, D.; Krahl, R.; et al. Individual Patient Data-Based Meta-Analysis of Patients Aged 16 to 60 Years with Core Binding Factor Acute Myeloid Leukemia: A Survey of the German Acute Myeloid Leukemia Intergroup. J. Clin. Oncol. 2004, 22, 3741–3750. [Google Scholar] [CrossRef]
  9. Kundu, M.; Liu, P.P. Function of the Inv(16) Fusion Gene CBFB-MYH11. Curr. Opin. Hematol. 2001, 8, 201–205. [Google Scholar] [CrossRef] [PubMed]
  10. Delaunay, J.; Vey, N.; Leblanc, T.; Fenaux, P.; Rigal-Huguet, F.; Witz, F.; Lamy, T.; Auvrignon, A.; Blaise, D.; Pigneux, A.; et al. Prognosis of Inv(16)/t(16;16) Acute Myeloid Leukemia (AML): A Survey of 110 Cases from the French AML Intergroup. Blood 2003, 102, 462–469. [Google Scholar] [CrossRef] [Green Version]
  11. Tallman, M.S.; Hakimian, D.; Shaw, J.M.; Lissner, G.S.; Russell, E.J.; Variakojis, D. Granulocytic Sarcoma Is Associated with the 8;21 Translocation in Acute Myeloid Leukemia. J. Clin. Oncol. 1993, 11, 690–697. [Google Scholar] [CrossRef]
  12. Boissel, N.; Leroy, H.; Brethon, B.; Philippe, N.; de Botton, S.; Auvrignon, A.; Raffoux, E.; Leblanc, T.; Thomas, X.; Hermine, O.; et al. Incidence and Prognostic Impact of C-Kit, FLT3, and Ras Gene Mutations in Core Binding Factor Acute Myeloid Leukemia (CBF-AML). Leukemia 2006, 20, 965–970. [Google Scholar] [CrossRef] [Green Version]
  13. Wang, D.; Qiao, C.; Xiao, M.; Geng, Z.; Shang, Z.; He, J.; Huang, M.; Yang, Y.; Zhang, N.; Liu, Y.; et al. Integrative Analysis of Prognostic Factors in Chinese Core Binding Factor Leukemia. Biochem. Biophys. Res. Commun. 2012, 428, 411–415. [Google Scholar] [CrossRef]
  14. Kim, H.J.; Kim, H.J.; Ahn, H.K.; Jung, C.W.; Moon, J.H.; Park, C.H.; Lee, K.O.; Kim, S.H.; Kim, Y.K.; Kim, H.J.; et al. KIT D816 Mutation Associates with Adverse Outcomes in Core Binding Factor Acute Myeloid Leukemia, Especially in the Subgroup with RUNX1/RUNX1T1 Rearrangement. Ann. Hematol. 2013, 92, 163–171. [Google Scholar] [CrossRef]
  15. Allen, C.; Hills, R.K.; Lamb, K.; Evans, C.; Tinsley, S.; Sellar, R.; O’Brien, M.; Yin, J.L.; Burnett, A.K.; Linch, D.C.; et al. The Importance of Relative Mutant Level for Evaluating Impact on Outcome of KIT, FLT3 and CBL Mutations in Core-Binding Factor Acute Myeloid Leukemia. Leukemia 2013, 27, 1891–1901. [Google Scholar] [CrossRef] [PubMed]
  16. Jourdan, E.; Boissel, N.; Chevret, S.; Delabesse, E.; Renneville, A.; Cornillet, P.; Blanchet, O.; Cayuela, J.-M.M.; Recher, C.; Raffoux, E.; et al. Prospective Evaluation of Gene Mutations and Minimal Residual Disease in Patients with Core Binding Factor Acute Myeloid Leukemia. Blood 2013, 121, 2213–2223. [Google Scholar] [CrossRef] [PubMed]
  17. Hoyos, M.; Nomdedeu, J.F.; Esteve, J.; Duarte, R.; Ribera, J.M.; Llorente, A.; Escoda, L.; Bueno, J.; Tormo, M.; Gallardo, D.; et al. Core Binding Factor Acute Myeloid Leukemia: The Impact of Age, Leukocyte Count, Molecular Findings and Minimal Residual Disease. Eur. J. Haematol. 2013, 91, 209–218. [Google Scholar] [CrossRef] [PubMed]
  18. Cairoli, R.; Beghini, A.; Turrini, M.; Bertani, G.; Nadali, G.; Rodeghiero, F.; Castagnola, C.; Lazzaroni, F.; Nichelatti, M.; Ferrara, F.; et al. Old and New Prognostic Factors in Acute Myeloid Leukemia with Deranged Core-Binding Factor Beta. Am. J. Hematol. 2013, 88, 594–600. [Google Scholar] [CrossRef] [Green Version]
  19. Paschka, P.; Du, J.; Schlenk, R.F.; Gaidzik, V.I.; Bullinger, L.; Corbacioglu, A.; Späth, D.; Kayser, S.; Schlegelberger, B.; Krauter, J.; et al. Secondary Genetic Lesions in Acute Myeloid Leukemia with Inv(16) or t(16;16): A Study of the German-Austrian AMLStudy Group (AMLSG). Blood 2013, 121, 170–177. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  20. Yoon, J.H.; Kim, H.J.; Kim, J.W.; Jeon, Y.W.; Shin, S.H.; Lee, S.E.; Cho, B.S.; Eom, K.S.; Kim, Y.J.; Lee, S.; et al. Identification of Molecular and Cytogenetic Risk Factors for Unfavorable Core-Binding Factor-Positive Adult AML with Post-Remission Treatment Outcome Analysis Including Transplantation. Bone Marrow Transpl. 2014, 49, 1466–1474. [Google Scholar] [CrossRef]
  21. Jung, H.A.; Maeng, C.H.; Park, S.; Kim, S.J.; Kim, K.; Jang, J.H.; Jung, C.W. Prognostic Factor Analysis in Core-Binding Factor-Positive Acute Myeloid Leukemia. Anticancer Res. 2014, 34, 1037–1046. [Google Scholar] [PubMed]
  22. Brunner, A.M.; Blonquist, T.M.; Sadrzadeh, H.; Perry, A.M.; Attar, E.C.; Amrein, P.C.; Ballen, K.K.; Chen, Y.B.; Neuberg, D.S.; Fathi, A.T. Population-Based Disparities in Survival among Patients with Core-Binding Factor Acute Myeloid Leukemia: A SEER Database Analysis. Leuk. Res. 2014, 38, 773–780. [Google Scholar] [CrossRef] [Green Version]
  23. Mosna, F.; Papayannidis, C.; Martinelli, G.; Di Bona, E.; Bonalumi, A.; Tecchio, C.; Candoni, A.; Capelli, D.; Piccin, A.; Forghieri, F.; et al. Complex Karyotype, Older Age, and Reduced First-Line Dose Intensity Determine Poor Survival in Core Binding Factor Acute Myeloid Leukemia Patients with Long-Term Follow-Up. Am. J. Hematol. 2015, 90, 515–523. [Google Scholar] [CrossRef] [Green Version]
  24. Yui, S.; Kurosawa, S.; Yamaguchi, H.; Kanamori, H.; Ueki, T.; Uoshima, N.; Mizuno, I.; Shono, K.; Usuki, K.; Chiba, S.; et al. D816 Mutation of the KIT Gene in Core Binding Factor Acute Myeloid Leukemia Is Associated with Poorer Prognosis than Other KIT Gene Mutations. Ann. Hematol. 2017, 96, 1641–1652. [Google Scholar] [CrossRef] [PubMed]
  25. Prabahran, A.; Tacey, M.; Fleming, S.; Wei, A.; Tate, C.; Marlton, P.; Wight, J.; Grigg, A.; Tuckfield, A.; Szer, J.; et al. Prognostic Markers in Core-Binding Factor AML and Improved Survival with Multiple Consolidation Cycles of Intermediate-/High-Dose Cytarabine. Eur. J. Haematol. 2018, 101, 174–184. [Google Scholar] [CrossRef]
  26. Shin, H.-J.; Min, W.-S.; Min, Y.H.; Cheong, J.-W.; Lee, J.-H.; Kim, I.-H.; Hong, D.S.; Ahn, J.-S.; Kim, H.-J.; Lee, W.-S.; et al. Different Prognostic Effects of Core-Binding Factor Positive AML with Korean AML Registry Data. Ann. Hematol. 2019, 98, 1135–1147. [Google Scholar] [CrossRef] [PubMed]
  27. Opatz, S.; Bamopoulos, S.A.; Metzeler, K.H.; Herold, T.; Ksienzyk, B.; Bräundl, K.; Tschuri, S.; Vosberg, S.; Konstandin, N.P.; Wang, C.; et al. The Clinical Mutatome of Core Binding Factor Leukemia. Leukemia 2020, 34, 1553–1562. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  28. Ishikawa, Y.; Kawashima, N.; Atsuta, Y.; Sugiura, I.; Sawa, M.; Dobashi, N.; Yokoyama, H.; Doki, N.; Tomita, A.; Kiguchi, T.; et al. Prospective Evaluation of Prognostic Impact of KIT Mutations on Acute Myeloid Leukemia with RUNX1-RUNX1T1 and CBFB-MYH11. Blood Adv. 2020, 4, 66–75. [Google Scholar] [CrossRef] [PubMed]
  29. Ustun, C.; Morgan, E.A.; Ritz, E.M.; Vestergaard, H.; Pullarkat, S.; Kluin, P.M.; Ohgami, R.; Baughn, L.B.; Kim, Y.; Ku, N.K.; et al. Core-Binding Factor Acute Myeloid Leukemia with Inv(16): Older Age and High White Blood Cell Count Are Risk Factors for Treatment Failure. Int. J. Lab. Hematol. 2020, 43, e19–e25. [Google Scholar] [CrossRef]
  30. Jahn, N.; Terzer, T.; SträngStr, E.; Dolnik, A.; Cocciardi, S.; Panina, E.; Corbacioglu, A.; Herzig, J.; Weber, D.; Schrade, A.; et al. Genomic Heterogeneity in Core-Binding Factor Acute Myeloid Leukemia and Its Clinical Implication. Blood Adv. 2020, 4, 6342–6352. [Google Scholar] [CrossRef] [PubMed]
  31. Duan, W.; Liu, X.; Jia, J.; Wang, J.; Gong, L.; Jiang, Q.; Zhao, T.; Wang, Y.; Zhang, X.; Xu, L.; et al. The Loss or Absence of Minimal Residual Disease of at Any Time after Two Cycles of <0·1% Consolidation Chemotherapy in CBFB–MYH11 -positive Acute Myeloid Leukaemia Indicates Poor Prognosis. Br. J. Haematol. 2021, 192, 265–271. [Google Scholar] [CrossRef]
  32. Duan, W.; Liu, X.; Zhao, X.; Jia, J.; Wang, J.; Gong, L.; Jiang, Q.; Zhao, T.; Wang, Y.; Zhang, X.; et al. Both the Subtypes of KIT Mutation and Minimal Residual Disease Are Associated with Prognosis in Core Binding Factor Acute Myeloid Leukemia: A Retrospective Clinical Cohort Study in Single Center. Ann. Hematol. 2021, 100, 1203–1212. [Google Scholar] [CrossRef] [PubMed]
  33. Han, S.Y.; Mrózek, K.; Voutsinas, J.; Wu, Q.; Morgan, E.A.; Vestergaard, H.; Ohgami, R.; Kluin, P.M.; Kristensen, T.K.; Pullarkat, S.; et al. Secondary Cytogenetic Abnormalities in Core-Binding Factor AML Harboring Inv(16) vs t(8;21). Blood Adv. 2021, 5, 2481–2489. [Google Scholar] [CrossRef]
  34. Fröhling, S.; Schlenk, R.F.; Kayser, S.; Morhardt, M.; Benner, A.; Döhner, K.; Döhner, H. Cytogenetics and Age Are Major Determinants of Outcome in Intensively Treated Acute Myeloid Leukemia Patients Older than 60 Years: Results from AMLSG Trial AML HD98-B. Blood 2006, 108, 3280–3288. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  35. Grimwade, D.; Hills, R.K.; Moorman, A.V.; Walker, H.; Chatters, S.; Goldstone, A.H.; Wheatley, K.; Harrison, C.J.; Burnett, A.K.; National Cancer Research Institute Adult Leukaemia Working Group. 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 2010, 116, 354–365. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  36. Appelbaum, F.R.; Gundacker, H.; Head, D.R.; Slovak, M.L.; Willman, C.L.; Godwin, J.E.; Anderson, J.E.; Petersdorf, S.H. Age and Acute Myeloid Leukemia. Blood 2006, 107, 3481–3485. [Google Scholar] [CrossRef]
  37. Sekeres, M.A.; Stone, R.M. The Challenge of Acute Myeloid Leukemia in Older Patients. Curr. Opin. Oncol. 2002, 14, 24–30. [Google Scholar] [CrossRef]
  38. Schoch, C.; Kern, W.; Schnittger, S.; Büchner, T.; Hiddemann, W.H.T. The Influence of Age on Prognosis of de Novo Acute Myeloid Leukemia Differs According to Cytogenetic Subgroups. Haematologica 2004, 89, 1082–1090. [Google Scholar]
  39. Farag, S.S.; Archer, K.J.; Mrózek, K.; Ruppert, A.S.; Carroll, A.J.; Vardiman, J.W.; Pettenati, M.J.; Baer, M.R.; Qumsiyeh, M.B.; Koduru, P.R.; et al. Pretreatment Cytogenetics Add to Other Prognostic Factors Predicting Complete Remission and Long-Term Outcome in Patients 60 Years of Age or Older with Acute Myeloid Leukemia: Results from Cancer and Leukemia Group B 8461. Blood 2006, 108, 63–73. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  40. Martin, G.; Barragan, E.; Bolufer, P.; Chillon, C.; Garcia-Sanz, R.; Gomez, T.; Brunet, S.; Gonzalez, M.; Sanz, M.A. Relevance of Presenting White Blood Cell Count and Kinetics of Molecular Remission in the Prognosis of Acute Myeloid Leukemia with CBFβ/MYH11 Rearrangement. Haematologica 2000, 85, 699–703. [Google Scholar]
  41. Cairoli, R.; Beghini, A.; Grillo, G.; Nadali, G.; Elice, F.; Ripamonti, C.B.; Colapietro, P.; Nichelatti, M.; Pezzetti, L.; Lunghi, M.; et al. Prognostic Impact of C-KIT Mutations in Core Binding Factor Leukemias: An Italian Retrospective Study. Blood 2006, 107, 3463–3468. [Google Scholar] [CrossRef]
  42. Nguyen, S.; Leblanc, T.; Fenaux, P.; Witz, F.; Blaise, D.; Pigneux, A.; Thomas, X.; Rigal-Huguet, F.; Lioure, B.; Auvrignon, A.; et al. A White Blood Cell Index as the Main Prognostic Factor in t(8;21) Acute Myeloid Leukemia (AML): A Survey of 161 Cases from the French AML Intergroup. Blood 2002, 99, 3517–3523. [Google Scholar] [CrossRef] [Green Version]
  43. Paschka, P.; Marcucci, G.; Ruppert, A.S.; Mrózek, K.; Chen, H.; Kittles, R.A.; Vukosavljevic, T.; Perrotti, D.; Vardiman, J.W.; Carroll, A.J.; et al. Adverse Prognostic Significance of KIT Mutations in Adult Acute Myeloid Leukemia with Inv(16) and t(8;21): A Cancer and Leukemia Group B Study. J. Clin. Oncol. 2006, 24, 3904–3911. [Google Scholar] [CrossRef]
  44. Gilliland, D.G. Molecular Genetics of Human Leukemias: New Insights into Therapy. Semin. Hematol. 2002, 39, 6–11. [Google Scholar] [CrossRef]
  45. Duployez, N.; Willekens, C.; Marceau-Renaut, A.; Boudry-Labis, E.; Preudhomme, C. Prognosis and Monitoring of Core-Binding Factor Acute Myeloid Leukemia: Current and Emerging Factors. Expert Rev. Hematol. 2015, 8, 43–56. [Google Scholar] [CrossRef] [PubMed]
  46. Huh, J.; Kim, H.J.; Jung, C.W.; Kim, H.J.; Kim, S.H.; Kim, Y.K.; Kim, H.J.; Shin, M.G.; Moon, J.H.; Sohn, S.K.; et al. A Genome-Wide Single-Nucleotide Polymorphism-Array Can Improve the Prognostic Stratification of the Core Binding Factor Acute Myeloid Leukemia. Am. J. Hematol. 2012, 87, 961–968. [Google Scholar] [CrossRef]
  47. Qin, Y.Z.; Zhu, H.H.; Jiang, Q.; Jiang, H.; Zhang, L.P.; Xu, L.P.; Wang, Y.; Liu, Y.R.; Lai, Y.Y.; Shi, H.X.; et al. Prevalence and Prognostic Significance of C-KIT Mutations in Core Binding Factor Acute Myeloid Leukemia: A Comprehensive Large-Scale Study from a Single Chinese Center. Leuk. Res. 2014, 38, 1435–1440. [Google Scholar] [CrossRef]
  48. Care, R.S.; Valk, P.J.M.; Goodeve, A.C.; Abu-Duhier, F.M.; Geertsma-Kleinekoort, W.M.C.; Wilson, G.A.; Gari, M.A.; Peake, I.R.; Löwenberg, B.; Reilly, J.T. Incidence and Prognosis of C-KIT and FLT3 Mutations in Core Binding Factor (CBF) Acute Myeloid Leukaemias. Br. J. Haematol. 2003, 121, 775–777. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  49. Park, S.H.; Chi, H.S.; Min, S.K.; Park, B.G.; Jang, S.; Park, C.J. Prognostic Impact of C-KIT Mutations in Core Binding Factor Acute Myeloid Leukemia. Leuk. Res. 2011, 35, 1376–1383. [Google Scholar] [CrossRef]
  50. Schwind, S.; Edwards, C.G.; Nicolet, D.; Mrózek, K.; Maharry, K.; Wu, Y.Z.; Paschka, P.; Eisfeld, A.K.; Hoellerbauer, P.; Becker, H.; et al. Inv(16)/t(16;16) Acute Myeloid Leukemia with Non-Type A CBFB-MYH11 Fusions Associate with Distinct Clinical and Genetic Features and Lack KIT Mutations. Blood 2013, 121, 385–391. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  51. Paschka, P. Core Binding Factor Acute Myeloid Leukemia. Semin. Oncol. 2008, 35, 410–417. [Google Scholar] [CrossRef]
  52. Paschka, P.; Döhner, K. Core-Binding Factor Acute Myeloid Leukemia: Can We Improve on HiDAC Consolidation? Hematol. Am. Soc. Hematol. Educ. Program 2013, 2013, 209–219. [Google Scholar] [CrossRef] [Green Version]
  53. Marková, J.; Trnková, Z.; Michková, P.; Maaloufová, J.; Starý, J.; Cetkovský, P.; Schwarz, J. Monitoring of Minimal Residual Disease in Patients with Core Binding Factor Acute Myeloid Leukemia and the Impact of C-KIT, FLT3, and JAK2 Mutations on Clinical Outcome. Leuk. Lymphoma 2009, 50, 1448–1460. [Google Scholar] [CrossRef]
  54. Riera, L.; Marmont, F.; Toppino, D.; Frairia, C.; Sismondi, F.; Audisio, E.; Di Bello, C.; D’Ardia, S.; Di Celle, P.F.; Messa, E.; et al. Core Binding Factor Acute Myeloid Leukaemia and C-KIT Mutations. Oncol. Rep. 2013, 29, 1859–1866. [Google Scholar] [CrossRef] [Green Version]
  55. Park, S.H.; Lee, H.J.; Kim, I.S.; Kang, J.E.; Lee, E.Y.; Kim, H.J.; Kim, Y.K.; Won, J.H.; Bang, S.M.; Kim, H.; et al. Incidences and Prognostic Impact of C-KIT, WT1, CEBPA, and CBL Mutations, and Mutations Associated with Epigenetic Modification in Core Binding Factor Acute Myeloid Leukemia: A Multicenter Study in a Korean Population. Ann. Lab. Med. 2015, 35, 288–297. [Google Scholar] [CrossRef] [Green Version]
  56. Ustun, C.; Marcucci, G. Emerging Diagnostic and Therapeutic Approaches in Core Binding Factor Acute Myeloid Leukaemia. Curr. Opin. Hematol. 2015, 22, 85–91. [Google Scholar] [CrossRef]
  57. Buccisano, F.; Maurillo, L.; Del Principe, M.I.; Di Veroli, A.; De Bellis, E.; Biagi, A.; Zizzari, A.; Rossi, V.; Rapisarda, V.; Amadori, S.; et al. Minimal Residual Disease as a Biomarker for Outcome Prediction and Therapy Optimization in Acute Myeloid Leukemia. Expert Rev. Hematol. 2018, 11, 307–313. [Google Scholar] [CrossRef] [PubMed]
  58. Ossenkoppele, G.; Schuurhuis, G.J. MRD in AML: Does It Already Guide Therapy Decision-Making? Hematology 2016, 2016, 356–365. [Google Scholar] [CrossRef]
  59. Ossenkoppele, G.; Schuurhuis, G.J. MRD in AML: Time for Redefinition of CR? Blood 2013, 121, 2166–2168. [Google Scholar] [CrossRef] [PubMed]
  60. Liu Yin, J.A.; Frost, L. Monitoring AML1-ETO and CBFΒ-MYH11 Transcripts in Acute Myeloid Leukemia. Curr. Oncol. Rep. 2003, 5, 399–404. [Google Scholar] [CrossRef]
  61. Buonamici, S.; Ottaviani, E.; Testoni, N.; Montefusco, V.; Visani, G.; Bonifazi, F.; Amabile, M.; Terragna, C.; Ruggeri, D.; Piccaluga, P.P.; et al. 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 2002, 99, 443–449. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  62. Evans, P.; Short, M.; Jack, A.; Norfolk, D.; Child, J.; Shiach, C.; Davies, F.; Tobal, K.; Yin, J.L.; Morgan, G. Detection and Quantitation of the CBFβ/MYH11 Transcripts Associated with the Inv(16) in Presentation and Follow-up Samples from Patients with AML. Leukemia 1997, 11, 364–369. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  63. Laczika, K.; Novak, M.; Hilgarth, B.; Mitterbauer, M.; Mitterbauer, G.; Scheidel-Petrovic, A.; Scholten, C.; Thalhammer-Scherrer, R.; Brugger, S.; Keil, F.; et al. Competitive CBFbeta/MYH11 Reverse-Transcriptase Polymerase Chain Reaction for Quantitative Assessment of Minimal Residual Disease during Postremission Therapy in Acute Myeloid Leukemia with Inversion(16): A Pilot Study. J. Clin. Oncol. 1998, 16, 1519–1525. [Google Scholar] [CrossRef]
  64. Van Dongen, J.J.M.; Seriu, T.; Panzer-Grümayer, E.R.; Biondi, A.; Pongers-Willemse, M.J.; Corral, L.; Stolz, F.; Schrappe, M.; Masera, G.; Kamps, W.A.; et al. Prognostic Value of Minimal Residual Disease in Acute Lymphoblastic Leukaemia in Childhood. Lancet 1998, 352, 1731–1738. [Google Scholar] [CrossRef]
  65. Olavarria, E.; Kanfer, E.; Szydlo, R.; Kaeda, J.; Rezvani, K.; Cwynarski, K.; Pocock, C.; Dazzi, F.; Craddock, C.; Apperley, J.F.; et al. Early Detection of BCR-ABL Transcripts by Quantitative Reverse Transcriptase-Polymerase Chain Reaction Predicts Outcome after Allogeneic Stem Cell Transplantation for Chronic Myeloid Leukemia. Blood 2001, 97, 1560–1565. [Google Scholar] [CrossRef] [Green Version]
  66. Ehinger, M.; Pettersson, L. Measurable Residual Disease Testing for Personalized Treatment of Acute Myeloid Leukemia. APMIS 2019, 127, 337–351. [Google Scholar] [CrossRef] [Green Version]
  67. Mosna, F.; Capelli, D.; Gottardi, M. Minimal Residual Disease in Acute Myeloid Leukemia: Still a Work in Progress? J. Clin. Med. 2017, 6, 57. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  68. Schuurhuis, G.J.; Heuser, M.; Freeman, S.; Béne, M.C.; Buccisano, F.; Cloos, J.; Grimwade, D.; Haferlach, T.; Hills, R.K.; Hourigan, C.S.; et al. Minimal/Measurable Residual Disease in AML: A Consensus Document from the European LeukemiaNet MRD Working Party. Blood 2018, 131, 1275–1291. [Google Scholar] [CrossRef] [Green Version]
  69. Short, N.J.; Ravandi, F. How Close Are We to Incorporating Measurable Residual Disease into Clinical Practice for Acute Myeloid Leukemia? Haematologica 2019, 104, 1532–1541. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  70. Dix, C.; Lo, T.-H.; Clark, G.; Abadir, E. Measurable Residual Disease in Acute Myeloid Leukemia Using Flow Cytometry: A Review of Where We Are and Where We Are Going. J. Clin. Med. 2020, 9, 1714. [Google Scholar] [CrossRef] [PubMed]
  71. Tsai, C.-H.; Tang, J.-L.; Tien, F.-M.; Kuo, Y.-Y.; Wu, D.-C.; Lin, C.-C.; Tseng, M.-H.; Peng, Y.-L.; Hou, M.-F.; Chuang, Y.-K.; et al. Clinical Implications of Sequential MRD Monitoring by NGS at 2 Time Points after Chemotherapy in Patients with AML. Blood Adv. 2021, 5, 2456–2466. [Google Scholar] [CrossRef]
  72. Ouyang, J.; Goswami, M.; Peng, J.; Zuo, Z.; Daver, N.; Borthakur, G.; Tang, G.; Medeiros, L.J.; Jorgensen, J.L.; Ravandi, F.; et al. Comparison of Multiparameter Flow Cytometry Immunophenotypic Analysis and Quantitative RT-PCR for the Detection of Minimal Residual Disease of Core Binding Factor Acute Myeloid Leukemia. Am. J. Clin. Pathol. 2016, 145, 769–777. [Google Scholar] [CrossRef]
  73. Perea, G.; Lasa, A.; Aventín, A.; Domingo, A.; Villamor, N.; Paz Queipo de Llano, M.; Llorente, A.; Juncà, J.; Palacios, C.; Fernández, C.; et al. Prognostic Value of Minimal Residual Disease (MRD) in Acute Myeloid Leukemia (AML) with Favorable Cytogenetics [t(8;21) and Inv(16)]. Leukemia 2006, 20, 87–94. [Google Scholar] [CrossRef] [Green Version]
  74. Marcucci, G.; Caligiuri, M.; Döhner, H.; Archer, K.; Schlenk, R.; Döhner, K.; Maghraby, E.; Bloomfield, C. Quantification of CBFβ/MYH11 Fusion Transcript by Real Time RT-PCR in Patients with INV(16) Acute Myeloid Leukemia. Leukemia 2001, 15, 1072–1080. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  75. Guerrasio, A.; Pilatrino, C.; De Micheli, D.; Cilloni, D.; Serra, A.; Gottardi, E.; Parziale, A.; Marmont, F.; Diverio, D.; Divona, M.; et al. Assessment of Minimal Residual Disease (MRD) in CBFbeta/MYH11-Positive Acute Myeloid Leukemias by Qualitative and Quantitative RT-PCR Amplification of Fusion Transcripts. Leukemia 2002, 16, 1176–1181. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  76. Krauter, J.; Görlich, K.; Ottmann, O.; Lübbert, M.; Döhner, H.; Heit, W.; Kanz, L.; Ganser, A.; Heil, G. 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. 2003, 21, 4413–4422. [Google Scholar] [CrossRef] [PubMed]
  77. Schnittger, S.; Weisser, M.; Schoch, C.; Hiddemann, W.; Haferlach, T.; Kern, W. New Score Predicting for Prognosis in PML-RARA, AML1-ETO, or CBFB-MYH11 Acute Myeloid Leukemia Based on Quantification of Fusion Transcripts. Blood 2003, 102, 2746–2755. [Google Scholar] [CrossRef] [Green Version]
  78. Stentoft, J.; Hokland, P.; Østergaard, M.; Hasle, H.; Nyvold, C.G. Minimal Residual Core Binding Factor AMLs by Real Time Quantitative PCR-Initial Response to Chemotherapy Predicts Event Free Survival and Close Monitoring of Peripheral Blood Unravels the Kinetics of Relapse. Leuk. Res. 2006, 30, 389–395. [Google Scholar] [CrossRef]
  79. Lane, S.; Saal, R.; Mollee, P.; Jones, M.; Grigg, A.; Taylor, K.; Seymour, J.; Kennedy, G.; Williams, B.; Grimmett, K.; et al. A ≥1 Log Rise in RQ-PCR Transcript Levels Defines Molecular Relapse in Core Binding Factor Acute Myeloid Leukemia and Predicts Subsequent Morphologic Relapse. Leuk. Lymphoma 2008, 49, 517–523. [Google Scholar] [CrossRef]
  80. Guièze, R.; Renneville, A.; Cayuela, J.-M.; Abdelali, R.B.; Boissel, N.; de Botton, S.; Rubio, M.-T.; Mazingue, F.; Macintyre, E.A.; Cheok, M.; et al. Prognostic Value of Minimal Residual Disease by Real-Time Quantitative PCR in Acute Myeloid Leukemia with CBFB-MYH11 Rearrangement: The French Experience. Leukemia 2010, 24, 1386–1388. [Google Scholar] [CrossRef] [Green Version]
  81. Corbacioglu, A.; Scholl, C.; Schlenk, R.F.; Eiwen, K.; Du, J.; Bullinger, L.; Fröhling, S.; Reimer, P.; Rummel, M.; Derigs, H.-G.; et al. Prognostic Impact of Minimal Residual Disease in CBFB-MYH11-Positive Acute Myeloid Leukemia. J. Clin. Oncol. 2010, 28, 3724–3729. [Google Scholar] [CrossRef]
  82. Yin, J.A.L.; O’brien, M.A.; Hills, R.K.; Daly, S.B.; Wheatley, K.; Burnett, A.K. Minimal Residual Disease Monitoring by Quantitative RT-PCR in Core Binding Factor AML Allows Risk Stratification and Predicts Relapse: Results of the United Kingdom MRC AML-15 Trial. Blood 2012, 120, 2826–2835. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  83. Wang, L.; Gao, L.; Xu, S.; Gong, S.; Liu, M.; Qiu, H.; Xu, X.; Ni, X.; Chen, L.; Lu, S.; et al. High Prognostic Value of Minimal Residual Disease Detected by Flow-Cytometry-Enhanced Fluorescence in Situ Hybridization in Core-Binding Factor Acute Myeloid Leukemia (CBF-AML). Ann. Hematol. 2014, 93, 1685–1694. [Google Scholar] [CrossRef] [PubMed]
  84. Qin, Y.-Z.Z.; Xu, L.-P.P.; Chen, H.; Jiang, Q.; Wang, Y.; Jiang, H.; Zhang, X.-H.H.; Han, W.; Chen, Y.-H.H.; Wang, F.-R.R.; et al. Allogeneic Stem Cell Transplant May Improve the Outcome of Adult Patients with Inv(16) Acute Myeloid Leukemia in First Complete Remission with Poor Molecular Responses to Chemotherapy. Leuk. Lymphoma 2015, 56, 3116–3123. [Google Scholar] [CrossRef] [PubMed]
  85. Puckrin, R.; Atenafu, E.G.; Claudio, J.O.; Chan, S.; Gupta, V.; Maze, D.; McNamara, C.; Murphy, T.; Shuh, A.C.; Yee, K.; et al. Measurable Residual Disease Monitoring Provides Insufficient Lead-Time to Prevent Morphologic Relapse in the Majority of Patients with Core-Binding Factor Acute Myeloid Leukemia. Haematologica 2021, 106, 56–63. [Google Scholar] [CrossRef] [Green Version]
  86. Löwenberg, B.; Pabst, T.; Vellenga, E.; van Putten, W.; Schouten, H.C.; Graux, C.; Ferrant, A.; Sonneveld, P.; Biemond, B.J.; Gratwohl, A.; et al. Cytarabine Dose for Acute Myeloid Leukemia. N. Engl. J. Med. 2011, 364, 1027–1036. [Google Scholar] [CrossRef] [Green Version]
  87. Löwenberg, B. Sense and Nonsense of High-Dose Cytarabine for Acute Myeloid Leukemia. Blood 2013, 121, 26–28. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  88. Martinelli, G.; Ottaviani, E.; Testoni, N.; Montefusco, V.; Buonamici, S.; Tura, S. Long-Term Disease-Free Acute Myeloblastic Leukemia with Inv(16) Is Associated with PCR Undetectable CBFbeta/MYH11 Transcript This. Haematologica 2000, 85, 552–555. [Google Scholar]
  89. Elmaagacli, A.H.; Beelen, D.W.; Kroll, M.; Trzensky, S.; Stein, C.; Schaefer, U.W. Detection of CBFβ/MYH11 Fusion Transcripts in Patients with Inv(16) Acute Myeloid Leukemia after Allogeneic Bone Marrow or Peripheral Blood Progenitor Cell Transplantation. Bone Marrow Transpl. 1998, 21, 159–166. [Google Scholar] [CrossRef] [Green Version]
  90. Tobal, K.; Johnson, P.R.E.; Saunders, M.J.; Harrison, C.J.; Yin, J.A.L. Detection of CBFB/MYH11 Transcripts in Patients with Inversion and Other Abnormalities of Chromosome 16 at Presentation and Remission. Br. J. Haematol. 1995, 91, 104–108. [Google Scholar] [CrossRef] [PubMed]
  91. Claxton, D.F.; Liu, P.; Hsu, H.B.; Marlton, P.; Hester, J.; Collins, F.; Deisseroth, A.B.; Rowley, J.D.; Siciliano, M.J. Detection of Fusion Transcripts Generated by the Inversion 16 Chromosome in Acute Myelogenous Leukemia. Blood 1994, 83, 1750–1756. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  92. Jaiswal, S.; Fontanillas, P.; Flannick, J.; Manning, A.; Grauman, P.V.; Mar, B.G.; Lindsley, R.C.; Mermel, C.H.; Burtt, N.; Chavez, A.; et al. Age-Related Clonal Hematopoiesis Associated with Adverse Outcomes. N. Engl. J. Med. 2014, 371, 2488–2498. [Google Scholar] [CrossRef] [Green Version]
  93. Xie, M.; Lu, C.; Wang, J.; McLellan, M.D.; Johnson, K.J.; Wendl, M.C.; McMichael, J.F.; Schmidt, H.K.; Yellapantula, V.; Miller, C.A.; et al. Age-Related Mutations Associated with Clonal Hematopoietic Expansion and Malignancies. Nat. Med. 2014, 20, 1472–1478. [Google Scholar] [CrossRef] [PubMed]
  94. Costello, R.; Sainty, D.; Blaise, D.; Gastaut, J.A.; Gabert, J.; Poirel, H.; Buzyn- Veil, A.; Macintyre, E. Prognosis Value of Residual Disease Monitoring by Polymerase Chain Reaction in Patients with CBFβ/MYH11-Positive Acute Myeloblastic Leukemia. Blood 1997, 89, 2222–2223. [Google Scholar] [CrossRef]
  95. Yalniz, F.F.; Patel, K.P.; Bashir, Q.; Marin, D.; Ahmed, S.; Alousi, A.M.; Chen, J.; Ciurea, S.O.; Rezvani, K.; Popat, U.R.; et al. Significance of Minimal Residual Disease Monitoring by Real-time Quantitative Polymerase Chain Reaction in Core Binding Factor Acute Myeloid Leukemia for Transplantation Outcomes. Cancer 2020, 126, 2183–2192. [Google Scholar] [CrossRef]
  96. Biernacki, M.A.; Rongvaux, A.; Bleakley, M. CBFB-MYH11 Fusion Neoantigen Enables T Cell Recognition and Killing of Acute Myeloid Leukemia The Journal of Clinical Investigation. J. Clin. Investig. 2020, 130, 5127–5141. [Google Scholar] [CrossRef] [PubMed]
  97. Dillon, R.; Potter, N.; Freeman, S.; Russell, N. How We Use Molecular Minimal Residual Disease (MRD) Testing in Acute Myeloid Leukaemia (AML). Br. J. Haematol. 2021, 193, 231–244. [Google Scholar] [CrossRef] [PubMed]
  98. Ommen, H.B.; Schnittger, S.; Jovanovic, J.V.; Ommen, I.B.; Hasle, H.; Østergaard, M.; Grimwade, D.; Hokland, P. Strikingly Different Molecular Relapse Kinetics in NPM1c, PML-RARA, RUNX1-RUNX1T1, and CBFB-MYH11 Acute Myeloid Leukemias. Blood 2010, 115, 198–205. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  99. Skou, A.S.; Juul-Dam, K.L.; Ommen, H.B.; Hasle, H. Peripheral Blood Molecular Measurable Residual Disease Is Sufficient to Identify Patients with Acute Myeloid Leukaemia with Imminent Clinical Relapse. Br. J. Haematol. 2021. [Google Scholar] [CrossRef]
  100. Ivey, A.; Hills, R.K.; Simpson, M.A.; Jovanovic, J.V.; Gilkes, A.; Grech, A.; Patel, Y.; Bhudia, N.; Farah, H.; Mason, J.; et al. Assessment of Minimal Residual Disease in Standard-Risk AML. N. Engl. J. Med. 2016, 374, 422–433. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  101. Boeckx, N.; De Roover, J.; van der Velden, V.H.J.; Maertens, J.; Uyttebroeck, A.; Vandenberghe, P.; van Dongen, J.J.M. Quantification of CBFB-MYH11 Fusion Gene Levels in Paired Peripheral Blood and Bone Marrow Samples by Real-Time PCR. Leukemia 2005, 19, 1988–1990. [Google Scholar] [CrossRef] [Green Version]
  102. Halaburda, K.; Labopin, M.; Mailhol, A.; Socié, G.; Craddock, C.; Aljurf, M.; Beelen, D.; Cornelissen, J.J.; Bourhis, J.-H.; Labussière-Wallet, H.; et al. Allogeneic Stem Cell Transplantation in Second Complete Remission for Core Binding Factor Acute Myeloid Leukemia: A Study from the Acute Leukemia Working Party of the European Society for Blood and Marrow Transplantation. Haematologica 2020, 105, 1723–1730. [Google Scholar] [CrossRef]
  103. Gorin, N.C.; Labopin, M.; Frassoni, F.; Milpied, N.; Attal, M.; Blaise, D.; Meloni, G.; Iori, A.P.; Michallet, M.; Willemze, R.; et al. Identical Outcome after Autologous or Allogeneic Genoidentical Hematopoietic Stem-Cell Transplantation in First Remission of Acute Myelocytic Leukemia Carrying Inversion 16 or t(8;21): A Retrospective Study from the European Cooperative Group for Blood An. J. Clin. Oncol. 2008, 26, 3183–3188. [Google Scholar] [CrossRef]
  104. Kuwatsuka, Y.; Miyamura, K.; Suzuki, R.; Kasai, M.; Maruta, A.; Ogawa, H.; Tanosaki, R.; Takahashi, S.; Koda, K.; Yago, K.; et al. Hematopoietic Stem Cell Transplantation for Core Binding Factor Acute Myeloid Leukemia: T(8;21) and Inv(16) Represent Different Clinical Outcomes. Blood 2009, 113, 2096–2103. [Google Scholar] [CrossRef] [Green Version]
  105. Koreth, J.; Schlenk, R.; Kopecky, K.J.; Honda, S.; Sierra, J.; Djulbegovic, B.J.; Wadleigh, M.; DeAngelo, D.J.; Stone, R.M.; Sakamaki, H.; et al. Allogeneic Stem Cell Transplantation for Acute Myeloid Leukemia in First Complete Remission: Systematic Review and Meta-Analysis of Prospective Clinical Trials. JAMA 2009, 301, 2349–2361. [Google Scholar] [CrossRef] [Green Version]
  106. Yao, J.; Zhang, G.; Liang, C.; Li, G.; Chen, X.; Ma, Q.; Zhai, W.; Yang, D.; He, Y.; Jiang, E.; et al. Combination of Cytogenetic Classification and MRD Status Correlates with Outcome of Autologous versus Allogeneic Stem Cell Transplantation in Adults with Primary Acute Myeloid Leukemia in First Remission. Leuk. Res. 2017, 55, 97–104. [Google Scholar] [CrossRef] [PubMed]
  107. Shin, H.J.; Kim, H.J.; Sohn, S.K.; Min, Y.H.; Won, J.H.; Kim, I.; Yoon, H.J.; Lee, J.H.; Jo, D.Y.; Joo, Y.D.; et al. Re-Analysis of the Outcomes of Post-Remission Therapy for Acute Myeloid Leukemia with Core Binding Factor According to Years of Patient Enrolment. Jpn. J. Clin. Oncol. 2010, 40, 556–566. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  108. Buckley, S.A.; Wood, B.L.; Othus, M.; Hourigan, C.S.; Ustun, C.; Linden, M.A.; DeFor, T.E.; Malagola, M.; Anthias, C.; Valkova, V.; et al. Minimal Residual Disease Prior to Allogeneic Hematopoietic Cell Transplantation in Acute Myeloid Leukemia: A Meta-Analysis. Haematologica 2017, 102, 865–873. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  109. Zhao, X.S.; Qin, Y.Z.; Liu, Y.R.; Chang, Y.J.; Xu, L.P.; Zhang, X.H.; Huang, X.J. The Impact of Minimal Residual Disease Prior to Unmanipulated Haploidentical Hematopoietic Stem Cell Transplantation in Patients with Acute Myeloid Leukemia in Complete Remission. Leuk. Lymphoma 2017, 58, 1135–1143. [Google Scholar] [CrossRef]
  110. Chang, Y.J.; Wang, Y.; Liu, Y.R.; Xu, L.P.; Zhang, X.H.; Chen, H.; Chen, Y.H.; Wang, F.R.; Han, W.; Sun, Y.Q.; et al. Haploidentical Allograft Is Superior to Matched Sibling Donor Allograft in Eradicating Pre-Transplantation Minimal Residual Disease of AML Patients as Determined by Multiparameter Flow Cytometry: A Retrospective and Prospective Analysis. J. Hematol. Oncol. 2017, 10, 1–13. [Google Scholar] [CrossRef] [PubMed]
  111. Xiaosu, Z.; Leqing, C.; Yazhen, Q.; Yu, W.; Xiaohui, Z.; Lanping, X.; Xiaojun, H.; Yingjun, C. Classifying AML Patients with Inv(16) into High-Risk and Low-Risk Relapsed Patients Based on Peritransplantation Minimal Residual Disease Determined by CBFβ/MYH11 Gene Expression. Ann. Hematol. 2019, 98, 73–81. [Google Scholar] [CrossRef]
  112. Walter, R.B.; Gooley, T.A.; Wood, B.L.; Milano, F.; Fang, M.; Sorror, M.L.; Estey, E.H.; Salter, A.I.; Lansverk, E.; Chien, J.W.; et al. Impact of Pretransplantation Minimal Residual Disease, as Detected by Multiparametric Flow Cytometry, on Outcome of Myeloablative Hematopoietic Cell Transplantation for Acute Myeloid Leukemia. J. Clin. Oncol. 2011, 29, 1190–1197. [Google Scholar] [CrossRef] [Green Version]
  113. Klyuchnikov, E.; Christopeit, M.; Badbaran, A.; Bacher, U.; Fritzsche-Friedland, U.; von Pein, U.M.; Wolschke, C.; Kröger, N. Role of Pre-Transplant MRD Level Detected by Flow Cytometry in Recipients of Allogeneic Stem Cell Transplantation with AML. Eur. J. Haematol. 2021, 106, 606–615. [Google Scholar] [CrossRef]
  114. Buccisano, F.; Maurillo, L.; Piciocchi, A.; Del Principe, M.I.; De Angelis, G.; Di Veroli, A.; Cerretti, R.; Cefalo, M.; Ditto, C.; Picardi, A.; et al. Variable Outcome of Allogeneic Stem Cell Transplant According to the Different Levels of Pre-Transplant Minimal Residual Disease, in Adult Patients with Acute Myeloid Leukemia. Blood 2015, 126, 3230. [Google Scholar] [CrossRef]
  115. Zhang, W.P.; Yang, D.; Song, X.M.; Ni, X.; Chen, J.; Chen, L.; Yang, J.M.; Zhou, H.; Cheng, H.; Liu, B.H.; et al. Allogeneic Peripheral Blood Stem Cell Transplantation Is a Promising and Safe Choice for the Treatment of Refractory/Relapsed Acute Myelogenous Leukemia, Even with a Higher Leukemia Burden. Biol. Blood Marrow Transpl. 2013, 19, 653–660. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  116. Tang, F.F.; Xu, L.P.; Zhang, X.H.; Chen, H.; Chen, Y.H.; Han, W.; Wang, Y.; Yan, C.H.; Sun, Y.Q.; Mo, X.D.; et al. Monitoring of Post-Transplant CBFB-MYH11 as Minimal Residual Disease, Rather than KIT Mutations, Can Predict Relapse after Allogeneic Haematopoietic Cell Transplantation in Adults with Inv(16) Acute Myeloid Leukaemia. Br. J. Haematol. 2018, 180, 448–451. [Google Scholar] [CrossRef]
  117. Borthakur, G.; Cortes, J.E.; Estey, E.E.; Jabbour, E.; Faderl, S.; O’Brien, S.; Garcia-Manero, G.; Kadia, T.M.; Wang, X.; Patel, K.; et al. Gemtuzumab Ozogamicin with Fludarabine, Cytarabine, and Granulocyte Colony Stimulating Factor (FLAG-GO) as Front-Line Regimen in Patients with Core Binding Factor Acute Myelogenous Leukemia. Am. J. Hematol. 2014, 89, 964–968. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  118. Gottardi, M.; Mosna, F.; De Angeli, S.; Papayannidis, C.; Candoni, A.; Clavio, M.; Tecchio, C.; Piccin, A.; Dell’Orto, M.C.; Benedetti, F.; et al. Clinical and Experimental Efficacy of Gemtuzumab Ozogamicin in Core Binding Factor Acute Myeloid Leukemia. Hematol. Rep. 2017, 9, 87–90. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  119. Lambert, J.; Pautas, C.; Terré, C.; Raffoux, E.; Turlure, P.; Caillot, D.; Legrand, O.; Thomas, X.; Gardin, C.; Gogat-Marchant, K.; et al. Gemtuzumab Ozogamicin for de Novo Acute Myeloid Leukemia: Final Efficacy and Safety Updates from the Open-Label, Phase III ALFA-0701 Trial. Haematologica 2019, 104, 113–119. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  120. Surapally, S.; Tenen, D.G.; Pulikkan, J.A. Emerging Therapies for Inv(16) AML. Blood 2021, 137, 2579–2584. [Google Scholar] [CrossRef]
  121. Van der Kouwe, E.; Heller, G.; Czibere, A.; Pulikkan, J.A.; Agreiter, C.; Castilla, L.H.; Delwel, R.; Di Ruscio, A.; Ebralidze, A.K.; Forte, M.; et al. Core Binding Factor Leukemia Hijacks T-Cell Prone PU.1 Antisense Promoter. Blood 2021. Epub ahead of print. [Google Scholar] [CrossRef]
  122. Awada, H.; Durmaz, A.; Gurnari, C.; Kishtagari, A.; Meggendorfer, M.; Kerr, C.M.; Kuzmanovic, T.; Durrani, J.; Shreve, J.; Nagata, Y.; et al. Machine Learning Integrates Genomic Signatures for Subclassification Beyond Primary and Secondary Acute Myeloid Leukemia. Blood 2021. Epub ahead of print. [Google Scholar] [CrossRef] [PubMed]
  123. Rotchanapanya, W.; Hokland, P.; Tunsing, P.; Owattanapanich, W. Clinical Outcomes Based on Measurable Residual Disease Status in Patients with Core-Binding Factor Acute Myeloid Leukemia: A Systematic Review and Meta-Analysis. J. Pers. Med. 2020, 10, 250. [Google Scholar] [CrossRef] [PubMed]
Table 1. Prognostic impact of clinical features at diagnosis in patients with AML showing inv(16)/t(16;16).
Table 1. Prognostic impact of clinical features at diagnosis in patients with AML showing inv(16)/t(16;16).
Reference; Design of StudyN. of Patients with inv(16)Median Age, Years (Range); Median Follow-Up, MonthsSurvival OutcomeFactors of Prognostic Relevance
Patient’s Characteristics and Clinical FeaturesGenetic Features (Other than KIT Mutations)
Delaunay et al. [10],
Blood 2003
11034 (0.7–64)
CR 93%
3-y OS 58%
3-y DFS 48%
3-y CIR 42%
UVA—WBC > 120 × 109/L: lower CR
PLT < 30 × 109/L: lower CR, OS in CR
Age >35: lower 3-y DFS, OS in CR; higher CIR
MVA—WBC > 120 × 109/L: lower CR
PLT < 30 × 109/L lower OS in CR
Age > 35: lower 3-y DFS, OS in CR
+22: lower CR
Schlenk et al. [8],
J. Clin. Oncol. 2004
20142 (17–60)
CR 89%
CR2 78%
3-y OS 74%
3-y RFS 58%
Older age, higher WBC: increased early/hypoplastic death+22: higher RFS
Marcucci et al. [6],
J. Clin. Oncol. 2005
16840 (17–77)
CR 87%
5-y OS 54%
5-y CIR 57%
Lower PLT, hepatomegaly: lower CR
Older age, lower PLT: lower OS
Older age: lower OS after relapse
In younger than 60, sex (male): lower CIR
+22: lower RR
In younger than 60, secondary chromosome abnormalities: lower CIR
Boissel et al. [12],
Leukemia 2006;
4733 (1–75) *
52.8 *
CR 89%
6-y OS 71%
6-y EFS 60%
NAFLT3mut: lower CR, OS, EFS *
Appelbaum et al. [7],
Br. J. Haematol. 2006;
19641 (16–83)
CR 85%
5-y OS 50%
5-y RFS 44%
UVA—Older age, secondary AML: lower CR *
UVA—Older age, PB and BM blast %: lower OS *
MVA/UVA—Older age, PB blast%: lower RFS *
−7/7q-: higher RD *
+8, complex abnormality: lower OS *
Wang et al. [13],
Biochem. Biophys. Res. Commun. 2012
1128 (16–64)CR 81.8%WBC >100 × 109: lower CR and OS *NA
Kim et al. [14],
Ann. Hematol. 2013
3938 (18–69)
CR 100%
2-y OS 57.1%
2-y EFS 47.5%
MVA—Older age: lower EFSNA
Allen et al. [15],
Leukemia 2013
15539 (15–70) *
99.6 *
10-y OS 54%NAFLT3-TKDHIGH: lower RR, higher OS
FLT3-ITDHIGH: higher RR, lower OS *
CBLHIGH: higher OS *
Jourdan et al. [16],
Blood 2013
10242 (18–60)
3-y RFS 61%
3-y CIR 34%
3-y OS 86%
UVA—Higher WBC: higher SHR *
Older age, BM blast %: lower OS *
MVA—3-log MRD2 reduction or MRD2 < 0.1%: lower CIR, higher RFS, higher OS from CR *
RTKmut: higher CIR, lower RFS *
Hoyos et al. [17],
Eur. J. Haematol. 2013
7642 (18–68)
CR 84%
5-y CIR 29%
5-y DFS 58%
5-y OS 64%
Age > 50: lower CR, lower OS*
WBC > 20 × 109/L: higher CIR, lower DFS, lower OS *
High copies at diagnosis: higher CIR, lower DFS, lower OS *
High MRD after induction: higher CIR, lower DFS, lower OS
High MRD after consolidation: higher CIR, lower DFS, lower OS
BAALC and MN1 overexpression: higher CIR, lower DFS
Cairoli et al. [18],
Am. J. Hematol. 2013
5842 (15–60)
CR 96.5%;
CR2 74%
5-y RI 48.4%
5-y OS 69.2%
UVA—Age > 43: lower OS
MVA—Age > 43: lower OS
Higher WBC: higher RI
Paschka et al. [19],
Blood 2013
17641 (18–74)
CR 90%
6-y RFS 52%
6-y OS 66%
MVA—Higher WBC: lower RFS
Older age: lower OS
UVA—+22: higher RFS
+8, FLT3 mutation: lower OS
MVA—+8, FLT3 mutation: lower OS
Yoon et al. [20],
Bone Marrow Transplant. 2014
7139 (18–89) *
61.8 *
NAUVA—Age > 40: lower OS, higher CIR *
Post-induction MRD reduction < or =3-log: lower OS *
MRD after final treatment undetectable: higher OS
NK mosaicism: higher OS, higher EFS §
UVA—additional chromosome > or =2: lower OS, higher CIR *
Jung et al. [21],
Anticancer Res. 2014
1647 (18–75)
CR 92.3% *
Median OS 80.6 months *
Median RFS 68.4 months *
PLT < 20 × 109/L, PB blasts > 50%, BM blasts > 50%: lower OS *
PLT < 20 × 109/L, BM blasts >50%: lower LFS *
Y deletion: higher OS and LFS *
Brunner et al. [22],
Leuk. Res. 2014
32054 (15–84) *
1-y OS 71.9%
3-y OS 57.3%
5-y OS 46.9%
Older age: higher early death rate, lower OS *
Black ethnicity, year of diagnosis before 2003: lower OS *
Mosna et al. [23],
Am. J. Hematol. 2015
11245.1 (15–73)
CR 93.8% §
5-y OS 67% *
10-y OS 63.9% *
5-y DFS 58.2% *
10-y DFS 54.8% *
5-y EFS 53.9% *
10-y EFS 49.9% *
UVA—PLT ≤ 20 × 103/mm3, failure to achieve CR1 after induction therapy: lower OS
MVA—Age > 60, PLT ≤ 20 × 103/mm3: lower OS
+22, +8: higher OS and DFS *
Additional cytogenetic abnormalities > or =3: lower DFS, EFS and OS *
Yui et al. [24],
Ann. Hematol. 2017
2845 (15–80) *
3-y RFS 48.6% *
3-y OS 69.9% *
3-y CIR 46.7% *
Age > 60, no HDAC as post-remission therapy: lower OS and RFS *NA
Prabahran et al. [25],
Eur. J. Haematol. 2018
3046.5 (17–73)
CR 97% *
5-y OS 71% *
5-y RFS 39% §
5-y RR 57% §
UVA and MVA—age > 50: lower OS *
UVA—WBC > 40 × 109/L: lower RFS *
RTKmut: no impact on OS, RFS
Shin et al. [26],
Ann. Hematol. 2019
11145 (17–85)
3-y EFS 47.1%
3-y OS 59.9%
UVA—Age > 60, number of induction cht > 1, not CR after first induction, not CR before SCT: lower OS
MVA—not CR before SCT: lower OS
del(7q): higher OS (NS)
Opatz et al. [27],
Leukemia 2020
16244 (17–83)
CR 97.1%UVA—Age > 60: lower OSUVA—+8, +22: higher OS (NS)
Ishikawa et al. [28],
Blood Adv. 2020
6737 (17–64)
2-y RFS 59.6%MVA—MRD ≥ 50 copies/μg RNA after 3 courses of consolidation: lower RFSMVA—Loss of X/Y, NRAS mutation: lower RFS
Ustun et al. [29],
Int. J. Lab. Hematol. 2020
29049 (5–78)
Median EFS 25.5 m
Median DFS 29.5 m
MVA—Age > or =43: lower EFS, DFS, OS
WBC ≥ 98 × 109/L: lower EFS, DFS
Jahn et al. [30],
Blood Adv. 2020
16046 (18–77)
CR 92%Age: lower OS
WBC, t-AML: lower RFS
+8, FLT3-ITD, TET2,
DNMT3A: lower OS *
WT1wt: higher OS *
NRASwt: higher OS (NS) *
Duan et al. [31],
Br. J. Haematol. 2021
5838 (17–66)
CR 98.3%
3-y CIR 29.4%
3-y CIM 24.4%
Age > 41: lower RFS
MRD > 0.1% after 2 courses of consolidation: lower RFS, EFS
Duan et al. [32],
Ann. Hematol. 2021
6839 (15–70) *
26 *
CR 99.5% *
3-y CIR 29.4% *
3-y CIM 27% *
MRD < 0.1% after 2 course of consolidation: higher RFS, OSNA
Han et al. [33],
Blood Adv. 2021
29050 (5–81)
CR 93%
5-y OS 68%
5-y DFS 47%
UVA—Age: lower OS, DFSUVA—Hyperdiploidy, +8, secondary chromosomal abnormalities: higher DFS
MVA—Chromosomal abnormalities
other than +8: lower OS
+8: higher OS
CR: complete remission after induction; CR1: 1st CR; CR2: 2nd CR; OS: overall survival; RFS: relapse-free survival; EFS: event-free survival; DFS: disease-free survival; LFS: leukemia-free survival; CIR: cumulative incidence of relapse; CIM: cumulative incidence of mortality; RI: relapse incidence; RR: relapse rate; RD: resistant disease; cht: chemotherapy cycle; HDAC: high-dose cytarabine; mut: mutated; wt: wild-type; UVA: univariate analysis; MVA: multivariate analysis; WBC: white blood cell count; PLT: platelets count; PB: peripheral blood; BM: bone marrow; MRD: measurable residual disease; MRD2: MRD before second consolidation course; SCT: stem cell transplant; SHR: specific hazard of relapse; AML: acute myeloid leukemia; t-AML: therapy-related AML; NK normal karyotype; NA: not available data; NS: not statistically significant data; * Data referred to entire cohort of the study; § Data referred to CBFB-MYH11 AML cohort.
Table 2. Prognostic relevance of KIT gene mutation in AML positive for inv(16)/t(16;16).
Table 2. Prognostic relevance of KIT gene mutation in AML positive for inv(16)/t(16;16).
ReferenceN. Median Age, Years (Range)KIT Exons AnalyzedProportion of Patients with KIT Mutations, %Prognostic Relevance of KIT Mutations
Care et al. [48],
Br. J. Haematol. 2003
6343.9 (15–74)8, 1732 (20/63)Higher RR with KIT exon 8 mutation
Boissel et al. [12],
Leukemia 2006
4733 (1–75) *8, 1722 (10/46)No impact on OS, RFS, EFS
In t(8;21): negative impact on OS, RFS, EFS and association to higher WBC
Cairoli et al. [41],
Blood 2006
2551 (17–88)8, 11, 1748 (12/25)No impact on RI, OS
In t(8;21): negative impact on OS, RFS, EFS for D816 and association to higher WBC and extramedullary leukemia
Paschka et al. [43],
J. Clin. Oncol. 2006
61NA8, 1729.5 (18/61)Higher CIR in mutKIT patients, mainly in exon 17 mutations (six times RR)
Inferior OS in MVA in mutKIT patients
Association to higher PB blast percentage and older age
Marková et al. [53],
Leuk. Lymphoma 2009
2629.3 (1.6–72.2) *8, 9, 10, 11, 17, 1850 (13/26)No impact on RFS, OS
Park et al. [49],
Leuk. Res. 2011
38NA8, 1734 (13/38)Lower CR with KIT exon 8 mutation; no impact on EFS, OS
In t(8;21): negative impact on OS, EFS with KIT exon 17 mutation
Wang et al. [13],
Biochem. Biophys. Res. Commun. 2012
1128 (16–64)8, 1728.9 (22/76) *Lower CR with KIT exon 17 mutation *
Lower OS, RFS in mutKIT patients *
Huh et al. [46],
Am. J. Hematol. 2012
3541 (15–75) *8, 10, 11, 12, 13, 1723 (21/91) *No impact on OS
In t(8;21): negative impact on OS, EFS, LFS with KIT exon 17 mutation (D816)
Kim et al. [14],
Ann. Hematol. 2013
3938 (18–69)8, 10, 11, 12, 13, 1726.4 (32/121) *No impact on OS, EFS
In t(8;21): negative impact on OS, EFS with KIT exon 17 mutation (D816)
Allen et al. [15],
Leukemia 2013
15539 (15–70) *8,9, 10, 11, 17, 1835 (54/155)No impact on CIR, OS in MVA
In t(8;21): negative impact on CIR for KITHIGH mutant level
Jourdan et al. [16],
Blood 2013
10242 (18–60)8, 1718 (18/102)Negative impact on CIR (p = 0.057) *
Hoyos et al. [17],
Eur. J. Haematol. 2013
7642 (18–68)8, 1749 (19/39)No impact on CIR, DFS, OS
In t(8;21): negative impact on CIR
Cairoli et al. [18],
Am. J. Hematol. 2013
5842 (15–60)
2, 8, 10, 11, 1725.9 (15/58)No impact on CR, RI, OS
Paschka et al. [19],
Blood 2013
17641 (18–74)8, 10, 11, 1737 (65/175)Lower RFS with KIT exon 8 mutation
Association to higher WBC and PB blast %
Riera et al. [54],
Oncol. Rep. 2013
1442.7 (19–64) *8, 9, 10, 11, 13, 14, 1728.6 (4/14)No impact on CR, OS, DFS
Association to higher lactate dehydrogenase level
Schwind et al. [50],
Blood 2013
20841 (17–74)8, 1724 (48/208)Lower OS, EFS
Yoon et al. [20],
Bone Marrow Transplant. 2014
7139 (18–89) *1725 (6/24)Lower OS
Park et al. [55],
Ann. Lab. Med. 2015
2147 (16–82)8, 1714.3 (3/21)No impact on DFS, OS
In t(8;21): negative impact on DFS, OS
Qin et al. [47],
Leuk. Res. 2014
98(0.5–73)8, 1729.6 (29/98)No impact on CIR, DFS, OS
Less reduction in fusion transcript levels after first induction therapy
In t(8;21): negative impact on OS, DFS, CIR
Mosna et al. [23],
Am. J. Hematol. 2015
11245.1 (15–73)810.2 (4/39)No impact on OS
In t(8;21): negative impact on OS
Yui et al. [24],
Ann. Hematol. 2017
2845 (15–80) *8, 1716 (10/28)Lower OS, RFS with KIT exon 17 mutation (D816)
Prabahran et al. [25],
Eur. J. Haematol. 2018
3046.5 (17–73)NA58 (7/12)No impact on OS, RFS
Shin et al. [26],
Ann. Hematol. 2019
11145 (17–85)17NANo impact on OS, EFS
In t(8;21): negative impact on OS, EFS with KIT exon 17 mutation (D816)
Opatz et al. [27],
Leukemia 2020
16244 (17–83)1726 (41/162)No impact on RFS, OS
In t(8;21): negative impact on RFS with KIT exon 17 mutation (D816)
Ishikawa et al. [28],
Blood Adv. 2020
6737 (17–64)8, 10, 11, 1731.3 (21/67)No impact on OS, RFS
In t(8;21): negative impact on OS, RFS with KIT exon 17 mutation; association to higher WBC and BM blast %; association to MRD level after consolidation
Jahn et al. [30],
Blood Adv. 2020
16046 (18–77)8, 1726In t(8;21): negative impact on OS with KIT exon 17 mutation
Duan et al. [31],
Br. J. Haematol. 2021
5838 (17–66)8, 1727.5 (16/58)Lower RFS
Duan et al. [32],
Ann. Hematol. 2021
6839 (15–70) *8, 1727.9 (19/68)Lower RFS, OS with KIT mutation, especially with KIT exon 17 mutation (D816, D820) *
Han et al. [33],
Blood Adv. 2021
29050 (5–81)1713In t(8;21): negative impact on OS, DFS with KIT exon 17 (D816) mutation
CR: complete remission after induction; RFS: relapse-free survival; OS: overall survival; RI: relapse incidence; RR: relapse rate; DFS: disease-free survival; EFS: event-free survival; LFS: leukemia-free survival; CIR: cumulative incidence of relapse; MVA: multivariate analysis; MRD: measurable residual disease; WBC: white blood cell count; PB: peripheral blood; BM: bone marrow; NA: not available data. * Data referred to entire cohort of the study.
Table 3. Molecular MRD monitoring in AML with CBFB-MYH11 fusion transcript.
Table 3. Molecular MRD monitoring in AML with CBFB-MYH11 fusion transcript.
ReferenceN. of Patients; Median Age, YearsMedian Follow-Up, Months; OutcomesTimepointPB or BMPrognostic Transcript
Level Cutoff or Trend of MRD Dynamics
Associated RiskSensitivity of the Assay
Marcucci et al. [74],
Leukemia 2001
CR 100%
At the end of treatmentBMCBFB-MYH11/18S × 106
>10 copies
Shorter CR duration and higher risk of relapse for CBFB-MYH11/18S × 106
>10 copies
Buonamici et al. [61],
Blood 2002
CR1 72%
3-y DFS 63%
3-y OS 82%
Any time during CRPB/BMCBFB-MYH11/ABL < 0.12%
> 0.25%
High probability of durable remission for
CBFB-MYH11/ABL < 0.12%
High risk of relapse for
CBFB-MYH11/ABL > 0.25%
Guerrasio et al. [75], Leukemia 200236
After inductionBMCBFB-MYH11/ABL × 104 > 100 copiesHigh risk of relapse for CBFB-MYH11/ABL × 104
>100 copies
After consolidationBMCBFB-MYH11/ABL × 104 > 10 copiesHigh risk of relapse for CBFB-MYH11/ABL × 104
>10 copies
At any time during CRBMCBFB-MYH11/ABL × 104 < 1 copyHigher probability of CCR
Krauter et al. [76],
J. Clin. Oncol. 2003
15 §
39 *
19 *
At least at one time point after inductionBMCBFB-MYH11:GAPDH in CR/CBFB-MYH11:GAPDH at diagnosis > or = 1%Shorter RFS *10−5
Schnittger et al. [77],
Blood 2003
122 §
48.9 §
17.7 §
At diagnosis
after consolidation
BMCBFB-MYH11/ABL × 102 < 75th percentile at diagnosis
CBFB-MYH11/ABL < 0.014 after consolidation
2-y OS 100% (vs. 69% if initial level >75th percentile and/or more than 0.014 after consolidation) §
2-y EFS 100% (vs. 40% if initial level > 75th percentile and/or more than 0.014 after consolidation) §
Perea et al. [73],
Leukemia 2006
35 §
43 §
34 *
2-y LFS 50% §
2-y OS 64% §
CR 84% *
After inductionBMCBFB-MYH11/ABL × 104 < or = 100 copies2-y CIR 35% (vs. 58% >100 copies) * (NS)10−5
After intensificationBMCBFB-MYH11/ABL × 104 < or = 10 copies2-y CIR 36% (vs. 70% >10 copies) * (NS)
At the end of treatmentBMCBFB-MYH11/ABL × 104 < or = 10 copies2-y CIR 26% (vs. 100% >10 copies) §
At follow-upBMCBFB-MYH11/ABL × 104 < or = 10 copies2-y CIR 13% (vs. 78% >10 copies) *
Stentoft et al. [78],
Leuk. Res. 2006
13 §
39 *
NAAfter inductionPB/BM<2-log reduction of the fusion transcript levelShorter EFS (p < 0.014) *10−4
Lane et al. [79],
Leuk. Lymphoma 2008
17 §
35 §
34 *
At follow-upBM> or = 1-log rise in transcript levels in consecutive samples in CRPredictive for imminent morphological relapse and shorter LFS (p = 0.008) *10−6
Guièze et al. [80], Leukemia 201059
2-y CCR 63%
2-y OS 88%
At CR achievementPB/BMCBFB-MYH11/ABL < 0.5%2-y CCR 76% (vs. 36% > 0.5%)NA
After 1st consolidation (MRD2)PB/BMCBFB-MYH11/ABL < 0.1%2-y CCR 74% (vs. 40% > 0.1%)
PB/BMMRD2 transcript level/
CBFB-MYH11 transcript level at diagnosis
(deltaMRD2) decrease >3 log
2-y CCR 83% (vs. 28% if deltaMRD2 decrease < 3 log)
2-y OS 100% (vs. 67% if deltaMRD2 decrease < 3 log)
At the end of consolidationPBCBFB-MYH11/ABL undetectable2-y CCR 85%
(vs. 13% for detectable MRD)
Corbacioglu et al. [81],
J. Clin. Oncol. 2010
From 1st consolidation until up to 4 weeks after last consolidation (checkpoint I)BMAt least 1 PCR negative sample2-y RFS 79% (vs. 54% for patients who never achieved PCR negativity during consolidation)10−4
From 1st consolidation until up to 3 months after last consolidation (checkpoint II)PB/BMAt least 2 PCR negative samples2-y RFS 91%
Longer OS
At follow-upBMConversion of PCR negativity to positivity
(>10 copies/B2M × 106)
High risk of relapse
Yin et al. [82],
Blood 2012
115 §
38 §
36 *
CR 92% §
5-y CIR 23% §
At remission after inductionPBCBFB-MYH11/ABL × 105 < 10 copies5-y CIR 21% (vs. 56% 10–500 copies) §
5-y survival after CR 89% (vs. 45% 10–500 copies) §
After courses 3 and 4PBCBFB-MYH11/ABL × 105 < 10 copies5-y CIR 36% (vs. 78% > 10 copies) §
At follow-up (4 weeks after last treatment)PBCBFB-MYH11/ABL × 105 < 10 copies5-y EoR 7% (vs. 97% > 10 copies) §
5-y EoS 91% (vs. 57% > 10 copies) §
BMCBFB-MYH11/ABL × 105 < 50 copies5-y EoR 10% (vs. 100% > 50 copies) §
5-y EoS 100% (vs. 25% > 50 copies) §
Jourdan et al. [16],
Blood 2013
102 §
42 §
32 *
3-y RFS 61% §
3-y CIR 34% §
3-y OS 86% §
Before 2nd consolidation (MRD2)BM> or = 3-log MRD2 reduction3-y CIR 22% (vs. 54% for patients who did not achieve a 3-log MRD2 reduction) *
3-y RFS 73% (vs. 44% for patients who did not achieve a 3-log MRD2 reduction) *
3-y OS 90% (vs. 71% for patients who did not achieve a 3-log MRD2 reduction) (NS) *
MRD2 < or = 0.1%Lower CIR and longer RFS
Hoyos et al. [17],
Eur. J. Haematol. 2013
76 §
42 §
55 *
CR 84% §
5-y CIR 29% §
5-y DFS 58% §
5-y OS 64% §
After inductionBMCBFB-MYH11/ABL < 100 copiesDFS 66% (vs. 34% > 100 copies) §
OS 82% (vs. 33% > 100 copies) §
After consolidationBMCBFB-MYH11/ABL < 82 copiesCIR 32% (vs. 75% > 82 copies) §
DFS 64% (vs. 25% > 82 copies) §
OS 86% (vs. 25% > 82 copies) §
Yoon et al. [20],
Bone Marrow Transplant. 2014
71 §
39 *
61.8 *
After inductionBMMRD qPCR reduction
> or = 3 log
Longer OS *NA
At the end of treatmentBMMRD qPCR undetectableLonger OS *
Wang et al. [83],
Ann. Hematol. 2014
10 §
40 §
11.2 *
CR 70% §
4 weeks after 3rd consolidationBMCBFB-MYH11/ABL × 106
< or = 0.1%
2-y RFS 56.8%
(vs. 15.8% > 0.1%) *
4 weeks after last consolidationBMCBFB-MYH11/ABL × 106
< or = 0.1%
2-y RFS 55.8%(vs. 25.4% > 0.1%) *
At follow-upBMCBFB-MYH11/ABL × 106
< or = 0.1%
2-y RFS 75% (vs. 0% > 0.1%) *
Qin et al. [84].,
Leuk. Lymphoma 2015
CR 95.3%
3-y CIR 33.7%
3-y DFS 62.2%
3-y OS 72.9%
After course 1 inductionBMCBFB-MYH11 transcript levels > 2.0% (corresponding to <2-log reduction)3-y CIR 68.5% (vs. 43.3% if CBFB-MYH11 levels < or = 2.0%)
3-y DFS 31.5% (vs. 56.7% if CBFB-MYH11 levels < or = 2.0%)
After achieving CR by inductionBMCBFB-MYH11 transcript levels > 2.0% (corresponding to <2-log reduction)3-y CIR 77.6% (vs. 40.5% if CBFB-MYH11 levels < 2.0%)
3-y DFS 22.4% (vs. 59.5% if CBFB-MYH11 levels < 2.0%)
After course 1 consolidationBMCBFB-MYH11 transcript levels > or = 0.2% (corresponding to < or = 3-log reduction)3-y CIR 69.8% (vs. 7.1% if CBFB-MYH11 levels < 2.0%)
3-y DFS 30.2% (vs. 92.9% if CBFB-MYH11 levels < 2.0%)
3-y OS 48.9% (vs. 100% if CBFB-MYH11 levels < 2.0%)
After course 2 consolidationBMCBFB-MYH11 transcript levels > 0.2% (corresponding to < or = 3-log reduction)3-y CIR 88.3% (vs. 26.9% if CBFB-MYH11 levels < or = 0.2%)
3-y DFS 11.7% (vs. 73.1% if CBFB-MYH11 levels < or = 0.2%)
3-y OS 26.9% (vs. 88.3% if CBFB-MYH11 levels < or = 0.2%)
Ishikawa et al. [28],
Blood Adv. 2020
67 §
37 §
52.2 *
2-y RFS 59.6% §
At the end of consolidationBMCBFB-MYH11 transcripts > or = 50 copies/μg RNALower RFS §NA
Duan et al. [31],
Br. J. Haematol. 2021
CR 98.3%
3-y CIR 29.4%
3-y CIM 24.4%
After 2nd consolidationBMCBFB–MYH11/ABL
< 0.1%
3-y RFS 100% (vs. 31.4% if CBFB–MYH11/ABL > 0.1%)
3-y EFS 100% (vs. 33.1% if CBFB–MYH11/ABL > 0.1%)
Puckrin et al. [85],
Haematologica 2021
47 §
46.5 *
44.4 *
CR 99.1% *
At the end of consolidationPB/BMCBFB-MYH11 transcripts reduction
> or = 3 log
RFS 61.1% (vs. 33.7% if CBFB-MYH11 transcripts reduction < 3 log) *10−4
At the end of treatmentPB/BMCBFB-MYH11 transcripts reduction
> or = 4 log
RFS 51.2% (vs. 29.3% if CBFB-MYH11 transcripts reduction < 4 log) *
Duan et al. [32],
Ann. Hematol. 2021
68 §
39 *
26 *
CR 99.5% *
3-y CIR 29.4% *
3-y CIM 27% *
After 2nd consolidationBMCBFB–MYH11/ABL
< 0.1%
3-y RFS 96.3% (vs. 34.6% if CBFB–MYH11/ABL > 0.1%) *
3-y OS 94.1% (vs. 51.3% if CBFB–MYH11/ABL > 0.1%) *
CR: complete remission after induction; CR1: CR after first induction; OS: overall survival; RFS: relapse-free survival; EFS: event-free survival; DFS: disease-free survival; LFS: leukemia-free survival; CIR: cumulative incidence of relapse; CIM: cumulative incidence of mortality; CCR: continuous CR; PB: peripheral blood; BM: bone marrow; MRD: measurable residual disease; PCR: quantitative polymerase chain reaction; qPCR: quantitative PCR; B2M: beta2-microglobulin; GAPDH: glyceraldehyde-3-phosphate dehydrogenase; EoR: estimate of relapse; EoS: estimate of survival; NA: not available data; NS: not statistically significant data. * Data referred to entire cohort of the study. § Data referred to CBFB-MYH11 AML cohort.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Talami, A.; Bettelli, F.; Pioli, V.; Giusti, D.; Gilioli, A.; Colasante, C.; Galassi, L.; Giubbolini, R.; Catellani, H.; Donatelli, F.; et al. How to Improve Prognostication in Acute Myeloid Leukemia with CBFB-MYH11 Fusion Transcript: Focus on the Role of Molecular Measurable Residual Disease (MRD) Monitoring. Biomedicines 2021, 9, 953.

AMA Style

Talami A, Bettelli F, Pioli V, Giusti D, Gilioli A, Colasante C, Galassi L, Giubbolini R, Catellani H, Donatelli F, et al. How to Improve Prognostication in Acute Myeloid Leukemia with CBFB-MYH11 Fusion Transcript: Focus on the Role of Molecular Measurable Residual Disease (MRD) Monitoring. Biomedicines. 2021; 9(8):953.

Chicago/Turabian Style

Talami, Annalisa, Francesca Bettelli, Valeria Pioli, Davide Giusti, Andrea Gilioli, Corrado Colasante, Laura Galassi, Rachele Giubbolini, Hillary Catellani, Francesca Donatelli, and et al. 2021. "How to Improve Prognostication in Acute Myeloid Leukemia with CBFB-MYH11 Fusion Transcript: Focus on the Role of Molecular Measurable Residual Disease (MRD) Monitoring" Biomedicines 9, no. 8: 953.

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop