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Review

A Focus on Intermediate-Risk Acute Myeloid Leukemia: Sub-Classification Updates and Therapeutic Challenges

by
Hassan Awada
1,†,
Moaath K. Mustafa Ali
2,3,†,
Bicky Thapa
4,
Hussein Awada
5,
Leroy Seymour
4,
Louisa Liu
6,
Carmelo Gurnari
5,7,
Ashwin Kishtagari
8,
Eunice Wang
1 and
Maria R. Baer
3,*
1
Roswell Park Comprehensive Cancer Center, Buffalo, NY 14203, USA
2
University of Maryland Greenebaum Comprehensive Cancer Center, Baltimore, MD 21201, USA
3
Leukemia Division, Taussig Cancer Institute, Cleveland Clinic, Cleveland, OH 44106, USA
4
Division of Hematology/Oncology, Department of Medicine, Medical College of Wisconsin, Milwaukee, WI 53226, USA
5
Department of Translational Hematology and Oncology Research, Taussig Cancer Institute, Cleveland Clinic, Cleveland, OH 44106, USA
6
University of California, Riverside, CA 92521, USA
7
Department of Biomedicine and Prevention, University of Rome Tor Vergata, 00133 Rome, Italy
8
Vanderbilt University, Ingram Cancer Center, Nashville, TN 37232, USA
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Cancers 2022, 14(17), 4166; https://doi.org/10.3390/cancers14174166
Submission received: 9 August 2022 / Revised: 16 August 2022 / Accepted: 25 August 2022 / Published: 28 August 2022
(This article belongs to the Collection Acute Myeloid Leukemia (AML))
Browse Figure
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Abstract

:

Simple Summary

Risk stratification models, including the European LeukemiaNet 2017 and 2022 guidelines, categorize newly diagnosed acute myeloid leukemia (AML) patients into several subgroups of distinct genetic characteristics and disease outcomes. The intermediate-risk group remains the most heterogenous group, as most AML patients fall into it (i.e., a basket category) by virtue of not fulfilling criteria that identify specific entities (e.g., core-binding factor AML, TP53 mutations, complex karyotypes) of well-recognized prognostic significance. In this review, we aim to discuss the latest updates on intermediate-risk definition and highlight the therapeutic advances and challenges that warrant refining the prognostic classification of this category.

Abstract

Acute myeloid leukemia (AML) represents a heterogeneous group of hematopoietic neoplasms deriving from the abnormal proliferation of myeloid progenitors in the bone marrow. Patients with AML may have highly variable outcomes, which are generally dictated by individual clinical and genomic characteristics. As such, the European LeukemiaNet 2017 and 2022 guidelines categorize newly diagnosed AML into favorable-, intermediate-, and adverse-risk groups, based on their molecular and cytogenetic profiles. Nevertheless, the intermediate-risk category remains poorly defined, as many patients fall into this group as a result of their exclusion from the other two. Moreover, further genomic data with potential prognostic and therapeutic influences continue to emerge, though they are yet to be integrated into the diagnostic and prognostic models of AML. This review highlights the latest therapeutic advances and challenges that warrant refining the prognostic classification of intermediate-risk AML.

1. Introduction

Acute myeloid leukemia (AML) is a diverse group of hematopoietic clonal disorders characterized by the accumulation of immature myeloid progenitors [1]. Despite recent advances in genomics and therapeutics, long-term outcomes are dismal in many AML subsets. Patient characteristics such as age and performance status (overall, summarized by the concept of fitness [2]) and heterogeneous cytogenetic and genomic underpinnings constitute the main determinants of outcomes [3]. Recent advances in genome scanning techniques have increased our understanding of AML pathogenesis, unveiling a plethora of driver gene lesions and possible disease-outcome modifiers [4]. Despite the abundance of genomic information on AML, current diagnostic and prognostic classifications somehow remain inexact. This is particularly true for the subgroup of patients classified as intermediate-risk according to the standard prognostic criteria used for AML clinical management (the European LeukemiaNet, ELN 2017 [5] and 2022 revision [6]). Apart from FLT3 mutants, most patients usually fall into this group (an umbrella category) by virtue of not fulfilling criteria that identify specific entities (e.g., core-binding factor AML, TP53 mutations, complex karyotypes) with well-recognized prognostic significance.

2. Intermediate-Risk Definition and Prognosis

AML classification and prognostic criteria are based on cytogenetic and molecular features at the time of diagnosis. At least 50% of cases exhibit karyotypic abnormalities by conventional cytogenetic analysis; in addition, mutational screening reveals at least one somatic alteration in virtually all patients [7,8]. Traditionally, AML has been categorized into favorable-, intermediate-, and adverse-risk groups [9]. While the favorable- and adverse-risk groups represent well-defined categories, the intermediate-risk group is generally characterized by the absence of favorable or unfavorable cytogenetic and molecular abnormalities and encompasses variable outcomes with standard-of-care therapies.
Modern genomic profiling using high-throughput technologies has led to the identification of molecular alterations reflective of disease biology and predictive of outcomes. For instance, identifying somatic mutations in the FLT3, NPM1, CEBPA, IDH1, IDH2, DNMT3A, TET2, and KIT genes provided important information that improved AML diagnosis, treatment stratification, and monitoring [10,11,12]. The ELN AML risk stratification in 2017 [5] (Table 1) integrated additional cytogenetic and molecular abnormalities [5] not present in the 2010 version. A subsequent study of 1116 AML patients validated the ELN 2017 prognostic stratification and showed that it assigned more patients to the favorable- and adverse-risk groups than the 2010 criteria, thereby shrinking the intermediate-risk group [13]. Nevertheless, this remained an ill-defined “basket category” for patients not fulfilling the criteria for the favorable- or adverse-risk groups. Moreover, with regard to clinical management, while current indications for consolidation treatment with allogeneic hematopoietic stem cell transplantation (HSCT) are well-established in favorable- and adverse-risk patients, information derived from disease monitoring is crucial in clinical decision-making in intermediate-risk patients because of their heterogeneity [14,15].
Interestingly, in a retrospective study of 863 de novo AML patients < 60 years, Eisfeld et al. found additional gene mutations able to refine the prognostic classification of ELN 2017 [16]. In this study, the authors found a total of 2354 mutations, averaging 3 per individual. WT1/NPM1 co-mutant, DNMT3A, and ZRSR2 mutated patients had very poor survival outcomes, similar to those of the adverse-risk group. Of note, BCOR- and SETBP1-mutated AML patients were categorized as favorable-risk, whereas IDH mutants were associated with adverse-risk patients and had outcomes similar to those of intermediate-risk patients. They also found that FLT3 internal tandem duplication (ITD) with a high allelic ratio had survival outcomes similar to those of the adverse-risk group rather than the intermediate-risk category, regardless of NPM1 mutational status. Based on these findings, 9% of favorable-risk, and 53% of intermediate-risk AML patients per ELN 2017 could be reclassified as belonging to the adverse-risk category, and 9% of adverse-risk and 4% of favorable-risk patients could be reclassified as intermediate-risk. Thus, the current AML prognostic criteria do not encompass the molecular heterogeneity inherent to the disease, and the inclusion of mutations in additional myeloid genes may refine classification [17]. However, identifying genomic alterations and their prognostic significance is still an evolving field, and guidelines will require ongoing refinements.
Given the expansion of the AML therapeutic arsenal, consideration of the mutational status of additional genes is of utmost importance also in older patients. Recently, the ALFA-1200 study evaluated genomic predictors of outcomes in 471 newly diagnosed AML patients ≥ 60 years treated with standard “7 + 3” induction chemotherapy [18]. The group developed a decision tool to predict survival outcomes in older AML patients using mutations in seven genes, NPM1, NRAS, KRAS, ASXL1, DNMT3A, TP53, and FLT3-ITD. In patients with poor-risk cytogenetics, TP53 and KRAS mutations were independently associated with poor survival, whereas SETBP1, NRAS, ASXL1, and RUNX1 status predicted lower complete remission rates even in patients with favorable- and intermediate-risk cytogenetics. Additionally, mutations in DNMT3A, ASXL1, NRAS, NMP1, and FLT3-ITD (regardless of allelic ratio) were independent predictors of overall survival (OS). When cytogenetic risk and mutations in the seven genes were combined, 39.1% of patients had a 2-year OS of 66.1% (assigned to “go-go” group), 7.6% of patients had a 2-year OS of 2.8% (assigned to “no-go” group), and 3.3% of patients had a 2-year OS of 39.1% (assigned to “slow-go” group). This genetic-based predictive model was validated in three independent cohorts.
Besides genomic characteristics at the time of diagnosis, host-related factors such as poor baseline functional status, multiple comorbidities, and advanced age are associated with poorer prognosis (Figure 1) [19].
Interestingly, machine learning (ML) techniques have been applied in leukemia research and represent a promising auxiliary tool for developing new approaches that aim to improve AML risk stratification. Several studies have implemented unsupervised and unbiased ML methods that demonstrated high accuracy in terms of genomic classification [20]. These approaches may be further employed to define ambiguous definitions by unmasking unexplored clinico-morphologic and genomic characteristics unique to intermediate-risk AML patients. Indeed, ML-based methods demonstrated a 97% accuracy rate when reclassifying AML patients according to four genomic signature clusters [4]. While the clusters exhibited a certain degree of overlap with the 2017 ELN groups, significant differences in survival across the two classification systems emphasized the need for a more subtle distinction of AML risk groups.
Most recently, the 2022 ELN guidelines for diagnosis and management of AML were published [6]. In this newest version, the risk classification of AML has changed to using a hierarchical model that depends on molecular aberrations detected rather than morphologic or historical criteria (e.g., therapy-related, secondary AML). Moreover, the intermediate-risk AML group was redefined with the abrogation of the value given to FLT3 allelic ratio, as demonstrated in Table 2.

3. Current Therapeutic Approaches

The current AML treatment paradigm recommended by the major societies, including NCCN and ESMO, is heavily based on four factors: age, performance status, organ function (in other words, patients’ fitness), and risk classification per ELN 2017 criteria [5]. Of note is that there is a lack of trials solely focusing on patients with intermediate-risk AML. Hence, the current evidence-based therapeutic approaches in this population are mainly extrapolated from large studies that included different risk categories of patients. In this scenario, it is essential to recognize that the heterogeneity in the studied populations makes generalization difficult and might over- or underestimate the actual benefit of any treatment in such subgroup. In addition, none of the current Food and Drug Administration (FDA)-approved agents are specific for the intermediate-risk category, thereby configuring an unmet clinical need in AML. As the prognostication of AML continues to evolve and trial inclusion criteria change, therapeutic recommendations from major societies will likely be modified accordingly. Moreover, since the criteria used to define risk groups significantly vary between trials, it is challenging to determine the benefit of treatments and compare it among different studies.
Treatment of intermediate-risk ELN patients eligible for intensive therapy has not substantially changed over the past few decades, and “7 + 3” induction therapy still represents the standard of care. Data from three randomized trials comparing anthracycline doses (daunorubicin 45 mg/m2 and 90 mg/m2) show a survival benefit with higher doses of anthracyclines in both younger and older patients (at least up to the age of 65 years) [21,22,23]. These regimens lead to complete remission (CR) in 60–80% of younger adults and 40–60% of older patients. The benefit of adding gemtuzumab ozogamicin (GO), a humanized anti-CD33 monoclonal antibody conjugated to calicheamicin, to standard therapy was limited to favorable- and intermediate-risk patients [24,25,26].
Table 3 summarizes therapeutic regimens recommended by the 2021 NCCN and the 2020 ESMO guidelines for use in intermediate-risk AML. In this subgroup, for patients aged <60 years and with intact organ function, current recommendations support induction chemotherapy, as described above [27,28]. Patients who achieve a CR to induction chemotherapy receive consolidation chemotherapy, most commonly with high-dose cytarabine, but this may vary based on the chosen induction regimen. [29]. Cytarabine administered at 3 g/m2 (high-dose) by 3 h infusion, every 12 h on days 1, 3, and 5, was associated with a lower relapse rate and improved OS compared to intermediate- and low-dose regimens. However, there was no subgroup analysis according to cytogenetics in the original trial [29]. A follow-up study evaluated the outcomes of high-dose cytarabine in patients stratified into three cytogenetic groups, based on the presence of core-binding factor rearrangements, a normal karyotype, and other cytogenetic abnormalities. In the modern era, intermediate-risk AML would constitute parts of the two latter groups. The 5-year relapse-free survival with high-dose cytarabine was 78%, 40%, and 21% in these three groups, respectively, and was superior to results obtained with the intermediate- and low-dose cytarabine regimens (p < 0.05) [30].
Since most studies have focused on stratifying patients to various first-line therapies, little is known about the outcomes of different consolidation regimens in the intermediate-risk AML group. As mentioned, patients who remain in remission may be considered for HSCT as a potentially curative option, when suitable for the procedure. However, randomized trials investigating the benefit of transplant in intermediate-risk AML are lacking. Studies investigating the benefit of allogeneic and autologous HSCT have used donor availability as a criterion for transplant [31,32]; hence, it remains difficult to assess precisely the absolute benefit of this procedure in this group. Moreover, because the definition of the intermediate-risk AML group continues to change along with the advancements in risk stratification and measurable residual disease (MRD)-directed treatment strategies, determining the benefit of consolidative allogeneic HSCT in this population remains challenging and must account for individual patients’ characteristics (disease status, MRD, performance status, and donor availability). In a retrospective analysis, AML patients, less than 60 years old, who underwent allogeneic HSCT had a trend toward improved relapse-free survival (RFS), OS, and a lower relapse rate than their non-transplanted counterparts, but the results did not reach statistical significance [33]. HSCT is currently considered an option after remission induction in the intermediate-risk group, per NCCN and ESMO guidelines [27,28]. Nevertheless, we recommend that the treating physician discusses the role of such a procedure with a patient diagnosed with intermediate-risk AML, including the potential benefits and risks. While consolidation with allogeneic HSCT is a potential option in younger patients who are generally fit and less likely to suffer from treatment-related morbidity and mortality, enrollment in clinical trials may be a reasonable alternative in cases rendered not medically fit for HSCT.
The role of MRD in treatment stratification is also evolving. MRD refers to the detection of malignant cells by molecular biology or flow cytometry techniques in patients in complete remission, defined as hematologic recovery and an absence of AML blasts by morphological bone marrow examination. Studies have demonstrated the usefulness of monitoring MRD in patients with RUNX1-RUNX1T1 rearrangements and NPM1 mutations [34,35]. Patients with these abnormalities that become undetectable by molecular techniques tend to have better OS and lower cumulative rates of relapse [36]. However, the application of MRD monitoring in clinical settings remains complicated, mainly due to conflicting results with other molecular abnormalities and different sensitivities inherent to the techniques used [37,38,39]. Other challenges include standardizing the approaches by which MRD is analyzed and interpreted, as well as determining the optimal time and specimen source for its measure [40]. Nevertheless, a growing body of evidence suggests a promising role for MRD monitoring in guiding therapy choices in intermediate-risk AML patients. For instance, in the Italian GIMEMA AML1310 trial, in which the NCCN 2009 recommendations were used for risk classification, intermediate-risk patients were allocated into post-consolidation autologous or allogeneic HSCT, in cases with MRD-negative or MRD-positive status using multiparametric flow cytometry (MFC), respectively [41]. No significant difference was seen in the 2-year OS (79% vs. 70%, p = 0.713) or disease-free survival (DFS) (61% vs. 67%, p = 0.773) rates between the MRD-negative and -positive groups. Remarkably, MRD-positive intermediate-risk AML patients treated with allogeneic HSCT had OS and DFS rates similar to favorable-risk patients. The same group confirmed the role of MRD when risk categorization according to the ELN 2017 recommendations was applied to the AML1310 trial [42]. Indeed, no significant difference in OS at two years was observed between intermediate-risk MRD-negative patients who received either autologous or allogeneic HSCT (85.7% vs. 77.8%, p = 0.234), whereas allogeneic HSCT did significantly increase survival compared to autologous HSCT in MRD-positive patients (75% vs. 0%, p = 0.0231).
Maintenance therapy is used to decrease the risk of disease relapse. In an open-label phase III study, patients ≥ 60 years with AML or refractory anemia with excess blasts who achieved remission post induction were randomized to receive azacitidine 50 mg/m2 subcutaneously days 1–5 every four weeks vs. observation. While patients treated with azacitidine had improved 12-month DFS (64% vs. 42%, p < 0.05), OS was similar (84% vs. 70% at 12 months, p = 0.69). Of note, the study design did not require patients to receive consolidation with cytarabine, and no subgroup analysis based on risk stratification was provided in this trial [43]. In another study of patients ≥ 55 years with de novo or secondary AML, with intermediate- or poor-risk cytogenetics according to 2011 NCCN risk classification, who were not candidates for HSCT, oral azacitidine 300 mg daily for 14 days per 28-day cycle improved OS compared to placebo (24.7 months and 14.8 months, respectively; p < 0.05) [44]. A subgroup analysis showed improved 2-year OS (difference 13.6%, 95% CI: 3.9–23.4) in the intermediate-risk group.
In patients who do not achieve remission with induction or relapse after treatment, the current NCCN and ESMO guidelines recommend targeted therapy or clinical trial enrollment whenever possible. Table 3 summarizes commonly used options in this setting. As with first-line regimens, most trials included intermediate-risk group AML in the study populations.

4. Clinical Trials

As discussed, meticulous clinical research from bench to bedside has led to a better understanding of the pathophysiology of AML and, subsequently, to the discovery of novel therapeutic agents. Nevertheless, the molecular heterogeneity of AML continues to remain a challenge. Indeed, the significant advances in elucidating the genomics of AML have not yet led to ameliorating outcomes, which remain dismal in relapsed and refractory patients (R/R AML). Moreover, the situation is even hazier when considering the treatment of older and frail (unfit) AML patients.
In the United States, more than 300 clinical trials are currently assessing the safety and efficacy of various therapeutic agents in AML patients. A detailed review of ongoing studies is beyond the scope of this review; however, in Table 4, we have listed some representative examples currently enrolling intermediate-risk AML patients who are newly diagnosed or relapsed/refractory.

5. Targeted Agents and Challenges in Intermediate-Risk AML

The entire schema of ELN risk classification currently used in the clinic is derived from the experience of patients treated with intensive chemotherapy. Over the past few years, with the advent of many new drugs for AML, including venetoclax combinations and a molecularly defined class of targeted therapies, IDH1/2 or FLT3 inhibitors, it is uncertain if this classification would still apply [59].

5.1. FLT3 Inhibitors

Mutations in the FLT3 gene are among the most common mutations in intermediate-risk AML, most commonly associated with a normal karyotype [60]. These mutations lead to constitutive activation of the FLT3 receptor tyrosine kinase and multiple downstream signaling cascades involved with AML cell survival, proliferation, and differentiation. In the ELN 2017, the allelic burden and the pattern of co-mutations (in particular in NPM1 and DNMT3A) modulated the prognostic significance of the more common and prognostic FLT3 mutation, FLT3-ITD [7,61]. For instance, FLT3-ITD with a high allelic ratio (>0.5) conferred adverse prognosis; however, the simultaneous presence of an NPM1 mutation made it instead recognized as intermediate-risk [4]. The new 2022 revision abated this differentiation by assigning all FLT3 mutants to the intermediate-risk category [6]. The treatment paradigm for FLT3-mutated AML patients has been transformed by the advent of small molecule tyrosine kinase inhibitors (midostaurin, gilteritinib) for both newly diagnosed and R/R AML [54,62]. Furthermore, the combination of azacitidine and venetoclax has changed treatment outcomes for adults who are not candidates for intensive induction chemotherapy [60,63]. Response rates of FLT3-mutated AML patients to the azacitidine/venetoclax combination are comparable to those of patients with wild-type FLT3. In light of response improvements from doublets, the need to study rational combinations of triplets or sequential therapies to continue improving the outcomes of patients with AML with FLT3-ITD is a current topic of research.

5.2. IDH1/2 Inhibitors

Characterization of the unique mechanism of leukemogenesis resulting from IDH1 and IDH2 mutations in AML led to the development of targeted oral therapies. This represents a remarkable bench-to-bedside journey. IDH1/2 mutations are present in ~20% of AML cases (IDH1: ~5%–8% and IDH2: 9%–12% [61]). These mutations frequently occur in normal-karyotype AML, representing a common subset of intermediate-risk diseases. First-in-class, oral, selective inhibitors of mutant IDH1 (ivosidenib) [64] and IDH2 (enasidenib) [65] are FDA-approved for the management of R/R AML, based on phase 1 clinical trials showing overall response rates of 42% and 39%, respectively, along with manageable toxicity profiles. Despite the initial success, several questions were raised based on the preliminary results of the recent randomized trials. The phase 2 study comparing azacitidine with or without enasidenib as a first-line treatment for AML patients who are unfit for intensive chemotherapy showed improved response rates but similar OS as the combination therapy [66]. Similarly, the phase 3 IDHENTIFY study enrolling IDH2-mutant R/R AML patients (after the failure of two or three lines of therapy) reported no survival benefit with enasidenib compared with standard of care [67]. These two studies highlight the challenges in deciding the optimal approach to using targeted therapies in AML and the need for randomized studies. Besides, a recent phase 3 trial evaluating azacitidine with or without ivosidenib in IDH1-mutant newly diagnosed AML unfit for intensive treatment showed a 12-month event-free survival rate significantly higher in the experimental group, along with a benefit in OS (24.0 vs. 7.9 months; p = 0.001), opening new therapeutic opportunities in such a setting. [58] Particularly, the use of ivosidentib plus azacitidine enabled the clearance of detectable IDH1-mutated cells, and less transfusion support was needed, with safety signals similar in the two groups if excepting the higher rate of differentiation syndrome in the experimental arm.

5.3. Others

CA-4948 is a potent interleukin-1 receptor-associated kinase 4 (IRAK-4)/FLT3 inhibitor, with potential for anti-tumor activity in AML, that is currently in the early phases of therapeutic development (NCT04278768). In adult patients with FLT3-mutated R/R AML, combinations with experimental oral agents such as TL-895 (tyrosine kinase inhibitor) and KRT-232 (MDM2 inhibitor) are being evaluated for safety and efficacy in an early phase clinical trial (NCT04669067). Minnelide is a potent heat shock protein 70 inhibitor that showed potent preclinical anti-tumor activity in AML [68]. A phase 1 study (NCT03760523) is ongoing to investigate this novel agent in patients with R/R-AML who are ineligible for intensive chemotherapy.

5.4. Challenges

Many challenges remain unsolved in intermediate-risk AML. A first challenge is to define the precise scenarios for using the plethora of novel targeted drugs [69]. The ELN criteria, including the latest revision, are based on data derived from intensively treated patients, thereby leaving unanswered the question if current schemes may still be valid in patients treated with newer agents [6]. This is particularly true for FLT3-positive cases, now representing a good fraction of the intermediate-risk group according to the latest classification, especially in light of the availability of specific targeted treatment options. A second challenge is represented by AML trial designs, which beg the question of what is the best setting to test these novel compounds. Indeed, since the intermediate-risk group is the most heterogeneous category, issues of clonal evolution and genomic and/or epigenomic complexity, after receiving standard of care therapies, and the emergence of subclones with distinct resistance mechanisms are only some of the challenges to be faced. A third challenge is the incorporation of novel agents and existing targeted therapies in the frontline regimens, which are likely to increase the proportion of patients achieving and maintaining CR for longer periods [70]. As a consequence, and with deeper responses resulting from the use of tailored therapeutic approaches in the induction schemes, the definition of the need for consolidation/maintenance regimens and HSCT will urge further refinements. While guiding treatment strategies by MRD-based approaches could answer some of these questions, individual patients’ characteristics and inherent subgroup genomic features (e.g., disease subclassifications exemplified in the recent WHO revision and other classifications [71,72]) may represent other difficult obstacles to overcome.

6. Immunotherapies in AML

Over the last decade, immunotherapies have shown encouraging anti-tumor activity across most cancer types and may offer a therapeutic opportunity also in intermediate-risk AML, in a way that is mutation-agnostic. Immune-based therapeutics, including monoclonal antibodies, immune checkpoint inhibitors (ICIs), bispecific T cell engagers (BiTE) antibodies, and chimeric antigen receptor T-cell therapy (CAR-T) are being extensively investigated to improve the outcome of AML patients.

6.1. The Role of Immune Checkpoint Inhibitors in AML

Immune checkpoints, namely cytotoxic T lymphocyte antigen 4 (CTLA-4), programmed death-1 (PD-1), and programmed death-ligand 1 (PD-L1), play a crucial role in regulating T cell immune response to the tumor cells [73]. ICIs, such as ipilimumab, nivolumab, pembrolizumab, and atezolizumab, have revolutionized the treatment landscape in various solid tumors. ICIs promote anti-tumor activity by enhancing T cell activation and preventing immune escape of tumor cells [74]. The role of ICIs in the management of AML is evolving, and various trials are ongoing to evaluate its efficacy. High expression of PD-1, PD-L1, and T-cell immunoglobulin mucin domain 3 (TIM3) and co-expression of PD-1/CTLA-4, PD-1/PD-L1, PD-1/LAG-3, and PD-L2/CTLA-4 are associated with poor prognosis in AML, particularly in patients with FLT3, RUNX1, and TET2 mutations [75,76,77]. High PD-1, PD-L1, and PD-L2 expression could potentially contribute to resistance to treatment with azacytidine [76]. However, a recent randomized phase II clinical trial of Azacitidine in combination with PD-L1 inhibitor (Durvalumab) in older patients (≥65 years) with AML failed to show clinical improvement, compared to azacitidine alone [78]. Of note is that in this study, the response to treatment was not associated with PD-L1 expression, DNA methylation, and mutational status. In a phase I/Ib clinical trial, the efficacy, and safety of ipilimumab were evaluated in patients with relapsed hematologic malignancies after allogeneic hematopoietic stem-cell transplantation (Allo-HSCT) [79]. Out of 28 patients enrolled, 12 were relapsed AML, and no response was observed in patients who received 3 mg/kg of ipilimumab. However, dose escalation to 10mg/kg demonstrated anti-tumor activity; CR was noted in 5 out of 12 relapsed AML patients (4 with extramedullary leukemia and 1 with secondary AML), with a durable response of more than 1 year in 3 patients. In another phase I clinical trial, PD-1 blockade (Nivolumab) was evaluated in patients with hematologic malignancies after Allo-HSCT [80]. Out of 28 patients enrolled in the clinical trial, 10 were AML. Only minimal response was observed in AML patients, and immune-related adverse events such as graft vs. host disease occurred even with lower doses of Nivolumab.
Ravandi et al. evaluated nivolumab in combination with Idarubicin and cytarabine in newly diagnosed AML patients. In this single-arm, phase 2 clinical trial, 44 patients were enrolled, of whom 17 (39%) were intermediate-risk AML based on ELN 2017 classification [77]. The median overall survival was 18.54 months. Overall, 19 patients had a response and subsequently underwent Allo-HSCT. Of note, the authors reported higher CD4+ T-cell co-expression of PD-1/TIM3 and PD-1/LAG-3 in non-responders compared to responders.

6.2. Monoclonal Antibodies and CAR-T Cell Therapy in AML

CD33 is highly expressed on AML cells, and unconjugated and conjugated CD33 monoclonal antibodies are in the early phase of drug development [81]. Current clinical trials targeting CD33 with GO (NCT03672539, NCT04207190, NCT03839446) are outlined in Table 4. For instance, lintuzumab Ac225, a radiolabeled anti-CD33 antibody, combined with chemotherapy, demonstrated a clinically acceptable safety profile [82]. A phase I/II study (NCT03441048) is underway to assess the safety and efficacy of this novel therapeutic agent in R/R AML. Flotetuzumab is a humanized bispecific antibody-based molecule binding to CD3 and CD123. Results from a phase 1/2 study (NCT02152956) demonstrated acceptable safety and evidence of anti-tumor activity in R/R AML patients [83]. A phase 2 study is ongoing to evaluate its efficacy in AML that has relapsed following allogeneic HSCT (NCT04582864).
Another active area of experimental drug development is CAR-T cell therapy [84]. In AML, targets such as CD33, CD123, CLL1, and CD44v6 are the most frequent (NCT04789408, NCT04219163, NCT03190278). Notably, commonly expressed CAR-T targets are also present in normal myeloid cells, leading to potential myelosuppression [81,85]. Newer generations of CAR-T cell products could potentially overcome these limitations. For instance, CD70 was recently identified as a promising target for CAR-T cell therapy in AML because of its selective expression on both leukemic blasts and leukemic stem cells [85], providing a rationale for targeted therapy in AML without adversely affecting normal hematopoiesis [86]. In a recent study, two CD70-CAR T constructs exhibited significant anti-tumor efficacy in vitro and in vivo [87], effectively eliminating AML cells and sparing normal hematopoietic stem cells, thereby avoiding potentially dangerous on-target/off-tumor toxicity.

7. Conclusions

AML is a disorder characterized by a puzzled molecular landscape. As a result, patients are characterized by different outcomes according to their individual genomic makeup, which, together with host factors such as age and performance status, contribute to the diverse therapeutic and survival scenarios. Intermediate-risk cases, as per ELN 2017, and more recently ELN 2022, represent the most heterogeneous group because of the broad features included in the definition of this category (or, better yet, the handful of characteristics used for the inclusion in the other two groups). While new genomic information is generating a more detailed dissection of the disease, as in the recent two classifications of myeloid disorders [71,72], an urgent need for a redefinition of diagnostic and prognostic criteria is vital for both better trial designing and adequate indications for new targeted treatments. Immunotherapies also offer potential opportunities, but this area needs further refinements and additional basic and translational studies in AML in general. Furthermore, the application of modern machine learning approaches with the current availability of genomic information and big data platforms will potentially unravel specific subgroups of patients, further contributing to identifying discrete differences in AML patients, particularly in the intermediate-risk group.
Perhaps, as our understanding of AML pathogenesis and risk-stratification modalities continues to improve, we anticipate that the intermediate-risk group definition will continue to change. In fact, the exponential growth in the targeted therapeutic options utilized in AML continues to alter the prognostic significance of many molecular derangements. Nonetheless, in harmony with the 2022 ELN guidelines, we recommend judicious incorporation of the patient’s fitness for the intensive regimens and disease molecular characteristics used as criteria for treatment selection.

Author Contributions

H.A. (Hassan Awada), M.K.M.A., B.T., H.A. (Hussein Awada), L.S., L.L., C.G. and A.K. collected the literature material and wrote the review; E.W. and M.R.B. designed the flow of the review and the content and wrote the review. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Arber, D.A.; Orazi, A.; Hasserjian, R.; Thiele, J.; Borowitz, M.J.; Le Beau, M.M.; Bloomfield, C.D.; Cazzola, M.; Vardiman, J.W. The 2016 revision to the World Health Organization classification of myeloid neoplasms and acute leukemia. Blood 2016, 127, 2391–2405. [Google Scholar] [CrossRef] [PubMed]
  2. Ferrara, F.; Barosi, G.; Venditti, A.; Angelucci, E.; Gobbi, M.; Pane, F.; Tosi, P.; Zinzani, P.; Tura, S. Consensus-based definition of unfitness to intensive and non-intensive chemotherapy in acute myeloid leukemia: A project of SIE, SIES and GITMO group on a new tool for therapy decision making. Leukemia 2013, 27, 997–999. [Google Scholar] [CrossRef] [PubMed]
  3. Gurnari, C.; Pagliuca, S.; Visconte, V. Deciphering the Therapeutic Resistance in Acute Myeloid Leukemia. Int. J. Mol. Sci. 2020, 21, 8505. [Google Scholar] [CrossRef] [PubMed]
  4. 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, 138, 1885–1895. [Google Scholar] [CrossRef]
  5. 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, 424–447. [Google Scholar] [CrossRef] [PubMed]
  6. Döhner, H.; Wei, A.H.; Appelbaum, F.R.; Craddock, C.; DiNardo, C.D.; Dombret, H.; Ebert, B.L.; Fenaux, P.; Godley, L.A.; Hasserjian, R.P.; et al. Diagnosis and Management of AML in Adults: 2022 ELN Recommendations from an International Expert Panel. Blood 2022, 129, 424–447. [Google Scholar] [CrossRef] [PubMed]
  7. Patel, J.P.; Gönen, M.; Figueroa, M.E.; Fernandez, H.; Sun, Z.; Racevskis, J.; Van Vlierberghe, P.; Dolgalev, I.; Thomas, S.; Aminova, O.; et al. Prognostic relevance of integrated genetic profiling in acute myeloid leukemia. N. Engl. J. Med. 2012, 366, 1079–1089. [Google Scholar] [CrossRef]
  8. Kayser, S.; Levis, M.J. Clinical implications of molecular markers in acute myeloid leukemia. Eur. J. Haematol. 2019, 102, 20–35. [Google Scholar] [CrossRef]
  9. Döhner, H.; Estey, E.H.; Amadori, S.; Appelbaum, F.R.; Büchner, T.; Burnett, A.K.; Dombret, H.; Fenaux, P.; Grimwade, D.; Larson, R.A.; et al. Diagnosis and management of acute myeloid leukemia in adults: Recommendations from an international expert panel, on behalf of the European LeukemiaNet. Blood 2010, 115, 453–474. [Google Scholar] [CrossRef]
  10. Ley, T.J.; Miller, C.; Ding, L.; Raphael, B.J.; Mungall, A.J.; Robertson, A.; Hoadley, K.; Triche, T.J., Jr.; Laird, P.W.; Baty, J.D.; et al. Genomic and epigenomic landscapes of adult de novo acute myeloid leukemia. N. Engl. J. Med. 2013, 368, 2059–2074. [Google Scholar] [CrossRef] [Green Version]
  11. Mardis, E.R.; Ding, L.; Dooling, D.J.; Larson, D.E.; McLellan, M.D.; Chen, K.; Koboldt, D.C.; Fulton, R.S.; Delehaunty, K.D.; McGrath, S.D.; et al. Recurring mutations found by sequencing an acute myeloid leukemia genome. N. Engl. J. Med. 2009, 361, 1058–1066. [Google Scholar] [CrossRef]
  12. Ley, T.J.; Ding, L.; Walter, M.J.; McLellan, M.D.; Lamprecht, T.; Larson, D.E.; Kandoth, C.; Payton, J.E.; Baty, J.; Welch, J.; et al. DNMT3A mutations in acute myeloid leukemia. N. Engl. J. Med. 2010, 363, 2424–2433. [Google Scholar] [CrossRef]
  13. Herold, T.; Rothenberg-Thurley, M.; Grunwald, V.V.; Janke, H.; Goerlich, D.; Sauerland, M.C.; Konstandin, N.P.; Dufour, A.; Schneider, S.; Neusser, M.; et al. Validation and refinement of the revised 2017 European LeukemiaNet genetic risk stratification of acute myeloid leukemia. Leukemia 2020, 34, 3161–3172. [Google Scholar] [CrossRef]
  14. Buccisano, F.; Maurillo, L.; Schuurhuis, G.J.; Del Principe, M.I.; Di Veroli, A.; Gurnari, C.; Venditti, A. The emerging role of measurable residual disease detection in AML in morphologic remission. Semin. Hematol. 2019, 56, 125–130. [Google Scholar] [CrossRef]
  15. Del Principe, M.I.; De Bellis, E.; Gurnari, C.; Buzzati, E.; Savi, A.; Consalvo, M.A.I.; Venditti, A. Applications and efficiency of flow cytometry for leukemia diagnostics. Expert Rev. Mol. Diagn. 2019, 19, 1089–1097. [Google Scholar] [CrossRef]
  16. Eisfeld, A.K.; Kohlschmidt, J.; Mims, A.; Nicolet, D.; Walker, C.J.; Blachly, J.S.; Carroll, A.J.; Papaioannou, D.; Kolitz, J.E.; Powell, B.E.; et al. Additional gene mutations may refine the 2017 European LeukemiaNet classification in adult patients with de novo acute myeloid leukemia aged <60 years. Leukemia 2020, 34, 3215–3227. [Google Scholar] [CrossRef]
  17. Döhner, H.; Weisdorf, D.J.; Bloomfield, C.D. Acute Myeloid Leukemia. N. Engl. J. Med. 2015, 373, 1136–1152. [Google Scholar] [CrossRef]
  18. Itzykson, R.; Fournier, E.; Berthon, C.; Röllig, C.; Braun, T.; Marceau-Renaut, A.; Pautas, C.; Nibourel, O.; Lemasle, E.; Micol, J.B.; et al. Genetic identification of patients with AML older than 60 years achieving long-term survival with intensive chemotherapy. Blood 2021, 138, 507–519. [Google Scholar] [CrossRef]
  19. Ossenkoppele, G.J.; Schuurhuis, G.J. MRD in AML: It is time to change the definition of remission. Best Pract. Res. Clin. Haematol. 2014, 27, 265–271. [Google Scholar] [CrossRef]
  20. Radakovich, N.; Cortese, M.; Nazha, A. Acute myeloid leukemia and artificial intelligence, algorithms and new scores. Best Pract. Res. Clin. Haematol. 2020, 33, 101192. [Google Scholar] [CrossRef]
  21. Fernandez, H.F.; Sun, Z.; Yao, X.; Litzow, M.R.; Luger, S.M.; Paietta, E.M.; Racevskis, J.; Dewald, G.W.; Ketterling, R.P.; Bennett, J.M.; et al. Anthracycline dose intensification in acute myeloid leukemia. N. Engl. J. Med. 2009, 361, 1249–1259. [Google Scholar] [CrossRef] [PubMed]
  22. Löwenberg, B.; Ossenkoppele, G.J.; van Putten, W.; Schouten, H.C.; Graux, C.; Ferrant, A.; Sonneveld, P.; Maertens, J.; Jongen-Lavrencic, M.; von Lilienfeld-Toal, M.; et al. High-dose daunorubicin in older patients with acute myeloid leukemia. N. Engl. J. Med. 2009, 361, 1235–1248. [Google Scholar] [CrossRef] [PubMed]
  23. Lee, J.H.; Joo, Y.D.; Kim, H.; Bae, S.H.; Kim, M.K.; Zang, D.Y.; Lee, J.L.; Lee, G.W.; Lee, J.H.; Park, J.H.; et al. A randomized trial comparing standard versus high-dose daunorubicin induction in patients with acute myeloid leukemia. Blood 2011, 118, 3832–3841. [Google Scholar] [CrossRef] [PubMed]
  24. Burnett, A.K.; Russell, N.H.; Hills, R.K.; Kell, J.; Freeman, S.; Kjeldsen, L.; Hunter, A.E.; Yin, J.; Craddock, C.F.; Dufva, I.H.; et al. Addition of gemtuzumab ozogamicin to induction chemotherapy improves survival in older patients with acute myeloid leukemia. J. Clin. Oncol. 2012, 30, 3924–3931. [Google Scholar] [CrossRef]
  25. 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]
  26. Fournier, E.; Duployez, N.; Ducourneau, B.; Raffoux, E.; Turlure, P.; Caillot, D.; Thomas, X.; Marceau-Renaut, A.; Chantepie, S.; Malfuson, J.V.; et al. Mutational profile and benefit of gemtuzumab ozogamicin in acute myeloid leukemia. Blood 2020, 135, 542–546. [Google Scholar] [CrossRef]
  27. Pollyea, D.A.; Bixby, D.; Perl, A.; Bhatt, V.R.; Altman, J.K.; Appelbaum, F.R.; de Lima, M.; Fathi, A.T.; Foran, J.M.; Gojo, I.; et al. NCCN Guidelines Insights: Acute Myeloid Leukemia, Version 2.2021. J. Natl. Compr. Cancer Netw. 2021, 19, 16–27. [Google Scholar] [CrossRef]
  28. Heuser, M.; Ofran, Y.; Boissel, N.; Brunet Mauri, S.; Craddock, C.; Janssen, J.; Wierzbowska, A.; Buske, C. Acute myeloid leukaemia in adult patients: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up. Ann. Oncol. 2020, 31, 697–712. [Google Scholar] [CrossRef]
  29. Mayer, R.J.; Davis, R.B.; Schiffer, C.A.; Berg, D.T.; Powell, B.L.; Schulman, P.; Omura, G.A.; Moore, J.O.; McIntyre, O.R.; Frei, E. Intensive Postremission Chemotherapy in Adults with Acute Myeloid Leukemia. N. Engl. J. Med. 1994, 331, 896–903. [Google Scholar] [CrossRef]
  30. Bloomfield, C.D.; Lawrence, D.; Byrd, J.C.; Carroll, A.; Pettenati, M.J.; Tantravahi, R.; Patil, S.R.; Davey, F.R.; Berg, D.T.; Schiffer, C.A.; et al. Frequency of prolonged remission duration after high-dose cytarabine intensification in acute myeloid leukemia varies by cytogenetic subtype. Cancer Res. 1998, 58, 4173–4179. [Google Scholar]
  31. Burnett, A.K.; Wheatley, K.; Goldstone, A.H.; Stevens, R.F.; Hann, I.M.; Rees, J.H.; Harrison, G. The value of allogeneic bone marrow transplant in patients with acute myeloid leukaemia at differing risk of relapse: Results of the UK MRC AML 10 trial. Br. J. Haematol. 2002, 118, 385–400. [Google Scholar] [CrossRef]
  32. Suciu, S.; Mandelli, F.; de Witte, T.; Zittoun, R.; Gallo, E.; Labar, B.; De Rosa, G.; Belhabri, A.; Giustolisi, R.; Delarue, R.; et al. Allogeneic compared with autologous stem cell transplantation in the treatment of patients younger than 46 years with acute myeloid leukemia (AML) in first complete remission (CR1): An intention-to-treat analysis of the EORTC/GIMEMAAML-10 trial. Blood 2003, 102, 1232–1240. [Google Scholar] [CrossRef]
  33. Röllig, C.; Bornhäuser, M.; Thiede, C.; Taube, F.; Kramer, M.; Mohr, B.; Aulitzky, W.; Bodenstein, H.; Tischler, H.-J.; Stuhlmann, R.; et al. Long-Term Prognosis of Acute Myeloid Leukemia According to the New Genetic Risk Classification of the European LeukemiaNet Recommendations: Evaluation of the Proposed Reporting System. J. Clin. Oncol. 2011, 29, 2758–2765. [Google Scholar] [CrossRef]
  34. Rücker, F.G.; Agrawal, M.; Corbacioglu, A.; Weber, D.; Kapp-Schwoerer, S.; Gaidzik, V.I.; Jahn, N.; Schroeder, T.; Wattad, M.; Lübbert, M.; et al. Measurable residual disease monitoring in acute myeloid leukemia with t(8;21)(q22;q22.1): Results from the AML Study Group. Blood 2019, 134, 1608–1618. [Google Scholar] [CrossRef]
  35. 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]
  36. Tobal, K.; Newton, J.; Macheta, M.; Chang, J.; Morgenstern, G.; Evans, P.A.; Morgan, G.; Lucas, G.S.; Liu Yin, J.A. Molecular quantitation of minimal residual disease in acute myeloid leukemia with t(8;21) can identify patients in durable remission and predict clinical relapse. Blood 2000, 95, 815–819. [Google Scholar] [CrossRef]
  37. Nucifora, G.; Larson, R.A.; Rowley, J.D. Persistence of the 8;21 translocation in patients with acute myeloid leukemia type M2 in long-term remission. Blood 1993, 82, 712–715. [Google Scholar] [CrossRef]
  38. Satake, N.; Maseki, N.; Kozu, T.; Sakashita, A.; Kobayashi, H.; Sakurai, M.; Ohki, M.; Kaneko, Y. Disappearance of AML1-MTG8(ETO) fusion transcript in acute myeloid leukaemia patients with t(8;21) in long-term remission. Br. J. Haematol. 1995, 91, 892–898. [Google Scholar] [CrossRef]
  39. Zhu, H.H.; Zhang, X.H.; Qin, Y.Z.; Liu, D.H.; Jiang, H.; Chen, H.; Jiang, Q.; Xu, L.P.; Lu, J.; Han, W.; et al. MRD-directed risk stratification treatment may improve outcomes of t(8;21) AML in the first complete remission: Results from the AML05 multicenter trial. Blood 2013, 121, 4056–4062. [Google Scholar] [CrossRef]
  40. Heuser, M.; Freeman, S.D.; Ossenkoppele, G.J.; Buccisano, F.; Hourigan, C.S.; Ngai, L.L.; Tettero, J.M.; Bachas, C.; Baer, C.; Béné, M.C.; et al. 2021 Update on MRD in acute myeloid leukemia: A consensus document from the European LeukemiaNet MRD Working Party. Blood 2021, 138, 2753–2767. [Google Scholar] [CrossRef]
  41. Venditti, A.; Piciocchi, A.; Candoni, A.; Melillo, L.; Calafiore, V.; Cairoli, R.; de Fabritiis, P.; Storti, G.; Salutari, P.; Lanza, F.; et al. GIMEMA AML1310 trial of risk-adapted, MRD-directed therapy for young adults with newly diagnosed acute myeloid leukemia. Blood 2019, 134, 935–945. [Google Scholar] [CrossRef]
  42. Buccisano, F.; Palmieri, R.; Piciocchi, A.; Arena, V.; Candoni, A.; Melillo, L.; Calafiore, V.; Cairoli, R.; De Fabritiis, P.; Storti, G.; et al. ELN2017 risk stratification improves outcome prediction when applied to the prospective GIMEMA AML1310 protocol. Blood Adv. 2021, 6, 2510–2516. [Google Scholar] [CrossRef]
  43. Huls, G.; Chitu, D.A.; Havelange, V.; Jongen-Lavrencic, M.; van de Loosdrecht, A.A.; Biemond, B.J.; Sinnige, H.; Hodossy, B.; Graux, C.; Kooy, R.v.M.; et al. Azacitidine maintenance after intensive chemotherapy improves DFS in older AML patients. Blood 2019, 133, 1457–1464. [Google Scholar] [CrossRef] [PubMed]
  44. Wei, A.H.; Döhner, H.; Pocock, C.; Montesinos, P.; Afanasyev, B.; Dombret, H.; Ravandi, F.; Sayar, H.; Jang, J.-H.; Porkka, K.; et al. Oral Azacitidine Maintenance Therapy for Acute Myeloid Leukemia in First Remission. N. Engl. J. Med. 2020, 383, 2526–2537. [Google Scholar] [CrossRef]
  45. Pautas, C.; Merabet, F.; Thomas, X.; Raffoux, E.; Gardin, C.; Corm, S.; Bourhis, J.H.; Reman, O.; Turlure, P.; Contentin, N.; et al. Randomized study of intensified anthracycline doses for induction and recombinant interleukin-2 for maintenance in patients with acute myeloid leukemia age 50 to 70 years: Results of the ALFA-9801 study. J. Clin. Oncol. 2010, 28, 808–814. [Google Scholar] [CrossRef]
  46. Castaigne, S.; Pautas, C.; Terré, C.; Raffoux, E.; Bordessoule, D.; Bastie, J.N.; Legrand, O.; Thomas, X.; Turlure, P.; Reman, O.; et al. Effect of gemtuzumab ozogamicin on survival of adult patients with de-novo acute myeloid leukaemia (ALFA-0701): A randomised, open-label, phase 3 study. Lancet 2012, 379, 1508–1516. [Google Scholar] [CrossRef]
  47. Burnett, A.K.; Russell, N.H.; Hills, R.K.; Hunter, A.E.; Kjeldsen, L.; Yin, J.; Gibson, B.E.; Wheatley, K.; Milligan, D. Optimization of chemotherapy for younger patients with acute myeloid leukemia: Results of the medical research council AML15 trial. J. Clin. Oncol. 2013, 31, 3360–3368. [Google Scholar] [CrossRef]
  48. Willemze, R.; Suciu, S.; Meloni, G.; Labar, B.; Marie, J.P.; Halkes, C.J.; Muus, P.; Mistrik, M.; Amadori, S.; Specchia, G.; et al. High-dose cytarabine in induction treatment improves the outcome of adult patients younger than age 46 years with acute myeloid leukemia: Results of the EORTC-GIMEMA AML-12 trial. J. Clin. Oncol. 2014, 32, 219–228. [Google Scholar] [CrossRef]
  49. Dombret, H.; Seymour, J.F.; Butrym, A.; Wierzbowska, A.; Selleslag, D.; Jang, J.H.; Kumar, R.; Cavenagh, J.; Schuh, A.C.; Candoni, A.; et al. International phase 3 study of azacitidine vs conventional care regimens in older patients with newly diagnosed AML with >30% blasts. Blood 2015, 126, 291–299. [Google Scholar] [CrossRef]
  50. Stone, R.M.; Mandrekar, S.J.; Sanford, B.L.; Laumann, K.; Geyer, S.; Bloomfield, C.D.; Thiede, C.; Prior, T.W.; Döhner, K.; Marcucci, G.; et al. Midostaurin plus Chemotherapy for Acute Myeloid Leukemia with a FLT3 Mutation. N. Engl. J. Med. 2017, 377, 454–464. [Google Scholar] [CrossRef]
  51. Amadori, S.; Suciu, S.; Selleslag, D.; Aversa, F.; Gaidano, G.; Musso, M.; Annino, L.; Venditti, A.; Voso, M.T.; Mazzone, C.; et al. Gemtuzumab Ozogamicin Versus Best Supportive Care in Older Patients with Newly Diagnosed Acute Myeloid Leukemia Unsuitable for Intensive Chemotherapy: Results of the Randomized Phase III EORTC-GIMEMA AML-19 Trial. J. Clin. Oncol. 2016, 34, 972–979. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  52. Welch, J.S.; Petti, A.A.; Miller, C.A.; Fronick, C.C.; O’Laughlin, M.; Fulton, R.S.; Wilson, R.K.; Baty, J.D.; Duncavage, E.J.; Tandon, B.; et al. TP53 and Decitabine in Acute Myeloid Leukemia and Myelodysplastic Syndromes. N. Engl. J. Med. 2016, 375, 2023–2036. [Google Scholar] [CrossRef] [PubMed]
  53. Ohanian, M.; Garcia-Manero, G.; Levis, M.; Jabbour, E.; Daver, N.; Borthakur, G.; Kadia, T.; Pierce, S.; Burger, J.; Richie, M.A.; et al. Sorafenib Combined with 5-azacytidine in Older Patients with Untreated FLT3-ITD Mutated Acute Myeloid Leukemia. Am. J. Hematol. 2018, 93, 1136–1141. [Google Scholar] [CrossRef] [PubMed]
  54. Cortes, J.E.; Heidel, F.H.; Hellmann, A.; Fiedler, W.; Smith, B.D.; Robak, T.; Montesinos, P.; Pollyea, D.A.; DesJardins, P.; Ottmann, O.; et al. Randomized comparison of low dose cytarabine with or without glasdegib in patients with newly diagnosed acute myeloid leukemia or high-risk myelodysplastic syndrome. Leukemia 2019, 33, 379–389. [Google Scholar] [CrossRef]
  55. Pollyea, D.A.; Tallman, M.S.; de Botton, S.; Kantarjian, H.M.; Collins, R.; Stein, A.S.; Frattini, M.G.; Xu, Q.; Tosolini, A.; See, W.L.; et al. Enasidenib, an inhibitor of mutant IDH2 proteins, induces durable remissions in older patients with newly diagnosed acute myeloid leukemia. Leukemia 2019, 33, 2575–2584. [Google Scholar] [CrossRef]
  56. DiNardo, C.D.; Jonas, B.A.; Pullarkat, V.; Thirman, M.J.; Garcia, J.S.; Wei, A.H.; Konopleva, M.; Döhner, H.; Letai, A.; Fenaux, P.; et al. Azacitidine and Venetoclax in Previously Untreated Acute Myeloid Leukemia. N. Engl. J. Med. 2020, 383, 617–629. [Google Scholar] [CrossRef]
  57. Roboz, G.J.; DiNardo, C.D.; Stein, E.M.; de Botton, S.; Mims, A.S.; Prince, G.T.; Altman, J.K.; Arellano, M.L.; Donnellan, W.; Erba, H.P.; et al. Ivosidenib induces deep durable remissions in patients with newly diagnosed IDH1-mutant acute myeloid leukemia. Blood 2020, 135, 463–471. [Google Scholar] [CrossRef]
  58. Montesinos, P.; Recher, C.; Vives, S.; Zarzycka, E.; Wang, J.; Bertani, G.; Heuser, M.; Calado, R.T.; Schuh, A.C.; Yeh, S.-P.; et al. Ivosidenib and Azacitidine in IDH1-Mutated Acute Myeloid Leukemia. N. Engl. J. Med. 2022, 386, 1519–1531. [Google Scholar] [CrossRef]
  59. Gurnari, C.; Voso, M.T.; Maciejewski, J.P.; Visconte, V. From Bench to Bedside and Beyond: Therapeutic Scenario in Acute Myeloid Leukemia. Cancers 2020, 12, 357. [Google Scholar] [CrossRef]
  60. Döhner, K.; Thiede, C.; Jahn, N.; Panina, E.; Gambietz, A.; Larson, R.A.; Prior, T.W.; Marcucci, G.; Jones, D.; Krauter, J.; et al. Impact of NPM1/FLT3-ITD genotypes defined by the 2017 European LeukemiaNet in patients with acute myeloid leukemia. Blood 2020, 135, 371–380. [Google Scholar] [CrossRef]
  61. Papaemmanuil, E.; Gerstung, M.; Bullinger, L.; Gaidzik, V.I.; Paschka, P.; Roberts, N.D.; Potter, N.E.; Heuser, M.; Thol, F.; Bolli, N.; et al. Genomic Classification and Prognosis in Acute Myeloid Leukemia. N. Engl. J. Med. 2016, 374, 2209–2221. [Google Scholar] [CrossRef]
  62. Perl, A.E.; Martinelli, G.; Cortes, J.E.; Neubauer, A.; Berman, E.; Paolini, S.; Montesinos, P.; Baer, M.R.; Larson, R.A.; Ustun, C.; et al. Gilteritinib or Chemotherapy for Relapsed or Refractory FLT3-Mutated AML. N. Engl. J. Med. 2019, 381, 1728–1740. [Google Scholar] [CrossRef]
  63. DiNardo, C.D.; Pratz, K.; Pullarkat, V.; Jonas, B.A.; Arellano, M.; Becker, P.S.; Frankfurt, O.; Konopleva, M.; Wei, A.H.; Kantarjian, H.M.; et al. Venetoclax combined with decitabine or azacitidine in treatment-naive, elderly patients with acute myeloid leukemia. Blood 2019, 133, 7–17. [Google Scholar] [CrossRef]
  64. DiNardo, C.D.; Stein, E.M.; de Botton, S.; Roboz, G.J.; Altman, J.K.; Mims, A.S.; Swords, R.; Collins, R.H.; Mannis, G.N.; Pollyea, D.A.; et al. Durable Remissions with Ivosidenib in IDH1-Mutated Relapsed or Refractory AML. N. Engl. J. Med. 2018, 378, 2386–2398. [Google Scholar] [CrossRef]
  65. Stein, E.M.; DiNardo, C.D.; Pollyea, D.A.; Fathi, A.T.; Roboz, G.J.; Altman, J.K.; Stone, R.M.; DeAngelo, D.J.; Levine, R.L.; Flinn, I.W.; et al. Enasidenib in mutant IDH2 relapsed or refractory acute myeloid leukemia. Blood 2017, 130, 722–731. [Google Scholar] [CrossRef]
  66. DiNardo, C.D.; Schuh, A.C.; Stein, E.M.; Montesinos, P.; Wei, A.H.; de Botton, S.; Zeidan, A.M.; Fathi, A.T.; Kantarjian, H.M.; Bennett, J.M.; et al. Enasidenib plus azacitidine versus azacitidine alone in patients with newly diagnosed, mutant-IDH2 acute myeloid leukaemia (AG221-AML-005): A single-arm, phase 1b and randomised, phase 2 trial. Lancet Oncol. 2021, 22, 1597–1608. [Google Scholar] [CrossRef]
  67. DiNardo, C.D.; Montesinos, P.; Schuh, A.C.; Papayannidis, C.; Vyas, P.; Wei, A.H.; Zeidan, A.M.; Bluemmert, I.; Yu, X.; Hasan, M.; et al. Outcomes for Patients with Late-Stage Mutant-IDH2 (m IDH2) Relapsed/Refractory Acute Myeloid Leukemia (R/R AML) Treated with Enasidenib Vs Other Lower-Intensity Therapies in the Randomized, Phase 3 IDHentify Trial. Blood 2021, 138, 1243. [Google Scholar] [CrossRef]
  68. Giri, B.; Gupta, V.K.; Yaffe, B.; Modi, S.; Roy, P.; Sethi, V.; Lavania, S.P.; Vickers, S.M.; Dudeja, V.; Banerjee, S.; et al. Preclinical evaluation of Minnelide as a therapy for acute myeloid leukemia. J. Transl. Med. 2019, 17, 163. [Google Scholar] [CrossRef]
  69. Kayser, S.; Levis, M.J. Advances in targeted therapy for acute myeloid leukaemia. Br. J. Haematol. 2018, 180, 484–500. [Google Scholar] [CrossRef]
  70. Perl, A.E. The role of targeted therapy in the management of patients with AML. Hematol. Am. Soc. Hematol. Educ. Program 2017, 2017, 54–65. [Google Scholar] [CrossRef]
  71. Khoury, J.D.; Solary, E.; Abla, O.; Akkari, Y.; Alaggio, R.; Apperley, J.F.; Bejar, R.; Berti, E.; Busque, L.; Chan, J.K.C.; et al. The 5th edition of the World Health Organization Classification of Haematolymphoid Tumours: Myeloid and Histiocytic/Dendritic Neoplasms. Leukemia 2022, 36, 1703–1719. [Google Scholar] [CrossRef] [PubMed]
  72. Arber, D.A.; Orazi, A.; Hasserjian, R.P.; Borowitz, M.J.; Calvo, K.R.; Kvasnicka, H.M.; Wang, S.A.; Bagg, A.; Barbui, T.; Branford, S.; et al. International Consensus Classification of Myeloid Neoplasms and Acute Leukemia: Integrating Morphological, Clinical, and Genomic Data. Blood 2022. [Google Scholar] [CrossRef] [PubMed]
  73. Han, Y.; Liu, D.; Li, L. PD-1/PD-L1 pathway: Current researches in cancer. Am. J. Cancer Res. 2020, 10, 727–742. [Google Scholar] [PubMed]
  74. Seidel, J.A.; Otsuka, A.; Kabashima, K. Anti-PD-1 and Anti-CTLA-4 Therapies in Cancer: Mechanisms of Action, Efficacy, and Limitations. Front. Oncol. 2018, 8, 86. [Google Scholar] [CrossRef]
  75. Huang, J.; Tan, J.; Chen, Y.; Huang, S.; Xu, L.; Zhang, Y.; Lu, Y.; Yu, Z.; Chen, S.; Li, Y. A skewed distribution and increased PD-1+Vβ+CD4+/CD8+ T cells in patients with acute myeloid leukemia. J. Leukoc. Biol. 2019, 106, 725–732. [Google Scholar] [CrossRef]
  76. Chen, C.; Liang, C.; Wang, S.; Chio, C.L.; Zhang, Y.; Zeng, C.; Chen, S.; Wang, C.; Li, Y. Expression patterns of immune checkpoints in acute myeloid leukemia. J. Hematol. Oncol. 2020, 13, 28. [Google Scholar] [CrossRef]
  77. Ravandi, F.; Assi, R.; Daver, N.; Benton, C.B.; Kadia, T.; Thompson, P.A.; Borthakur, G.; Alvarado, Y.; Jabbour, E.J.; Konopleva, M.; et al. Idarubicin, cytarabine, and nivolumab in patients with newly diagnosed acute myeloid leukaemia or high-risk myelodysplastic syndrome: A single-arm, phase 2 study. Lancet Haematol. 2019, 6, e480–e488. [Google Scholar] [CrossRef]
  78. Zeidan, A.M.; Boss, I.; Beach, C.L.; Copeland, W.B.; Thompson, E.; Fox, B.A.; Hasle, V.E.; Hellmann, A.; Taussig, D.C.; Tormo, M.; et al. A randomized phase 2 trial of azacitidine with or without durvalumab as first-line therapy for older patients with AML. Blood Adv. 2022, 6, 2219–2229. [Google Scholar] [CrossRef]
  79. Davids, M.S.; Kim, H.T.; Bachireddy, P.; Costello, C.; Liguori, R.; Savell, A.; Lukez, A.P.; Avigan, D.; Chen, Y.B.; McSweeney, P.; et al. Ipilimumab for Patients with Relapse after Allogeneic Transplantation. N. Engl. J. Med. 2016, 375, 143–153. [Google Scholar] [CrossRef]
  80. Davids, M.S.; Kim, H.T.; Costello, C.; Herrera, A.F.; Locke, F.L.; Maegawa, R.O.; Savell, A.; Mazzeo, M.; Anderson, A.; Boardman, A.P.; et al. A multicenter phase 1 study of nivolumab for relapsed hematologic malignancies after allogeneic transplantation. Blood 2020, 135, 2182–2191. [Google Scholar] [CrossRef]
  81. Isidori, A.; Cerchione, C.; Daver, N.; DiNardo, C.; Garcia-Manero, G.; Konopleva, M.; Jabbour, E.; Ravandi, F.; Kadia, T.; Burguera, A.F.; et al. Immunotherapy in Acute Myeloid Leukemia: Where We Stand. Front. Oncol. 2021, 11, 656218. [Google Scholar] [CrossRef]
  82. Abedin, S.; Guru Murthy, G.S.; Runaas, L.; Michaelis, L.C.; Atallah, E.L.; Hamadani, M.; Harrington, A.M.; Carlson, K. Lintuzumab Ac-225 in Combination with CLAG-M Chemotherapy in Relapsed/Refractory AML: Interim Results of a Phase I Study. Blood 2019, 134, 2605. [Google Scholar] [CrossRef]
  83. Uy, G.L.; Aldoss, I.; Foster, M.C.; Sayre, P.H.; Wieduwilt, M.J.; Advani, A.S.; Godwin, J.E.; Arellano, M.L.; Sweet, K.L.; Emadi, A.; et al. Flotetuzumab as salvage immunotherapy for refractory acute myeloid leukemia. Blood 2021, 137, 751–762. [Google Scholar] [CrossRef]
  84. Gill, S.I. How close are we to CAR T-cell therapy for AML? Best Pract. Res. Clin. Haematol. 2019, 32, 101104. [Google Scholar] [CrossRef]
  85. Nguyen, D.H.; Ball, E.D.; Varki, A. Myeloid precursors and acute myeloid leukemia cells express multiple CD33-related Siglecs. Exp. Hematol. 2006, 34, 728–735. [Google Scholar] [CrossRef]
  86. Riether, C.; Pabst, T.; Höpner, S.; Bacher, U.; Hinterbrandner, M.; Banz, Y.; Müller, R.; Manz, M.G.; Gharib, W.H.; Francisco, D.; et al. Targeting CD70 with cusatuzumab eliminates acute myeloid leukemia stem cells in patients treated with hypomethylating agents. Nat. Med. 2020, 26, 1459–1467. [Google Scholar] [CrossRef]
  87. Sauer, T.; Parikh, K.; Sharma, S.; Omer, B.; Sedloev, D.; Chen, Q.; Angenendt, L.; Schliemann, C.; Schmitt, M.; Müller-Tidow, C.; et al. CD70-specific CAR T cells have potent activity against acute myeloid leukemia without HSC toxicity. Blood 2021, 138, 318–330. [Google Scholar] [CrossRef]
Cancers 14 04166 g001 550
Figure 1. The clinical problem of intermediate-risk AML. The upper panel summarizes features responsible for molecular heterogeneity, and host-related outcome modifiers are summarized. In the lower panel, current research approaches to ameliorating the outcomes of such patients are illustrated. Specifically, the application of genome scanning techniques and machine learning methods may help better characterize AML populations to assess geno-phenotypic associations and identify therapeutic vulnerabilities.
Figure 1. The clinical problem of intermediate-risk AML. The upper panel summarizes features responsible for molecular heterogeneity, and host-related outcome modifiers are summarized. In the lower panel, current research approaches to ameliorating the outcomes of such patients are illustrated. Specifically, the application of genome scanning techniques and machine learning methods may help better characterize AML populations to assess geno-phenotypic associations and identify therapeutic vulnerabilities.
Cancers 14 04166 g001
Table
Table 1. 2017 ELN intermediate-risk stratification by genetics. Adapted from [5].
Table 1. 2017 ELN intermediate-risk stratification by genetics. Adapted from [5].
Intermediate-risk categoryMutated NPM1 and FLT3-ITDhigh †
Wild-type NPM1 without FLT3-ITD or with FLT3-ITDlow † (without adverse-risk genetic lesions)
t(9;11)(p21.3;q23.3); MLLT3-KMT2A ‡
Cytogenetic abnormalities not classified as favorable or adverse
† Low, low allelic ratio (<0.5); high, high allelic ratio (≥0.5). ‡ The presence of t(9;11)(p21.3;q23.3) takes precedence over rare, concurrent adverse.
Table
Table 2. 2022 European LeukemiaNet (ELN) risk classification by genetics at initial diagnosis. Adapted from [6].
Table 2. 2022 European LeukemiaNet (ELN) risk classification by genetics at initial diagnosis. Adapted from [6].
Intermediate-risk categoryMutated NPM1 †‡ with FLT3-ITD
Wild-type NPM1 with FLT3-ITD
t(9;11)(p21.3;q23.3)/MLLT3::KMT2A *†
Cytogenetic and/or molecular abnormalities not classified as favorable or adverse
† Mainly based on results observed in intensively treated patients. Initial risk assignment may change during the treatment course, based on the results from analyses of measurable residual disease. ‡ AML with NPM1 mutation and adverse-risk cytogenetic abnormalities are categorized as adverse-risk. * The presence of t(9;11)(p21.3;q23.3) takes precedence over rare, concurrent adverse-risk gene mutations.
Table
Table 3. Major therapeutic regimens and associated trials suggested in NCCN guidelines for intermediate-risk AML.
Table 3. Major therapeutic regimens and associated trials suggested in NCCN guidelines for intermediate-risk AML.
Drug/RegimenTrial/YearAML-Specific FDA ApprovalDesign/SettingStudy PopulationExperimental ArmComparison RegimenAge Group and CharacteristicsRisk GroupPertinent FindingRemarks
Newly Diagnosed AML-Induction-Eligible
7 + 3 RegimenFernandez [23]/2009Daunorubicin: remission induction in AML (myelogenous, monocytic, erythroid) in adults.Multi-institutional, randomized, open-label trialDe novo or secondary AML.Induction: daunorubicin 60 mg/m2 IV days 1–3 with Ara-C 100 mg/m2 continuous IV infusion days 1–7.Induction: daunorubicin 45 mg/m2 IV days 1–3 with Ara-C 100 mg/m2 continuous IV infusion days 1–7.17–60 yearsNo risk groups excludedHR for death in the high-dose daunorubicin group 0.74 (p < 0.05). Improved OS (HR 0.8, p = 0.02) in intermediate-risk with high-dose daunorubicin.Risk classification was based on the 2000 SWOG/ECOG classification.
7 + 3 RegimenPautas [45]/2010Idarubicin: indicated for the treatment of AML in adults.Multi-institutional, randomized, open-label trialde novo AMLInduction daunorubicin 80 mg/m2 IV days 1–3 with Ara-C 200 mg/m2 IV continuous infusion days 1–7.Induction Idarubicin 12 mg/m2 IV days 1–3 or 1–4 with Ara-C 200 mg/m2 continuous IV infusion days 1–7.50–70 yearsNo risk groups excludedCR rate 83% with idarubicin Days 1–3, 78% with idarubicin Days 1–4, and 70% with daunorubicin. No difference in OS, EFS or relapse incidence.
7 + 3 +GO RegimenCastaigne [46]/2012Gemtuzumab ozogamicin: newly diagnosed AML, CD33+.Multi-institutional, randomized, open-label trialDe novo AML, CD33+.Induction daunorubicin and Ara-C with gemtuzumab ozogamicin 3 mg/m2 days 1, 4, 7. Similar regimen in consolidation.Induction daunorubicin and Ara-C.50–70 yearsNo risk groups excludedTwo-year HR of EFS was 0.56 (p < 0.01), and HR for OS was 0.58 (p < 0.05) for 7 + 3 + GO. Combined favorable and intermediate cytogenetic groups showed improved outcomes with gemtuzumab (HR 0.5, p = 0.08).In follow-up study, 7 + 3 + GO improved EFS (HR: 0.66, p < 0.05) but not OS (0.81, p = 0.16) [27]. Risk classification was based on ISCN.
FLAG-Ida RegimenBurnett [47]/2013Fludarabine: NAMulti-institutional, randomized, open-label trialDe novo or secondary AML.Fludarabine 30 mg/m2 IV days 2–6, Ara-C 2 g/m2 days 2–6, G-CSF SC daily days 1–7, idarubicin 8 mg/m2 IV days 4–6.Induction daunorubicin plus Ara-C with or without etoposide/gemtuzumab ozogamicin. Variables doses and schedules were used.No age restrictionNo risk groups excludedCR rate 81% in ADE vs. 84% in FLAG-Ida (p = 0.2). No difference in 30- or 60-day mortality. Intermediate-risk cytogenetics had a lower relapse rate (OR 0.79, CI: 0.63–0.98) with FLAG-IDA.Risk classification was based on MRC AML 10 Trial (15).
ADE RegimenWillemze [48]/2013Cytarabine Injection in combination with other approved drugs is indicated for remission induction in AML in adults.Multi-institutional, randomized, open-label trialDe novo or secondary AML.Daunorubicin 50 mg/m2 IV days 1, 3, 5 plus etoposide 50 mg/m2 days 1–5 plus Ara-C 3000 mg/m2 every 12 h IV infusion days 1, 3, 5, 7.Daunorubicin 50 mg/m2 IV on days 1, 3, 5 plus etoposide 50 mg/m2 days 1–5 plus 10 days of Ara-C 100 mg/m2 as continuous IV infusion.15–60 yearsNo risk groups excluded6-year OS in high dose Ara-C, and the standard dose was 42.5% and 38.7% (p = 0.06). Subgroup analysis showed improved OS with high dose Ara-C in intermediate-risk (HR: 0.88, CI: 0.64–1.21).In patients < 46 years, high-dose Ara-C was associated with improved 6-year OS (51.9% vs. 43.3%, p < 0.05). Intermediate-risk was defined as a normal karyotype or absence of low- and high-risk cytogenetics and of FLT3-ITD.
AzacitidineDombret [49]/2015NAMulti-institutional, randomized, open-label trialDe novo or secondary AML from MDS with >30% BM blasts who are not considered eligible for hematopoietic stem cell transplantation.Azacitidine 75 mg/m2 SC daily for 7 consecutive days per 28-day treatment cycleInvestigators chose protocol-designated conventional care regimens (best supportive care, low-dose ara-c, or standard induction chemotherapy).≥65 yearsIntermediate- or poor-risk cytogeneticsMedian OS 10.4 mos in azacitidine arm was vs. 6.5 mos in comparison arm (p = 0.1).Outcomes with intermediate-risk cytogenetics were not statistically significant (HR: 0.9, p = 0.4). Risk classification was based on 2009 NCCN guidelines.
7 + 3 + Midostaurin RegimenStone [50]/2017Midostaurin: newly diagnosed AML with FLT3 mutation in combination with Ara-C and daunorubicin induction and Ara-C consolidation.Multi-institutional, randomized, double-blind placebo-controlled trialFLT3-ITD and TKD mutated. Not therapy-related.Induction daunorubicin 60 mg/m2 IV days 1,2,3 with Ara-C 200 mg/m2 IV continuous infusion days 1–7 with midostaurin 50 mg orally twice daily, days 8–21.Same but with placebo instead of midostaurin.18–59 yearsNo risk groups excludedHR for death in midostaurin group was 0.78 (p < 0.05). Subgroup analysis not statistically significant.The trial was stratified to high (>0.7) vs. low (0.05–0.7) ITD or TKD allelic ratio.
Newly Diagnosed AML-Induction-Ineligible
GOAmadori [51]/2016Gemtuzumab ozogamicin: newly diagnosed CD33-positive AML.Multi-institutional, randomized, open-label trialCD33+.Gemtuzumab ozogamicin 6 mg/m2, Day 1, 3 mg/m2 Day?Best supportive care.>75 years or ≤75 years with WHO PS > 2No risk groups excludedHR for OS was 0.69 (p < 0.05). Subgroup analysis of combined favorable and intermediate cytogenetics showed improved outcomes with gemtuzumab (HR 0.52, p < 0.05).Improvement in OS only seen with >80% CD33+ blasts.
DecitabineWelch [52]/2016NASingle-institution, prospective, single-armNewly diagnosed or relapsed AML and MDS.Decitabine 20 mg/m2 days 1–10 of 28-day cycles.-≥60 yearsNo risk groups excludedORR 46%. Median OS of favorable/intermediate-risk 10 mos.Intermediate-risk cytogenetics in 5% of TP53 mutated, 69% of TP53 wild-type and 65% of TP53 untested.
HMA + SorafenibOhanian [53]/2018Not approved.Phase II, multi-institutional, open-label trialUntreated patients with FLT3 mutated AML unfit for standard chemotherapy.Azacitidine 75 mg/m2 daily × 7 days and sorafenib 400 mg twice daily.NA≥60 yearsNo risk groups excludedORR 78%. Median OS 8.3 mos (range: 1–63).63% of patients had a normal karyotype, 7% had a complex karyotype, and 15% had other karyotypic changes.
Low-dose Ara-C + GlasdegibCortes [54]/2019Glasdegib: indicated in combination with low-dose Ara-C to treat newly diagnosed AML in adult patients ≥ 75 years old or with comorbidities that preclude the use of intensive induction chemotherapy.Phase II, multi-institutional, randomized, open-label trialPreviously untreated AML or high-risk MDS unfit for intensive chemotherapy.Glasdegib 100 mg orally QD continuously in 28-day cycles plus Ara-C 20 mg SC BID for 10 of 28 days.Ara-C 20 mg SC BID for 10 per 28 days.≥55 yearsNo risk groups excludedMedian OS 8.8 months in glasdegib group vs. 4.9 months in comparison group (p < 0.05).Benefits mainly seen in good/intermediate groups combined (12.2 vs. 4.8 months, p < 0.05) but not in high-risk group (4.7 vs. 4.9, p = 0.06).
EnasidenibPollyea [55]/2019Not FDA-approved.Phase I, multi-institutional, open-label trialPreviously untreated IDH2-mutated AML unfit for standard AML treatments.Enasedinib 100 mg orally once daily.NA≥18 yearsNo risk groups excludedORR 30.8%. Median OS 11.3 mos (CI: 5.7–15.1).49% had intermediate-risk cytogenetics.
Azacitidne + VenetoclaxDiNardo [56]/2020Venetoclax: it is approved in combination with azacitidine or decitabine, or low-dose cytarabine for the treatment of newly-diagnosed AML in adults 75 years or older or with comorbidities that preclude intensive induction chemotherapy. Accelerated approval.Multi-institutional randomized, double-blind placebo-controlled trialIneligible for standard induction therapy due to coexisting conditions or age 75 years. Excluded patients with previous MPN or MDS treated with a hypomethylating agent.Azacitidine 75 mg/m2 SC or IV days 1–7 every 28-days plus venetoclax with a target dose of 400 mg daily.Azacitidine 75 mg/m2 SC or IV days 1–7 every 28-day cycle plus placebo.≥18 yearsExcluded patients with favorable-risk cytogeneticsMedian OS in venetoclax group was 14.7 vs. 9.6 mos in the comparison (p < 0.05).Statistically significant benefit in patients with intermediate-risk cytogenetics (HR 0.57, CI: 0.41–0.79) but not in high-risk group (HR: 0.78, CIL 0.54–1.12). Cytogenetics risk classification was based on the 2016 NCCN classification.
IvosidenibRoboz [57]/2020Adult patients with newly-diagnosed AML ≥ 75 years old or with comorbidities that preclude intensive induction chemotherapy.Phase I, multi-institutional, open-label trialIDH1-mutated AML.Ivosidenib 500 mg daily.NA≥18 yearsNo risk groups excludedORR 42.4%. Median OS 12.6 mos (CI: 4.5–25.7).71% had intermediate-risk cytogenetics.
Ivosidenib + AzacitidineMontesinos [58]Adult patients with newly diagnosed IDH1-mutated uneligible for intensive treatment.Phase 3, multi-institutional, double-blind, randomized trialIDH1-mutated AML.Ivosidenib (500 mg once daily) plus Azacitidine 75 mg/m2 daily × 28-day cycle.Azacitidine 75 mg/m2 daily × 28-day cycle.≥18 yearsNo risk groups excludedMedian OS was 24.0 months with experimental combination and 7.9 months with placebo and azacitidine (p = 0.001).Similar toxicity profiles if expecting differentiation syndrome, higher in the experimental arm.
Abbreviations: CR = complete remission; ORR = overall response rate; EFS = event-free survival; OS = overall survival; HR = hazard ratio; mos = months; AML = acute myeloid leukemia; MDS = myelodysplastic syndromes; MRC-AML = acute myeloid leukemia with myelodysplasia-related changes; ITD = internal tandem duplication; TKD = tyrosine kinase domain; ISCN = International System for Human Cytogenetic Nomenclature; Ara-C = cytarabine; GO = gemtuzumab ozogamicin; FLAG = fludarabine, cytarabine, and filgrastim; Ida = idarubicin; ADE = cytarabine, daunorubicin hydrochloride, and etoposide phosphate; HMA = hypomethylating agents; SC = subcutaneously; BID = twice daily; NA = not applicable or not available.
Table
Table 4. List of ongoing clinical trials including patients with newly diagnosed or relapsed/refractory intermediate-risk AML in the United States.
Table 4. List of ongoing clinical trials including patients with newly diagnosed or relapsed/refractory intermediate-risk AML in the United States.
Clinical Trial IdentifierName of StudyDesign/PhaseAge Eligibility (Years)Disease CharacteristicsStudy Start Date
NCT02152956Flotetuzumab in Primary Induction Failure (PIF) or Early Relapse (ER) AMLMulticenter, phase ½, open-label>18R/R AMLJune 2014
NCT02397720Nivolumab and Azacitidine with or without Ipilimumab in Treating Patients with R/R or Newly Diagnosed AMLPhase 2, open-label study>18R/R AMLApril 2015
NCT03190278Study Evaluating Safety and Efficacy of UCART123 in Patients with R/R AML (AMELI-01)Phase 1, open-label 18–65R/R AML with >5% bone marrow blasts, CD123+June 2017
NCT03067571Daratumumab in Treating Patients with R/R AML or High-Risk MDSPhase 2, open-label study>18R/R AMLOctober 2017
NCT03390296OX40, Venetoclax, Avelumab, Glasdegib, Gemtuzumab Ozogamicin, and Azacitidine in Treating Patients with R/R AMLPhase 1b/2, open-label multi-arm study>18R/R AMLJanuary 2018
NCT03504410Study Evaluating Efficacy and Safety of CPI-613 in Combination with HD Cytarabine and Mitoxantrone Compared to HD Cytarabine and Mitoxantrone and Control Sub-groups: MEC and FLAG in Older Patients With R/R AMLMulticenter, phase 3, open-label, randomized study>50R/R AMLApril 2018
NCT03672539Liposome-encapsulated Daunorubicin-Cytarabine and Gemtuzumab Ozogamicin in Treating Patients with R/R AML or High-Risk MDSPhase 2, open-label study>18CD33+ (≥3%), R/R AMLDecember 2018
NCT03839446Phase II Study of the Combination of Mitoxantrone, Etoposide and Gemtuzumab Ozogamicin (MEGO) for Patients with AML refractory to Initial Standard Induction TherapyPhase 2, open-label, single-arm study18–75R/R AML with CD33 expression in ≥30% of leukemic blasts on the bone marrowFebruary 2019
NCT03760523Dose Escalation Study of Minnelide in R/R AMLPhase 1, dose-escalation study>18R/R AML ineligible for intensive chemotherapy April 2019
NCT04219163Chimeric Antigen Receptor T-cells for The Treatment of AML Expressing CLL-1 AntigenPhase 1, open-label≤75R/R AML, at least 30% CLL-1+ blastsJuly 2020
NCT04207190Talazoparib and Gemtuzumab Ozogamicin for the Treatment of CD33 Positive R/R AMLPhase 1, open-label study>18CD33+ R/R AML with evidence of ≥5% myeloblasts in the bone marrow, peripheral blood, or in an extramedullary site by pathologyJuly 2020
NCT04278768Dose Escalation/Expansion Trial of CA-4948 as Monotherapy and in Combination with Azacitidine or Venetoclax in Patients with AML or MDSPhase 1/2, open-label>18AML (primary or secondary, including treatment-related) after failing at least 1 standard treatmentJuly 2020
NCT04435691Magrolimab, Azacitidine, and Venetoclax for the Treatment of AMLPhase 1b/2, open-label study>18R/R AMLJuly 2020
NCT04659616Pemigatinib after Chemotherapy for the Treatment of Newly Diagnosed AMLMulticenter, phase 1, open-label study>18Adverse- or intermediate-risk newly diagnosed AMLJanuary 2021
NCT04666649Pegcrisantaspase in Combination with Venetoclax for Treatment of R/R AMLPhase 1, open-label >18R/R AMLMarch 2021
NCT04669067TL-895 and KRT-232 Study in AMLMulticenter, phase 1b/2, open-label>18FLT3-ITD or TKD mutation, TP53 wild-type, R/R AML, at least one prior therapy, including a FLT-3 inhibitorMarch 2021
NCT04752163DS-1594b with or without Azacitidine, Venetoclax, or Mini-HCVD for the Treatment of R/R AML or ALLPhase 1b/2, open-label multi-arm study>18R/R AML or R/R ALL subjects with an MLLr or NPM1mMarch 2021
NCT04582864Flotetuzumab for relapsed AML and MDS Following Allo-HCTPhase 2, open-label >18Relapsed AMLMay 2021
NCT04789408Study Evaluating the Safety of KITE-222 in Participants with R/R AMLMulticenter, phase 1, open-label>18R/R AMLJuly 2021
NCT05010122ASTX727, Venetoclax, and Gilteritinib for the Treatment of Newly Diagnosed, R/R FLT3-Mutated AML or High-Risk MDSPhase 1/2, open-label>18Newly diagnosed or R/R FLT3-mutated AMLJuly 2021
NCT04956042Study of Fosciclopirox in Patients with R/R AMLPhase 1, open-label study>18R/R AMLAugust 2021
NCT03441048Lintuzumab-Ac225 in Combination with Cladribine + Cytarabine + Filgastrim + Mitoxantrone (CLAG-M) for R/R AMLSingle center, non-randomized, open-label phase 1>18R/R AML with >25% of blasts must be CD33 positiveMay 2022
Abbreviations: R/R, relapsed or refractory; AML, acute myeloid leukemia; ALL, acute lymphoblastic leukemia; MDS, myelodysplastic syndrome; Allo-HCT, allogeneic hematopoietic cell transplantation; HD, high dose.
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Awada, H.; Mustafa Ali, M.K.; Thapa, B.; Awada, H.; Seymour, L.; Liu, L.; Gurnari, C.; Kishtagari, A.; Wang, E.; Baer, M.R. A Focus on Intermediate-Risk Acute Myeloid Leukemia: Sub-Classification Updates and Therapeutic Challenges. Cancers 2022, 14, 4166. https://doi.org/10.3390/cancers14174166

AMA Style

Awada H, Mustafa Ali MK, Thapa B, Awada H, Seymour L, Liu L, Gurnari C, Kishtagari A, Wang E, Baer MR. A Focus on Intermediate-Risk Acute Myeloid Leukemia: Sub-Classification Updates and Therapeutic Challenges. Cancers. 2022; 14(17):4166. https://doi.org/10.3390/cancers14174166

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Awada, Hassan, Moaath K. Mustafa Ali, Bicky Thapa, Hussein Awada, Leroy Seymour, Louisa Liu, Carmelo Gurnari, Ashwin Kishtagari, Eunice Wang, and Maria R. Baer. 2022. "A Focus on Intermediate-Risk Acute Myeloid Leukemia: Sub-Classification Updates and Therapeutic Challenges" Cancers 14, no. 17: 4166. https://doi.org/10.3390/cancers14174166

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Awada, H., Mustafa Ali, M. K., Thapa, B., Awada, H., Seymour, L., Liu, L., Gurnari, C., Kishtagari, A., Wang, E., & Baer, M. R. (2022). A Focus on Intermediate-Risk Acute Myeloid Leukemia: Sub-Classification Updates and Therapeutic Challenges. Cancers, 14(17), 4166. https://doi.org/10.3390/cancers14174166

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