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AML and ALL Classification and Metabolic Characteristics for Informing and Advancing Treatment

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Abstract
Acute myeloid leukaemia (AML) and acute lymphoblastic leukaemia (ALL) remain significant challenges in haematological oncology. This review examines the pathophysiology, classification, and risk stratification of these aggressive malignancies, emphasising their impact on treatment strategies and prognosis. We discuss current standard-of-care treatments, including chemother-apy regimens and targeted therapies, while addressing the associated adverse effects and hyper-sensitivity reactions. Delving into the metabolic characteristics and vulnerabilities of leukaemia cells, the review highlights the key differences between lymphoid and myeloid leukaemia and how metabolic insights can be utilised for therapeutic purposes, with special focus on asparagi-nase therapy and its potential for improvement in both ALL and AML treatment. The review conveys the importance of personalised medicine approaches based on individual metabolic pro-files and the challenges posed by metabolic heterogeneity and plasticity in leukaemia cells. Inte-grating molecular and metabolic profiling can inform and advance treatment strategies for acute leukaemia, potentially improving patient outcomes and quality of life.
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1. Introduction

Acute leukaemia, particularly acute myeloid leukaemia (AML) and acute lymphoblastic leukaemia (ALL), pose significant challenges in the field of haematological malignancies. Acute leukaemia impacts a diverse range of age groups. AML is more prevalent in adults, with 3100 new cases diagnosed in the UK each year. Despite treatment advances, the five-year survival rate of AML is still only 15%, with approximately 2,600 deaths in the UK annually [1]. ALL is the most common childhood cancer, peaking in children aged 3-4 years, with 790 new cases and 230 deaths annually in the UK [1].
This review provides a comprehensive overview of the cell lineage, and molecular and metabolic characteristics of these aggressive malignancies. This underpins the heterogeneity of the disease and the requirement for treatment to be personalised and tailored to individual cases. Understanding the specific cellular dependencies and vulnerabilities is crucial for future clinical advancements [2,3,4,5,6,7,8,9,10]. Treatment of acute leukaemia involves intensive chemotherapy regimens and targeted therapies, associated with significant toxicities [11,12]. These adverse effects range from myelosuppression and gastrointestinal issues to cardiotoxicity, pancreatitis, and secondary malignancies, necessitating a need for less toxic and more targeted treatments [13]. L-asparaginase has been used as a key component of ALL treatment protocols for the past 50 years and is particularly effective in lymphoblastic leukaemia due to these cells typically lacking the enzyme asparagine synthetase (ASNS) [89]. Exploration of the dual action of asparaginase against both asparagine and glutamine, highlights its potential utility across different leukaemia subtypes. Studies in metabolic characterisation reveal potential pathways for further individualised use of asparaginase as perhaps a more targeted treatment than currently considered.
The integration of molecular and metabolic profiling in personalised medicine is central to developing effective treatment strategies tailored to individual patients’ needs [14] that minimize toxicity and maximise efficacy. While challenges remain in the fight against acute leukaemia, ongoing research aimed at comprehensive classification and metabolic profiling of ALL and AML is a promising approach for enhancing treatment efficacy and improving outcomes for patients.

2. Pathophysiology

AML is a rapidly progressing heterogenous myeloid neoplasm characterised by clonal expansion of myeloid progenitor cells in the bone marrow and peripheral blood. This proliferation primarily stems from the accumulation of diverse genomic and cytogenetic abnormalities, resulting in ineffective erythropoiesis, megakaryopoiesis, organ infiltration and bone marrow failure, causing inadequate production of red blood cells and platelets [15].
ALL is an aggressive malignancy of B or T lymphoblasts, characterised by uncontrolled proliferation of abnormal, immature lymphocytes and their progenitors. Environmental damage to DNA, and genetic predisposition are among etiologies that precede disease, causing lymphoid cells to undergo uncontrolled growth, and spread throughout the body [16,17,18,19,20]. Like AML, this ultimately leads to the replacement of functional bone marrow elements and other lymphoid organs, leading to bone marrow failure. Furthermore, splenomegaly and hepatomegaly occur due to sequestration of platelets and lymphocytes [21].

3. Classification and Risk Stratification, Informing Treatment and Prognosis

The World Health Organisation (WHO) classifies AML and ALL according to cell lineage, gene or chromosome changes, and cell differentiation (see Table 1). Acute leukemia of ambiguous lineage (ALAL) and mixed-phenotype acute leukaemia (MPAL) have overlapping clinical and immunophenotypic features and are therefore grouped together. These have been found to share common molecular pathogenic mechanisms [22,23,24]. The separation of ALAL/MPAL allows for molecular classification, distinguishing those with genetic abnormalities from those defined by immunophenotyping. Cells may exhibit a pattern in which some leukaemia cells have myeloid features and others have lymphoid features, while some cells simultaneously display both myeloid and lymphoid features [25].

3.1. AML

AML is a heterogeneous disease requiring individualised cytogenetic and molecular characterisation (Table 1). Prognostic factors are subdivided into those related to either the patient or to the disease (Figure 1). The European LeukemiaNET (ELN) guidelines (2022) emphasise molecular characterisation and risk stratification as critical for prognostic classification and treatment strategy, categorising AML into favourable, intermediate, or adverse risk groups (see Table 2) [28]. Despite advancements in therapeutic approaches, prognosis remains suboptimal, especially among older populations. Characterising fitness in the adult population is important when deciding treatment strategy.

3.2. ALL

Clinical factors and cytogenetic changes play an important role in risk stratification, which guides initial treatment regimen and allogeneic stem cell transplantation (Allo-SCT) (Figure 1, and Table 1). The Philadelphia chromosome, t(9;22) cytogenetic aberration, has the greatest impact on prognosis and treatment. Prevalence in adult ALL can range from 15–30% and increases with age [30]. Response to initial therapy also predicts outcome. Patients are evaluated for minimal residual disease (MRD) using molecular techniques such as flow cytometry and PCR [31]. Bruggemann et al. re-stratified standard-risk patients to low risk (<10-4), intermediate risk and high risk (>=10-4) with relapse rates of 0%, 47% and 94%, respectively, based on the persistence of elevated MRD, defined as >10−4 [32]. The National Comprehensive Cancer Network (NCCN) has developed recommendations to approach risk stratification [29]. The NCCN recognises that adolescent and young adults (AYA) (those aged 15–39 years) may benefit from treatment with paediatric-inspired regimens, with adults (>40 years) considered separately[33,34]. Both age groups are then stratified into subgroups: high-risk Ph-positive (Philadelphia chromosome-positive ALL) and standard-risk Ph-negative. The Ph-negative subgroup can further be categorised as high, intermediate, or low risk (Table 3), with the 5-year overall survival rates based on risk categories being 55%, 34% and 5% respectively [35].

4. Treating Acute Leukaemia

4.1. Drug Classification

Cancer chemotherapy drugs are divided into two main categories: non-targeted agents with broad specificity, and targeted drugs developed for specific molecular targets on cancer cells.

4.2. Current Standard of Care

Treatment of ALL and AML typically follow an induction, maintenance, and consolidation regime. The induction phase typically involves intensive chemotherapy combination regimens and aims to achieve complete remission (Table 4, and Table 5). Targeted therapies are incorporated into induction protocols to improve outcomes in specific genetic and molecular subgroups (Table 6). The optimal sequence and combination of these targeted agents with standard chemotherapy is an active area of research in AML [36,37]. Less intensive options are considered for older adults or those with significant comorbidities who cannot tolerate intensive chemotherapy.

4.3. Adverse Reactions

Non-targeted anti-leukaemic drugs are cytotoxic, suppress haematopoiesis, and can cause cutaneous eruptions, vascular damage, and lung and liver injury (Table 5). Current research into dose optimisation aims to adjust drug doses and schedules to maintain efficacy while minimising adverse effects [38]. Further attempts in decreasing overall toxicity of leukaemia treatments focuses on increasing the specificity of drugs. Targeting molecular pathways specific to leukaemia cells has potential to spare healthy cells and reduce systemic adverse effects by reducing the dose of traditional chemotherapy agents required [12]. Adverse effect profiles of targeted treatments tend to be more manageable, however these include lengthened QT interval, a conduction disorder of the heart, febrile neutropenia, cytopenia, and infections, gastrointestinal issues, and skin disorders (Table 6). Additionally, targeted immune activation aims to harness the immune system to deliver precise treatment with reduced off-target effects [39].

4.4. Hypersensitivity Reactions

In chemotherapy treatment for acute leukaemia, various adverse effects may have an immune basis, including drug-induced thrombocytopenia, neutropenia, and anemia, vascular disorders, liver injury, lung disease and various dermatological manifestations (Table 5). Certain drugs cause specific hypersensitivity reactions, such as cytarabine, causing a Type IV, delayed and T cell-mediated reaction and L-asparaginase, causing a Type I, IgE antibody-mediated reaction (Table 5 and Table 7).
Table 5. Non-targeted Chemotherapy Drugs Used in the Treatment of AML and ALL.
Table 5. Non-targeted Chemotherapy Drugs Used in the Treatment of AML and ALL.
Drug Type Indication Common Adverse Effects Serious Adverse Effects Reference
Cytarabine Antimetabolite AML, ALL Myelosuppression, nausea/vomiting, diarrhea, mucositis Cerebellar toxicity, acute pulmonary syndrome, hepatotoxicity [41]
Daunorubicin Anthracycline AML, ALL Myelosuppression, cardiotoxicity, alopecia, mucositis Cardiotoxicity, secondary malignancies [42,43]
Idarubicin Anthracycline AML Myelosuppression, cardiotoxicity, alopecia, mucositis Cardiotoxicity, hepatotoxicity [44]
Mitoxantrone Anthracenedione AML Myelosuppression, cardiotoxicity, alopecia Cardiotoxicity, therapy-related acute myeloid leukemia [45]
Etoposide Topoisomerase II inhibitor AML Myelosuppression, nausea/vomiting, alopecia Secondary leukemias, anaphylaxis [46,47]
Methotrexate Antimetabolite ALL Myelosuppression, mucositis, hepatotoxicity, nephrotoxicity Neurotoxicity, severe mucositis, acute kidney injury, hepatotoxicity [48,49]
Vincristine Vinca alkaloid ALL Peripheral neuropathy, constipation Severe neurotoxicity, paralytic ileus [50,51]
L-Asparaginase Enzyme ALL Hypersensitivity reactions, pancreatitis, coagulopathy Pancreatitis, thrombosis [52,53,54,55]
6-Mercaptopurine Antimetabolite ALL Myelosuppression, hepatotoxicity Severe hepatotoxicity, pancreatitis [56]
Cyclophosphamide Alkylating agent ALL Myelosuppression, hemorrhagic cystitis, alopecia Hemorrhagic cystitis, cardiotoxicity, secondary malignancies [13,57,58]
Azacitidine Hypomethylating agent AML (older/unfit patients) Myelosuppression, nausea/vomiting, injection site reactions Tumor lysis syndrome, renal failure [59,60]
Decitabine Hypomethylating agent AML (older/unfit patients) Myelosuppression, fatigue, nausea Severe infections [61]
from [35,40].
Table 6. Targeted Chemotherapy Drugs Used in the Treatment of AML and ALL.
Table 6. Targeted Chemotherapy Drugs Used in the Treatment of AML and ALL.
Drug Target Type Indication Common Adverse Effects Serious Adverse Effects Reference
Venetoclax BCL2 BCL-2 Inhibitor AML Nausea, diarrhea, fatigue Tumor lysis syndrome, severe myelosuppression [62]
Midostaurin FLT3 FLT3 Inhibitor
 
FLT3-mutated AML Nausea, vomiting, headache QT prolongation, interstitial lung disease [12]
Gilteritinib FLT3 FLT3 Inhibitor
 
FLT3-mutated AML Myalgia, transaminase elevation Differentiation syndrome, posterior reversible encephalopathy syndrome [63]
Ivosidenib IDH1 IDH Inhibitor
 
IDH1-mutated AML Fatigue, nausea, diarrhea Differentiation syndrome, QT prolongation [64]
Enasidenib IDH2 IDH Inhibitor
 
IDH2-mutated AML Nausea, diarrhea, decreased appetite Differentiation syndrome, liver toxicity [65]
Gemtuzumab ozogamicin CD33 Antibody-Drug Conjugate CD33+ AML Fever, nausea, infection Veno-occlusive disease, severe myelosuppression [66]
Glasdegib Hedgehog pathway Hedgehog Pathway Inhibitor AML Muscle spasms, alopecia, fatigue QT prolongation, embryo-fetal toxicity [67]
Imatinib BCR-ABL Tyrosine Kinase Inhibitor (TKI)
 
Ph+ ALL Nausea, vomiting, diarrhea, muscle cramps, fluid retention Myelosuppression, hepatotoxicity [68]
Dasatinib BCR-ABL Tyrosine Kinase Inhibitor (TKI)
 
Ph+ ALL Diarrhea, nausea, headache, muscle/joint pain, fluid retention Myelosuppression, pleural effusion, pulmonary arterial hypertension, QT prolongation, pancreatitis [69,70,71]
Blinatumomab CD19, bispecific antibody Bispecific T-cell Engager
 
Relapsed or refractory B-cell ALL Fever, headache, nausea Cytokine release syndrome, neurotoxicity [72,73]
Inotuzumab ozogamicin CD22, antibody-drug conjugate Antibody-Drug Conjugate (ADC) Relapsed or refractory B-cell ALL Thrombocytopenia, neutropenia, infections Veno-occlusive disease, increased risk of infections [74]
from [35,40].
Table 7. Adverse Effects of Asparaginase Therapy.
Table 7. Adverse Effects of Asparaginase Therapy.
Body System Common Adverse Effects Serious Adverse Effects Mechanism of Action of Adverse Effects References
Gastrointestinal - Nausea
- Vomiting
- Diarrhea
- Loss of appetite
- Pancreatitis - Glutamine helps maintain the health of the intestinal mucosa. Depletion of glutamine contributes to gastrointestinal disturbances
- Interferes with the highly active pancreatic protein synthesis
- upregulates asparagine synthetase (ASNS) expression in acinar cells.
- Increases intracellular calcium levels in pancreatic acinar cells, leading to calcium overload, which can cause cell damage and necrosis
- Causes premature activation of trypsin within pancreatic acinar cells, acinar cell destruction, inflammation, and autodigestion.
[52,86,93]
Haematological - Thrombocytopenia
- Anemia
- Thromboembolism - Decreased synthesis of factors involved in coagulation and fibrinolysis due to reduced protein availability, increasing risk of thrombosis or bleeding
- Myelosuppression
[53,54,55] [94]
Neurological - Fatigue
- Headache
- Central nervous system toxicity - seizures, confusion - Depletion of plasma proteins involved in coagulation and fibrinolysis lead to both thrombotic and hemorrhagic events in the brain
- Hyperammonemia can lead to a diffuse encephalopathy
- Direct toxic effects causing reversible posterior leukoencephalopathy syndrome
[95]
Dermatological - Urticaria - Severe allergic reactions - Immune response to foreign proteins in asparaginase leads to hypersensitivity reactions [96]
Hepatic - Elevated transaminases - Hepatotoxicity - Disruption of protein synthesis affecting liver function [97]
Metabolic - Weight loss
- Changes in taste
- Hyperglycemia - L-asparaginase hydrolyzes asparagine, a key component of insulin. Depletion of asparagine leads to reduced insulin synthesis in pancreatic beta cells [98,99]
Renal - Mild changes in kidney function - Acute kidney injury - Hyperammonemia contributes to electrolyte disturbance and dehydration
- Reduced renal perfusion and function due to dehydration and thrombosis
[53,54,55]
Cardiovascular - Peripheral edema - Thrombotic events (e.g., stroke, myocardial infarction) - Reduced plasma oncotic pressure due to reduced albumin levels, causing fluid to leak from the intravascular space into the interstitial space.
- Coagulopathy due to decreased synthesis of fibrinogen and antithrombin III
[53,54,55]

5. Metabolic Characteristics, Vulnerabilities, and Treatment Strategy

Metabolic vulnerabilities in leukaemia cells present significant opportunities for targeted therapies by exploiting the unique dependencies of these cells. Understanding and targeting the metabolic vulnerabilities of leukaemia cells offers a promising strategy for developing more effective and personalised treatments for leukaemia.

5.1. Key Differences in Metabolic Profiles Between Lymphoid and Myeloid Leukaemia Cells

5.1.1. Glycolysis and Oxidative Phosphorylation

Lymphoid leukaemia cells rely more on oxidative phosphorylation (OxPhos) rather than glycolysis, exhibiting a reduced glucose uptake in comparison to normal hematopoietic stem cells (HSCs), with increased mitochondrial respiration and reactive oxygen species (ROS) production [2,3]. Myeloid leukaemia cells show significant alterations in glycolytic pathways, characterised by a different set of metabolic adaptations that may include both glycolysis and OxPhos, depending on the specific subtype of myeloid leukaemia [4]. AML cells can alter expression of glycolytic enzymes, upregulating glycolysis, and switching between glycolysis and OxPhos depending on environmental conditions [75,76].

5.1.2. Amino Acid Metabolism

In lymphoid leukaemia cells there is protective activity in glutathione metabolism, involving overexpression of enzymes like glutamine dehydrogenase, which is crucial for glutathione synthesis [5,6,7]. Myeloid leukaemia cells also exhibit aberrant regulation of glutathione, with significantly lower levels of reduced glutathione (GSH), higher levels of oxidised glutathione (GSSG) and reduced total glutathione. In addition, studies observe a decreased GSH to GSSG ratio in CD34+ AML cells [8].

5.1.3. Lipid Metabolism

Lymphoid leukaemia cells demonstrate active lipid metabolism, with an accumulation of ceramide and lipoprotein lipases, making them susceptible to fatty acid oxidation (FAO) inhibitors. This is observed to be useful in cases of treatment resistance [9]. Myeloid leukaemia cells undergo metabolic reprogramming of lipid metabolism crucial for tumorigenesis and disease progression, supporting processes such as invasion, metastasis, and abnormal signaling [10]. Pathway alterations and their implications can differ based on genetic and environmental factors. Leukaemia cells treated with L-asparaginase have been shown to react by reprogramming their metabolism to increase fatty acid oxidation (FAO) and autophagy to compensate for asparagine and glutamine depletion [77]. Pharmacological inhibition of FAO increases sensitivity to asparaginase in leukaemia cells, supporting the theory of their pro-survival effect and potential role in the mechanism of treatment resistance [77].

5.2. Key Insights into How These Vulnerabilities Are Being Utilised for Therapeutic Purposes

5.2.1. Targeting Specific Metabolic Pathways

Leukaemia cells exhibit altered metabolic pathways that support their rapid proliferation and survival. These include glycolysis, oxidation of fatty acids, and the Krebs cycle. Targeting these pathways can disrupt the energy supply and biosynthetic processes crucial for leukaemia cell survival.

5.2.2. Leukaemia Stem Cells

Leukaemia stem cells (LSCs) resistant to conventional treatments have distinct metabolic preferences, such as heavy reliance on OXPHOS and specific amino acid metabolisms [78]. Inhibiting these pathways, for example by targeting the enzyme Nicotinamide phosphribosyltransferase (NAMPT), can reduce OXPHOS, with potential to eradicate resistant LSCs, while sparing normal cells [79].

5.2.3. Combination Therapies

Combining metabolic inhibitors with chemotherapy or immunotherapy can enhance therapeutic efficacy. Venetoclax combined with azacytidine disrupts energy metabolism in AML cells, targeting both blasts and LSCs, and restores sensitivity to treatment in relapsed or refractory cases of AML [80]. Additionally, 2-deoxy-d-glucose (2-DG) interferes with D-glucose metabolism, enhancing the anti-cancer effects of idarubicin (IDA) in IDA-resistant P388 leukaemia cells [81].

5.2.4. Personalised Medicine

Leukaemia cells display distinct metabolic states and adaptation mechanisms, serving as potential targets for treatment. However, the heterogeneity of the disease advocates for therapies to be tailored more individually. AML displays significant metabolic heterogeneity between patients within genetically distinct subclones [82,83,84]. The serine/threonine protein kinase PDK1 acts as a targetable determinant of different metabolic states in AML, functioning as a gatekeeper of glycolysis by phosphorylating and inactivating pyruvate dehydrogenase (PDH) [85]. Studies identified two main metabolic states in AML: PDK1-low, which is OXPHOS-driven, and PDK1-high, which is associated with low OXPHOS and an increase in stemness transcriptional signatures [75]. Insights into metabolic differences alongside clonal heterogeneity in AML allows for personalised, subclone-specific targeting strategies.
In addition to metabolic heterogeneity, the metabolic plasticity of leukaemia cells also presents a challenge in treatment design. With flexibility to undergo compensatory metabolic and energetic adaptations in response to inhibition of metabolic pathways, leukaemia cells can adapt and survive when specific metabolic pathways are targeted therapeutically [86,87]. LSC plasticity in mixed lineage leukaemia-rearranged B-lymphoblastic leukaemia (MLL-r B-ALL) allows the cells to switch lineages and emerge from differentiated populations, seen most frequently when under chemotherapy pressure [88]. AML stem cells can switch between a low-cycling chemotherapy-resistant state, and actively proliferating state [86]. This plasticity allows for interruption in drug efficacy, contributing to treatment resistance and disease progression.

6. Asparaginase as Targeted Treatment in Acute Leukaemia

In healthy cells, the non-essential amino acid asparagine, can be synthesised by enzymatic action of asparagine synthetase (ASNS) or obtained from the diet. Sufficient levels of cellular asparagine are required for DNA, RNA and protein synthesis. Depleted asparagine levels ultimately lead to activation of apoptotic cell-death mechanisms (Figure 2).
L-asparaginase has been a key component of ALL treatment protocols for the past fifty years, and found to be particularly effective in lymphoblastic leukaemia due to cells typically lacking ASNS [89]. Lymphoblastic leukaemia cells are also naturally susceptible to asparagine depletion. Cells unable to produce asparagine on their own, are heavily dependent on extracellular sources. At sufficient activity levels, asparaginase depletes serum L-asparagine, eventually leading to leukaemic cell death.
Figure 2. Mechanism of Action of Asparaginase in the Treatment of Leukaemia. ASNase: L-asparaginase; ASNS: L-asparagine synthetase; dashed arrows: reduced or missing.
Figure 2. Mechanism of Action of Asparaginase in the Treatment of Leukaemia. ASNase: L-asparaginase; ASNS: L-asparagine synthetase; dashed arrows: reduced or missing.
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6.1. Current Limitations of Asparaginase Therapy

Despite effectiveness, the high toxicity and side effects of current L-asparaginase formulations limit optimal clinical application, with lack of tolerance often leading to treatment interruption and discontinuation (Table 7). Current studies aim to improve treatment adherence, to reduce treatment interruption and improve the quality of life of patients receiving this drug. Combining L-asparaginase with other drugs, such as FAOs may improve efficacy while reducing adverse effects. Development of L-asparaginase variants with reduced L-glutaminase coactivity have been found to reduce acute toxicity compared to FDA-approved high L-glutaminase enzymes, while maintaining anti-leukaemic efficacy [90]. The short half-life of current L-asparaginase formulations have prompted efforts to develop variants with longer half-lives, which correlate with lower immunogenicity and reduced toxicity, while maintaining efficacy [91]. Paediatric studies emphasise the importance of monitoring in the early detection of asparaginase-related toxicity, in addition to understanding risk factors for toxicity that can inform individualised treatment approaches [92]. Identified risk factors include the presence of the TEL-AML1 fusion gene, which is associated with a higher risk of clinical hypersensitivity. Additionally, T-cell ALL correlates with a higher risk of hepatotoxicity in comparison to B-cell ALL. Other identified factors include age, gender, response to treatment and presence of central nervous system (CNS) infiltration at diagnosis.

6.2. Obstacles to Asparaginase Use in AML

AML cells are, on average, 7-fold more resistant to L-asparaginase than ALL cells [100]. This may be due to AML cells having variable expression of ASNS, in comparison to ALL cells. However, ASNS activity in blast cells of acute monocytic leukaemia (10% of AML cases) are reported to have the lowest median of ASNS activity, with activity varying over only a fourfold range [89], therefore certain subgroups of AML may show more promising outcomes when treated with L-asparaginase. Lysosomal cysteine protease cathepsin B (CTSB), asparaginyl endopeptidase, and neutralising antibodies, may also play a role in resistance and sensitivity to L-asparaginase [101,102]. L-asparaginase should therefore be tested in combination with other drugs that counteract factors decreasing its efficacy, such as inhibition of ASNS and/ or CTSB with specific protease inhibitors. With its potential to down regulate transcription of the ASNS gene, cytarabine shows promising synergetic effects with L-asparaginase. For example, asparaginase intensification studies, consisting of a combination of high doses of cytarabine and asparaginase (with noted importance of drug sequence, with asparaginase following cytarabine) was found to eliminate the benefit of prolonged maintenance therapy in childhood AML. This was accompanied by an overall improvement in survival, and improved complete remission rate [103]. The efficacy of asparaginase was also observed when combined with methotrexate in both adult and paediatric refractory or relapsed AML [104,105]. L-asparaginase may have anti-leukaemic activity in AML cells in general, and leukaemic stem cells in particular, if the protective effect of the bone marrow microenvironment can be overcome. A proposed approach to counteract this protective effect on residual AML cells, is to interfere with the binding of residual cells to the bone marrow stroma with CXCR4 chemokine-receptor antagonists, such as plerixafor [106].
Although AML cells may have variable expression of ASNS, they are particularly susceptible to glutamine depletion [107]. While L-asparaginase’s primary target is asparagine, it has significant activity against glutamine (Figure 2). L-asparaginase’s primary activity hydrolyses L-asparagine into L-aspartic acid and ammonia, with secondary hydrolysis of L-glutamine into L-glutamic acid and ammonia (glutaminase activity). The glutaminase activity of FDA-approved L-asparaginases ranges from 2% to 10% of their primary asparaginase activity [90]. AML cells and LSCs rely heavily on glutamine metabolism for critical cellular processes and show increased sensitivity to glutamine depletion compared to normal cells [108]. Additionally, genetic knockdown or pharmacologic inhibition of glutaminase negatively affects AML cells, while sparing normal CD34+ HSCs [109]. The glutaminase activity of L-asparaginase enhances the drug’s anticancer effects in ASNS-positive cancer cells [90]. Further studies have also found that the glutaminase activity of L-asparaginase was necessary for durable anticancer activity in vivo, even against ASNS-negative cancer types [110].

6.3. Metabolic Characteristics and Sensitivity to Asparaginase Treatment

Leukaemia cells cluster into distinct groups based on their metabolic profiles, which correlate with their response to asparaginase treatment. In a recent study describing the relationship between the metabolic profile of leukaemia cells and their sensitivity to commonly used anti-leukaemic drugs, cells sensitive to asparaginase were ranked in a lower glycolytic cluster [14]. Indeed, a significant correlation was observed between higher ATP-linked respiration, lower basal mitochondrial membrane potential, and increased sensitivity to asparaginase. No similar correlation was found for other cytostatic drugs tested [14]. The findings suggest that the metabolic profile of leukaemia cells plays a crucial role in determining the efficacy of asparaginase treatment, and that metabolic profiling could be used to predict asparaginase sensitivity in leukaemia patients. Thus, patients with higher glycolytic activity might benefit from alternative or additional treatments to asparaginase. Targeting specific metabolic pathways (e.g., glycolysis or mitochondrial respiration) could potentially enhance the efficacy of asparaginase treatment, especially in less sensitive patients who would otherwise be more likely to fail the conventional therapy without having any other detectable risk factors. Characterising leukaemic cell and blast metabolic state, at the time of diagnosis, may help identify patients who are particularly sensitive, or with lower sensitivity to asparaginase, and offer a potential pathway for personalised treatment strategies in leukaemia therapy.

7. Conclusions

The treatment landscape for acute leukaemia is evolving due to advances in our understanding of their cellular and metabolic characteristics, and the targeting of these for therapeutic benefit. Statistics surrounding these diseases highlight the urgency for improved treatment options. With AML resulting in over 2,600 deaths each year and a mere 15% five-year survival rate despite treatment advances, and ALL being the most common childhood cancer, it is evident that more effective and better tolerated therapies are critically needed.
The toxicity profile of current leukaemia treatments remains a significant challenge, impacting patient quality of life and limiting therapeutic options, however exploration of metabolic characteristics reveal potential pathways for targeted therapies. The effectiveness of L-asparaginase in treating ALL exemplifies how understanding metabolic dependencies can inform treatment strategies. Individual susceptibility to asparaginase therapy has potential to inform its utilisation across the subtypes of leukaemia on a case-by-case basis. This prompts the question of need for further screening prior to therapy and perhaps a change of outlook on asparaginase as an increasingly targeted therapy for both ALL and AML.
Continued collaboration among researchers, clinicians and patients will be essential to navigate these scientific insights into clinical practice. While challenges remain in the fight against acute leukaemia, ongoing research into more personalised medicine offers promising avenues for enhancing treatment efficacy, while reducing toxicity, and provide hope for improved outcomes for all patients affected by AML and ALL.

Author Contributions

Conceptualization, C.W. and S.R.C..; methodology, C.W., E.J. and R.S.; investigation, C.W.; resources, S.R.C. and C.W.; writing—original draft preparation, C.W..; writing—review and editing, C.W., E.J., R.S., and S.R.C..; visualization, C.W..; supervision, E.J. and R.S..; acquisition, C.W., and S.R.C. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported in part by the UK Biotechnology and Biological Sciences Research Council (BBSRC) under grant numbers BB/J004529/1, BB/R012490/1, and BBS/E/F000PR10355 (S.R.C.). C.W. was supported by a student bursary from Big C Cancer Charity, registered charity number 281730.

Data Availability Statement

No new data were created or analyzed in this study. Data sharing is not applicable to this article.

Acknowledgments

Big C Cancer Charity.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. https://www.cancerresearchuk.org/health-professional/cancer-statistics-for-the-uk.
  2. Chen, C., et al., Oxidative phosphorylation enhances the leukemogenic capacity and resistance to chemotherapy of B cell acute lymphoblastic leukemia. Sci Adv, 2021. 7(11). [CrossRef]
  3. Jia, L. and J.G. Gribben, Dangerous power: mitochondria in CLL cells. Blood, 2014. 123(17): p. 2596-2597. [CrossRef]
  4. Baker, F., et al., Metabolic Rewiring Is Essential for AML Cell Survival to Overcome Autophagy Inhibition by Loss of ATG3. Cancers (Basel), 2021. 13(23). [CrossRef]
  5. Galicia-Vázquez, G., S. Smith, and R. Aloyz, Del11q-positive CLL lymphocytes exhibit altered glutamine metabolism and differential response to GLS1 and glucose metabolism inhibition. Blood Cancer J, 2018. 8(1): p. 13. [CrossRef]
  6. Mayer, R.L., et al., Proteomics and metabolomics identify molecular mechanisms of aging potentially predisposing for chronic lymphocytic leukemia *<sup></sup>. Molecular & Cellular Proteomics, 2018. 17(2): p. 290-303.
  7. Zhang, W., et al., Stromal control of cystine metabolism promotes cancer cell survival in chronic lymphocytic leukaemia. Nature Cell Biology, 2012. 14(3): p. 276-286. [CrossRef]
  8. Pei, S., et al., Targeting aberrant glutathione metabolism to eradicate human acute myelogenous leukemia cells. J Biol Chem, 2013. 288(47): p. 33542-33558. [CrossRef]
  9. Thurgood, L.A., et al., Lipid uptake in chronic lymphocytic leukemia. Experimental Hematology, 2022. 106: p. 58-67. [CrossRef]
  10. Li, D., et al., A distinct lipid metabolism signature of acute myeloid leukemia with prognostic value. Front Oncol, 2022. 12: p. 876981. [CrossRef]
  11. Schilstra, C.E., et al., Prospective longitudinal evaluation of treatment-related toxicity and health-related quality of life during the first year of treatment for pediatric acute lymphoblastic leukemia. BMC Cancer, 2022. 22(1): p. 985. [CrossRef]
  12. Stone, R.M., et al., Midostaurin plus Chemotherapy for Acute Myeloid Leukemia with a FLT3 Mutation. N Engl J Med, 2017. 377(5): p. 454-464. [CrossRef]
  13. Schmiegelow, K., et al., Second malignant neoplasms after treatment of childhood acute lymphoblastic leukemia. J Clin Oncol, 2013. 31(19): p. 2469-76. [CrossRef]
  14. Hlozkova, K., et al., Metabolic profile of leukemia cells influences treatment efficacy of L-asparaginase. BMC Cancer, 2020. 20(1): p. 526. [CrossRef]
  15. Ley, T.J., et al., Genomic and epigenomic landscapes of adult de novo acute myeloid leukemia. N Engl J Med, 2013. 368(22): p. 2059-74.
  16. Sehgal, S., et al., High incidence of Epstein Barr virus infection in childhood acute lymphocytic leukemia: a preliminary study. Indian J Pathol Microbiol, 2010. 53(1): p. 63-7.
  17. Gérinière, L., et al., Heterogeneity of acute lymphoblastic leukemia in HIV-seropositive patients. Ann Oncol, 1994. 5(5): p. 437-40. [CrossRef]
  18. German, J., Bloom’s syndrome. XX. The first 100 cancers. Cancer Genet Cytogenet, 1997. 93(1): p. 100-6.
  19. Cimino, G., et al., ALL-1 gene at chromosome 11q23 is consistently altered in acute leukemia of early infancy. Blood, 1993. 82(2): p. 544-6.
  20. Shah, A., B.M. John, and V. Sondhi, Acute lymphoblastic leukemia with treatment--naive Fanconi anemia. Indian Pediatr, 2013. 50(5): p. 508-10.
  21. Wu, C., et al., Spleen mediates a distinct hematopoietic progenitor response supporting tumor-promoting myelopoiesis. The Journal of Clinical Investigation, 2018. 128(8): p. 3425-3438. [CrossRef]
  22. Wang, W., et al., T(6;14)(q25;q32) involves BCL11B and is highly associated with mixed-phenotype acute leukemia, T/myeloid. Leukemia, 2020. 34(9): p. 2509-2512. [CrossRef]
  23. Di Giacomo, D., et al., 14q32 rearrangements deregulating BCL11B mark a distinct subgroup of T-lymphoid and myeloid immature acute leukemia. Blood, 2021. 138(9): p. 773-784.
  24. Montefiori, L.E., et al., Enhancer Hijacking Drives Oncogenic BCL11B Expression in Lineage-Ambiguous Stem Cell Leukemia. Cancer Discov, 2021. 11(11): p. 2846-2867. [CrossRef]
  25. Alexander, T.B., et al., The genetic basis and cell of origin of mixed phenotype acute leukaemia. Nature, 2018. 562(7727): p. 373-379. [CrossRef]
  26. Arber, D.A., et al., The 2016 revision to the World Health Organization classification of myeloid neoplasms and acute leukemia. Blood, 2016. 127(20): p. 2391-405. [CrossRef]
  27. Khoury, J.D., et al., The 5th edition of the World Health Organization Classification of Haematolymphoid Tumours: Myeloid and Histiocytic/Dendritic Neoplasms. Leukemia, 2022. 36(7): p. 1703-1719. [CrossRef]
  28. Döhner, H., et al., Diagnosis and management of AML in adults: 2022 recommendations from an international expert panel on behalf of the ELN. Blood, 2022. 140(12): p. 1345-1377. [CrossRef]
  29. Alvarnas, J.C., et al., Acute Lymphoblastic Leukemia, Version 2.2015. J Natl Compr Canc Netw, 2015. 13(10): p. 1240-79.
  30. Faderl, S., et al., Clinical Significance of Cytogenetic Abnormalities in Adult Acute Lymphoblastic Leukemia. Blood, 1998. 91(11): p. 3995-4019.
  31. van Dongen, J.J., et al., Minimal residual disease diagnostics in acute lymphoblastic leukemia: need for sensitive, fast, and standardized technologies. Blood, 2015. 125(26): p. 3996-4009.
  32. Brüggemann, M., et al., Clinical significance of minimal residual disease quantification in adult patients with standard-risk acute lymphoblastic leukemia. Blood, 2006. 107(3): p. 1116-23. [CrossRef]
  33. Huguet, F., et al., Pediatric-inspired therapy in adults with Philadelphia chromosome-negative acute lymphoblastic leukemia: the GRAALL-2003 study. J Clin Oncol, 2009. 27(6): p. 911-8. [CrossRef]
  34. Stock, W., et al., What determines the outcomes for adolescents and young adults with acute lymphoblastic leukemia treated on cooperative group protocols? A comparison of Children’s Cancer Group and Cancer and Leukemia Group B studies. Blood, 2008. 112(5): p. 1646-54.
  35. Rowe, J.M., et al., Induction therapy for adults with acute lymphoblastic leukemia: results of more than 1500 patients from the international ALL trial: MRC UKALL XII/ECOG E2993. Blood, 2005. 106(12): p. 3760-7. [CrossRef]
  36. Kantarjian, H., et al., Acute myeloid leukemia: current progress and future directions. Blood Cancer Journal, 2021. 11(2): p. 41. [CrossRef]
  37. Bhansali, R.S., K.W. Pratz, and C. Lai, Recent advances in targeted therapies in acute myeloid leukemia. Journal of Hematology & Oncology, 2023. 16(1): p. 29. [CrossRef]
  38. Iqbal, A., et al., Improved Treatment Outcomes With Modified Induction Therapy in Acute Myeloid Leukemia (AML): A Retrospective Observational Study From a Regional Cancer Center. Cureus, 2024. 16(1): p. e53303. [CrossRef]
  39. Jitschin, R., et al., CD33/CD3-bispecific T-cell engaging (BiTE®) antibody construct targets monocytic AML myeloid-derived suppressor cells. Journal for ImmunoTherapy of Cancer, 2018. 6(1): p. 116. [CrossRef]
  40. Rowe, J.M. and M.S. Tallman, How I treat acute myeloid leukemia. Blood, 2010. 116(17): p. 3147-3156.
  41. Di Francia, R., et al., Response and Toxicity to Cytarabine Therapy in Leukemia and Lymphoma: From Dose Puzzle to Pharmacogenomic Biomarkers. Cancers (Basel), 2021. 13(5).
  42. Blair, H.A., Daunorubicin/Cytarabine Liposome: A Review in Acute Myeloid Leukaemia. Drugs, 2018. 78(18): p. 1903-1910. [CrossRef]
  43. Wang, Y., et al., Subsequent female breast cancer risk associated with anthracycline chemotherapy for childhood cancer. Nature Medicine, 2023. 29(9): p. 2268-2277. [CrossRef]
  44. Ohtake, S., et al., Randomized study of induction therapy comparing standard-dose idarubicin with high-dose daunorubicin in adult patients with previously untreated acute myeloid leukemia: the JALSG AML201 Study. Blood, 2011. 117(8): p. 2358-2365. [CrossRef]
  45. Stroet, A., et al., Incidence of therapy-related acute leukaemia in mitoxantrone-treated multiple sclerosis patients in Germany. Ther Adv Neurol Disord, 2012. 5(2): p. 75-9. [CrossRef]
  46. Relling, M.V., et al., Etoposide and antimetabolite pharmacology in patients who develop secondary acute myeloid leukemia. Leukemia, 1998. 12(3): p. 346-352. [CrossRef]
  47. Cotteret, C., et al., Severe hypersensitivity reaction to etoposide phosphate: A case report. Clin Case Rep, 2020. 8(9): p. 1821-1823. [CrossRef]
  48. Apiraksattayakul, N., et al., Potential neurotoxicity associated with methotrexate. Scientific Reports, 2024. 14(1): p. 18548. [CrossRef]
  49. Maiguma, T., et al., Relationship between oral mucositis and high-dose methotrexate therapy in pediatric acute lymphoblastic leukemia. Int J Clin Pharmacol Ther, 2008. 46(11): p. 584-90. [CrossRef]
  50. Gomber, S., P. Dewan, and D. Chhonker, Vincristine induced neurotoxicity in cancer patients. The Indian Journal of Pediatrics, 2010. 77(1): p. 97-100. [CrossRef]
  51. Yasu, T., et al., Vincristine-induced paralytic ileus during induction therapy of treatment protocols for acute lymphoblastic leukemia in adult patients. Int J Clin Pharmacol Ther, 2016. 54(6): p. 471-3. [CrossRef]
  52. Rank, C.U., et al., Asparaginase-Associated Pancreatitis in Acute Lymphoblastic Leukemia: Results From the NOPHO ALL2008 Treatment of Patients 1-45 Years of Age. J Clin Oncol, 2020. 38(2): p. 145-154. [CrossRef]
  53. Hernández-Espinosa, D., et al., L-asparaginase-induced antithrombin type I deficiency: implications for conformational diseases. Am J Pathol, 2006. 169(1): p. 142-53. [CrossRef]
  54. Hongo, T., et al., Low plasma levels of hemostatic proteins during the induction phase in children with acute lymphoblastic leukemia: A retrospective study by the JACLS. Japan Association of Childhood Leukemia Study. Pediatr Int, 2002. 44(3): p. 293-9. [CrossRef]
  55. Mitchell, L., et al., Increased endogenous thrombin generation in children with acute lymphoblastic leukemia: risk of thrombotic complications in L’Asparaginase-induced antithrombin III deficiency. Blood, 1994. 83(2): p. 386-91.
  56. Zerra, P., et al., Maintenance Treatment With Low-Dose Mercaptopurine in Combination With Allopurinol in Children With Acute Lymphoblastic Leukemia and Mercaptopurine-Induced Pancreatitis. Pediatr Blood Cancer, 2016. 63(4): p. 712-5. [CrossRef]
  57. Varma, P.P., D.B. Subba, and P. Madhoosudanan, CYCLOPHOSPHAMIDE INDUCED HAEMORRHAGIC CYSTITIS (A Case Report). Med J Armed Forces India, 1998. 54(1): p. 59-60. [CrossRef]
  58. Xu, Y., et al., Risk of second malignant neoplasms after cyclophosphamide-based chemotherapy with or without radiotherapy for non-Hodgkin lymphoma. Leukemia & Lymphoma, 2013. 54(7): p. 1396-1404. [CrossRef]
  59. Naka, R., et al., PB1862: VENETOCLAX AND AZACITIDINE THERAPY IN ACUTE MYELOID LEUKEMIA PATIENTS WITH SEVERE RENAL IMPAIRMENT. HemaSphere, 2023. 7(S3): p. e8463360. [CrossRef]
  60. DiNardo, C.D., et al., Azacitidine and Venetoclax in Previously Untreated Acute Myeloid Leukemia. N Engl J Med, 2020. 383(7): p. 617-629. [CrossRef]
  61. Michael, L., et al., A multicenter phase II trial of decitabine as first-line treatment for older patients with acute myeloid leukemia judged unfit for induction chemotherapy. Haematologica, 2012. 97(3): p. 393-401.
  62. Esparza, S., et al., Venetoclax-induced tumour lysis syndrome in acute myeloid leukaemia. Br J Haematol, 2020. 188(1): p. 173-177. [CrossRef]
  63. McMahon, C.M., et al., Gilteritinib induces differentiation in relapsed and refractory FLT3-mutated acute myeloid leukemia. Blood Adv, 2019. 3(10): p. 1581-1585. [CrossRef]
  64. DiNardo, C.D., et al., Durable Remissions with Ivosidenib in <i>IDH1</i>-Mutated Relapsed or Refractory AML. New England Journal of Medicine, 2018. 378(25): p. 2386-2398.
  65. Stein, E.M., et al., Enasidenib in mutant IDH2 relapsed or refractory acute myeloid leukemia. Blood, 2017. 130(6): p. 722-731. [CrossRef]
  66. Baron, J. and E.S. Wang, Gemtuzumab ozogamicin for the treatment of acute myeloid leukemia. Expert Rev Clin Pharmacol, 2018. 11(6): p. 549-559. [CrossRef]
  67. Norsworthy, K.J., et al., FDA Approval Summary: Glasdegib for Newly Diagnosed Acute Myeloid Leukemia. Clinical Cancer Research, 2019. 25(20): p. 6021-6025. [CrossRef]
  68. Ottmann, O.G., et al., A phase 2 study of imatinib in patients with relapsed or refractory Philadelphia chromosome–positive acute lymphoid leukemias. Blood, 2002. 100(6): p. 1965-1971. [CrossRef]
  69. Shen, S., et al., Effect of Dasatinib vs Imatinib in the Treatment of Pediatric Philadelphia Chromosome-Positive Acute Lymphoblastic Leukemia: A Randomized Clinical Trial. JAMA Oncol, 2020. 6(3): p. 358-366.
  70. Özgür Yurttaş, N. and A.E. Eşkazan, Dasatinib-induced pulmonary arterial hypertension. Br J Clin Pharmacol, 2018. 84(5): p. 835-845. [CrossRef]
  71. Abu Rmilah, A.A., et al., Risk of QTc prolongation among cancer patients treated with tyrosine kinase inhibitors. Int J Cancer, 2020. 147(11): p. 3160-3167. [CrossRef]
  72. Stein, A.S., et al., Neurologic adverse events in patients with relapsed/refractory acute lymphoblastic leukemia treated with blinatumomab: management and mitigating factors. Ann Hematol, 2019. 98(1): p. 159-167. [CrossRef]
  73. Turtle, C.J., et al., CD19 CAR-T cells of defined CD4+:CD8+ composition in adult B cell ALL patients. J Clin Invest, 2016. 126(6): p. 2123-38. [CrossRef]
  74. Kantarjian, H.M., et al., Hepatic adverse event profile of inotuzumab ozogamicin in adult patients with relapsed or refractory acute lymphoblastic leukaemia: results from the open-label, randomised, phase 3 INO-VATE study. Lancet Haematol, 2017. 4(8): p. e387-e398. [CrossRef]
  75. Erdem, A., et al., The Glycolytic Gatekeeper PDK1 defines different metabolic states between genetically distinct subtypes of human acute myeloid leukemia. Nature Communications, 2022. 13(1): p. 1105. [CrossRef]
  76. Chen, W.-L., et al., A distinct glucose metabolism signature of acute myeloid leukemia with prognostic value. Blood, 2014. 124(10): p. 1645-1654. [CrossRef]
  77. Hermanova, I., et al., Pharmacological inhibition of fatty-acid oxidation synergistically enhances the effect of l-asparaginase in childhood ALL cells. Leukemia, 2016. 30(1): p. 209-18. [CrossRef]
  78. Ye, H., et al., Leukemic Stem Cells Evade Chemotherapy by Metabolic Adaptation to an Adipose Tissue Niche. Cell Stem Cell, 2016. 19(1): p. 23-37. [CrossRef]
  79. Jones, C.L., et al., Nicotinamide Metabolism Mediates Resistance to Venetoclax in Relapsed Acute Myeloid Leukemia Stem Cells. Cell Stem Cell, 2020. 27(5): p. 748-764.e4. [CrossRef]
  80. Jones, C.L., et al., Inhibition of Amino Acid Metabolism Selectively Targets Human Leukemia Stem Cells. Cancer Cell, 2018. 34(5): p. 724-740.e4. [CrossRef]
  81. Pajak, B., et al., 2-Deoxy-d-Glucose and Its Analogs: From Diagnostic to Therapeutic Agents. International Journal of Molecular Sciences, 2020. 21(1): p. 234.
  82. Klco, J.M., et al., Functional heterogeneity of genetically defined subclones in acute myeloid leukemia. Cancer Cell, 2014. 25(3): p. 379-92. [CrossRef]
  83. de Boer, B., et al., Prospective Isolation and Characterization of Genetically and Functionally Distinct AML Subclones. Cancer Cell, 2018. 34(4): p. 674-689.e8.
  84. Anderson, K., et al., Genetic variegation of clonal architecture and propagating cells in leukaemia. Nature, 2011. 469(7330): p. 356-61. [CrossRef]
  85. Takubo, K., et al., Regulation of glycolysis by Pdk functions as a metabolic checkpoint for cell cycle quiescence in hematopoietic stem cells. Cell Stem Cell, 2013. 12(1): p. 49-61. [CrossRef]
  86. Ebinger, S., et al., Plasticity in growth behavior of patients’ acute myeloid leukemia stem cells growing in mice. Haematologica, 2020. 105(12): p. 2855-2860. [CrossRef]
  87. Poort, V.M., et al., Transient Differentiation-State Plasticity Occurs during Acute Lymphoblastic Leukemia Initiation. Cancer Research, 2024. 84(16): p. 2720-2733. [CrossRef]
  88. Morris, V., et al., Single-cell analysis reveals mechanisms of plasticity of leukemia initiating cells. bioRxiv, 2020: p. 2020.04.29.066332.
  89. Dübbers, A., et al., Asparagine synthetase activity in paediatric acute leukaemias: AML-M5 subtype shows lowest activity. Br J Haematol, 2000. 109(2): p. 427-9. [CrossRef]
  90. Nguyen, H.A., et al., A Novel l-Asparaginase with low l-Glutaminase Coactivity Is Highly Efficacious against Both T- and B-cell Acute Lymphoblastic Leukemias In Vivo. Cancer Research, 2018. 78(6): p. 1549-1560. [CrossRef]
  91. Sengupta, S., et al., Preclinical evaluation of engineered L-asparaginase variants to improve the treatment of Acute Lymphoblastic Leukemia. Transl Oncol, 2024. 43: p. 101909. [CrossRef]
  92. Schmidt, M.P., et al., L-Asparaginase Toxicity in the Treatment of Children and Adolescents with Acute Lymphoblastic Leukemia. J Clin Med, 2021. 10(19). [CrossRef]
  93. Mukherjee, A., et al., Asparagine Synthetase Is Highly Expressed at Baseline in the Pancreas Through Heightened PERK Signaling. Cell Mol Gastroenterol Hepatol, 2020. 9(1): p. 1-13. [CrossRef]
  94. Merryman, R., et al., Asparaginase-associated myelosuppression and effects on dosing of other chemotherapeutic agents in childhood acute lymphoblastic leukemia. Pediatr Blood Cancer, 2012. 59(5): p. 925-7. [CrossRef]
  95. Kieslich, M., et al., Cerebrovascular Complications of l-Asparaginase in the Therapy of Acute Lymphoblastic Leukemia. Journal of Pediatric Hematology/Oncology, 2003. 25(6): p. 484-487. [CrossRef]
  96. Rathod, S., et al., Hypersensitivity reactions to asparaginase in mice are mediated by anti-asparaginase IgE and IgG and the immunoglobulin receptors FcεRI and FcγRIII. Haematologica, 2019. 104(2): p. 319-329. [CrossRef]
  97. Kamal, N., et al., Asparaginase-induced hepatotoxicity: rapid development of cholestasis and hepatic steatosis. Hepatol Int, 2019. 13(5): p. 641-648.
  98. Lavine, R.L., et al., The effect of E. coli L-asparaginase on oral glucose tolerance and insulin release in man. Diabetologia, 1978. 15(2): p. 113-6. [CrossRef]
  99. Cetin, M., et al., Hyperglycemia, ketoacidosis and other complications of L-asparaginase in children with acute lymphoblastic leukemia. J Med, 1994. 25(3-4): p. 219-29.
  100. Zwaan, C.M., et al., Cellular drug resistance profiles in childhood acute myeloid leukemia: differences between FAB types and comparison with acute lymphoblastic leukemia. Blood, 2000. 96(8): p. 2879-86.
  101. Michelozzi, I.M., et al., Acute myeloid leukaemia niche regulates response to L-asparaginase. British Journal of Haematology, 2019. 186(3): p. 420-430. [CrossRef]
  102. Kaspers, G.J.L., Acute myeloid leukaemia niche regulates response to L-asparaginase. Br J Haematol, 2019. 186(3): p. 397-399. [CrossRef]
  103. Capizzi, R.L., et al., Synergy between high-dose cytarabine and asparaginase in the treatment of adults with refractory and relapsed acute myelogenous leukemia--a Cancer and Leukemia Group B Study. J Clin Oncol, 1988. 6(3): p. 499-508. [CrossRef]
  104. Buaboonnam, J., et al., Sequential administration of methotrexate and asparaginase in relapsed or refractory pediatric acute myeloid leukemia. Pediatr Blood Cancer, 2013. 60(7): p. 1161-4. [CrossRef]
  105. Chen, T., et al., Antiproliferative effects of L-asparaginase in acute myeloid leukemia. Exp Ther Med, 2020. 20(3): p. 2070-2078. [CrossRef]
  106. Martínez-Cuadrón, D., et al., A phase I-II study of plerixafor in combination with fludarabine, idarubicin, cytarabine, and G-CSF (PLERIFLAG regimen) for the treatment of patients with the first early-relapsed or refractory acute myeloid leukemia. Ann Hematol, 2018. 97(5): p. 763-772. [CrossRef]
  107. Fathi, A.T., et al., Biochemical, Epigenetic, and Metabolic Approaches to Target IDH Mutations in Acute Myeloid Leukemia. Semin Hematol, 2015. 52(3): p. 165-71. [CrossRef]
  108. Willems, L., et al., Inhibiting glutamine uptake represents an attractive new strategy for treating acute myeloid leukemia. Blood, 2013. 122(20): p. 3521-3532. [CrossRef]
  109. Willems, L., et al., Inhibiting glutamine uptake represents an attractive new strategy for treating acute myeloid leukemia. Blood, 2013. 122(20): p. 3521-32. [CrossRef]
  110. Chan, W.K., et al., Glutaminase Activity of L-Asparaginase Contributes to Durable Preclinical Activity against Acute Lymphoblastic Leukemia. Mol Cancer Ther, 2019. 18(9): p. 1587-1592. [CrossRef]
Figure 1. Risk Stratification in AML and ALL as per European LeukemiaNET (ELN) guidelines and the National Comprehensive Cancer Network (NCCN) [28,29].
Figure 1. Risk Stratification in AML and ALL as per European LeukemiaNET (ELN) guidelines and the National Comprehensive Cancer Network (NCCN) [28,29].
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Table 1. WHO Classification of AML and ALL.
Table 1. WHO Classification of AML and ALL.
Cell Lineage Classification Subtype
Lymphoid B-cell ALL with
certain genetic
abnormalities
• B-cell ALL with hypodiploidy
• B-cell ALL with hyperdiploidy
• B-cell ALL with t(9;22) (Philadelphia chromosome, BCR-ABL1 fusion)
• B-cell ALL with translocation involving chromosome 11
• B-cell ALL with t(12;21)
• B-cell ALL with t(1;19)
• B-cell ALL with t(5;14)
• B-cell ALL with iAMP21*
• B-cell ALL with BCR-ABL1–like ALL*
• B-cell ALL, not otherwise specified
T-cell ALL • Early T-cell precursor lymphoblastic leukaemia*
Myeloid AML with defining genetic
abnormalities
• Acute promyelocytic leukaemia with PML::RARA fusion
• AML with RUNX1::RUNX1T1 fusion
• AML with CBFB::MYH11 fusion
• AML with DEK::NUP214 fusion
• AML with RBM15::MRTFA fusion
• AML with BCR::ABL1 fusion
• AML with KMT2A rearrangement
• AML with MECOM rearrangement
• AML with NUP98 rearrangement
• AML with NPM1 mutation
• AML with CEBPA mutation
• AML, myelodysplasia-related
• AML with other defined genetic alterations
AML, defined by differentiation • AML with minimal differentiation
• AML without maturation
• AML with maturation
• Acute basophilic leukaemia
• Acute myelomonocytic leukaemia
• Acute monocytic leukaemia
• Acute erythroid leukaemia
• Acute megakaryoblastic leukaemia
Acute leukaemia of ambiguous lineage (ALAL) and mixed-phenotype acute leukaemia (MPAL)
 
ALAL/ MPAL with defining genetic
abnormalities
• Mixed-phenotype acute leukaemia with BCR::ABL1 fusion
• Mixed-phenotype acute leukaemia with KMT2A rearrangement
• Acute leukaemia of ambiguous lineage with other defined genetic alterations
• Mixed-phenotype acute leukaemia with ZNF384 rearrangement
• Acute leukaemia of ambiguous lineage with BCL11B rearrangement
ALAL, immunophenotypically defined • Mixed-phenotype acute leukaemia, B/myeloid
• Mixed-phenotype acute leukaemia, T/myeloid
• Mixed-phenotype acute leukaemia, rare types
• Acute leukaemia of ambiguous lineage, not otherwise specified
• Acute undifferentiated leukaemia
*(from [26,27]): *Provisional entity.
Table 2. ELN Recommended Stratification of Molecular and Cytogenic Alterations in AML.
Table 2. ELN Recommended Stratification of Molecular and Cytogenic Alterations in AML.
Risk Profile Subsets
Favourable t(8;21)(q22;q22); RUNX1-RUNX1T1
inv(16)(p13.1q22); or t(16;16)(p13.1;q22); CBFB-MYH11
Mutated NPM1 without FLT3-ITD (normal karyotype)
Biallelic mutated CEBPA (normal karyotype)
Intermediate-I Mutated NPM1 and FLT3-ITD (normal karyotype)
Wild-type NPM1 and FLT3-ITD (normal karyotype)
Wild-type NPM1 without FLT3-ITD (normal karyotype)
Intermediate-II t(9;11)(p22;q23); MLLT3-KMT2A
Cytogenic abnormalities not classified as favourable or adverse
Adverse inv(3)(q21;q26.2) or t(3;3)(q21;q26.2); GATA2-MECOM (EVI1)
t(6;9)(p23;q34); DEK-NUP214
t(v;11)(v;q23); KMT2A rearranged
-5 or del(5q); -7; abnl(17p); complex karyotype
From [28].
Table 3. Standard Risk Ph-negative Acute Lymphoid Leukaemia (ALL) Subdivision.
Table 3. Standard Risk Ph-negative Acute Lymphoid Leukaemia (ALL) Subdivision.
High risk Unfavourable cytogenetics OR Age >35
AND Elevated white blood cell (WBC) countb
OR MRD (>10−4)
Intermediate risk No risk factors based on cytogenetics Age >35
OR Elevated WBC count
MRD (<10-4)
Low risk No risk factors based on cytogenetics No risk factors based on:
Age OR WBC count
MRD (<10-4)
from [29] aUnfavourable cytogenetics defined in Figure 1. bElevated WBC count (>30 × 109 for B-ALL or >100 109 for T-ALL).
Table 4. Standard Induction Regimes for AML and ALL.
Table 4. Standard Induction Regimes for AML and ALL.
AML Vincristine
 
An anthracycline drug:
- Daunorubicin
- Doxorubicin
A steroid:
- Dexamethasone
- Prednisone
Additional drugs as per risk factors:
- Cyclophosphamide
- Pegaspargase
- Crisantaspase recombinant
- High-dose methotrexate
- High dose cytarabine
- L-asparaginase
Targeted drugs,
For Ph+ ALL:
- Imatinib
- Dasatinib
For relapsed or refractory B-cell precursor ALL:
- Blinatumomab
- Inotuzumab ozogamicin
ALL "7+3" regimen: - Cytarabine
(7-day continuous IV infusion)
AND
An anthracycline (3 day)
- Daunorubicin
- Idarubicin
 
In combination with standard induction:
- Quizartinib
- Venetoclax
Targeted therapy as per molecular type:
For FLT3-mutated AML:
- Midostaurin
For CD33-positive AML:
- Gemtuzumab ozogamicin
For therapy-related AML:
- Liposomal daunorubicin-cytarabine
For IDH1/2-mutated AML:
- Ivosidenib
- Enasidenib
Less intensive:
- Azacitidine or decitabine
- Low-dose cytarabine
- Venetoclax, combined with hypomethylating agents or low-dose cytarabine
- Glasdegib plus low-dose cytarabine
Ivosidenib +/- azacitidine
- Enasidenib
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