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Review

The Role of Epithelial-to-Mesenchymal Transition Transcription Factors (EMT-TFs) in Acute Myeloid Leukemia Progression

1
Laboratorio de Investigación en Ciencias Biomédicas, Departamento de Ciencias Básicas y Morfología, Facultad de Medicina, Universidad Católica de la Santísima Concepción, Concepción 4030000, Chile
2
Laboratorio de Regulación Transcripcional, Departamento de Bioquímica y Biología Molecular, Facultad de Ciencias Biológicas, Universidad de Concepción, Concepción 4030000, Chile
3
Departamento de Biología Celular, Facultad de Ciencias Biológicas, Universidad de Concepción, Concepción 4030000, Chile
4
Paul Albrechtsen Research Institute, CancerCare Manitoba, Winnipeg, MB R3E 0V9, Canada
5
Department of Pharmacology and Therapeutics, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB R3T 2N2, Canada
*
Authors to whom correspondence should be addressed.
These authors contributed equally to this work.
Biomedicines 2024, 12(8), 1915; https://doi.org/10.3390/biomedicines12081915
Submission received: 12 July 2024 / Revised: 31 July 2024 / Accepted: 2 August 2024 / Published: 21 August 2024
(This article belongs to the Special Issue Advances in the Pathogenesis and Treatment of Acute Myeloid Leukemia)

Abstract

:
Acute myeloid leukemia (AML) is a diverse malignancy originating from myeloid progenitor cells, with significant genetic and clinical variability. Modern classification systems like those from the World Health Organization (WHO) and European LeukemiaNet use immunophenotyping, molecular genetics, and clinical features to categorize AML subtypes. This classification highlights crucial genetic markers such as FLT3, NPM1 mutations, and MLL-AF9 fusion, which are essential for prognosis and directing targeted therapies. The MLL-AF9 fusion protein is often linked with therapy-resistant AML, highlighting the risk of relapse due to standard chemotherapeutic regimes. In this sense, factors like the ZEB, SNAI, and TWIST gene families, known for their roles in epithelial–mesenchymal transition (EMT) and cancer metastasis, also regulate hematopoiesis and may serve as effective therapeutic targets in AML. These genes contribute to cell proliferation, differentiation, and extramedullary hematopoiesis, suggesting new possibilities for treatment. Advancing our understanding of the molecular mechanisms that promote AML, especially how the bone marrow microenvironment affects invasion and drug resistance, is crucial. This comprehensive insight into the molecular and environmental interactions in AML emphasizes the need for ongoing research and more effective treatments.

1. Definition of Acute Myeloid Leukemia (AML), Genetic Variability, and Classification

Acute Myeloid Leukemia (AML) is characterized by the inhibition of proper blood cell differentiation, with a significant blockage at the level of hematopoietic stem cells (HSCs) or early myeloid progenitors like myeloblasts. This leads to rapid disease progression and is clinically diagnosed as AML when there are 20% of AML blasts in the peripheral blood [1]. In contrast, Acute Lymphocytic Leukemia (ALL) arises from a block at the lymphoid progenitors and predominantly affects young children [2]. Chronic leukemias (CLs), on the other hand, allow for more mature and functional blood cells to accumulate [3,4]. AML is more prevalent in elderly adults and accounts for approximately 80% of all leukemias in adults [5], often leading to aberrant hematopoiesis and bone marrow failure. Recent treatments have improved cure rates to around 15% in 60-year-old patients and approximately 40% in those under 60 [6]. In 2018, the global cancer surveillance system (GLOBOCAN) reported a significant incidence of AML worldwide, with 474,519 cases globally and 67,784 in North America, reflecting a prevalence of about 11 cases per 100,000 population [7].
Acute myeloid leukemia (AML) was initially classified from M0 to M7 based on the French–American–British (FAB) system, emphasizing morphological and immunological characteristics [8]. These subtypes include M0 with minimal differentiation and M1 with a higher proportion of mature myeloid forms, which shows advanced stages of cell maturation and is associated with AML1 and ETO fusion proteins [9,10]. M3, or Acute Promyelocytic Leukemia (APL), comprises about 10% of all AML cases and features the PML-RARα fusion protein from the t(15;17) translocation, with a favorable prognosis due to effective treatments with all-trans retinoic acid (ATRA) and arsenic trioxide (ATO) [11,12,13,14]. M4 represents acute myelomonocytic leukemia [15,16], while M5, or monocytic leukemia, often presents with poor prognosis, extramedullary disease, and abnormalities on chromosome 11q, including the MLLT3 (MLL-AF9) fusion protein, causing the Mixed-Lineage Leukemia (MLL) subtype [17,18,19,20]. Subtype M6, also known as erythroleukemia, is a rare form of AML (comprising less than 5% of AML cases) [21,22,23]. Finally, the rare M7 subtype, megakaryocytic/megakaryoblastic leukemia, exhibits poor differentiation and prognosis [24,25].
The advent of flow cytometry and next-generation sequencing (NGS) has enhanced the understanding of AML’s molecular and genetic complexities, highlighting the need for a more precise classification system to better stratify patients based on genetic profiles, affecting treatment and prognosis [26,27,28]. These classifications are further illustrated in Table 1.
The 2022 International Consensus Classification (ICC) and the World Health Organization (WHO) fifth edition classification updated and introduced new AML categories to align more closely with genetic and clinical data. Notably, the ICC introduced a category for AML with TP53 mutations, characterized by a poor prognosis due to at least 20% blasts and a TP53 variant allele fraction over 10% [29,30]. This classification acknowledges the unique biology of TP53 mutations in AML. Additionally, the ICC has refined the category of AML with myelodysplasia-related changes into two separate groups as follows: one for gene mutations and another for cytogenetic abnormalities, both requiring at least 20% blasts [29,30]. Recent updates from WHO-ICC 2022 and the European Leukemia Net (ELN) guidelines in 2022 reflect these changes, emphasizing the role of genetic and molecular data in AML management, indicative of a shift towards precision medicine in oncology [31,32]. The ELN 2022 updates also introduced a categorization system that considers hierarchical genetic abnormalities, establishing a new category for MDS/AML with 10–19% blasts if specific genetic abnormalities are present, highlighting the importance of genetic markers [32].
Table 2 Summarizes the findings of the WHO 2022 and European LeukemiaNet 2022 guidelines alongside additional literature, detailing the impact of genetic variations on the prognosis of different AML subtypes. AML subtypes are characterized based on specific genetic abnormalities and their corresponding blast percentage requirements, highlighting how these factors influence ELN risk classification.
Next, we will explore one of the well-studied genetic aberrations in AML, specifically within the M5 subtype—the MLL-AF9 fusion protein. We will review the molecular mechanisms underlying its pathogenicity and its significant role in therapy-related AML (t-AML), underscoring how these genetic fusions influence disease progression and impact treatment strategies.

2. MLL-AF9 Fusion Protein Oncogenic Mechanisms and Incidence in AML

MLL, a large protein weighing 431 kDa, is encoded by the KMT2A gene located on chromosome 11q23 [52,53]. This protein undergoes intracytoplasmic cleavage by the enzyme Taspase 1, resulting in two functional subunits, MLL-N and MLL-C, which are essential for its role in the MLL complex along with WDR5 (WD repeat-containing protein 5), RBBP5 (RB binding protein 5, histone lysine methyltransferase complex subunit), and ASH2L (ASH2-like, histone lysine methyltransferase complex subunit) proteins [54]. This complex is integral to maintaining proper chromatin structure and facilitates the efficient transcription of critical developmental genes, including those involved in hematopoiesis [55,56,57,58]. One of the crucial functions of the MLL complex is the methylation of lysine 4 on histone H3 (H3K4), an epigenetic mark that is vital for the activation of HOX genes. These genes are essential for developmental processes and are particularly notable for their roles in maintaining the properties of hematopoietic stem or progenitor cells [56,59]. The epidemiology of MLL rearrangements indicates a high incidence in infant leukemias and a significant presence in adult AML, often leading to monocytic differentiation corresponding to FAB classifications AML-M4 or AML-M5. These rearrangements, particularly the MLL-AF9 fusion protein resulting from the t(9;11)(p22;q23) translocation, are associated with a poorer prognosis in AML patients, highlighting the clinical importance of recognizing this genetic alteration for targeted treatment strategies [60,61,62,63,64,65].
The AF9 protein, encoded by the MLLT3 gene, is a protein varying in molecular weight between 63 and 88 kDa. Part of the YEATS family, the MLLT3 gene encodes intrinsically disordered proteins and is characterized by its distinctive YEATS domain. AF9 is pivotal in hematopoiesis, primarily tasked with maintaining the population of hematopoietic stem or progenitor cells (HSPCs), essential for the generation and regulation of blood cells [66,67]. AF9 also plays a critical role in gene expression regulation through its interaction with acetylated lysine 27 on histone H3. This interaction is important for enhancing the recruitment of the Like Histone Lysine Methyltransferase protein, encoded by the DOT1L gene. Nuclear magnetic resonance (NMR) studies have shown that DOT1L binds to AF9 across three of its domains, facilitating this process [68]; through this interaction, DOT1L specifically targets lysine 79 residues on histone H3 for methylation. This mark plays a pivotal role in chromatin remodeling, leading to the decompaction of the chromatin structure and facilitating the transition from a more condensed heterochromatin state to a more relaxed euchromatin state, promoting gene expression [69].
In the context of AML, the interaction between AF9 and MLL proteins is crucial for the regulation of gene expression, specifically facilitating the binding of the MLL enzyme complex to gene promoters in an active transcriptional state [70]. This interaction significantly promotes the activation of HOX genes, which are key transcription factors regulating the development of the anteroposterior axis across various organisms. Their continuous expression is vital for maintaining the undifferentiated state of progenitor cells, similar to blast cells in AML [70].
HOX genes, organized into four clusters (HOXA, HOXB, HOXC, HOXD), play crucial roles in development and disease. In early vertebrate development, their expression is regulated by chromosomal positioning, with specific clusters being condensed and inaccessible to transcription machinery, thereby inhibiting expression during early phases [42,71,72,73]. These genes are typically downregulated post-embryogenesis and can become aberrantly reactivated in neoplastic conditions, potentially leading to states that favor uncontrolled cellular proliferation [74]. Humans possess 39 HOX genes across seven families, with specific genes like HOXB3, HOXB4, and HOXA1 to HOXA10 linked to adverse outcomes in diseases such as acute myeloid leukemia (AML) [75,76,77,78,79,80,81,82].
Specifically, the RUNX1 and MLL-AF9 interaction disrupts normal hematopoietic gene expression, highlighting the significance of the NPM1 gene in AML pathology [83]. NPM1 mutations, present in about 30% of AML cases, correlate with HOX gene expression and impact leukemogenesis through pathways like the CEBPα pathway, which activates CTBP transcriptional regulators and affects the expression of HOXA5, HOXB5, and HOXA10 in NPM1-mutant AMLs [83,84,85,86,87].
Therefore, the recognition of the presence of the MLL-AF9 fusion gene in AML is clinically significant, as this genetic alteration can influence treatment selection and therapeutic response monitoring. Patients with this gene fusion may require more aggressive therapeutic approaches and combined treatment strategies to enhance outcomes and overcome resistance to conventional treatments [88].

3. First-Line Treatments for AML May Cause t(9;11)—A Mechanistic Perspective

A range of anticancer agents specifically target topoisomerase II (TOP2), an essential enzyme in DNA replication encoded by the TOP2A gene, has been used in the treatment of AML. These drugs disrupt the TOP2 catalytic cycle in various steps (Figure 1), leading to an accumulation of TOP2-DNA cleavage complexes and double-strand breaks (DSBs), culminating with cell death. TOP2 poison drugs such as etoposide, teniposide, and doxorubicin inhibit the re-ligation of DNA following TOP2-induced cleavage, while other compounds like quinolone CP-115953 and Azatoxins initiate DNA break formation [89,90]. Notably, doxorubicin, a well-known anthracycline, acts as an inhibitor of DNA re-ligation at lower concentrations (<1 μM) but may interfere with TOP2’s DNA binding at higher concentrations (>10 μM) [90]. Despite their effectiveness, these TOP2 poisons, which remain in clinical use, are linked to severe adverse effects, including the emergence of secondary malignancies [91,92,93]. Notably, treatment-related myelodysplastic syndromes (t-MDSs) often culminate in therapy-related acute myelocytic leukemia (t-AML), presenting significant clinical challenges [94,95]. Etoposide, a chemotherapy drug, is linked to an increased risk of t-AML and t-MDS, particularly when used in cumulative doses exceeding 2000 mg/m2/day in the treatment of testicular and extragonadal germ cell tumors [96,97]. The risk is notably higher within the first five years post-treatment, although cases of t-AML/MDS have been reported even two decades after initial treatment with this drug [98]. Systematic reviews reported that in the context of germ cell tumor treatment, the incidence rates of t-AML/MDS far surpass those of spontaneously occurring AML/MDS, underscoring the significant risk increase attributable to etoposide-based chemotherapy regimens [99,100].
Comparative analysis reveals that the risk of developing therapy-related AML/MDS (t-AML/MDS) is significantly higher than that of de novo AML/MDS, with t-AML/MDS being 13 to 200 times more likely to occur. This heightened risk, notably following etoposide and anthracycline treatments, extends to other chemotherapies for various cancers [98,100,101]. A common feature in t-AML is chromosomal translocations, particularly involving the MLL gene on chromosome 11q23, with translocations such as MLL-AF9 being pivotal in leukemia development [102,103,104,105]. The MLL gene frequently translocates with partners such as ENL (MLLT1), AF4 (MLLT2), and AF9 (MLLT3), among over a hundred identified partner genes [20,106,107]. These translocations play a crucial role in leukemia development; for instance, MLL-AF9 can transform hematopoietic precursors and induce leukemia in animal models [108,109,110].
The most frequent translocation partners for the MLL gene are AF4 (MLLT2), AF9 (MLLT3), ENL (MLLT1), AF10 (MLLT10), and the ELL gene [20,106,107]. However, in the case of therapy-induced leukemia, the most frequent translocation partners are AF9, ELL, AF4, and ENL proteins. Interestingly, AF9 is very common in pediatric AML cases with most of the MLL translocation at intron 9; however, in adult AML cases with MLL-AF9 fusion protein, MLL translocations occur more frequently at intron 11 [106], probably caused by poison-induced DNA cleavage [19,106].
Taken together, first-line treatments for AML, and other malignancies, use drugs against TOP2 because of their ability to disrupt DNA replication processes. However, their use is associated with significant adverse effects, notably the increased risk of therapy-related malignancies like t-AML and t-MDS, largely because of the induction of chromosomal translocations involving the MLL gene, among others. These insights underscore the need for a delicate balance in cancer therapy, weighing the benefits of effective cancer treatment against the potential for long-term genetic consequences and the development of secondary malignancies. In t-AML, the most frequent translocation presented corresponds to MLL-AF9, and patients with this fusion protein usually have aggressive AML with a bad prognosis. Also, as previously described, once MLL-AF9 has been formed, different target genes and cellular processes will be affected by this fusion protein. This leads to patients having aggressive AML with a bad prognosis, which underscores the need to have a better understanding of the mechanism downstream and upstream of this fusion protein.
Figure 1. Anticancer drugs can interfere with the catalytic cycle of TOP2, causing chromosomal translocation. (1) DNA supercoiling and catenation. (2) TOP2 dimer binds to one DNA double helix (green), and some compounds can inhibit TOP2 binding to DNA [111]. (3,4) Top2 generates a double-strand break in green DNA in the presence of Mg2+, and TOP2 remains attached to both DNA ends. A second DNA double helix (red) passes through the break in an ATP-dependent process. Some compounds can stimulate or inhibit DNA break formation [111]. (5–7) After the red DNA passage is completed, green DNA is re-ligated and both DNAs are released from the enzyme. (5a) Etoposide and doxorubicin can inhibit DNA re-ligation [111], resulting in the accumulation of TOP2 attached to DNA ends. After proteasomal action, DNA with double-strand breaks is repaired by Non-Homologous End-Joining (NHEJ), potentially leading to mutation (6a) or chromosome translocation (6b) [19].
Figure 1. Anticancer drugs can interfere with the catalytic cycle of TOP2, causing chromosomal translocation. (1) DNA supercoiling and catenation. (2) TOP2 dimer binds to one DNA double helix (green), and some compounds can inhibit TOP2 binding to DNA [111]. (3,4) Top2 generates a double-strand break in green DNA in the presence of Mg2+, and TOP2 remains attached to both DNA ends. A second DNA double helix (red) passes through the break in an ATP-dependent process. Some compounds can stimulate or inhibit DNA break formation [111]. (5–7) After the red DNA passage is completed, green DNA is re-ligated and both DNAs are released from the enzyme. (5a) Etoposide and doxorubicin can inhibit DNA re-ligation [111], resulting in the accumulation of TOP2 attached to DNA ends. After proteasomal action, DNA with double-strand breaks is repaired by Non-Homologous End-Joining (NHEJ), potentially leading to mutation (6a) or chromosome translocation (6b) [19].
Biomedicines 12 01915 g001
Metabolic reprogramming, including the dysregulation of lipid metabolism, is indispensable for cancer cell survival and propagation through the accumulation of Lipid Droplets (LDs) [112]. LDs not only function as energy reservoirs but also provide building blocks for membrane biosynthesis and produce signaling molecules critical for tumor progression. In AML, elevated LD accumulation leads to poor prognosis and chemoresistance by activating oncogenic pathways and through interaction with the tumor microenvironment [113]. Targeting LD biogenesis has been gaining increased attention, and several inhibitors have shown promise in AML such as hydrophobic aminopeptidase inhibitor CHR2863 plus Rapamycin [114], 3-Methyladenine [115], and Pioglitazone [116], among others, that can complement current AML treatment regimes.

4. Emergence of Epithelial-to-Mesenchymal Transition (EMT) Factors in the Risk and Progression of AML: The Role of ZEB Transcription Factors

The acknowledgment of increased t-AML incidence following first-line treatments for AML underscores a critical need for innovative therapeutic strategies that mitigate the risk of secondary malignancies while effectively combating primary disease states. As research progresses, a promising area of exploration involves the epithelial–mesenchymal transition (EMT) factors, known for their pivotal roles in cell differentiation and migration. In the context of AML, EMT factors contribute to the plasticity of leukemic cells, influencing their ability to resist apoptosis and evade the immune system, thus presenting a dual challenge and opportunity in leukemia treatment. By targeting these EMT factors, new treatments could potentially disrupt the cellular mechanisms that contribute to the aggressiveness and poor prognosis often observed in MLL-AF9-mediated AML.
Based on the work of Prange et al. [84] and Stavropoulou et al. [117], it is increasingly clear that ZEB1 and ZEB2 genes may act as transcriptional targets of MLL fusion proteins. Prange et al. highlighted the genome-wide binding of MLL-AF9 and MLL-AF4 fusion proteins in AML cell lines, revealing both shared and unique target genes marked by specific epigenetic signatures. Their study demonstrated how MLL fusions, alongside subsets of transcription factors, can deregulate critical gene programs in AML, suggesting a role for ZEB1 and ZEB2 within this framework. Similarly, Stavropoulou et al. 2016 underscored the impact of cellular origin on AML aggressiveness and identified EMT-related genes, including ZEB1, associated with poor outcomes in AML patients [117]. Their work emphasized the complex interplay between MLL fusion proteins and cellular origin in determining AML characteristics, where ZEB1 and ZEB2 emerge as potential mediators in the MLL-driven leukemic processes. These findings offer a refined perspective on the molecular mechanisms underpinning MLL-associated leukemia, highlighting the potential of ZEB1 and ZEB2 as EMT factors to be critical components within this oncogenic network in AML.

5. Role of ZEB Transcription Factors

ZEB1/2 transcription factor dysregulation has previously been demonstrated to play pathological roles in the EMT processes involved in (1) the malignant dissemination (metastasis) of epithelial-derived tumor cells [118,119], (2) the acquisition of cancer or tumor stem cell properties [120,121], and (3) the development of treatment resistance [122,123]. The ZEB transcription factors are large multidomain proteins that contain both amino-terminal and carboxy-terminal Zinc Finger DNA binding domains that bind to bi-partite E-box binding sites (CACCT(G), sometimes CACANNT(G)) [124] in the promoter/enhancer regions of target genes. These proteins can either suppress transcription by recruiting corepressor complexes such as the Nucleosome Remodeling and Deacetylase (NuRD) complex that contain Histone Deacetylase (HDAC) 1/2, resulting in chromatin closure and gene repression, or enhance transcription by attracting additional transcription complexes containing p300 acetylation factor that opens chromatin, allowing access to transcription factors [125,126] and the basic transcriptional machinery.
ZEB2 [127,128] and, more recently, ZEB1 [129,130] have been demonstrated to play important roles in regulating murine hematopoiesis as well as immune cell differentiation and function [131,132,133] distinct from their roles in EMT. In hematopoietic stem and progenitor cells (HSPCs) ZEB2 and, to a lesser degree, ZEB1 limit the inappropriate expression of innate and adaptive immune cell programs [129,130]. Upon lineage commitment, ZEB2 maintains distinct immune programs to produce defined populations of functional macrophage, dendritic, natural killer, and T cells [131,132,133,134]. Not only does ZEB2 ensure immune cell lineage fidelity that is unique to a given lineage, but it does so with very little overlap in terms of common gene expression programs it regulates. To exemplify this point, ZEB2 interacts with signals from the tissue environment to specify macrophage identity that is unique to the host organ (lung vs. colon, etc.) with very little overlap of common Differentially Expressed Genes (DEGs) among organs, which is associated with murine Zeb2 loss [134]. Given the importance of these unique genetic programs in controlling lineage fate/function, it is perhaps not surprising that ZEB protein dysregulation can lead to various different forms of leukemia via lineage-specific mechanisms including myeloid lineage transformation leading to AML [135]. Recently, the role of ZEB1 in macrophage differentiation [136] and dendritic cell homeostasis [137] has been described, pointing out that oncogenic ZEB1 can alter these processes during leukemogenesis.
Within the AML context, ZEB1 and ZEB2 may become dysregulated through direct transcriptional control of the MLL-AF9 and MLL-AF4 oncofusion proteins [116,117]. Additionally, ZEB1/2 are known to be negatively regulated by the miR200 family of miRNAs [138], and in their absence, ZEB protein levels may accumulate to oncogenic levels. Within AML, the miR200 family of miRNAs has been found to be methylated and repressed, associated with increased ZEB2 levels [139,140]. Additional AML oncofusions including AML-ETO and PML-RARα have also been demonstrated to transcriptionally upregulate Zeb2 [141], implying that ZEB2 upregulation may be a common driver of AML progression.
In terms of the importance of ZEB proteins in driving AML development/progression, ZEB2 plays an oncogenic role. In two separate and unrelated genetic screening approaches, ZEB2 was found to be involved in myeloid and lymphoid leukemic transformation and a novel genetic dependency in murine and human AML [120,139]. In the first instance, ZEB2 was overexpressed from the ROSA26 (R26) safe-harbor locus in Tie2-Cre lineage marked cells, which includes the endothelium and entire hematopoietic system that is derived from the hemogenic endothelium of the Aorta–Gonad–Mesonephros (AGM) region [120]. Tie2-Cre, R26Tg/Tg mice develop spontaneous T cell transformation around 6 months of age that genetically and phenotypically resembles Early Thymic Progenitor Acute Lymphoblastic Leukemia (ETP-ALL). ETP-ALL is characterized by transformed early T cell progenitors that express HSPC as well as myeloid cell markers. On a sensitized p53 null background, Tie-Cre, R26Tg/Tg mice also developed AML and B-ALL but at lower frequencies. These results imply that ZEB2 may play oncogenic roles in myeloid and B cells, but additional genetic hits may be required for ZEB2-mediated leukemic transformation. In line with the latter, genetic alterations frequently implicate ZEB2 in various translocations and mutations within T-lymphoid leukemia and AML, with 14q32 rearrangements involving the BCL11B gene marking a distinct subgroup. These genetic rearrangements form a unique expression profile that significantly affects leukemia biology and patient prognosis [142].
In a separate unbiased CRISPR/Cas9-based screening approach, ZEB2 was found to be a top genetic dependency involved in both human AML cell lines and MLL-AF9 murine AML proliferation [139]. Knock-down of ZEB2 in human AML cell lines resulted in enhanced morphological differentiation as assayed by May–Grunwald–Giemsa staining analysis and increased mature CD11B myeloid marker expression in flow cytometry analysis [139]. Genetic deletion of ZEB2 using a tamoxifen-inducible Cre-based approach in an established murine MLL-AF9 model was found to significantly increase overall survival [130]. Moreover, several studies support the oncogenic role of ZEB2 in human AML. Mechanistically, it has been shown that miR-454-3p targets ZEB2, playing a critical role in AML progression. Overexpression of miR-454-3p induces apoptosis and autophagy in AML cells by downregulating ZEB2 expression, which concurrently inhibits the AKT/mTOR signaling pathway [143]. Additionally, the overexpression of ZEB2-AS1 long non-coding RNA (lncRNA), which leads to increased ZEB2 levels, has been associated with poorer clinical outcomes in acute myeloid leukemia [144]. These findings highlight the necessity of maintaining tight regulation of ZEB2 to prevent its upregulation to oncogenic levels.
The oncogenic role of ZEB1 in AML is more controversial, as Almotiri et al. recently postulated that ZEB1 may act as a tumor suppressor given that murine Zeb1 deletion in MLL-AF9 models can accelerate AML progression [129]. Bioinformatically, evidence was provided that ZEB1 levels may be lower in certain subtypes of AML [129]. However, simultaneous deletion of both murine Zeb2 and Zeb1 in murine MLL-AF9 AML settings was found to significantly increase the overall survival of mice transplanted with MLL-AF9 secondary tumor cells compared with nontreated vehicle-treated controls [130]. A separate bioinformatic analysis by Almotiri et al. demonstrated that both ZEB1 and ZEB2 in human AML are significantly higher in the leukemic blast population than in the bulk tumor population, suggesting that these transcription factors may be diluted in the bulk RNA-sample analysis as well as in overall levels of expression used in the Kaplan–Meier survival curves [130]. Consistent with an oncogenic role of ZEB1 in AML, Stavropoulou et al. identified murine Zeb1 as an essential target of MLL-AF9 in HSC-like leukemic AML blast populations, which play an important role in leukemic blast invasion to extramedullary sites [117]. In line with the latter, it has been demonstrated that the hematopoietic transcription factor ZNF521 increases its levels in AML with MLL rearrangements, enhancing hematopoietic stem cell transformation via ZEB1, among other genes [145]. ZEB1 was also found to play an oncogenic role in human AML cell lines by increasing PI3K/AKT signaling [146], which relies on p53-PTEN pathway modulation. In the latter study, it was demonstrated that ZEB1 expression is negatively correlated with tumor suppressor P53 expression, and ZEB1 can directly bind to P53 as a molecular mechanism to exert oncogenesis.
The complex role of ZEB1 within AML extends to its effect on the immunological landscape, where it downregulates CD8 T cell activity and promotes the expansion of Th17 cells, enhancing the survival and proliferative capabilities of leukemia cells in the AML niche. Recently, Bassani et al. demonstrated that high levels of ZEB1 correlate with increased Th17 cell development and a pro-invasive phenotype associated with poor patient outcomes [147,148]. The analysis of ZEB1 expression in larger datasets of AML identifies two distinct groups, ZEB1high and ZEB1low, each with specific immunological and gene expression signatures. Importantly, ZEB1high patients exhibit increased expression of IL-17, SOCS2, and TGF-β (Transforming Growth Factor Beta) pathways and a negative association with overall survival [147].
The role of ZEB1 is beyond the protein level. It has been shown that mutations in the splicing factor 3b subunit 1 encoded by the SF3B1 gene are frequent in myelodysplastic neoplasms (MDS). In this context, a strong upregulation of Circular RNAs (circRNAs) processed from the ZEB1 locus has been reported, which may impact mitochondrial function and cellular metabolism in myelodysplastic syndrome (MDS) [149]. Moreover, ZEB1 interacts with long non-coding RNA MALAT1, influencing its activity and stability through m6A modification and thereby modulating the aggressiveness of AML [150]. Taken together this evidence highly suggests that ZEB1 serves as an oncogene at various levels of AML.
Overall, the ZEB1 and ZEB2 transcription factors play important roles in the progression and aggressiveness of acute myeloid leukemia (AML) by influencing the epithelial–mesenchymal transition, stem cell characteristics, and therapy resistance. These factors are often dysregulated because of transcriptional control by MLL fusion proteins or repression by the miR200 family of miRNAs, leading to enhanced oncogenic activity. Specifically, ZEB2 has been linked to both myeloid and lymphoid leukemic transformations, affecting hematopoietic differentiation and immune modulation, while ZEB1 impacts the immune system by regulating T cell activities and promoting Th17 cell expansion, which correlates with poor clinical outcomes. Given their significant roles, targeting ZEB proteins offers a promising therapeutic approach to potentially improve treatment efficacy and reduce the incidence of secondary malignancies like therapy-related AML (t-AML).
At present, small molecules are available with the ability to interact with EMT-TFs to potentially halt AML progression, and chemotherapeutics currently available for AML treatment may be combined with specific inhibitors of EMT-TFs to provide better treatment against AML progression. Currently, three noteworthy studies have utilized ZEB2 inhibitor compounds for this purpose (all commercially available). The first study focused on Honokiol, a phenolic compound primarily investigated in breast and kidney cancer research, which downregulated EMT genes including ZEB2 [151]. The second study employed Teniposide at low doses to inhibit ZEB2, significantly reducing the pulmonary colonization of breast cancer cells [152]. While Teniposide has been used in AML treatment at higher doses, it leads to therapy-related relapse at standard clinical doses; thus, combined therapy is necessary [153]. Importantly, the third study identified the novel small molecule CD3254 as an effective agent for promoting mouse chemical reprogramming (0.5 μM). This molecule operates through the CD3254–RXRα axis to activate the RNA exosome and specifically downregulates Zeb1/2, Twist, and SNAI1 EMT factors [154]. These drugs hold potential for inclusion in AML treatment strategies to inhibit EMT-TFs and improve therapeutic outcomes.

6. Role of SNAI Transcription Factors

The SNAI family (SNAI1, SNAI2, and SNAI3) of transcription factors have also been demonstrated to play essential roles in EMT [155] as well as the acquisition of cancer stemness properties [156] and drug resistance [157]. SNAI proteins have conserved carboxy-terminal Zinc Finger DNA binding domains that are also capable of binding to E-box elements (5′-CAGGTG-3′) in the promoter of epithelial genes such as E-cadherin, which is involved in its transcriptional repression. Regarding the miR200-SNAI1 relationship, studies have shown that SNAI1 plays a key role in facilitating EMT and mesoderm differentiation during a particular phase of embryonic stem cell differentiation, which aligns with the early epiblast stage. In this period, SNAI1 modifies the levels of various miRNAs, notably those within the miR200 microRNA family, but it is unclear if this relationship occurs in hematopoiesis [158]. The SNAI proteins all have an amino-terminal SNAI-GFI (SNAG) binding domain that is responsible for the recruitment and promoter binding of epigenetic factors such as KDM1A (Lysine Demethylase 1A) (LSD1 protein), which is responsible for histone 3 lysine 4 demethylation (H3K4me1/2) and gene repression [159]. This SNAG domain, as its name implies, is shared with other proteins including the GFI1/1B transcription factors that play important roles in hematopoiesis [160]. SNAI proteins have also been demonstrated to play roles in hematopoiesis. SNAI2 has been demonstrated to act downstream of the c-Kit signaling pathway in HSPCs (hematopoietic stem and progenitor cells) [161] and SNAI2/3 have been demonstrated to play functionally redundant roles in B and T cell development [162].
From an AML perspective, SNAI1 has been found to be overexpressed broadly in both primary AML samples and cell lines irrespective of the driver mutations [163] present. shRNA-mediated knock-down (KD) of SNAI1 in human AML cell lines was found to lead to enhanced morphological differentiation as assayed by May–Grunwald–Giemsa staining analysis and increased mature CD11B (Integrin αM protein) myeloid marker expression in flow cytometry analysis [163], similar to the effects associated with ZEB2 KD [142]. Also, tamoxifen-mediated knockout of murine Snai1 significantly improved the survival of mice transplanted with MLL-AF9 as well as AML-ETO/N-RAS models of AML [164], also similar to ZEB2 knockouts [130].
Mechanistically, increased mouse Snai1 was demonstrated to alter myeloid development and lead to the enhanced self-renewal of myeloid progenitors [163]. Vav-iCre, R26-Snai1Tg mice go on to develop a myeloproliferative disorder that progresses to full AML transformation, with 50% of these mice succumbing to AML by 400 days [163]. These effects on myeloid differentiation were demonstrated to be due to binding to KDM1A (LSD1), as point mutants in the SNAG (Snail1/GFI) protein domain that ablated LSD1 binding while still preserving protein stability did not alter myeloid development [163]. Also, RNA-seq and ChIP-seq experiments demonstrated that increased SNAI1 expression leads to enhanced recruitment of LSD1 to repress SNAI1 target genes, potentially at the expense of other key transcriptional regulators that require LSD1 for ensuring normal hematopoiesis such as GFI-1 (Growth Factor Independent 1 Transcriptional Repressor) proteins [163,165].

7. LSD1 and Other Potential Therapeutic Targets

The ability of EMT transcription factors to alter LSD1 function is an emerging theme in AML and other leukemias such as ETP-ALL, as ZEB2 has previously been demonstrated to interact with LSD1 [139,166] in both of these settings. Within the ETP-ALL context, increasing levels of ZEB2 were shown to be associated with increased susceptibility to LSD1 inhibitors [166]. The same likely holds true for the levels of SNAI1 and ZEB2 in human AML. LSD1 inhibitor therapy is an emerging promising new cancer therapy not only in AML [166] but other solid forms of cancer including Non-Small Cell Lung Cancer (NSCLC) and childhood sarcomas [164,167]. Whether or not EMT-TF levels also drive LSD1 inhibitor sensitivity in solid tumor settings remains to be determined.
Like other monotherapies, resistance mechanisms to LSD1 inhibition are likely to occur. As an example, ZEB2 has been demonstrated to upregulate IL-7R expression, which may be part of its ability to transform T cells [120,168]. Enhanced IL-7 signaling has recently emerged as a resistance mechanism for developing LSD1 inhibitor resistance [169], as the IL-7R pathway drives increased JAK/STAT signaling and increases the amount of the pro-survival BCL2 protein. ZEB2-LSD1 complexes in ETP-ALL were shown to repress pro-apoptotic BIM protein levels. Therefore, combination therapies using LSD1i with JAK/BCL2 inhibition were demonstrated to be synergistic in treating ETP-ALL in vitro and in vivo in patient-derived xenotransplant settings [169]; this combination was demonstrated to shift the balance of survival factors towards pro-apoptotic programs.
IL-7 is not known to be expressed in AML; however, ZEB2 has been demonstrated to modulate other myeloid-relevant cytokines such as IL-6 and G-CSF [128], and SNAI1 may enhance TNF/NFkb signaling [163], which may activate similar pro-survival pathways in AML.
Overall, as we learn more about this crosstalk, the ability of ZEB and SNAI family members to influence key epigenetic modulators such as LSD1 and control key cytokine signaling pathways may offer new therapeutic options for treating AML. The roles of SNAI and ZEB proteins are summarized in Table 2. In addition, the ability of ZEB and SNAI proteins to control genes involved in adhesion and migration that may also offer new therapeutic avenues in AML.

8. Role of SNAI2 in AML

It has been shown that SNAI2, like SNAI1, is closely linked with the progression and treatment response of leukemia. SNAI2 promotes leukemogenesis, and its loss or pharmacological inhibition impairs leukemic stem cell (LSC) self-renewal and delays leukemia progression. At the transcriptional level, Slc13A3, a direct target of SNAI2 in LSCs, restricts the self-renewal of LSCs and significantly prolongs recipient survival, highlighting its potential as a therapeutic target [170]. Furthermore, SNAI2’s involvement in chemoresistance complicates treatment strategies; its expression is associated with robust resistance to conventional chemotherapy in LSCs, underscoring the need for targeted therapies that can overcome this barrier [171]. Taken together, these studies underscore SNAI2’s oncogenic role in leukemia biology, influencing stem cell dynamics and conferring drug resistance, each aspect offering potential opportunities for therapeutic intervention.

9. Role of TWIST1 in AML

TWIST1, a transcription factor, is central to the pathophysiology of acute myeloid leukemia (AML), affecting multiple biological processes that govern disease progression and treatment response. TWIST1 promotes cell growth, drug resistance, and progenitor clonogenic capacities in myeloid leukemia, and it is linked to poor prognostic factors [172]. In line with this, a recent study demonstrated TWIST1 expression and promoter methylation levels were significantly upregulated in AML tissues and cell lines, and its expression was further downregulated by using demethylating agent 5′-azacitidine (5-Aza)-treated cells, leading to apoptosis [173]. The PI3K/AKT signaling pathway was positively regulated by Twist1, suggesting that Twist1 serves as an oncogene in AML.
Moreover, TWIST1 is notably involved in the extramedullary manifestations of AML, where it significantly promotes tissue invasion and metastasis. Treatments with TWIST1-siRNA or metformin downregulate TWIST1, including SNAI2, which is associated with significant impairment of migration and invasion processes [174]. TWIST1 is also essential for the viability and self-renewal of leukemia stem cells (LSCs), especially in MLL-AF9 leukemia, thus promoting disease initiation and maintenance [175]. The role of TWIST1 is not only restricted to LSCs since it has been demonstrated that TWIST1 influences bone marrow microenvironment interactions by modulating mesenchymal stem cell differentiation, which in turn promotes leukemia expansion [176]. In line with the latter, the role of TWIST1 in promoting AML is also seen in the recruitment of regulatory T cells within the tumor microenvironment, potentially providing new targets for immunotherapeutic approaches [177].
TWIST1’s role extends to chemoresistance, where it interacts with DNA methyltransferase 3a (DNMT3a) to regulate resistance to decitabine, a key therapeutic agent in treating AML [178]. This interaction underscores the potential for targeting TWIST1 in therapeutic strategies aimed at overcoming chemoresistance.
In summary, the extensive involvement of TWIST1 in AML suggests its utility not only as a biomarker for disease progression and treatment response but also as a promising target for therapeutic intervention. This could lead to the development of more personalized and effective treatment strategies for AML, transforming current paradigms and improving patient outcomes [172]. A comparative overview of EMT factors and their roles in AML are presented in Table 3.

10. Spread of AML Cells

In this section, we review some of the most studied molecular components of microenvironments responsible for AML spread and extramedullary hematopoiesis. AML, as a liquid tumor, inherently possesses greater mobility and penetration capabilities than solid tumors. Still, AML cells require robust molecular mechanisms for invading other bone marrow sites or establishing Extramedullary Engraftment (hereafter referred to as EME) [179]. Certain molecular factors involved in AML-EME can hinder immunotherapy effectiveness and protect AML cells within the bone marrow [180]. Others enhance engraftment properties, facilitate cell motility, and enable the transition of AML cells between the bone marrow and bloodstream, contributing to EME [181,182].
A critical area of focus is the role of EMT factors in AML-EME, which may elucidate aspects of the disease’s aggressive progression. A recent study using RNA-seq analyses to compare gene expression between AML patients with and without relapse identified EMT-related genes such as CDH2 [183], LOX [184], and COL3A1 [185,186,187] as strong correlates of AML prognosis and EME. CDH2, also known as N-cadherin, plays a pivotal role in cell adhesion and motility, thereby enhancing the potential for leukemic cells to invade distant tissues. Similarly, LOX and COL3A1, which are crucial to extracellular matrix (ECM) functionality, support the structural dynamics necessary for tumor metastasis and invasion [186].

11. Intravasation and Extravasation Mechanisms of AML

The mechanism by which AML cells gain the ability to extravasate from the bone marrow and into the bloodstream marks the beginning of AML-EME. A key component in this process is the formation of invadosomes, cellular structures in cancer cells that degrade the ECM and facilitate entry into the bloodstream [188]. These structures are also crucial during extravasation, where AML cells must breach the endothelial cell barrier to exit the vasculature and invade surrounding tissues. The transformation of AML cell structures into invadopodia, actin-based membrane protrusions capable of degrading the ECM, is critical for penetration through the vasculature endothelium. Invadopodia also recruit ECM proteases, aiding this process [189,190]. These actin-based membrane protrusion structures can degrade the ECM and cause cell penetration through the endothelium of vasculature and, in addition, invadopodia can recruit ECM proteases that contribute to this process [191].
Proteins commonly found in invadopodia include cortactin [192], actin filament nucleating proteins like N-WASP (Neural Wiskott–Aldrich Syndrome protein) [193], scaffold proteins such as Tks4 protein (Tyrosine Kinase Substrate With Four SH3 Domains, SH3PXD2B gene) [194], Tks5 (SH3 and PX domains 2A protein, SH3PXD2A gene) [194,195], and various metalloproteases [196]. These proteins work together to facilitate cell motility and ECM degradation, enabling intravasation and extravasation in metastatic AML, including other leukemias [197,198]. The Vascular Endothelial Growth Factor (VEGF gene) produced by AML cells induces bone marrow degradation, specifically targeting laminin and type IV collagen, and promoting vessel sprouting [199]. This process creates thin ECM “hotspots”, making these sites more susceptible to invasion by AML cells [200]. Once relocated to other bone marrow sites, AML cells can grow by re-establishing their initial niche microenvironments.
From a mechanistic perspective, the Myocardin-Related Transcription Factors and Serum-Response Factor (MRTF-SRF) pathway mediates some migration properties of AML cells and is notably present in the MLL-AF9 model [201]. E-selectin, a surface glycoprotein expressed by the vasculature [202], binds to ligands on both normal immune and AML cells. Activated endothelial cells expressing E-selectin may signal AML cell attachment and facilitate intravasation, working in conjunction with motility strategies [200]. While in the bloodstream, AML cells require additional molecular tools to evade immune detection. SETDB1 (the SETB1 Protein), a lysine methyltransferase key in epigenetic regulation, helps AML cells escape immune response by methylating retrotransposons [203]. While SETDB1 can repress tumorigenic genes, it also enables AML cells to evade immune detection [203,204]. Similarly, CD36 (the CD36 Protein), a multifunctional scavenger receptor, is linked to EME dissemination and increased relapse risk post-chemotherapy. Blocking the CD36 protein delays AML relapse, while binding of thrombospondin 1 (TSP-1, the THBS1 gene) to CD36 promotes AML migration [205]. Altogether, these findings suggest that a balance is required between molecular properties for migration and those that improve homing and treatment resistance.
During extramedullary invasion, AML cells may adhere to microenvironments near critical organs during their journey through the bloodstream, initiating extramedullary colonization [206]. The survival of AML cells within the bone marrow depends on the chemokine Stromal Cell-Derived Factor (the SDF-1 protein, the CXCL12 gene), which acts as a survival and attachment factor within the bone [207]. SDF-1 is produced by stromal cells in the spleen, bone marrow, and extramedullary sites like the skin and central nervous system, facilitating AML cell attachment outside the bone marrow [208]. This aspect of AML is less studied than in ALL.
Interestingly, SDF-1 receptor (the CXCR4 gene) is expressed variably among AML cells [209]. AML cells show lower CXCR4 expression compared with normal bone marrow cells [210], suggesting that reduced CXCR4 expression is linked to loss of bone marrow attachment. Blocking CXCR4 increases AML cell migration, indicating CXCR4’s role in regulating bone marrow niche adherence [182]. Additionally, poor prognosis in AML patients is associated with the expression of CXCR4 or E-selectin [211]. ZEB2, a regulator of CXCR4, therefore emerges as a potential target in the EME process [127,139].
Regarding the extravasation process, there is an opportunity for targeted therapies. Extravasation by E-selectin is reduced by the action of Uproleselan, an E-selectin antagonist that also induces AML cell mobilization from the bone marrow into the bloodstream, making them more vulnerable to chemotherapy [212]. On the other hand, Integrin β2, expressed by AML cells, binds to Matrix Metalloprotease 2 (the MMP2 gene), which is responsible for extramedullary cell invasion and metastasis by degrading the ECM [188]. Altogether these findings highlight the complexity of AML metastasis and suggest novel potential targets for therapeutic intervention. An analysis of the referred molecular factors that significantly impact the behavior of AML cells are presented in Table 4.
AML-EME can manifest as sarcomas, which are solid myeloblasts proliferating outside the bone marrow. This occurs in approximately 2.5–9.1% of adults with AML [214]. However, certain AML subtypes, such as those involving the t(8;21) translocation, show a higher incidence of AML-EME, as reported in 18–24% of cases [215]. Locations reported include soft tissues, ovaries, intestines, testes, breasts, lymph nodes, renal masses, and eyes, but the most common ones are soft tissue and lymph nodes [215]. CD56, a Neural Cell Adhesion Molecule (NCAM1 gene) commonly expressed in the brain, has been consistently linked to poor prognosis in AML [216,217,218]. The brain, considered a sanctuary tissue, is often associated with a poor leukemia prognosis [218].
The infiltration of AML-EME cells into the central nervous system (CNS), including the skull, meninges, and brain, is considered rare, though its incidence may be underestimated because of infrequent diagnostic procedures [219]. The most documented cases involve cranial bone marrow infiltration by AML cells. For example, a patient case report indicated a bone marrow replacement disorder in the skull’s bone marrow, leading to an AML diagnosis [219]. Notably, CNS involvement is more common in pediatric AML than in adult cases [220]. Key risk factors for CNS involvement in AML include complex karyotypes, AML relapse, FAB M5 classification, high LDH levels (Lactate Dehydrogenase A, LDHA), the presence of other extramedullary AML manifestations, and FLT3-ITD mutations [221]. In contrast, CNS involvement in APL (Acute Promyelocytic Leukemia) typically presents as meningeal leukemia and is more frequently observed [214].
In summary, the role of epithelial–mesenchymal transition (EMT) factors is particularly notable in AML-EME, impacting prognosis and disease progression. Genes like CDH2, LOX, and COL3A1 have been identified as key correlates of AML-EME. Also, intravasation and extravasation mechanisms, including the formation of invadosomes and invadopodia, are crucial in the spread of AML cells. These mechanisms are supported by proteins such as cortactin, N-WASP, Tks4, Tks5, and metalloproteases, which facilitate cell motility and degrade the extracellular matrix. Adaptation to new tissue environments requires AML cells to evade immune detection by many of the discussed mechanisms. In conclusion, understanding the molecular mechanisms behind AML’s EME ability is crucial. This knowledge provides insight into potential therapeutic targets and strategies to combat the spread of AML, particularly in challenging cases involving extramedullary sites including CNS involvement.
The overall roles of EMT-TFs in normal hematopoiesis, AML transformation and EME are summarized in Figure 2.

12. Overall Conclusions and Future Directions

AML, with its profound genetic, molecular, and clinical heterogeneity, continues to pose significant challenges in oncology. This review explored the complex landscape of AML, considering the current disease classification, molecular characteristics, and the dynamic mechanisms that drive its aggressive progression and spread. The presence of genetic aberrations, such as FLT3, NPM1 mutations, and MLL-AF9 gene fusion, are pivotal in predicting the prognosis, relapse, and therapeutic responses in AML, emphasizing the crucial role of personalized medicine in its management.
The exploration of EMT factors, particularly the ZEB, SNAI, and TWIST gene families, reveals promising avenues for new therapeutic targets. Their significant roles in regulating hematopoiesis and influencing AML’s aggressive EME behaviors highlight potential innovative treatment strategies that could target these pathways. Furthermore, understanding the molecular mechanisms that facilitate AML-EME—including the adaptation of AML cells to various microenvironments and their ability to evade immune surveillance—is essential. This knowledge opens new avenues for research and therapeutic interventions, which are crucial for developing novel strategies to manage and potentially overcome the aggressive nature of this malignancy.
The need to enhance the precision of genetic and molecular diagnostics is crucial for accurately categorizing AML subtypes and predicting treatment responses. Current strategies for stratifying AML increasingly rely on next-generation sequencing (NGS) and other genomic technologies. These methods, including targeted gene panels and low-coverage whole genome sequencing, provide a more efficient classification of leukemia, pushing the boundaries of precision medicine. Such advancements not only improve diagnostic accuracy but also facilitate the development of targeted therapeutic strategies in AML.
Additionally, the development of targeted therapies that address the unique molecular aberrations of each AML subtype is critical. This approach may include novel drug combinations and advanced immunotherapies, including novel gene-editing technologies. Given the significant role of the bone marrow microenvironment in the progression of AML, targeting this niche presents a promising strategy to combat the disease. The exploration of EME and CNS involvement in AML also requires further investigation to develop effective treatments for these particularly challenging manifestations of the disease.
Lastly, AML’s management requires a multifaceted approach that integrates genetics, molecular biology, and innovative therapeutic strategies. Future research and clinical approaches should aim to incorporate these elements, moving towards more personalized and effective treatment modalities for patients afflicted with this complex form of leukemia.

Author Contributions

Conceptualization, D.C., R.A., A.A., A.A.H., A.R.-B., C.F., J.J.H. and T.C.; investigation, D.C., R.A., A.R.-B., A.A., A.A.H., C.F., J.J.H. and T.C.; writing—original draft preparation, D.C., R.A., A.A., A.A.H., A.R.-B., C.G., V.G.-P., C.F., J.J.H. and T.C.; writing—review and editing, A.R.-B., C.F., J.J.H., T.C., V.G.-P. and C.G.; visualization, C.F., R.A. and J.J.H.; funding acquisition, C.F. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by ANID SIA/PAI program code SA77210106: Estudio de los factores de transcripción ZEB1 y ZEB2 en el desarrollo de células madre leucémicas para descubrir nuevos blancos terapéuticos contra la leucemia mieloide aguda (LMA). J.J.H. was supported by Canadian Institutes for Health Research (CIHR) project grants program and CancerCare Manitoba Foundation (CCMF).

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

AMLacute myeloid leukemia
WHOWorld Health Organization
MLL-AF9Mixed-Lineage Leukemia-AF9 fusion protein
EMTepithelial-to-mesenchymal transition
EMT-TFsepithelial-to-mesenchymal transition transcription factors
FABFrench–American–British
APLAcute Promyelocytic Leukemia
PML-RARαPromyelocytic Leukemia-Retinoic Acid Receptor Alpha
ATRAall-trans retinoic acid
ATOarsenic trioxide
MDSmyelodysplastic syndrome
TP53Tumor Protein 53
ELNElastin
HSCshematopoietic stem cells
BMbone marrow
PBperipheral blood
RUNX1::RUNX1T1Runt-Related Transcription Factor 1–RUNX1 Translocation Partner 1
CBFB::MYH11Core-Binding Factor Beta Subunit–Myosin Heavy Chain 11
BCR::ABL1Breakpoint Cluster Region–Abelson Tyrosine Kinase 1
CEBPACCAAT/Enhancer Binding Protein Alpha
VAFvariant allele fraction
MLLT3MLLT3 super elongation complex subunit
NMRnuclear magnetic resonance
H3K4histone H3 lysine 4
HSPCshematopoietic stem and progenitor cells
DOT1LDisruptor of Telomeric Silencing 1-Like Protein
ETORUNX1 partner transcriptional co-repressor 1
TOP2Topoisomerase II
DSBsdouble-strand breaks
NSCLCNon-Small Cell Lung Cancer
WBCsWhite Blood Cells
AKT/mTORAKT Serine/Threonine Kinase/Mechanistic Target of Rapamycin
ZEBZinc Finger E-Box Binding Homeobox
CTBPC-Terminal Binding Protein
SLc13A3Solute Carrier Family 13 Member 3
CD36Cluster of Differentiation 36
THBS1thrombospondin 1
IL-17Interleukin 17
SOCS2Suppressor of Cytokine Signaling 2
TGF-βTransforming Growth Factor Beta
CXCR4C-X-C Motif Chemokine Receptor 4
CDH2cadherin 2
LOXLysyl Oxidase
COL3A1Collagen Type III Alpha 1 Chain
MRTF-SRFMyocardin-Related Transcription Factors and Serum-Response Factor
SDF-1Stromal Cell-Derived Factor 1
CXCL12C-X-C Motif Chemokine Ligand 12
NPM1Nucleophosmin 1
FLT3-ITDFms-Like Tyrosine Kinase 3-Internal Tandem Duplication
LDHLactate Dehydrogenase
LDHALactate Dehydrogenase A
SF3B1splicing factor 3b subunit 1
circRNAsCircular RNAs
MALAT1Metastasis-Associated Lung Adenocarcinoma Transcript 1
HoxHomeobox
LSD1lysine-specific demethylase 1
GFI1Growth Factor Independent 1
miRNAmicroRNA
CRISPR/Cas9Clustered Regularly Interspaced Short Palindromic Repeats/CRISPR Associated Protein 9
lncRNAlong non-coding RNA
TGFTransforming Growth Factor
CD8Cluster of Differentiation 8
TGF-βTransforming Growth Factor Beta
VEGFVascular Endothelial Growth Factor
SETDB1SET Domain Bifurcated Histone Lysine Methyltransferase 1
N-WASPNeural Wiskott–Aldrich Syndrome Protein
Tks4Tyrosine Kinase Substrate With Four SH3 Domains
Tks5SH3 and PX Domains 2A Protein
G-CSFGranulocyte Colony-Stimulating Factor
IL-6Interleukin 6
LDS1lysine-specific histone demethylase 1A
GATA2GATA Binding Protein 2
MECOMMDS1 and EVI1 Complex Locus
DEKDEK oncogene
NUP214Nucleoporin 214

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. Chennamadhavuni, A.; Lyengar, V.; Mukkamalla, S.K.R.; Shimanovsky, A. Leukemia. In StatPearls [Internet]; StatPearls Publishing: Treasure Island, FL, USA, 2023. [Google Scholar]
  3. Clarkson, B.; Strife, A.; Wisniewski, D.; Lambek, C.L.; Liu, C. Chronic myelogenous leukemia as a paradigm of early cancer and possible curative strategies. Leukemia 2003, 17, 1211–1262. [Google Scholar] [CrossRef] [PubMed]
  4. Pasternak, G.; Hochhaus, A.; Schultheis, B.; Hehlmann, R. Chronic myelogenous leukemia: Molecular and cellular aspects. J. Cancer Res. Clin. Oncol. 1998, 124, 643–660. [Google Scholar] [CrossRef] [PubMed]
  5. Davis, A.S.; Viera, A.J.; Mead, M.D. Leukemia: An overview for primary care. Am. Fam. Physician 2014, 89, 731–738. [Google Scholar] [PubMed]
  6. Vakiti, A.; Reynolds, S.B.; Mewawalla, P. Acute Myeloid Leukemia. In StatPearls [Internet]; StatPearls: Treasure Island, FL, USA, 2023. Available online: https://www.ncbi.nlm.nih.gov/books/NBK507875/ (accessed on 6 August 2024).
  7. Bray, F.; Ferlay, J.; Soerjomataram, I.; Siegel, R.L.; Torre, L.A.; Jemal, A. Global cancer statistics 2018: GLOBOCAN estimates ofincidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J. Clin. 2018, 68, 394–424. [Google Scholar] [CrossRef] [PubMed]
  8. Dohner, H.; Weisdorf, D.J.; Bloomfield, C.D. Acute Myeloid Leukemia. N. Engl. J. Med. 2015, 373, 1136–1152. [Google Scholar] [CrossRef] [PubMed]
  9. Reikvam, H.; Hatfield, K.J.; Kittang, A.O.; Hovland, R.; Bruserud, Ø. Acute Myeloid Leukemia with the t(8;21) Translocation: Clinical Consequences and Biological Implications. BioMed Res. Int. 2011, 2011, 104631. [Google Scholar] [CrossRef] [PubMed]
  10. Tallman, M.S.; Kim, H.T.; Paietta, E.; Bennett, J.M.; Dewald, G.; Cassileth, P.A.; Wiernik, P.H.; Rowe, J.M. Acute Monocytic Leukemia (French-American-British classification M5) Does Not Have a Worse Prognosis Than Other Subtypes of Acute Myeloid Leukemia: A Report From the Eastern Cooperative Oncology Group. J. Clin. Oncol. 2004, 22, 1276–1286. [Google Scholar] [CrossRef]
  11. De Rossi, G.; Avvisati, G.; Coluzzi, S.; Fenu, S.; LoCoco, F.; Lopez, M.; Nanni, M.; Pasqualetti, D.; Mandelli, F. Immunological definition of acute promyelocyte leukemia (FAB M3): A study of 39 cases. Eur. J. Haematol. 1990, 45, 168–171. [Google Scholar] [CrossRef]
  12. Randolph, T.R. Acute promyelocytic leukemia (AML-M3)—Part 1: Pathophysiology, clinical diagnosis, and differentiation therapy. Clin. Lab. Sci. 2000, 13, 98–105. [Google Scholar] [PubMed]
  13. Randolph, T.R. Acute promyelocytic leukemia (AML-M3)—Part 2: Molecular defect, DNA diagnosis, and proposed models of leukemogenesis and differentiation therapy. Clin. Lab. Sci. 2000, 13, 106–116. [Google Scholar] [PubMed]
  14. Saeed, S.; Logie, C.; Stunnenberg, H.G.; Martens, J.H. Genome-wide functions of PML-RARalpha in acute promyelocytic leukaemia. Br. J. Cancer 2011, 104, 554–558. [Google Scholar] [CrossRef] [PubMed]
  15. Delaunay, J.; Vey, N.; Leblanc, T.; Fenaux, P.; Rigal-Huguet, F.; Witz, F.; Lamy, T.; Auvrignon, A.; Blaise, D.; Pigneux, A.; et al. Prognosis of inv(16)/t(16;16) acute myeloid leukemia (AML): A survey of 110 cases from the French AML Intergroup. Blood 2003, 102, 462–469. [Google Scholar] [CrossRef] [PubMed]
  16. Plantier, I.; Lai, J.L.; Wattel, E.; Bauters, F.; Fenaux, P. Inv(16) may be one of the only ‘favorable’ factors in acute myeloid leukemia: A report on 19 cases with prolonged follow-up. Leuk. Res. 1994, 18, 885–888. [Google Scholar] [CrossRef] [PubMed]
  17. Varotto, E.; Munaretto, E.; Stefanachi, F.; Della Torre, F.; Buldini, B. Acute myeloid leukemia with the t(8;21) translocation: Clinical consequences and biological implications. J. Biomed. Biotechnol. Front. Pediatr. 2022, 10, 911093. [Google Scholar]
  18. De Boer, J.; Walf-Vorderwülbecke, V.; Williams, O. In focus: MLL-rearranged leukemia. Leukemia 2013, 27, 1224–1228. [Google Scholar] [CrossRef] [PubMed]
  19. Cowell, I.G.; Austin, C.A. DNA fragility at the KMT2A/MLL locus: Insights from old and new technologies. Open Biol. 2023, 13, 220232. [Google Scholar] [CrossRef] [PubMed]
  20. Meyer, C.; Hofmann, J.; Burmeister, T.; Gröger, D.; Park, T.S.; Emerenciano, M.P.; De Oliveira, M.P.; Renneville, A.; Villarese, P.; Macintyre, E.; et al. The MLL recombinome of acute leukemias in 2013. Leukemia 2013, 27, 2165–2176. [Google Scholar] [CrossRef] [PubMed]
  21. Zuo, Z.; Polski, J.M.; Kasyan, A.; Medeiros, L.J. Acute erythroid leukemia. Arch. Pathol. Lab. Med. 2010, 134, 1261–1270. [Google Scholar] [CrossRef] [PubMed]
  22. Cervera, N.; Lhoumeau, A.-C.; Adélaïde, J.; Guille, A.; Murati, A.; Mozziconacci, M.-J.; Vey, N.; Birnbaum, D.; Gelsi-Boyer, V. Acute erythroid leukemias have a distinct molecular hierarchy from non-erythroid acute myeloid leukemias. Haematologica 2020, 105, e340–e342. [Google Scholar] [CrossRef] [PubMed]
  23. Santos, F.P.; Faderl, S.; Garcia-Manero, G.; Koller, C.; Beran, M.; O’Brien, S.; Pierce, S.; Freireich, E.J.; Huang, X.; Borthakur, G.; et al. Adult acute erythroleukemia: An analysis of 91 patients treated at a single institution. Leukemia 2009, 23, 2275–2280. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  24. Gassmann, W.; Löffler, H. Acute megakaryoblastic leukemia. Leuk. Lymphoma 1995, 18, 69–73. [Google Scholar] [CrossRef] [PubMed]
  25. Dima, D.; Oprita, L.; Rosu, A.-M.; Trifa, A.; Selicean, C.; Moisoiu, V.; Frinc, I.; Zdrenghea, M.; Tomuleasa, C. Adult acute megakaryoblastic leukemia: Rare association with cytopenias of undetermined significance and p210 and p190 BCR–ABL transcripts. OncoTargets Ther. 2017, 10, 5047–5051. [Google Scholar] [CrossRef] [PubMed]
  26. Hwang, S.M. Classification of acute myeloid leukemia. Blood Res. 2020, 55, S1–S4. [Google Scholar] [CrossRef] [PubMed]
  27. Arber, D.A. The 2016 WHO classification of acute myeloid leukemia: What the practicing clinician needs to know. Semin. Hematol. 2019, 56, 90–95. [Google Scholar] [CrossRef] [PubMed]
  28. Vardiman, J.W.; Thiele, J.; Arber, D.A.; Brunning, R.D.; Borowitz, M.J.; Porwit, A.; Harris, N.L.; Le Beau, M.M.; Hellström-Lindberg, E.; Tefferi, A.; et al. The 2008 revision of the World Health Organization (WHO) classification of myeloid neoplasms and acute leukemia: Rationale and important changes. Blood 2009, 114, 937–951. [Google Scholar] [CrossRef] [PubMed]
  29. Marks, J.A.; Wang, X.; Fenu, E.M.; Bagg, A.; Lai, C. TP53 in AML and MDS: The new (old) kid on the block. Blood Rev. 2023, 60, 101055. [Google Scholar] [CrossRef] [PubMed]
  30. Daver, N.G.; Iqbal, S.; Renard, C.; Chan, R.J.; Hasegawa, K.; Hu, H.; Tse, P.; Yan, J.; Zoratti, M.J.; Xie, F.; et al. Treatment outcomes for newly diagnosed, treatment-naive TP53-mutated acute myeloid leukemia: A systematic review and meta-analysis. J. Hematol. Oncol. 2023, 16, 19. [Google Scholar] [CrossRef] [PubMed]
  31. Shimony, S.; Stahl, M.; Stone, R.M. Acute myeloid leukemia: 2023 update on diagnosis, risk-stratification, and management. Am. J. Hematol. 2023, 98, 502–526. [Google Scholar] [CrossRef] [PubMed]
  32. Huber, S.; Baer, C.; Hutter, S.; Dicker, F.; Meggendorfer, M.; Pohlkamp, C.; Kern, W.; Haferlach, T.; Haferlach, C.; Hoermann, G. AML classification in the year 2023: How to avoid a Babylonian confusion of languages. Leukemia 2023, 37, 1413–1420. [Google Scholar] [CrossRef]
  33. Cicconi, L.; Platzbecker, U.; Avvisati, G.; Paoloni, F.; Thiede, C.; Vignetti, M.; Fazi, P.; Ferrara, F.; Divona, M.; Albano, F.; et al. Long-term results of all-trans retinoic acid and arsenic trioxide in non-high-risk acute promyelocytic leukemia: Update of the APL0406 Italian-German randomized trial. Leukemia 2020, 34, 914–918. [Google Scholar] [CrossRef] [PubMed]
  34. Sanz, M.A.; Montesinos, P. Risk-Adapted Treatment for Low- and Intermediate-Risk Acute Promyelocytic Leukemia. Clin. Lymphoma Myeloma Leuk. 2010, 10 (Suppl. S3), S130–S134. [Google Scholar] [CrossRef] [PubMed]
  35. Cicconi, L.; Testi, A.M.; Montesinos, P.; Rego, E.; Zhu, H.H.; Takahashi, H.; Dworzak, M.; Estey, E.; Schwarer, A.; Esteve, J.; et al. Characteristics and outcome of acute myeloid leukemia with uncommon retinoic acid receptor-alpha (RARA) fusion variants. Blood Cancer J. 2021, 11, 167. [Google Scholar] [CrossRef]
  36. Fan, G.L.; Jiang, P.J.; Yuan, M. Clinical Prognostic Factors Analysis of Initially Treated AML Children with t (8;21)/RUNX1-RUNX1T1. Zhongguo Shi Yan Xue Ye Xue Za Zhi 2020, 28, 1510–1515. [Google Scholar]
  37. Schnittger, S.; Bacher, U.; Haferlach, C.; Kern, W.; Haferlach, T. Rare CBFB-MYH11 fusion transcripts in AML with inv (16)/t (16;16) are associated with therapy-related AML M4eo, atypical cytomorphology, atypical immunophenotype, atypical additional chromosomal rearrangements and low white blood cell count: A study on 162 patients. Leukemia 2007, 21, 725–731. [Google Scholar] [CrossRef] [PubMed]
  38. Ye, Y.; Labopin, M.; Gérard, S.; Yakoub-Agha, I.; Blau, I.W.; Aljurf, M.; Forcade, E.; Gedde-Dahl, T.; Burns, D.; Vydra, J.; et al. Lower relapse incidence with haploidentical versus matched sibling or unrelated donor hematopoietic cell transplantation for core-binding factor AML patients in CR2: A study from the Global Committee and the Acute Leukemia Working Party of the European Society for Blood and Marrow Transplantation. Am. J. Hematol. 2024, 99, 1290–1299. [Google Scholar] [CrossRef] [PubMed]
  39. Van Weelderen, R.E.; Harrison, C.J.; Klein, K.; Jiang, Y.; Abrahamsson, J.; Alonzo, T.; Aplenc, R.; Arad-Cohen, N.; Bart-Delabesse, E.; Buldini, B.; et al. Optimized cytogenetic risk-group stratification of KMT2A-rearranged pediatric acute myeloid leukemia. Blood Adv. 2024, 8, 3200–3213. [Google Scholar] [CrossRef] [PubMed]
  40. Chiriches, C.; Nicolaisen, N.; Wieske, M.; Elhaddad, H.; Mehmetbeyoglu, E.; Alvares, C.; Becher, D.; Hole, P.; Ottmann, O.G.; Ruthardt, M. Understanding a high-risk acute myeloid leukemia by analyzing the interactome of its major driver mutation. PLOS Genet. 2022, 18, e1010463. [Google Scholar] [CrossRef] [PubMed]
  41. Lo, M.; Tsai, X.C.; Lin, C.; Tien, F.; Kuo, Y.; Lee, W.; Peng, Y.; Liu, M.; Tseng, M.; Hsu, C.; et al. Validation of the prognostic significance of the 2022 European LeukemiaNet risk stratification system in intensive chemotherapy treated aged 18 to 65 years patients with de novo acute myeloid leukemia. Am. J. Hematol. 2023, 98, 760–769. [Google Scholar] [CrossRef] [PubMed]
  42. Ikeda, D.; Chi, S.; Uchiyama, S.; Nakamura, H.; Guo, Y.-M.; Yamauchi, N.; Yuda, J.; Minami, Y. Molecular Classification and Overcoming Therapy Resistance for Acute Myeloid Leukemia with Adverse Genetic Factors. Int. J. Mol. Sci. 2022, 23, 5950. [Google Scholar] [CrossRef] [PubMed]
  43. Rørvik, S.D.; Torkildsen, S.; Bruserud, Ø.; Tvedt, T.H.A. Acute myeloid leukemia with rare recurring translocations—An overview of the entities included in the international consensus classification. Ann. Hematol. 2024, 103, 1103–1119. [Google Scholar] [CrossRef] [PubMed]
  44. Branford, S.; Yeung, D.T.; Parker, W.T.; Roberts, N.D.; Purins, L.; Braley, J.A.; Altamura, H.K.; Yeoman, A.L.; Georgievski, J.; Jamison, B.A.; et al. Prognosis for patients with CML and >10% BCR-ABL1 after 3 months of imatinib depends on the rate of BCR-ABL1 decline. Blood 2014, 124, 511–518. [Google Scholar] [CrossRef] [PubMed]
  45. Othman, J.; Potter, N.; Ivey, A.; Tazi, Y.; Papaemmanuil, E.; Jovanovic, J.; Freeman, S.D.; Gilkes, A.F.; E Gale, R.; Rapoz-D’Silva, T.; et al. Molecular, clinical and therapeutic determinants of outcome in NPM1 mutated AML. Blood J. 2024. [Google Scholar] [CrossRef] [PubMed]
  46. Tien, F.-M.; Hou, H.-A. CEBPA mutations in acute myeloid leukemia: Implications in risk stratification and treatment. Int. J. Hematol. 2024, 1–7. [Google Scholar] [CrossRef] [PubMed]
  47. Yuan, X.L.; Wu, Y.B.; Song, X.L.; Chen, Y.; Lu, Y.; Lai, X.Y.; Shi, J.M.; Liu, L.Z.; Zhao, Y.M.; Yu, J.; et al. Efficacy and prognostic factors of allogeneic hematopoietic stem cell transplantation in the treatment of secondary acute myeloid leukemia. Chin. J. Hematol. 2024, 45, 41–47. [Google Scholar] [CrossRef]
  48. Tsai, X.C.-H.; Sun, K.-J.; Lo, M.-Y.; Tien, F.-M.; Kuo, Y.-Y.; Tseng, M.-H.; Peng, Y.-L.; Chuang, Y.-K.; Ko, B.-S.; Tang, J.-L.; et al. Poor prognostic implications of myelodysplasia-related mutations in both older and younger patients with de novo AML. Blood Cancer J. 2023, 13, 1–11. [Google Scholar] [CrossRef] [PubMed]
  49. Kawankar, N.; Vundinti, B.R. Cytogenetic abnormalities in myelodysplastic syndrome: An overview. Hematology 2011, 16, 131–138. [Google Scholar] [CrossRef] [PubMed]
  50. Fuhrmann, I.; Lenk, M.; Haferlach, T.; Stengel, A.; Hutter, S.; Baer, C.; Meggendorfer, M.; Kern, W.; Haferlach, C. AML, NOS and AML-MRC as defined by multilineage dysplasia share a common mutation pattern which is distinct from AML-MRC as defined by MDS-related cytogenetics. Leukemia 2022, 36, 1939–1942. [Google Scholar] [CrossRef] [PubMed]
  51. Zhao, H.; Dong, Z.; Wan, D.; Cao, W.; Xing, H.; Liu, Z.; Fan, J.; Wang, H.; Lu, R.; Zhang, Y.; et al. Clinical characteristics, treatment, and prognosis of 118 cases of myeloid sarcoma. Sci. Rep. 2022, 12, 1–10. [Google Scholar] [CrossRef] [PubMed]
  52. Takahashi, S.; Yokoyama, A. The molecular functions of common and atypical MLL fusion protein complexes. Biochim. Biophys. Acta Gene Regul. Mech. 2020, 1863, 194548. [Google Scholar] [CrossRef] [PubMed]
  53. Iacobucci, I.; Mullighan, C.G. KMT2A-rearranged leukemia: The shapeshifter. Blood 2022, 140, 1833–1835. [Google Scholar] [CrossRef] [PubMed]
  54. Jiang, H. The complex activities of the SET1/MLL complex core subunits in development and disease. Biochim Biophys Acta Gene Regul Mech. 2020, 1863, 194560. [Google Scholar] [CrossRef] [PubMed]
  55. Thiel, A.T.; Blessington, P.; Zou, T.; Feather, D.; Wu, X.; Yan, J.; Zhang, H.; Liu, Z.; Ernst, P.; Koretzky, G.A.; et al. MLL-AF9-induced leukemogenesis requires coexpression of the wild-type Mll allele. Cancer Cell 2010, 17, 148–159. [Google Scholar] [CrossRef] [PubMed]
  56. Slany, R.K. The molecular biology of mixed lineage leukemia. Haematologica 2009, 94, 984–993. [Google Scholar] [CrossRef] [PubMed]
  57. Vedadi, M.; Blazer, L.; Eram, M.S.; Barsyte-Lovejoy, D.; Arrowsmith, C.H.; Hajian, T. Targeting human SET1/MLL family of proteins. Protein Sci. 2017, 26, 662–676. [Google Scholar] [CrossRef]
  58. Yang, W.; Ernst, P. SET/MLL family proteins in hematopoiesis and leukemia. Int. J. Hematol. 2016, 105, 7–16. [Google Scholar] [CrossRef] [PubMed]
  59. Cosgrove, M.S.; Patel, A. Mixed lineage leukemia: A structure–function perspective of the MLL1 protein. FEBS J. 2010, 277, 1832–1842. [Google Scholar] [CrossRef] [PubMed]
  60. Winters, A.C.; Bernt, K.M. MLL-Rearranged Leukemias—An Update on Science and Clinical Approaches. Front. Pediatr. 2017, 5, 4. [Google Scholar] [CrossRef] [PubMed]
  61. Li, X.; Song, Y. Structure, function and inhibition of critical protein–protein interactions involving mixed lineage leukemia 1 and its fusion oncoproteins. J. Hematol. Oncol. 2021, 14, 1–33. [Google Scholar] [CrossRef]
  62. Heuts, B.M.H.; Arza-Apalategi, S.; Alkema, S.G.; Tijchon, E.; Jussen, L.; Bergevoet, S.M.; van der Reijden, B.A.; Martens, J.H.A. Inducible MLL-AF9 Expression Drives an AML Program during Human Pluripotent Stem Cell-Derived Hematopoietic Differentiation. Cells 2023, 12, 1195. [Google Scholar] [CrossRef]
  63. Schoch, C.; Schnittger, S.; Klaus, M.; Kern, W.; Hiddemann, W.; Haferlach, T. AML with 11q23/MLL abnormalities as defined by the WHO classification: Incidence, partner chromosomes, FAB subtype, age distribution, and prognostic impact in an unselected series of 1897 cytogenetically analyzed AML cases. Blood 2003, 102, 2395–2402. [Google Scholar] [CrossRef]
  64. Hagag, A.A.; Shebl, S.S.; El-Fadaly, N.H. Frequency of 11q23/MLL gene rearrangement in Egyptian childhood acute myeloblastic leukemia: Biologic and clinical significance. South Asian J. Cancer 2014, 3, 206–208. [Google Scholar] [CrossRef]
  65. Marschalek, R. MLL, Life Sciences; Elsevier: Amsterdam, The Netherlands, 2017. [Google Scholar]
  66. Kabra, A.; Bushweller, J. The Intrinsically Disordered Proteins MLLT3 (AF9) and MLLT1 (ENL)—Multimodal Transcriptional Switches With Roles in Normal Hematopoiesis, MLL Fusion Leukemia, and Kidney Cancer. J. Mol. Biol. 2022, 434, 167117. [Google Scholar] [CrossRef]
  67. GeneCards. MLLT3 Gene. Available online: https://www.genecards.org/cgi-bin/carddisp.pl?gene=MLLT3 (accessed on 6 August 2024).
  68. Yi, Y.; Ge, S. Targeting the histone H3 lysine 79 methyltransferase DOT1L in MLL-rearranged leukemias. J. Hematol. Oncol. 2022, 15, 1–21. [Google Scholar] [CrossRef]
  69. Olsen, S.N.; Godfrey, L.; Healy, J.P.; Choi, Y.A.; Kai, Y.; Hatton, C.; Perner, F.; Haarer, E.L.; Nabet, B.; Yuan, G.C.; et al. MLL::AF9 degradation induces rapid changes in transcriptional elongation and subsequent loss of an active chromatin landscape. Mol. Cell 2022, 82, 1140–1155. [Google Scholar] [CrossRef]
  70. Stavropoulou, V.; Peters, A.H.F.M.; Schwaller, J. Aggressive leukemia driven by MLL-AF9. Mol. Cell. Oncol. 2017, 5, e1241854. [Google Scholar] [CrossRef]
  71. Francis, J.C.; Gardiner, J.R.; Renaud, Y.; Chauhan, R.; Weinstein, Y.; Gomez-Sanchez, C.; Lefrançois-Martinez, A.-M.; Bertherat, J.; Val, P.; Swain, A. HOX genes promote cell proliferation and are potential therapeutic targets in adrenocortical tumours. Br. J. Cancer 2020, 124, 805–816. [Google Scholar] [CrossRef]
  72. Myers, P. Hox Genes in Development: The Hox Code. Nat. Educ. 2008, 1, 2. [Google Scholar]
  73. Hubert, K.A.; Wellik, D.M. Hox genes in development and beyond. Development 2023, 150, dev192476. [Google Scholar] [CrossRef]
  74. Lappin, T.R.; Grier, G.D.; Thompson, A.; Halliday, H.L. HOX genes: Seductive science, mysterious mechanisms., HOX genes: Seductive science, mysterious mechanisms. Ulster Med. J. 2006, 75, 23–31. [Google Scholar] [PubMed Central]
  75. Luo, Z.; Rhie, S.K.; Farnham, P.J. The Enigmatic HOX Genes: Can We Crack Their Code? Cancers 2019, 11, 323. [Google Scholar] [CrossRef] [PubMed]
  76. A Alharbi, R.; Pettengell, R.; Pandha, H.S.; Morgan, R. The role of HOX genes in normal hematopoiesis and acute leukemia. Leukemia 2012, 27, 1000–1008. [Google Scholar] [CrossRef] [PubMed]
  77. Nagy, Á.; Ősz, Á.; Budczies, J.; Krizsán, S.; Szombath, G.; Demeter, J.; Bödör, C.; Győrffy, B. Elevated HOX gene expression in acute myeloid leukemia is associated with NPM1 mutations and poor survival. J. Adv. Res. 2019, 20, 105–116. [Google Scholar] [CrossRef] [PubMed]
  78. Aryal, S.; Zhang, Y.; Wren, S.; Li, C.; Lu, R. Molecular regulators of HOXA9 in acute myeloid leukemia. FEBS J. 2021, 290, 321–339. [Google Scholar] [CrossRef] [PubMed]
  79. Chen, S.-L.; Qin, Z.-Y.; Hu, F.; Wang, Y.; Dai, Y.-J.; Liang, Y. The Role of the HOXA Gene Family in Acute Myeloid Leukemia. Genes 2019, 10, 621. [Google Scholar] [CrossRef] [PubMed]
  80. Lindblad, O.; Chougule, R.A.; Moharram, S.A.; Kabir, N.N.; Sun, J.; Kazi, J.U.; Rönnstrand, L. The role of HOXB2 and HOXB3 in acute myeloid leukemia. Biochem. Biophys. Res. Commun. 2015, 467, 742–747. [Google Scholar] [CrossRef]
  81. Umeda, S.; Yamamoto, K.; Murayama, T.; Hidaka, M.; Kurata, M.; Ohshima, T.; Suzuki, S.; Sugawara, E.; Kawano, F.; Kitagawa, M. Prognostic significance of HOXB4 in de novo acute myeloid leukemia. Hematology 2012, 17, 125–131. [Google Scholar] [CrossRef] [PubMed]
  82. Afonja, O.; Smith, J.E., Jr.; Cheng, D.M.; Goldenberg, A.S.; Amorosi, E.; Shimamoto, T.; Nakamura, S.; Ohyashiki, K.; Ohyashiki, J.; Toyama, K.; et al. MEIS1 and HOXA7 genes in human acute myeloid leukemia. Leuk. Res. 2000, 24, 849–855. [Google Scholar] [CrossRef] [PubMed]
  83. Lachowiez, C.A.; Loghavi, S.; Kadia, T.M.; Daver, N.; Borthakur, G.; Pemmaraju, N.; Naqvi, K.; Alvarado, Y.; Yilmaz, M.; Short, N.; et al. Outcomes of older patients with NPM1-mutated AML: Current treatments and the promise of venetoclax-based regimens. Blood Adv. 2020, 4, 1311–1320. [Google Scholar] [CrossRef] [PubMed]
  84. Prange, K.H.M.; Mandoli, A.; Kuznetsova, T.; Wang, S.Y.; Sotoca, A.M.; Marneth, A.E.; van der Reijden, B.A.; Stunnenberg, H.G.; Martens, J.H. MLL-AF9 and MLL-AF4 oncofusion proteins bind a distinct enhancer repertoire and target the RUNX1 program in 11q23 acute myeloid leukemia. Oncogene 2017, 36, 3346–3356. [Google Scholar] [CrossRef] [PubMed]
  85. Ranieri, R.; Pianigiani, G.; Sciabolacci, S.; Perriello, V.M.; Marra, A.; Cardinali, V.; Pierangeli, S.; Milano, F.; Gionfriddo, I.; Brunetti, L.; et al. Current status and future perspectives in targeted therapy of NPM1-mutated AML. Leukemia 2022, 36, 2351–2367. [Google Scholar] [CrossRef] [PubMed]
  86. Sharma, N.; Liesveld, J.L. NPM 1 Mutations in AML—The Landscape in 2023. Cancers 2023, 15, 1177. [Google Scholar] [CrossRef] [PubMed]
  87. Wang, C.; Song, C.-M.; Liu, S.; Chen, L.-M.; Xue, S.-F.; Huang, S.-H.; Lin, H.; Liu, G.-H. ZFX-mediated upregulation of CEBPA-AS1 contributes to acute myeloid leukemia progression through miR-24-3p/CTBP2 axis. Cell Biol. Toxicol. 2023, 39, 2631–2645. [Google Scholar] [CrossRef]
  88. Chen, X.; Burkhardt, D.B.; Hartman, A.A.; Hu, X.; Eastman, A.E.; Sun, C.; Wang, X.; Zhong, M.; Krishnaswamy, S.; Guo, S. MLL-AF9 initiates transformation from fast-proliferating myeloid progenitors. Nat. Commun. 2019, 10, 5767. [Google Scholar] [CrossRef] [PubMed]
  89. Fortune, J.M.; Osheroff, N. Topoisomerase II as a target for anticancer drugs: When enzymes stop being nice. Prog. Nucleic Acid. Res. Mol. Biol. 2000, 64, 221–253. [Google Scholar] [CrossRef] [PubMed]
  90. Pommier, Y.; Leo, E.; Zhang, H.; Marchand, C. DNA Topoisomerases and Their Poisoning by Anticancer and Antibacterial Drugs. Chem. Biol. 2010, 17, 421–433. [Google Scholar] [CrossRef] [PubMed]
  91. Anand, U.; Dey, A.; Chandel, A.K.S.; Sanyal, R.; Mishra, A.; Pandey, D.K.; De Falco, V.; Upadhyay, A.; Kandimalla, R.; Chaudhary, A.; et al. Cancer chemotherapy and beyond: Current status, drug candidates, associated risks and progress in targeted therapeutics. Genes Dis. 2023, 10, 1367–1401. [Google Scholar] [CrossRef] [PubMed]
  92. 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 recommendations from an international expert panel on behalf of the ELN. Blood 2022, 140, 1345–1377. [Google Scholar] [CrossRef] [PubMed]
  93. Kerr, A.J.; Dodwell, D.; McGale, P.; Holt, F.; Duane, F.; Mannu, G.; Darby, S.C.; Taylor, C.W. Adjuvant and neoadjuvant breast cancer treatments: A systematic review of their effects on mortality. Cancer Treat. Rev. 2022, 105, 102375. [Google Scholar] [CrossRef] [PubMed]
  94. Cowell, I.G.; Austin, C.A. Do transcription factories and TOP2B provide a recipe for chromosome translocations in therapy-related leukemia? Cell Cycle 2012, 11, 3143–3144. [Google Scholar] [CrossRef]
  95. Pedersen-Bjergaard, J.; Andersen, M.K.; Christiansen, D.H.; Nerlov, C. Genetic pathways in therapy-related myelodysplasia and acute myeloid leukemia. Blood 2002, 99, 1909–1912. [Google Scholar] [CrossRef] [PubMed]
  96. Kollmannsberger, C.; Beyer, J.; Droz, J.P.; Harstrick, A.; Hartmann, J.T.; Biron, P.; Flechon, A.; Schoffski, P.; Kuczyk, M.; Schmoll, H.J.; et al. Secondary leukemia following high cumulative doses of etoposide in patients treated for advanced germ cell tumors. J. Clin. Oncol. 1998, 16, 3386–3391. [Google Scholar] [CrossRef] [PubMed]
  97. Pedersen-Bjergaard, J.; Daugaard, G.; Hansen, S.W.; Philip, P.; Larsen, S.O.; Rorth, M. Increased risk of myelodysplasia and leukaemia after etoposide, cisplatin, and bleomycin for germ-cell tumours. Lancet 1991, 338, 359–363. [Google Scholar] [CrossRef]
  98. Howard, R.; Gilbert, E.; Lynch, C.F.; Hall, P.; Storm, H.; Holowaty, E.; Pukkala, E.; Langmark, F.; Kaijser, M.; Andersson, M.; et al. Risk of leukemia among survivors of testicular cancer: A population-based study of 42,722 patients. Ann. Epidemiol. 2008, 18, 416–421. [Google Scholar] [CrossRef] [PubMed]
  99. Inoue, Y.; Nakamura, T.; Nakanishi, H.; Oishi, M.; Hongo, F.; Okihara, K.; Mizutani, S.; Kuroda, J.; Ukimura, O. Therapy-related acute myeloid leukemia and myelodysplastic syndrome among refractory germ cell tumor patients. Int. J. Urol. 2018, 25, 678–683. [Google Scholar] [CrossRef] [PubMed]
  100. Richiardi, L.; Scelo, G.; Boffetta, P.; Hemminki, K.; Pukkala, E.; Olsen, J.H.; Weiderpass, E.; Tracey, E.; Brewster, D.H.; McBride, M.L.; et al. Second malignancies among survivors of germ-cell testicular cancer: A pooled analysis between 13 cancer registries. Int. J. Cancer 2007, 120, 623–631. [Google Scholar] [CrossRef] [PubMed]
  101. Travis, L.B.; Andersson, M.; Gospodarowicz, M.; van Leeuwen, F.E.; Bergfeldt, K.; Lynch, C.F.; Curtis, R.E.; Kohler, B.A.; Wiklund, T.; Storm, H.; et al. Treatment-associated leukemia following testicular cancer. J. Natl. Cancer Inst. 2000, 92, 1165–1171. [Google Scholar] [CrossRef] [PubMed]
  102. Winick, N.J.; McKenna, R.W.; Shuster, J.J.; Schneider, N.R.; Borowitz, M.J.; Bowman, W.P.; Jacaruso, D.; Kamen, B.A.; Buchanan, G.R. Secondary acute myeloid leukemia in children with acute lymphoblastic leukemia treated with etoposide. J. Clin. Oncol. 1993, 11, 209–217. [Google Scholar] [CrossRef] [PubMed]
  103. Ratain, M.J.; Kaminer, L.S.; Bitran, J.D.; Larson, R.A.; Le Beau, M.M.; Skosey, C.; Purl, S.; Hoffman, P.C.; Wade, J.; Vardiman, J.W.; et al. Acute nonlymphocytic leukemia following etoposide and cisplatin combination chemotherapy for advanced non-small-cell carcinoma of the lung. Blood 1987, 70, 1412–1417. [Google Scholar] [CrossRef] [PubMed]
  104. Kushner, B.H.; Kramer, K.; Modak, S.; Qin, L.X.; Yataghena, K.; Jhanwar, S.C.; Cheung, N.K. Reduced risk of secondary leukemia with fewer cycles of dose-intensive induction chemotherapy in patients with neuroblastoma. Pediatr. Blood Cancer 2009, 53, 17–22. [Google Scholar] [CrossRef] [PubMed]
  105. Le Deley, M.C.; Vassal, G.; Taibi, A.; Shamsaldin, A.; Leblanc, T.; Hartmann, O. High cumulative rate of secondary leukemia after continuous etoposide treatment for solid tumors in children and young adults. Pediatr. Blood Cancer 2005, 45, 25–31. [Google Scholar] [CrossRef] [PubMed]
  106. Meyer, C.; Burmeister, T.; Groger, D.; Tsaur, G.; Fechina, L.; Renneville, A.; Sutton, R.; Venn, N.C.; Emerenciano, M.; Pombo-de-Oliveira, M.S.; et al. The MLL recombinome of acute leukemias in 2017. Leukemia 2018, 32, 273–284. [Google Scholar] [CrossRef] [PubMed]
  107. Rowley, J.D.; Olney, H.J. International workshop on the relationship of prior therapy to balanced chromosome aberrations in therapy-related myelodysplastic syndromes and acute leukemia: Overview report. Genes Chromosomes Cancer 2002, 33, 331–345. [Google Scholar] [CrossRef] [PubMed]
  108. Dobson, C.L.; Warren, A.J.; Pannell, R.; Forster, A.; Lavenir, I.; Corral, J.; Smith, A.J.; Rabbitts, T.H. The mll-AF9 gene fusion in mice controls myeloproliferation and specifies acute myeloid leukaemogenesis. EMBO J. 1999, 18, 3564–3574. [Google Scholar] [CrossRef] [PubMed]
  109. Ghisi, M.; Kats, L.; Masson, F.; Li, J.; Kratina, T.; Vidacs, E.; Gilan, O.; Doyle, M.A.; Newbold, A.; Bolden, J.E.; et al. Id2 and E Proteins Orchestrate the Initiation and Maintenance of MLL-Rearranged Acute Myeloid Leukemia. Cancer Cell 2016, 30, 59–74. [Google Scholar] [CrossRef] [PubMed]
  110. Krivtsov, A.V.; Twomey, D.; Feng, Z.; Stubbs, M.C.; Wang, Y.; Faber, J.; Levine, J.E.; Wang, J.; Hahn, W.C.; Gilliland, D.G.; et al. Transformation from committed progenitor to leukaemia stem cell initiated by MLL-AF9. Nature 2006, 442, 818–822. [Google Scholar] [CrossRef] [PubMed]
  111. Nitiss, J.L. Targeting DNA topoisomerase II in cancer chemotherapy. Nat. Rev. Cancer 2009, 9, 338–350. [Google Scholar] [CrossRef]
  112. Bian, X.; Liu, R.; Meng, Y.; Xing, D.; Xu, D.; Lu, Z. Lipid metabolism and cancer. J. Exp. Med. 2021, 218, e20201606. [Google Scholar] [CrossRef] [PubMed]
  113. Nistico, C.; Chiarella, E. An Overview on Lipid Droplets Accumulation as Novel Target for Acute Myeloid Leukemia Therapy. Biomedicines 2023, 11, 3186. [Google Scholar] [CrossRef]
  114. Verbrugge, S.E.; Al, M.; Assaraf, Y.G.; Kammerer, S.; Chandrupatla, D.M.; Honeywell, R.; Musters, R.P.; Giovannetti, E.; O’Toole, T.; Scheffer, G.L.; et al. Multifactorial resistance to aminopeptidase inhibitor prodrug CHR2863 in myeloid leukemia cells: Down-regulation of carboxylesterase 1, drug sequestration in lipid droplets and pro-survival activation ERK/Akt/mTOR. Oncotarget 2016, 7, 5240–5257. [Google Scholar] [CrossRef] [PubMed]
  115. Bosc, C.; Broin, N.; Fanjul, M.; Saland, E.; Farge, T.; Courdy, C.; Batut, A.; Masoud, R.; Larrue, C.; Skuli, S.; et al. Autophagy regulates fatty acid availability for oxidative phosphorylation through mitochondria-endoplasmic reticulum contact sites. Nat. Commun. 2020, 11, 4056. [Google Scholar] [CrossRef] [PubMed]
  116. Esmaeili, S.; Salari, S.; Kaveh, V.; Ghaffari, S.H.; Bashash, D. Alteration of PPAR-GAMMA (PPARG.; PPARgamma) and PTEN gene expression in acute myeloid leukemia patients and the promising anticancer effects of PPARgamma stimulation using pioglitazone on AML cells. Mol. Genet. Genom. Med. 2021, 9, e1818. [Google Scholar] [CrossRef] [PubMed]
  117. Stavropoulou, V.; Kaspar, S.; Brault, L.; Sanders, M.A.; Juge, S.; Morettini, S.; Tzankov, A.; Iacovino, M.; Lau, I.J.; Milne, T.A.; et al. MLL-AF9 Expression in Hematopoietic Stem Cells Drives a Highly Invasive AML Expressing EMT-Related Genes Linked to Poor Outcome. Cancer Cell 2016, 30, 43–58. [Google Scholar] [CrossRef] [PubMed]
  118. Krebs, A.M.; Mitschke, J.; Lasierra Losada, M.; Schmalhofer, O.; Boerries, M.; Busch, H.; Boettcher, M.; Mougiakakos, D.; Reichardt, W.; Bronsert, P.; et al. The EMT-activator Zeb1 is a key factor for cell plasticity and promotes metastasis in pancreatic cancer. Nat. Cell Biol. 2017, 19, 518–529. [Google Scholar] [CrossRef]
  119. Vandamme, N.; Denecker, G.; Bruneel, K.; Blancke, G.; Akay, Ö.; Taminau, J.; De Coninck, J.; De Smedt, E.; Skrypek, N.; Van Loocke, W.; et al. The EMT Transcription Factor ZEB2 Promotes Proliferation of Primary and Metastatic Melanoma While Suppressing an Invasive, Mesenchymal-Like Phenotype. Cancer Res. 2020, 80, 2983–2995. [Google Scholar] [CrossRef] [PubMed]
  120. Goossens, S.; Radaelli, E.; Blanchet, O.; Durinck, K.; Van der Meulen, J.; Peirs, S.; Taghon, T.; Tremblay, C.S.; Costa, M.; Farhang Ghahremani, M.; et al. ZEB2 drives immature T-cell lymphoblastic leukaemia development via enhanced tumour-initiating potential and IL-7 receptor signalling. Nat. Commun. 2015, 6, 5794. [Google Scholar] [CrossRef] [PubMed]
  121. Wellner, U.; Schubert, J.; Burk, U.C.; Schmalhofer, O.; Zhu, F.; Sonntag, A.; Waldvogel, B.; Vannier, C.; Darling, D.; zur Hausen, A.; et al. The EMT-activator ZEB1 promotes tumorigenicity by repressing stemness-inhibiting microRNAs. Nat. Cell Biol. 2009, 11, 1487–1495. [Google Scholar] [CrossRef]
  122. Arumugam, T.; Ramachandran, V.; Fournier, K.F.; Wang, H.; Marquis, L.; Abbruzzese, J.L.; Gallick, G.E.; Logsdon, C.D.; McConkey, D.J.; Choi, W. Epithelial to mesenchymal transition contributes to drug resistance in pancreatic cancer. Cancer Res. 2009, 69, 5820–5828. [Google Scholar] [CrossRef] [PubMed]
  123. Sayan, A.E.; Griffiths, T.R.; Pal, R.; Browne, G.J.; Ruddick, A.; Yagci, T.; Edwards, R.; Mayer, N.J.; Qazi, H.; Goyal, S.; et al. SIP1 protein protects cells from DNA damage-induced apoptosis and has independent prognostic value in bladder cancer. Proc. Natl. Acad. Sci. USA 2009, 106, 14884–14889. [Google Scholar] [CrossRef]
  124. Verschueren, K.; Remacle, J.E.; Collart, C.; Kraft, H.; Baker, B.S.; Tylzanowski, P.; Nelles, L.; Wuytens, G.; Su, M.T.; Bodmer, R.; et al. SIP1, a novel zinc finger/homeodomain repressor, interacts with Smad proteins and binds to 5′-CACCT sequences in candidate target genes. J. Biol. Chem. 1999, 274, 20489–20498. [Google Scholar] [CrossRef] [PubMed]
  125. Postigo, A.A.; Dean, D.C. ZEB represses transcription through interaction with the corepressor CtBP. Proc. Natl. Acad. Sci. USA 1999, 96, 6683–6688. [Google Scholar] [CrossRef] [PubMed]
  126. Drápela, S.; Bouchal, J.; Jolly, M.K.; Culig, Z.; Souček, K. ZEB1: A Critical Regulator of Cell Plasticity, DNA Damage Response, and Therapy Resistance. Front. Mol. Biosci. 2020, 7, 36. [Google Scholar] [CrossRef] [PubMed]
  127. Goossens, S.; Janzen, V.; Bartunkova, S.; Yokomizo, T.; Drogat, B.; Crisan, M.; Haigh, K.; Seuntjens, E.; Umans, L.; Riedt, T.; et al. The EMT regulator Zeb2/Sip1 is essential for murine embryonic hematopoietic stem/progenitor cell differentiation and mobilization. Blood 2011, 117, 5620–5630. [Google Scholar] [CrossRef] [PubMed]
  128. Li, J.; Riedt, T.; Goossens, S.; Carrillo Garcia, C.; Szczepanski, S.; Brandes, M.; Pieters, T.; Dobrosch, L.; Gutgemann, I.; Farla, N.; et al. The EMT transcription factor Zeb2 controls adult murine hematopoietic differentiation by regulating cytokine signaling. Blood 2017, 129, 460–472. [Google Scholar] [CrossRef] [PubMed]
  129. Almotiri, A.; Alzahrani, H.; Menendez-Gonzalez, J.B.; Abdelfattah, A.; Alotaibi, B.; Saleh, L.; Greene, A.; Georgiou, M.; Gibbs, A.; Alsayari, A.; et al. Zeb1 modulates hematopoietic stem cell fates required for suppressing acute myeloid leukemia. J. Clin. Investig. 2021, 131, e129115. [Google Scholar] [CrossRef] [PubMed]
  130. Wang, J.; Farkas, C.; Benyoucef, A.; Carmichael, C.; Haigh, K.; Wong, N.; Huylebroeck, D.; Stemmler, M.P.; Brabletz, S.; Brabletz, T.; et al. Interplay between the EMT transcription factors ZEB1 and ZEB2 regulates hematopoietic stem and progenitor cell differentiation and hematopoietic lineage fidelity. PLoS Biol. 2021, 19, e3001394. [Google Scholar] [CrossRef]
  131. Omilusik, K.D.; Best, J.A.; Yu, B.; Goossens, S.; Weidemann, A.; Nguyen, J.V.; Seuntjens, E.; Stryjewska, A.; Zweier, C.; Roychoudhuri, R.; et al. Transcriptional repressor ZEB2 promotes terminal differentiation of CD8+ effector and memory T cell populations during infection. J. Exp. Med. 2015, 212, 2027–2039. [Google Scholar] [CrossRef]
  132. Scott, C.L.; Soen, B.; Martens, L.; Skrypek, N.; Saelens, W.; Taminau, J.; Blancke, G.; Van Isterdael, G.; Huylebroeck, D.; Haigh, J.; et al. The transcription factor Zeb2 regulates development of conventional and plasmacytoid DCs by repressing Id2. J. Exp. Med. 2016, 213, 897–911. [Google Scholar] [CrossRef]
  133. Van Helden, M.J.; Goossens, S.; Daussy, C.; Mathieu, A.L.; Faure, F.; Marcais, A.; Vandamme, N.; Farla, N.; Mayol, K.; Viel, S.; et al. Terminal NK cell maturation is controlled by concerted actions of T-bet and Zeb2 and is essential for melanoma rejection. J. Exp. Med. 2015, 212, 2015–2025. [Google Scholar] [CrossRef] [PubMed]
  134. Scott, C.L.; T’Jonck, W.; Martens, L.; Todorov, H.; Sichien, D.; Soen, B.; Bonnardel, J.; De Prijck, S.; Vandamme, N.; Cannoodt, R.; et al. The Transcription Factor ZEB2 Is Required to Maintain the Tissue-Specific Identities of Macrophages. The Transcription Factor ZEB2 Is Required to Maintain the Tissue-Specific Identities of Macrophages. Immunity 2018, 49, 312–325.e5. [Google Scholar] [CrossRef] [PubMed]
  135. Soen, B.; Vandamme, N.; Berx, G.; Schwaller, J.; Van Vlierberghe, P.; Goossens, S. ZEB Proteins in Leukemia: Friends, Foes, or Friendly Foes? Hemasphere 2018, 2, e43. [Google Scholar] [CrossRef] [PubMed]
  136. Jiang, H.; Wei, H.; Wang, H.; Wang, Z.; Li, J.; Ou, Y.; Xiao, X.; Wang, W.; Chang, A.; Sun, W.; et al. Zeb1-induced metabolic reprogramming of glycolysis is essential for macrophage polarization in breast cancer. Cell Death Dis. 2022, 13, 1–14. [Google Scholar] [CrossRef] [PubMed]
  137. Wang, Y.; Zhang, Q.; He, T.; Wang, Y.; Lu, T.; Wang, Z.; Xiao, N. The transcription factor Zeb1 controls homeostasis and function of type 1 conventional dendritic cells. Nat. Commun. 2023, 14, 6639. [Google Scholar] [CrossRef] [PubMed]
  138. Brabletz, S.; Brabletz, T. The ZEB/miR-200 feedback loop—A motor of cellular plasticity in development and cancer? EMBO Rep. 2010, 11, 670–677. [Google Scholar] [CrossRef] [PubMed]
  139. Li, H.; Mar, B.G.; Zhang, H.; Puram, R.V.; Vazquez, F.; Weir, B.A.; Hahn, W.C.; Ebert, B.; Pellman, D. The EMT regulator ZEB2 is a novel dependency of human and murine acute myeloid leukemia. Blood 2017, 129, 497–508. [Google Scholar] [CrossRef] [PubMed]
  140. Zhou, J.D.; Zhang, L.C.; Zhang, T.J.; Gu, Y.; Wu, D.H.; Zhang, W.; Ma, J.C.; Wen, X.M.; Guo, H.; Lin, J.; et al. Dysregulation of miR-200s clusters as potential prognostic biomarkers in acute myeloid leukemia. J. Transl. Med. 2018, 16, 135. [Google Scholar] [CrossRef] [PubMed]
  141. De Conti, G.; Gruszka, A.M.; Valli, D.; Cammarata, A.U.; Righi, M.; Mazza, M.; Pelicci, P.G. A Novel Platform to Test In Vivo Single Gene Dependencies in t(8,21) and t(15,17) AML Confirms Zeb2 as Leukemia Target. Cancers 2020, 12, 3768. [Google Scholar] [CrossRef]
  142. Di Giacomo, D.; La Starza, R.; Gorello, P.; Pellanera, F.; Kalender Atak, Z.; De Keersmaecker, K.; Pierini, V.; Harrison, C.J.; Arniani, S.; Moretti, M.; et al. 14q32 rearrangements deregulating BCL11B mark a distinct subgroup of T-lymphoid and myeloid immature acute leukemia. Blood 2021, 138, 773–784. [Google Scholar] [CrossRef] [PubMed]
  143. Wang, X.; Zhong, L.; Dan, W.; Chu, X.; Luo, X.; Liu, C.; Wan, P.; Lu, Y.; Liu, Z.; Zhang, Z.; et al. MiR-454-3p promotes apoptosis and autophagy of AML cells by targeting ZEB2 and regulating AKT/mTOR pathway. Hematology 2023, 28, 2223874. [Google Scholar] [CrossRef]
  144. Shi, X.; Li, J.; Ma, L.; Wen, L.; Wang, Q.; Yao, H.; Ruan, C.; Wu, D.; Zhang, X.; Chen, S. Overexpression of ZEB2-AS1 lncRNA is associated with poor clinical outcomes in acute myeloid leukemia. Oncol. Lett. 2019, 17, 4935–4947. [Google Scholar] [CrossRef] [PubMed]
  145. Chiarella, E.; Aloisio, A.; Scicchitano, S.; Todoerti, K.; Cosentino, E.G.; Lico, D.; Neri, A.; Amodio, N.; Bond, H.M.; Mesuraca, M. ZNF521 Enhances MLL-AF9-Dependent Hematopoietic Stem Cell Transformation in Acute Myeloid Leukemias by Altering the Gene Expression Landscape. Int. J. Mol. Sci. 2021, 22, 10814. [Google Scholar] [CrossRef] [PubMed]
  146. Li, L.; Feng, Y.; Hu, S.; Du, Y.; Xu, X.; Zhang, M.; Peng, X.; Chen, F. ZEB1 serves as an oncogene in acute myeloid leukaemia via regulating the PTEN/PI3K/AKT signalling pathway by combining with P53. J. Cell. Mol. Med. 2021, 25, 5295–5304. [Google Scholar] [CrossRef] [PubMed]
  147. Bassani, B.; Simonetti, G.; Cancila, V.; Fiorino, A.; Ciciarello, M.; Piva, A.; Khorasani, A.M.; Chiodoni, C.; Lecis, D.; Gulino, A.; et al. ZEB1 shapes AML immunological niches, suppressing CD8 T cell activity while fostering Th17 cell expansion. Cell Rep. 2024, 43, 113794. [Google Scholar] [CrossRef] [PubMed]
  148. Han, Y.; Ye, A.; Bi, L.; Wu, J.; Yu, K.; Zhang, S. Th17 cells and interleukin-17 increase with poor prognosis in patients with acute myeloid leukemia. Cancer Sci. 2014, 105, 933–942. [Google Scholar] [CrossRef]
  149. Trsova, I.; Hrustincova, A.; Krejcik, Z.; Kundrat, D.; Holoubek, A.; Staflova, K.; Janstova, L.; Vanikova, S.; Szikszai, K.; Klema, J.; et al. Expression of circular RNAs in myelodysplastic neoplasms and their association with mutations in the splicing factor gene SF3B1. Mol. Oncol. 2023, 17, 2565–2583. [Google Scholar] [CrossRef] [PubMed]
  150. Jin, J.; Fu, L.; Hong, P.; Feng, W. MALAT-1 regulates the AML progression by promoting the m6A modification of ZEB1. Acta Biochim. Pol. 2023, 70, 37–43. [Google Scholar] [CrossRef]
  151. Li, W.; Wang, Q.; Su, Q.; Ma, D.; An, C.; Ma, L.; Liang, H. Honokiol suppresses renal cancer cells’ metastasis via dual-blocking epithelial-mesenchymal transition and cancer stem cell properties through modulating miR-141/ZEB2 signaling. Mol. Cells 2014, 37, 383–388. [Google Scholar] [CrossRef] [PubMed]
  152. Metge, B.J.; Alsheikh, H.A.M.; Kammerud, S.C.; Chen, D.; Das, D.; Nebane, N.M.; Bostwick, J.R.; Shevde, L.A.; Samant, R.S. Targeting EMT using low-dose Teniposide by downregulating ZEB2-driven activation of RNA polymerase I in breast cancer. Cell Death Dis. 2024, 15, 322. [Google Scholar] [CrossRef] [PubMed]
  153. Smith, M.A.; Rubinstein, L.; Ungerleider, R.S. Therapy-related acute myeloid leukemia following treatment with epipodophyllotoxins: Estimating the risks. Med. Pediatr. Oncol. 1994, 23, 86–98. [Google Scholar] [CrossRef] [PubMed]
  154. Jin, Y.; Lu, Y.; Lin, L.; Liu, C.; Ma, X.; Chen, X.; Zhou, Z.; Hu, Z.; Pu, J.; Chen, G.; et al. Harnessing endogenous transcription factors directly by small molecules for chemically induced pluripotency inception. Proc. Natl. Acad. Sci. USA 2023, 120, e2215155120. [Google Scholar] [CrossRef] [PubMed]
  155. Kahlert, U.D.; Joseph, J.V.; Kruyt, F.A.E. EMT- and MET-related processes in nonepithelial tumors: Importance for disease progression, prognosis, and therapeutic opportunities. Mol. Oncol. 2017, 11, 860–877. [Google Scholar] [CrossRef] [PubMed]
  156. Wilson, M.M.; Weinberg, R.A.; Lees, J.A.; Guen, V.J. Emerging Mechanisms by which EMT Programs Control Stemness. Trends Cancer 2020, 6, 775–780. [Google Scholar] [CrossRef] [PubMed]
  157. Santamaria, P.G.; Moreno-Bueno, G.; Cano, A. Contribution of Epithelial Plasticity to Therapy Resistance. J. Clin. Med. 2019, 8, 676. [Google Scholar] [CrossRef] [PubMed]
  158. Gill, J.G.; Langer, E.M.; Lindsley, R.C.; Cai, M.; Murphy, T.L.; Kyba, M.; Murphy, K.M. Snail and the microRNA-200 family act in opposition to regulate epithelial-to-mesenchymal transition and germ layer fate restriction in differentiating ESCs. Stem Cells 2011, 29, 764–776. [Google Scholar] [CrossRef] [PubMed]
  159. Chiang, C.; Ayyanathan, K. Snail/Gfi-1 (SNAG) family zinc finger proteins in transcription regulation, chromatin dynamics, cell signaling, development, and disease. Cytokine Growth Factor Rev. 2013, 24, 123–131. [Google Scholar] [CrossRef] [PubMed]
  160. Beauchemin, H.; Moroy, T. Multifaceted Actions of GFI1 and GFI1B in Hematopoietic Stem Cell Self-Renewal and Lineage Commitment. Front. Genet. 2020, 11, 591099. [Google Scholar] [CrossRef] [PubMed]
  161. Pioli, P.D.; Weis, J.H. Snail transcription factors in hematopoietic cell development: A model of functional redundancy. Exp. Hematol. 2014, 42, 425–430. [Google Scholar] [CrossRef] [PubMed]
  162. Pioli, P.D.; Whiteside, S.K.; Weis, J.J.; Weis, J.H. Snai2 and Snai3 transcriptionally regulate cellular fitness and functionality of T cell lineages through distinct gene programs. Immunobiology 2016, 221, 618–633. [Google Scholar] [CrossRef] [PubMed]
  163. Carmichael, C.L.; Wang, J.; Nguyen, T.; Kolawole, O.; Benyoucef, A.; De Maziere, C.; Milne, A.R.; Samuel, S.; Gillinder, K.; Hediyeh-Zadeh, S.; et al. The EMT modulator SNAI1 contributes to AML pathogenesis via its interaction with LSD1. Blood 2020, 136, 957–973. [Google Scholar] [CrossRef] [PubMed]
  164. Hartung, E.E.; Singh, K.; Berg, T. LSD1 inhibition modulates transcription factor networks in myeloid malignancies. Front. Oncol. 2023, 13, 1149754. [Google Scholar] [CrossRef] [PubMed]
  165. Malinge, S. SNAIL trail in myeloid malignancies. Blood 2020, 136, 920–921. [Google Scholar] [CrossRef] [PubMed]
  166. Goossens, S.; Peirs, S.; Van Loocke, W.; Wang, J.; Takawy, M.; Matthijssens, F.; Sonderegger, S.E.; Haigh, K.; Nguyen, T.; Vandamme, N.; et al. Oncogenic ZEB2 activation drives sensitivity toward KDM1A inhibition in T-cell acute lymphoblastic leukemia. Blood 2017, 129, 981–990. [Google Scholar] [CrossRef] [PubMed]
  167. Noce, B.; Di Bello, E.; Fioravanti, R.; Mai, A. LSD1 inhibitors for cancer treatment: Focus on multi-target agents and compounds in clinical trials. Front. Pharmacol. 2023, 14, 1120911. [Google Scholar] [CrossRef] [PubMed]
  168. Goossens, S.; Wang, J.; Tremblay, C.S.; De Medts, J.; T’Sas, S.; Nguyen, T.; Saw, J.; Haigh, K.; Curtis, D.J.; Van Vlierberghe, P.; et al. ZEB2 and LMO2 drive immature T-cell lymphoblastic leukemia via distinct oncogenic mechanisms. Haematologica 2019, 104, 1608–1616. [Google Scholar] [CrossRef] [PubMed]
  169. Benyoucef, A.; Haigh, K.; Cuddihy, A.; Haigh, J.J. JAK/BCL2 inhibition acts synergistically with LSD1 inhibitors to selectively target ETP-ALL. Leukemia 2022, 36, 2802–2816. [Google Scholar] [CrossRef] [PubMed]
  170. Zhang, Z.; Li, L.; Wu, C.; Yin, G.; Zhu, P.; Zhou, Y.; Hong, Y.; Ni, H.; Qian, Z.; Wu, W.S. Inhibition of Slug effectively targets leukemia stem cells via the Slc13a3/ROS signaling pathway. Leukemia 2020, 34, 380–390. [Google Scholar] [CrossRef] [PubMed]
  171. Dorn, D.C.; Kou, C.A.; Png, K.J.; Moore, M.A. The effect of cantharidins on leukemic stem cells. Int. J. Cancer 2009, 124, 2186–2199. [Google Scholar] [CrossRef] [PubMed]
  172. Wang, N.; Guo, D.; Zhao, Y.Y.; Dong, C.Y.; Liu, X.Y.; Yang, B.X.; Wang, S.W.; Wang, L.; Liu, Q.G.; Ren, Q.; et al. TWIST-1 promotes cell growth, drug resistance and progenitor clonogenic capacities in myeloid leukemia and is a novel poor prognostic factor in acute myeloid leukemia. Oncotarget 2015, 6, 20977–20992. [Google Scholar] [CrossRef] [PubMed]
  173. Gong, A.; Wang, X.; Wang, X.; Zhao, Y.; Cui, Y. Twist1 Promoter Methylation Regulates the Proliferation and Apoptosis of Acute Myeloid Leukemia Cells via PI3K/AKT Pathway. Indian J. Hematol. Blood Transfus. 2023, 39, 25–32. [Google Scholar] [CrossRef] [PubMed]
  174. Ottone, T.; Silvestrini, G.; Piazza, R.; Travaglini, S.; Gurnari, C.; Marchesi, F.; Nardozza, A.M.; Fabiani, E.; Attardi, E.; Guarnera, L.; et al. Expression profiling of extramedullary acute myeloid leukemia suggests involvement of epithelial-mesenchymal transition pathways. Leukemia 2023, 37, 2383–2394. [Google Scholar] [CrossRef] [PubMed]
  175. Wang, N.; Yin, J.; You, N.; Zhu, W.; Guo, N.; Liu, X.; Zhang, P.; Huang, W.; Xie, Y.; Ren, Q.; et al. Twist family BHLH transcription factor 1 is required for the maintenance of leukemia stem cell in MLL-AF9(+) acute myeloid leukemia. Haematologica 2024, 109, 84–97. [Google Scholar] [CrossRef] [PubMed]
  176. Li, H.; Wang, Y.; Yang, F.; Feng, S.; Chang, K.; Yu, X.; Guan, F.; Li, X. Clonal MDS/AML cells with enhanced TWIST1 expression reprogram the differentiation of bone marrow MSCs. Redox Biol. 2023, 67, 102900. [Google Scholar] [CrossRef] [PubMed]
  177. Zhao, C.; Yang, S.; Lu, W.; Liu, J.; Wei, Y.; Guo, H.; Zhang, Y.; Shi, J. Increased NFATC4 Correlates With Poor Prognosis of AML Through Recruiting Regulatory T Cells. Front. Genet. 2020, 11, 573124. [Google Scholar] [CrossRef] [PubMed]
  178. Li, H.; Wang, Y.; Feng, S.; Chang, K.; Yu, X.; Yang, F.; Huang, H.; Wang, Y.; Li, X.; Guan, F. Reciprocal regulation of TWIST1 and OGT determines the decitabine efficacy in MDS/AML. Cell Commun. Signal. 2023, 21, 255. [Google Scholar] [CrossRef] [PubMed]
  179. Eckardt, J.N.; Stolzel, F.; Kunadt, D.; Rollig, C.; Stasik, S.; Wagenfuhr, L.; Johrens, K.; Kuithan, F.; Kramer, A.; Scholl, S.; et al. Molecular profiling and clinical implications of patients with acute myeloid leukemia and extramedullary manifestations. J. Hematol. Oncol. 2022, 15, 60. [Google Scholar] [CrossRef] [PubMed]
  180. Tettamanti, S.; Pievani, A.; Biondi, A.; Dotti, G.; Serafini, M. Catch me if you can: How AML and its niche escape immunotherapy. Leukemia 2022, 36, 13–22. [Google Scholar] [CrossRef] [PubMed]
  181. Cancilla, D.; Rettig, M.P.; DiPersio, J.F. Targeting CXCR4 in AML and ALL. Front. Oncol. 2020, 10, 1672. [Google Scholar] [CrossRef] [PubMed]
  182. Hanoun, M.; Zhang, D.; Mizoguchi, T.; Pinho, S.; Pierce, H.; Kunisaki, Y.; Lacombe, J.; Armstrong, S.A.; Duhrsen, U.; Frenette, P.S. Acute myelogenous leukemia-induced sympathetic neuropathy promotes malignancy in an altered hematopoietic stem cell niche. Cell Stem Cell 2014, 15, 365–375. [Google Scholar] [CrossRef] [PubMed]
  183. Parker, J.; Hockney, S.; Blaschuk, O.W.; Pal, D. Targeting N-cadherin (CDH2) and the malignant bone marrow microenvironment in acute leukaemia. Expert Rev. Mol. Med. 2023, 25, e16. [Google Scholar] [CrossRef] [PubMed]
  184. Kunadt, D.; Kramer, M.; Dill, C.; Altmann, H.; Wagenfuhr, L.; Mohr, B.; Thiede, C.; Rollig, C.; Schetelig, J.; Bornhauser, M.; et al. Lysyl oxidase expression is associated with inferior outcome and Extramedullary disease of acute myeloid leukemia. Biomark. Res. 2020, 8, 20. [Google Scholar] [CrossRef] [PubMed]
  185. Pizzo, R.J.; Azadniv, M.; Guo, N.; Acklin, J.; Lacagnina, K.; Coppage, M.; Liesveld, J.L. Phenotypic, genotypic, and functional characterization of normal and acute myeloid leukemia-derived marrow endothelial cells. Exp. Hematol. 2016, 44, 378–389. [Google Scholar] [CrossRef] [PubMed]
  186. Qu, S.; Huang, X.; Guo, X.; Zheng, Z.; Wei, T.; Chen, B. Metastasis Related Epithelial-Mesenchymal Transition Signature Predicts Prognosis and Response to Chemotherapy in Acute Myeloid Leukemia. Drug Des. Dev. Ther. 2023, 17, 1651–1663. [Google Scholar] [CrossRef] [PubMed]
  187. Li, G.; Gao, Y.; Li, K.; Lin, A.; Jiang, Z. Genomic analysis of biomarkers related to the prognosis of acute myeloid leukemia. Oncol. Lett. 2020, 20, 1824–1834. [Google Scholar] [CrossRef] [PubMed]
  188. Stefanidakis, M.; Karjalainen, K.; Jaalouk, D.E.; Gahmberg, C.G.; O’Brien, S.; Pasqualini, R.; Arap, W.; Koivunen, E. Role of leukemia cell invadosome in extramedullary infiltration. Blood 2009, 114, 3008–3017. [Google Scholar] [CrossRef] [PubMed]
  189. Paz, H.; Pathak, N.; Yang, J. Invading one step at a time: The role of invadopodia in tumor metastasis. Oncogene 2014, 33, 4193–4202. [Google Scholar] [CrossRef] [PubMed]
  190. Whiteley, A.E.; Price, T.T.; Cantelli, G.; Sipkins, D.A. Leukaemia: A model metastatic disease. Nat. Rev. Cancer 2021, 21, 461–475. [Google Scholar] [CrossRef] [PubMed]
  191. Augoff, K.; Hryniewicz-Jankowska, A.; Tabola, R. Invadopodia: Clearing the way for cancer cell invasion. Ann. Transl. Med. 2020, 8, 902. [Google Scholar] [CrossRef] [PubMed]
  192. Ren, X.L.; Qiao, Y.D.; Li, J.Y.; Li, X.M.; Zhang, D.; Zhang, X.J.; Zhu, X.H.; Zhou, W.J.; Shi, J.; Wang, W.; et al. Cortactin recruits FMNL2 to promote actin polymerization and endosome motility in invadopodia formation. Cancer Lett. 2018, 419, 245–256. [Google Scholar] [CrossRef] [PubMed]
  193. Gligorijevic, B.; Wyckoff, J.; Yamaguchi, H.; Wang, Y.; Roussos, E.T.; Condeelis, J. N-WASP-mediated invadopodium formation is involved in intravasation and lung metastasis of mammary tumors. J. Cell Sci. 2012, 125 Pt 3, 724–734. [Google Scholar] [CrossRef] [PubMed]
  194. Iizuka, S.; Abdullah, C.; Buschman, M.D.; Diaz, B.; Courtneidge, S.A. The role of Tks adaptor proteins in invadopodia formation, growth and metastasis of melanoma. Oncotarget 2016, 7, 78473–78486. [Google Scholar] [CrossRef]
  195. Chen, Y.C.; Baik, M.; Byers, J.T.; Chen, K.T.; French, S.W.; Diaz, B. TKS5-positive invadopodia-like structures in human tumor surgical specimens. Exp. Mol. Pathol. 2019, 106, 17–26. [Google Scholar] [CrossRef] [PubMed]
  196. Kudlik, G.; Takacs, T.; Radnai, L.; Kurilla, A.; Szeder, B.; Koprivanacz, K.; Mero, B.L.; Buday, L.; Vas, V. Advances in Understanding TKS4 and TKS5: Molecular Scaffolds Regulating Cellular Processes from Podosome and Invadopodium Formation to Differentiation and Tissue Homeostasis. Int. J. Mol. Sci. 2020, 21, 8117. [Google Scholar] [CrossRef] [PubMed]
  197. Daubon, T.; Rochelle, T.; Bourmeyster, N.; Genot, E. Invadopodia and rolling-type motility are specific features of highly invasive p190(bcr-abl) leukemic cells. Eur. J. Cell Biol. 2012, 91, 978–987. [Google Scholar] [CrossRef] [PubMed]
  198. Poincloux, R.; Vincent, C.; Labrousse, A.; Castandet, J.; Rigo, M.; Cougoule, C.; Bordier, C.; Le Cabec, V.; Maridonneau-Parini, I. Re-arrangements of podosome structures are observed when Hck is activated in myeloid cells. Eur. J. Cell Biol. 2006, 85, 327–332. [Google Scholar] [CrossRef] [PubMed]
  199. Mukwaya, A.; Jensen, L.; Lagali, N. Relapse of pathological angiogenesis: Functional role of the basement membrane and potential treatment strategies. Exp. Mol. Med. 2021, 53, 189–201. [Google Scholar] [CrossRef] [PubMed]
  200. Seano, G.; Primo, L. Podosomes and invadopodia: Tools to breach vascular basement membrane. Cell Cycle 2015, 14, 1370–1374. [Google Scholar] [CrossRef] [PubMed]
  201. Morimatsu, M.; Yamashita, E.; Seno, S.; Sudo, T.; Kikuta, J.; Mizuno, H.; Okuzaki, D.; Motooka, D.; Ishii, M. Migration arrest of chemoresistant leukemia cells mediated by MRTF-SRF pathway. Inflamm. Regen. 2020, 40, 15. [Google Scholar] [CrossRef] [PubMed]
  202. Auvinen, K.; Jalkanen, S.; Salmi, M. Expression and function of endothelial selectins during human development. Immunology 2014, 143, 406–415. [Google Scholar] [CrossRef] [PubMed]
  203. Cuellar, T.L.; Herzner, A.M.; Zhang, X.; Goyal, Y.; Watanabe, C.; Friedman, B.A.; Janakiraman, V.; Durinck, S.; Stinson, J.; Arnott, D.; et al. Silencing of retrotransposons by SETDB1 inhibits the interferon response in acute myeloid leukemia. J. Cell Biol. 2017, 216, 3535–3549. [Google Scholar] [CrossRef] [PubMed]
  204. Johnson, E.; Salari, K.; Yang, S. SETDB1: A perspective into immune cell function and cancer immunotherapy. Immunology 2023, 169, 3–12. [Google Scholar] [CrossRef] [PubMed]
  205. Farge, T.; Nakhle, J.; Lagarde, D.; Cognet, G.; Polley, N.; Castellano, R.; Nicolau, M.L.; Bosc, C.; Sabatier, M.; Sahal, A.; et al. CD36 Drives Metastasis and Relapse in Acute Myeloid Leukemia. Cancer Res. 2023, 83, 2824–2838. [Google Scholar] [CrossRef]
  206. Xu, J.; Zhang, W.; Yan, X.J.; Lin, X.Q.; Li, W.; Mi, J.Q.; Li, J.M.; Zhu, J.; Chen, Z.; Chen, S.J. DNMT3A mutation leads to leukemic extramedullary infiltration mediated by TWIST1. J. Hematol. Oncol. 2016, 9, 106. [Google Scholar] [CrossRef] [PubMed]
  207. Ponomaryov, T.; Peled, A.; Petit, I.; Taichman, R.S.; Habler, L.; Sandbank, J.; Arenzana-Seisdedos, F.; Magerus, A.; Caruz, A.; Fujii, N.; et al. Induction of the chemokine stromal-derived factor-1 following DNA damage improves human stem cell function. J. Clin. Investig. 2000, 106, 1331–1339. [Google Scholar] [CrossRef] [PubMed]
  208. Voermans, C.; van Heese, W.P.; de Jong, I.; Gerritsen, W.R.; van Der Schoot, C.E. Migratory behavior of leukemic cells from acute myeloid leukemia patients. Leukemia 2002, 16, 650–657. [Google Scholar] [CrossRef] [PubMed]
  209. Zhang, Y.; Saavedra, E.; Tang, R.; Gu, Y.; Lappin, P.; Trajkovic, D.; Liu, S.H.; Smeal, T.; Fantin, V.; De Botton, S.; et al. Targeting primary acute myeloid leukemia with a new CXCR4 antagonist IgG1 antibody (PF-06747143). Sci. Rep. 2017, 7, 7305. [Google Scholar] [CrossRef] [PubMed]
  210. Tavor, S.; Petit, I.; Porozov, S.; Avigdor, A.; Dar, A.; Leider-Trejo, L.; Shemtov, N.; Deutsch, V.; Naparstek, E.; Nagler, A.; et al. CXCR4 regulates migration and development of human acute myelogenous leukemia stem cells in transplanted NOD/SCID mice. Cancer Res. 2004, 64, 2817–2824. [Google Scholar] [CrossRef] [PubMed]
  211. Konoplev, S.; Rassidakis, G.Z.; Estey, E.; Kantarjian, H.; Liakou, C.I.; Huang, X.; Xiao, L.; Andreeff, M.; Konopleva, M.; Medeiros, L.J. Overexpression of CXCR4 predicts adverse overall and event-free survival in patients with unmutated FLT3 acute myeloid leukemia with normal karyotype. Cancer 2007, 109, 1152–1156. [Google Scholar] [CrossRef]
  212. Muz, B.; Abdelghafer, A.; Markovic, M.; Yavner, J.; Melam, A.; Salama, N.N.; Azab, A.K. Targeting E-selectin to Tackle Cancer Using Uproleselan. Cancers 2021, 13, 335. [Google Scholar] [CrossRef] [PubMed]
  213. Li, M.; Ye, J.; Xia, Y.; Li, M.; Li, G.; Hu, X.; Su, X.; Wang, D.; Zhao, X.; Lu, F.; et al. METTL3 mediates chemoresistance by enhancing AML homing and engraftment via ITGA4. Leukemia 2022, 36, 2586–2595. [Google Scholar] [CrossRef]
  214. Bakst, R.L.; Tallman, M.S.; Douer, D.; Yahalom, J. How I treat extramedullary acute myeloid leukemia. Blood 2011, 118, 3785–3793. [Google Scholar] [CrossRef]
  215. Paydas, S.; Zorludemir, S.; Ergin, M. Granulocytic sarcoma: 32 cases and review of the literature. Leuk. Lymphoma 2006, 47, 2527–2541. [Google Scholar] [CrossRef] [PubMed]
  216. Chang, H.; Brandwein, J.; Yi, Q.L.; Chun, K.; Patterson, B.; Brien, B. Extramedullary infiltrates of AML are associated with CD56 expression, 11q23 abnormalities and inferior clinical outcome. Leuk. Res. 2004, 28, 1007–1011. [Google Scholar] [CrossRef] [PubMed]
  217. Novotny, J.R.; Nuckel, H.; Duhrsen, U. Correlation between expression of CD56/NCAM and severe leukostasis in hyperleukocytic acute myelomonocytic leukaemia. Eur. J. Haematol. 2006, 76, 299–308. [Google Scholar] [CrossRef] [PubMed]
  218. Alegretti, A.P.; Bittar, C.M.; Bittencourt, R.; Piccoli, A.K.; Schneider, L.; Silla, L.M.; Bo, S.D.; Xavier, R.M. The expression of CD56 antigen is associated with poor prognosis in patients with acute myeloid leukemia. Rev. Bras. Hematol. Hemoter. 2011, 33, 202–206. [Google Scholar] [CrossRef] [PubMed]
  219. Assaad, M.; Kumar, V.; Carmack, A.; Karki, A.; Golden, D. Acute Myeloid Leukemia with Central Nervous System Involvement Following Routine Surgical Procedures: A Bridge between Surgical, Medical, and Neurological Critical Care. Cureus 2022, 14, e21245. [Google Scholar] [CrossRef] [PubMed]
  220. Abbott, B.L.; Rubnitz, J.E.; Tong, X.; Srivastava, D.K.; Pui, C.H.; Ribeiro, R.C.; Razzouk, B.I. Clinical significance of central nervous system involvement at diagnosis of pediatric acute myeloid leukemia: A single institution’s experience. Leukemia 2003, 17, 2090–2096. [Google Scholar] [CrossRef] [PubMed]
  221. Alakel, N.; Stolzel, F.; Mohr, B.; Kramer, M.; Oelschlagel, U.; Rollig, C.; Bornhauser, M.; Ehninger, G.; Schaich, M. Symptomatic central nervous system involvement in adult patients with acute myeloid leukemia. Cancer Manag. Res. 2017, 9, 97–102. [Google Scholar] [CrossRef] [PubMed]
Figure 2. Overview of the role of EMT factors in normal hematopoiesis, AML development, and EME. EMT factors such as ZEB2 ensure hematopoietic lineage fidelity during early hematopoiesis by restraining mature gene expression programs. Later in hematopoiesis, EMT factors lock in cell identity once committed. Upregulated expression of ZEB2 can specifically transform T cell lineage and cause Early T cell Precursor Acute Lymphoblastic Leukemia (ETP-ALL). AML driver mutations can increase EMT factor expression, including ZEB1/2, SNAI1/2, and TWIST1, which can corrupt epigenetic factors such as LSD1 and lead to leukemic stem cell (LSC) gene expression program and transformation. EMT factors can also enhance survival signal pathway expression and increase drug resistance. EMT processes also drive extramedullary tissue engraftment, tissue colonization, and blast crisis development by altering AML cell adhesion and homing and survival signals. Ery—erythrocyte, Meg—megakaryocyte, Mac—macrophage, Gr—granulocyte, DC—dendritic cell, NK—natural killer cells, B—B cells, T—T cells, EME—extramedullary engraftment, HSC—hematopoietic stem cell, HPC—hematopoietic progenitor cell, LSC—leukemic stem cell.
Figure 2. Overview of the role of EMT factors in normal hematopoiesis, AML development, and EME. EMT factors such as ZEB2 ensure hematopoietic lineage fidelity during early hematopoiesis by restraining mature gene expression programs. Later in hematopoiesis, EMT factors lock in cell identity once committed. Upregulated expression of ZEB2 can specifically transform T cell lineage and cause Early T cell Precursor Acute Lymphoblastic Leukemia (ETP-ALL). AML driver mutations can increase EMT factor expression, including ZEB1/2, SNAI1/2, and TWIST1, which can corrupt epigenetic factors such as LSD1 and lead to leukemic stem cell (LSC) gene expression program and transformation. EMT factors can also enhance survival signal pathway expression and increase drug resistance. EMT processes also drive extramedullary tissue engraftment, tissue colonization, and blast crisis development by altering AML cell adhesion and homing and survival signals. Ery—erythrocyte, Meg—megakaryocyte, Mac—macrophage, Gr—granulocyte, DC—dendritic cell, NK—natural killer cells, B—B cells, T—T cells, EME—extramedullary engraftment, HSC—hematopoietic stem cell, HPC—hematopoietic progenitor cell, LSC—leukemic stem cell.
Biomedicines 12 01915 g002
Table 1. Classification and characteristics of acute myeloid leukemia (AML) subtypes according to the French–American–British (FAB) system.
Table 1. Classification and characteristics of acute myeloid leukemia (AML) subtypes according to the French–American–British (FAB) system.
SubtypeCharacteristicsPrognosis and Features
M0High percentage of minimally differentiated blasts, negative for peroxidase, confirmed with myeloid markers by flow cytometry.Poor prognosis, associated with complex chromosomal abnormalities.
M1Less than 10% promyelocytes, blasts lack granules with distinct nucleoli, >3% positive for myeloperoxidase.
M2Presence of mature cells, including cells with Auer rods, associated with t(8;21) translocations and AML1-ETO/ETO-AML1 fusion proteins.More favorable prognosis when linked with specific translocations.
M3 (APL)Hypergranulated promyelocytes, bilobed nuclei, characterized by the PML-RARα fusion from t(15;17) translocation. Treatable with ATRA and arsenic trioxide (ATO).Favorable prognosis due to effective treatment options.
M4Presence of monocytes and promonocytes in bone marrow. The M4Eo variant shows abnormal eosinophils and inv(16) cytogenetic abnormality.Favorable prognosis for variants like M4Eo depending on WBC levels.
M5High number of monocytic lineage cells, over 30% blast cells in BM or PB, often associated with 11q abnormalities and MLL gene rearrangements (e.g., MLL-AF9).Poor prognosis, common extramedullary disease, and linkage to severe clinical features.
M6Over 50% nucleated erythroid cells in bone marrow with substantial abnormalities, positive for PAS staining and glycophorin A.Rare, less than 5% of AML cases, associated with severe developmental abnormalities in erythroid cells.
M7Poor megakaryocytic differentiation, megakaryoblasts with scant cytoplasm and dense chromatin, negative for common stains, confirmed by CD41 and electron microscopy.Extremely rare (~1% of cases), poor prognosis due to aggressive nature and difficulty in treatment due to morphological variability in the cells.
Table 2. Subtypes of AML according to specific genetic markers and the required percentage of blasts. Each subtype is further classified by the ELN risk category, ranging from favorable to adverse. The presence of certain genetic abnormalities such as t(15;17)/PML:RARA, RUNX1:RUNX1T1, and mutations in NPM1 or TP53 influence the prognosis and therapeutic approach. References are provided for each subtype to support evidence.
Table 2. Subtypes of AML according to specific genetic markers and the required percentage of blasts. Each subtype is further classified by the ELN risk category, ranging from favorable to adverse. The presence of certain genetic abnormalities such as t(15;17)/PML:RARA, RUNX1:RUNX1T1, and mutations in NPM1 or TP53 influence the prognosis and therapeutic approach. References are provided for each subtype to support evidence.
AML TypeBlast %GeneticsELN Risk Class (2022)Literature (2024)Refs.
APL with t(15;17)/PML::RARA>10%PML:RARA-Favorable[33,34]
APL with other RARA
rearrangements
>10%Various RARA rearrangements-Variable, depends on the rearrangement[35]
AML with t(8;21)/RUNX1::RUNX1T1>10%RUNX1:RUNX1T1FavorableFavorable[36]
AML with inv(16) or t(16;16)/CBFB::MYH11>10%CBFB:MYH11FavorableFavorable[37,38]
AML with t(9;11)/MLLT3::KMT2A>10%MLLT3:KMT2AIntermediateIntermediate[39]
AML with other KMT2A
rearrangements
>10%Various KMT2A rearrangements-Variable, depends on the rearrangement[39]
AML with t(6;9)/DEK::NUP214>10%DEK:NUP214AdverseAdverse[40]
AML with inv(3) or t(3;3)/GATA2; MECOM>10%GATA2; MECOMAdverseAdverse[41]
AML with other MECOM
rearrangements
>10%Various MECOM rearrangements-Adverse[42]
AML with other rare recurring translocations>10%Rare recurring translocations-Adverse[43]
AML with t(9;22)/BCR::ABL1>10%BCR:ABL1AdverseAdverse[44]
AML with mutated NPM1>10%Mutated NPM1FavorableFavorable[45]
AML with bZIP CEBPA mutations>10%bZIP CEBPA mutationsFavorableFavorable[46]
AML/MDS with mutated TP5310–19%/>20%Mutated TP53AdverseAdverse[47]
AML/MDS with myelodysplasia-related gene mutations10–19%/>20%Myelodysplasia-related gene mutations-Adverse[48]
AML with myelodysplasia-related cytogenetic abnormalities10–19%/>20%Myelodysplasia-related cytogenetic abnormalities-Intermediate[49]
AML not otherwise specified (NOS)10–19%/>20%---[50]
Myeloid sarcomaNot specified-AdverseAdverse[51]
MDS with mutated TP530–9%Multi-hit TP53 mutation or TP53 mutation (VAF > 10%) and complex karyotype often with loss of 17pAdverseAdverse[29,30]
MDS/AML with mutated TP5310–19%Any somatic TP53 mutation (VAF > 10%)AdverseAdverse[29,30]
AML with mutated TP53>20%Any somatic TP53 mutation (VAF > 10%)AdverseAdverse[29,30]
Table 3. Comparative overview of EMT factors and their roles in AML: summary of the diverse roles of the ZEB1, ZEB2, SNAI1, SNAI2, and TWIST1 epithelial–mesenchymal transition (EMT) factors, namely, across various dimensions relevant to acute myeloid leukemia (AML) pathophysiology. Each column represents a specific EMT factor, outlining its involvement in EMT processes, roles in hematopoiesis, regulation by the miR200 family of miRNAs, influence on AML patient outcomes, interactions with oncofusion proteins, findings from genetic screenings, functional roles in immune cell differentiation, contribution to leukemic transformation, and potential as therapeutic targets. The table incorporates references to significant studies, providing a broad yet detailed perspective on the molecular and cellular functions of these factors in AML and highlighting their potential impacts on disease progression and treatment outcomes.
Table 3. Comparative overview of EMT factors and their roles in AML: summary of the diverse roles of the ZEB1, ZEB2, SNAI1, SNAI2, and TWIST1 epithelial–mesenchymal transition (EMT) factors, namely, across various dimensions relevant to acute myeloid leukemia (AML) pathophysiology. Each column represents a specific EMT factor, outlining its involvement in EMT processes, roles in hematopoiesis, regulation by the miR200 family of miRNAs, influence on AML patient outcomes, interactions with oncofusion proteins, findings from genetic screenings, functional roles in immune cell differentiation, contribution to leukemic transformation, and potential as therapeutic targets. The table incorporates references to significant studies, providing a broad yet detailed perspective on the molecular and cellular functions of these factors in AML and highlighting their potential impacts on disease progression and treatment outcomes.
FeatureZEB1ZEB2SNAI1SNAI2TWIST1
Roles in EMT ProcessesInvolved in malignant dissemination and metastasis [116,117]Plays a role in cancer or tumor stem cell properties, development, and treatment resistance [118,119]Essential for EMT, cancer stemness, and drug resistance [155,156,157]Promotes leukemogenesis and influences chemotherapy resistance [170,171]Central to AML pathophysiology; affects growth and drug resistance [172]
Roles in HematopoiesisLesser degree of influence compared with ZEB2
[129,130]
Limits inappropriate expression of immune cell programs [131,132,133,134]Influences stem and progenitor cell functions [158]Impairs LSC self-renewal, restricts LSC self-renewal via Slc13a3 [170]Impacts progenitor clonogenic capacities [175]
Regulation by the MiR200 Family of miRNAsNegatively regulated, lower levels in certain AML subtypes [138]Negatively regulated; absence leads to oncogenic levels [138,139,140]Relationship in hematopoiesis is unclear [158]Not specifiedNot specified
Influence on AML Patient OutcomesAssociated with poor outcomes, essential for leukemic blast invasion [117,130]Upregulation associated with leukemic blasts [130]Overexpression contributes to impaired differentiation and enhanced self-renewal [163]Associated with poor clinical outcomes [171]Linked to poor prognostic factors; promotes tissue invasion [172,174]
Oncofusion Protein InteractionsUpregulated by MLL-AF9 and MLL-AF4 [117]Upregulated by AML-ETO, MLL-AF9, MLL-AF4, and PML-RARα [116,117]Not clearNot specifiedNotably involved in extramedullary manifestations [174]
Genetic Screening FindingsDeletion may accelerate AML progression
[129,130]
Involved in myeloid and lymphoid leukemic transformation
[120,139]
Knock-down enhances morphological differentiation and improves survival [163]Not specifiedEssential for viability and self-renewal of LSCs [175]
Functional Roles in Immune Cell DifferentiationPlays a role in macrophage differentiation [136] and dendritic cell homeostasis [137]Ensures immune cell lineage fidelity
[131,132,133,134]
Implicated in myeloid development and self-renewal of progenitors [161,162]Not specifiedInfluences bone marrow microenvironment interactions [176]
Contribution to Leukemic TransformationPotentially oncogenic, may act as a tumor suppressor [129,130]Involved in myeloid leukemia transformation [135]Leads to myeloproliferative disorders and AML transformation [162,163]Promotes leukemogenesis [170]Promotes disease initiation and maintenance [175]
Potential Therapeutic TargetsCould offer novel approaches for AML treatment if targeted [146,147,148]Inhibition may improve outcomes [139,140,141,169]Knockout or inhibition improves survival [163]Targeting could impair LSC self-renewal and chemoresistance [171]Targeting TWIST1 could overcome chemoresistance and influence treatment [178]
Table 4. An analysis of various molecular factors that significantly impact the behavior of AML cells, particularly in the context of metastasis. The factors are evaluated based on their influence in three key areas including survival, motility, and adherence.
Table 4. An analysis of various molecular factors that significantly impact the behavior of AML cells, particularly in the context of metastasis. The factors are evaluated based on their influence in three key areas including survival, motility, and adherence.
FactorSurvivalMotilityAdherence
SDF-1[207] [208]
METTL-3[213]
Integrin β [188][188]
N-WASP [193]
Tks4, Tks5 [194,195]
E-selectin [202][202]
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Cuevas, D.; Amigo, R.; Agurto, A.; Heredia, A.A.; Guzmán, C.; Recabal-Beyer, A.; González-Pecchi, V.; Caprile, T.; Haigh, J.J.; Farkas, C. The Role of Epithelial-to-Mesenchymal Transition Transcription Factors (EMT-TFs) in Acute Myeloid Leukemia Progression. Biomedicines 2024, 12, 1915. https://doi.org/10.3390/biomedicines12081915

AMA Style

Cuevas D, Amigo R, Agurto A, Heredia AA, Guzmán C, Recabal-Beyer A, González-Pecchi V, Caprile T, Haigh JJ, Farkas C. The Role of Epithelial-to-Mesenchymal Transition Transcription Factors (EMT-TFs) in Acute Myeloid Leukemia Progression. Biomedicines. 2024; 12(8):1915. https://doi.org/10.3390/biomedicines12081915

Chicago/Turabian Style

Cuevas, Diego, Roberto Amigo, Adolfo Agurto, Adan Andreu Heredia, Catherine Guzmán, Antonia Recabal-Beyer, Valentina González-Pecchi, Teresa Caprile, Jody J. Haigh, and Carlos Farkas. 2024. "The Role of Epithelial-to-Mesenchymal Transition Transcription Factors (EMT-TFs) in Acute Myeloid Leukemia Progression" Biomedicines 12, no. 8: 1915. https://doi.org/10.3390/biomedicines12081915

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