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Editorial

Acute Myeloid Leukemia: Updates on Diagnosis, Treatment and Management

Hematology Unit, Ravenna Hospital, University of Bologna, 48121 Ravenna, Italy
*
Author to whom correspondence should be addressed.
Cancers 2025, 17(14), 2387; https://doi.org/10.3390/cancers17142387
Submission received: 14 July 2025 / Accepted: 16 July 2025 / Published: 18 July 2025

1. Introduction

This Special Issue of Cancers, entitled “Acute Myeloid Leukemia (AML): Updates on Diagnosis, Treatment and Management”, will be a forum for stimulating discussions and thought-provoking debates, featuring cutting-edge scientific manuscripts on the most relevant topics related to the diagnosis and therapeutic advances for the management of AML. This Special Issue will also provide invaluable opportunities to read articles from leading scientists who are shaping the future of AML research and treatment.
This editorial will attempt to highlight key issues and crucial developments in these areas of AML.
It is well known that AML is a clonal disorder resulting from acquired somatic mutations in hematopoietic progenitor cells that leads to the dysregulation of proliferation and differentiation of the hematopoietic system [1,2,3]. In recent years, many scientific publications have reported a huge number of genomic alterations, which can be used for AML classification [2,3,4,5,6,7,8]. Furthermore, the identification of genetic lesions is playing an increasing role in the prognosis and treatment of AML patients [4,5,6,7]. From a diagnostic point of view, the routine application of next-generation sequencing (NGS) as well as whole genome sequencing (WGS) into clinical practice has allowed better risk stratification of AML patients [2,3,4,5,6,7,8]. The most commonly altered genes include FLT3, NPM1, DNMT3A, IDH1, IDH2, TET2, RUNX1, NRAS, and TP53 [4,5,6,7]. The incidence of these aberrations varies by patient age, previous exposure to chemotherapy and/or radiotherapy, and history of antecedent hematologic cancer. Accurate risk stratification and prognostication play a fundamental role in the management of AML patients, since it is well known that clinical outcomes vary widely for patients belonging to different cytogenetics and molecular-biology-based subcategories. These genetic risk subgroups are now being used for therapeutic guidance [4,5,6].
European LeukemiaNet (ELN) genetic risk classification is a reference document for the hematology community, and is widely used in either clinical practice or clinical trials [4,5].
However, there is a limitation to the use of this classification, since it is based exclusively on data from AML patients who have been receiving intensive chemotherapy, and cannot be applied in unfit/frail and/or older patients receiving less-intensive therapeutic approaches, especially for those individuals who belong to adverse risk categories [7]. Based on these considerations, we do believe that a novel genetic classification is needed for a correct prognostic stratification of patients receiving less-intensive treatment modalities, which may include hypomethylating agent (HMA, azacitidine (AZA) or decitabine)-based regimens alone or in combination with the B-cell leukemia/lymphoma 2 inhibitor venetoclax (VEN), or with the IDH1inhibitor ivosidenib (IVO) for the IDH1-mutated AML subgroup [9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24]. Preliminary efforts conducted at the Mayo Clinic [25] and by ELN authors [26] are based on a relatively low number of patients and have consequently already been demonstrated to require several refinements [27]. As far as the treatment scenario for AML is concerned, it must be pointed out that the treatment landscape for this disease is rapidly evolving, with novel mono- and combination therapies approved in the last decade [4,5,6,27,28].
Unfortunately, the prognosis for AML patients with high-risk genetic subsets remains unfavorable, and the development of more active treatment options for these patients is highly demanding.
High-risk AML is a heterogeneous group which includes therapy-related AML, AML originating from myelodysplastic syndrome (MDS) or myeloid neoplasms, and AML carrying a complex karyotype or multiple genetic lesions associated with worse prognosis [2,3,4,5,29,30,31].
The most relevant high-risk AML patient categories include (1) Tp53-mutated AML, (2) AML harbouring rearrangements involving the KMT2A locus, (3) secondary AML and (4) AML with a complex karyotype or carrying a chromosome and/or genetic lesions associated with poor outcomes (monosomal karyotype, −5 or del(5q); −7; −17/abn(17p), t(3q26.2;v)/MECOM(EVI1)-rearranged, inv(3)(q21.3q26.2) or t(3;3)(q21.3;q26.2)/GATA2, MECOM(EVI1), t(8;16)(p11;p13)/KAT6A::CREBBP, t(9;22)(q34.1;q11.2)/BCR::ABL1, t(6;9)(p23;q34.1)/DEK::NUP214) [4,5].

2. TP53 AML

2.1. Biological Mechanisms Beyond This Special Entity

Mutations in TP53 disrupt the normal function of p53, the “guardian of the genome”, leading to loss of cell-cycle control, impaired DNA repair, and apoptotic escape in hematopoietic stem/progenitor cells. In AML, TP53 alterations often result in biallelic inactivation (e.g., TP53 mutation with 17p deletion or multiple TP53 hits), conferring a particularly aggressive phenotype [31,32,33,34]. Mechanistically, TP53 mutations can exert loss-of-function (LOF) effects by eliminating wild-type p53 activity, as well as dominant-negative effects, wherein a mutant p53 protein inhibits the remaining wild-type protein. Notably, certain missense mutations also have potential gain-of-function (GOF) properties—for example, aberrant p53 mutants can co-opt chromatin-modifying enzymes (such as EZH2) to promote leukemic self-renewal [34]. Preclinical models illustrate that hematopoietic stem cells (HSCs) bearing a TP53 missense mutation gain a competitive fitness advantage over HSCs with only monoallelic TP53 loss, yet are outcompeted by cells with complete TP53 loss. This hierarchy suggests that residual wild-type p53 activity imposes a dose-dependent tumor suppressor effect (biallelic loss > missense > monoallelic), affecting clonal fitness [35,36,37,38].
TP53-mutated AML frequently arises from antecedent clonal hematopoiesis or myelodysplasia. Although TP53-mutant clones have a relatively low intrinsic proliferative fitness in steady-state hematopoiesis—especially compared to common CHIP mutations such as DNMT3A—they possess marked resilience against cellular stresses. Cytotoxic exposures—notably chemotherapy and radiation—act as evolutionary bottlenecks that selectively favor the expansion of TP53-mutant clones present at low frequency prior to treatment. This phenomenon is evident in therapy-related AML, where the malignant clone can often be traced back to a preexisting TP53-mutated population that survived initial cancer therapy. Indeed, TP53 mutations are enriched in therapy-related myeloid neoplasms and bone marrow failure conditions, indicating that genotoxic stressors allow these mutant clones to outcompete normal HSCs. In summary, the loss of p53 confers a survival advantage under selective pressures (DNA damage, immune clearance), facilitating clonal evolution from pre-cancerous stages to frank leukemia [36,38].
A final striking aspect of TP53-mutated AML is an immunosuppressive tumor microenvironment. TP53-mutant leukemic stem cells upregulate immune checkpoint proteins like PD-L1, driving T-cell exhaustion and permitting immune escape [39]. In myelodysplastic syndromes (MDSs) and secondary AML, TP53 mutations confer an immune-evasive phenotype characterized by high PD-L1 expression on stem/progenitor cells, expansion of immunosuppressive regulatory T cells and myeloid-derived suppressor cells, and a paucity of cytotoxic T lymphocytes [40].

2.2. Clinical Outcomes and Prognostic Implications

Clinically, TP53-mutated AML offers one of the poorest prognoses in adult leukemia. Unlike many other AML subtypes, outcomes for TP53-mutant cases have not improved despite new therapies, with a median overall survival of approximately 6 months, even with intensive treatment, regardless of patient age or fitness status [37,41,42,43,44,45]. This dismal outcome reflects a high rate of primary chemo-refractoriness and early relapse. A recent analysis of frontline trials confirmed that median survival remained uniformly short across therapeutic approaches (chemotherapy, hypomethylating agents, venetoclax-based regimens), highlighting intrinsic chemoresistance in TP53-mutant AML [37].
Current research has focused on whether specific features of TP53 mutations modify this grim prognosis, specifically focusing on the burden of mutations and bi-allelic inactivation. Within a variety of results and thresholds, at the moment such speculation seems more relevant for MDS than for AML [32,37].

2.3. Therapies of TP53 Mutant AML

The therapeutic management of TP53-mutated AML remains challenging and is an area of active research. Standard cytotoxic chemotherapy (e.g., 7 + 3 regimen or CPX-351) yields complete remission rates of only approximately 30–40%, with short-lived remissions (median relapse-free survival of 3–6 months), and overall survival similar to less intensive approaches [37]. Venetoclax combined with hypomethylating agents (HMAs) has become standard for older or unfit patients; however, TP53-mutant AML demonstrates limited benefit. While venetoclax-based combinations induce initial responses, retrospective analyses indicate no significant survival advantage compared to HMA monotherapy [46,47,48].
Multiple novel agents have been explored to improve outcomes in TP53-mutated AML, but the parade of promising drugs that have not held up in later-phase studies has OK curbed progress, including with strategies to restore p53 function (Eprenetapopt combined with venetoclax) [49], bispecific antibodies [50], and agents to target pathways of immune evasion [51].
Allogeneic hematopoietic cell transplantation is, at the moment, the only treatment that offers chances for durable remission, even if the median survival of this population remains dismal (~15–20% at 2 years) [47,48,49,50,51,52].
Due to these biological considerations and poor clinical outcomes, the scientific community is reflecting on considering the TP53 mutant myeloid neoplasms as an entity [53,54].

3. KMT2A-rAML

AML carrying a rearrangement of KMT2A has been found to be associated with poor outcomes, with current treatment approaches not effective for treating patients with relapsed/refractory AML [55,56]. Recent data have documented that several types of AML have overexpression of HOXA/B cluster genes and MEIS1, which are key regulators of stem cell self-renewal and differentiation [57,58,59]. These can be dysregulated when aberrations of histone lysine N-methyltransferase 2A (KMT2A, formerly called “mixed-lineage leukemia fusion 1” (MLL1) and/or NPM1 mutations occur [55,56]. Interestingly, the cytoplasmic localization of the mutant NPM1 is associated with a similar phenotype and genetic signature compared to KMT2A-altered AML.
The inhibition of the protein menin, (KMT2Ar;) and the mutated nucleophosmin gene (NPM1c), leading to the activation of transcription factors such as HOXA and MEIS1, is an innovative target therapy currently under investigation [55,56,57]. KMT2Ar is detected in 10% of AML cases, with a higher prevalence in younger patients who respond poorly to standard therapy [4,5]. NPM1 mutations are prevalent in AML patients and are mostly associated with a favorable prognosis. Comparable to KMT2Ar, NPM1c AML is characterized by the overexpression of HOXA/HOXB and menin, while a blockage of the MLL–menin complex can reinduce differentiation, leading to the inclusion of these patients in ongoing clinical trials using menin inhibitors [56,60]. Various menin inhibitors have been developed and investigated in pre-clinical and clinical trials; the use of revumenib (SNDX-5613) and ziftomenib has been associated with significant complete remission rates (30%) in relapsed/refractory (r/r) AML patients harboring KMT2Ar or NPM1c. Interestingly, menin inhibition was found to be associated with a substantial downregulation of key mediators of the MLL–menin complex, such as HOXA9, PBX3, CDK6 and MEIS1, thus reducing anti-apoptotic signaling molecules like BCL-2 and FLT3 and promoting the differentiation of AML cells.
Based on current investigations, we can speculate that in the near future, most of these patients will be treated successfully with menin inhibitors.

4. Secondary AML (sAML)

sAML is a heterogeneous group of AML, including therapy-related AML, AML originating from myelodysplastic syndrome or chronic myeloid neoplasms, and AML carrying genetic lesions associated with worse prognosis [61].
sAML presents as a complex of disorders, sometimes evolving from germline predisposing mutations, or the sequelae of cytotoxic therapies, and its development is driven by intricate genetic and epigenetic modifications [4,5,56]. Nowadays, genetic lesions are the hallmark of this entity. According to ICC and ELN classifications, the recognition of sAML is based exclusively on the presence of genetic mutations, such as aberrations in SRSF2, SF3B1, U2AF1, ZRSR2, ASXL1, EZH2, BCOR, or STAG2 genes [4,5]. Although the importance of prior therapy, antecedent myeloid neoplasms (i.e., MDS or MDS/MPN), and the development of underlying germline genetic disorders predisposed to AML is well recognized, current classifications now identify such associations as qualifiers for diagnosis rather than as specific disease categories [5]. Using this approach, the prior stand-alone categories of therapy-related myeloid neoplasms and AML with myelodysplasia-related changes are eliminated—genetic lesions are the hallmark of this entity.
The immunophenotypic profiles of these disorders are variable; however, accumulating data seem to support the role played by flow cytometry in the recognition of some of these varieties. This complexity requires a spectrum of therapeutic strategies, each meticulously tailored to address the distinct genetic profiles. Such strategies require a personalized approach, considering the heterogeneous clinical manifestations and biological characteristics of the leukemia clones [62,63,64].
According to ICC Classification, sAML encompasses both therapy-related myeloid neoplasms and antecedent MDS and/or myeloproliferative neoplasms, and are characterized by unfavorable outcomes. Allogeneic stem cell transplantation (HSCT) is a potentially curative approach for high-risk AML. HSCT should be used in combination with innovative treatment modalities such as CPX-351, venetoclax, tamibarotene, tamibarotene, and glasdegib (among many others), which have demonstrated promising results in enhancing prognosis and survival [65,66,67]. The evolving landscape of sAML treatment underscores the importance of continued research and innovation in the field, aiming not only to improve patient outcomes but also to enhance our knowledge of AML, thus allowing the application of more effective and personalized therapies. Based on this consideration, it can be stated that sAML represents a heterogeneous group of leukemias often associated with diverse immunophenotypic and genetic characteristics but inferior outcomes and survival.
Favorable-risk sAML is rare but can be managed similarly to de novo favorable-risk disease.
Furthermore, it must be pointed out that patients with FLT3—ITD-mutated AML continue to have suboptimal outcomes with standard therapies and experience high rates of relapse following HSCT. However, according to current AML classification, these entities are placed either in the intermediate or favorable group [67,68,69,70,71,72].
Another interesting area of investigation in this field is represented by artificial intelligence (AI). In recent years, cytogenetics and molecular biology studies have shown an impressive capacity to accurately define disease biology, with relevant prognostic implications. So far, AI–based algorithms have mainly focused on learning morphologic features that are associated with leukemia diagnosis. In oncology, these algorithms have been used to improve the current risk stratification capabilities of non-genitourinary cancers, colorectal cancer and cholangio carcinoma. Moreover, these algorithms have successfully been used to predict which patients may respond to standard-of-care therapies in several solid tumors. Furthermore, in the hematology field, preliminary investigations have demonstrated that the development of an AI-based predictive model may improve the prediction of post-transplant relapse in patients with AML receiving induction chemotherapy followed by HSCT, thus providing an effective tool for the early prediction and timely management of post-transplant relapse [73]. It is conceivable that this tool could soon aid hematologists in achieving improved and more precise prognosis and therapy for AML.

Acknowledgments

We thank AIL Ravenna (Italian Leukemia Association) for the support.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Pollyea, D.A.; Altman, J.K.; Assi, R.; Bixby, D.; Fathi, A.T.; Foran, J.M.; Gojo, I.; Hall, A.C.; Jonas, B.A.; Kishtagari, A.; et al. Acute Myeloid Leukemia, Version 3.2023, NCCN Clinical Practice Guidelines in Oncology. J. Natl. Compr. Cancer Netw. 2023, 21, 503–513. [Google Scholar] [CrossRef]
  2. Gönen, M.; Figueroa, M.E.; Fernandez, H.; Sun, A.; Racevskis, J.; Van Vlierberghe, P.; Dolgalev, I.; Thomas, S.; Aminova, O.; Patel, J.P.; et al. Prognostic relevance of integrated genetic profiling in acute myeloid leukemia. N. Engl. J. Med. 2012, 366, 1079–1089. [Google Scholar] [CrossRef]
  3. Papaemmanuil, E.; Gerstung, M.; Bullinger, L.; Gaidzik, V.I.; Paschka, P.; Roberts, N.D.; Potter, N.E.; Heuser, M.; Thol, F.; Bolli, N.; et al. Genomic Classification and Prognosis in Acute Myeloid Leukemia. N. Engl. J. Med. 2016, 374, 2209–2221. [Google Scholar] [CrossRef]
  4. Dohner, 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]
  5. Arber, D.A.; Orazi, A.; Hasserjian, R.P.; Borowitz, M.J.; Calvo, K.R.; Kvasnicka, H.-M.; Wang, S.A.; Bagg, A.; Barbui, T.; Branford, S.; et al. International Consensus Classification of Myeloid Neoplasms and Acute Leukemias: Integrating morphologic, clinical, and genomic data. Blood 2022, 140, 1200–1228. [Google Scholar] [CrossRef] [PubMed]
  6. Khoury, J.D.; Solary, E.; Abla, O.; Akkari, Y.; Alaggio, R.; Apperley, J.D.; Bejar, R.; Berti, E.; Busque, L.; Chan, J.K.C.; et al. The 5th edition of the World Health Organization Classification of Haematolymphoid Tumours: Myeloid and Histiocytic/Dendritic Neoplasms. Leukemia 2022, 36, 1703–1719. [Google Scholar] [CrossRef] [PubMed]
  7. Döhner, H.; DiNardo, C.D.; Appelbaum, F.R.; Craddock, C.; Dombret, H.; Ebert, B.L.; Fenaux, P.; Godley, L.A.; Hasserjian, R.P.; Larson, R.A.; et al. Genetic risk classification for adults with AML receiving less-intensive therapies: The 2024 ELN Recommendations. Blood 2024, 144, 2169–2173. [Google Scholar] [CrossRef]
  8. Lanza, F.; Bazarbachi, A. Targeted Therapies and Druggable Genetic Anomalies in Acute Myeloid Leukemia: From Diagnostic Tools to Therapeutic Interventions. Cancers 2021, 13, 4698. [Google Scholar] [CrossRef]
  9. DiNardo, C.D.; Lachowiez, C.A.; Takahashi, K.; Loghavi, S.; Xiao, L.; Kadia, T.; Daver, N.; Adeoti, M.; Short, N.J.; Sasaki, K.; et al. Venetoclax Combined With FLAG-IDA Induction and Consolidation in Newly Diagnosed and Relapsed or Refractory Acute Myeloid Leukemia. J. Clin. Oncol. 2021, 39, 2768–2778. [Google Scholar] [CrossRef]
  10. Todisco, E.; Papayannidis, C.; Fracchiolla, N.; Petracci, E.; Zingaretti, C.; Vetro, C.; Martelli, M.P.; Zappasodi, P.; Di Renzo, N.; Gallo, S.; et al. AVALON: The Italian cohort study on real-life efficacy of hypomethylating agents plus venetoclax in newly diagnosed or relapsed/refractory patients with acute myeloid leukemia. Cancer 2023, 129, 992–1004. [Google Scholar] [CrossRef]
  11. Marconi, G.; Petracci, E.; Lanzarone, G.; Vetro, C.; Martelli, M.P.; Papayannidis, C.; Audisio, E.; Minetto, P.; Riva, C.; Guolo, F.; et al. Impact of Pre-Treatment Comorbidity Burden on Survival in Patients Receiving Venetoclax Plus Hypomethylating Agents. Am. J. Hematol. 2025, 100, 708–711. [Google Scholar] [CrossRef]
  12. Willekens, C.; Bazinet, A.; Chraibi, S.; Bataller, A.; Decroocq, J.; Arani, N.; Carpentier, B.; Rausch, C.; Lebon, D.; Maiti, A.; et al. Reduced venetoclax exposure to 7 days vs standard exposure with hypomethylating agents in newly diagnosed AML patients. Blood Cancer J. 2025, 15, 68. [Google Scholar] [CrossRef] [PubMed]
  13. Ikoma, Y.; Nakamura, N.; Kaneda, Y.; Takamori, H.; Seki, T.; Hiramoto, N.; Kitagawa, J.; Kanda, J.; Fujita, K.; Morishita, T.; et al. Impact of myelodysplasia-related gene mutations and residual mutations at remission in venetoclax/azacitidine for AML. Leukemia 2025, 39, 1362–1367. [Google Scholar] [CrossRef] [PubMed]
  14. Chou, W.C.; Lei, W.C.; Ko, B.S.; Hou, H.A.; Chen, C.Y.; Tang, J.L.; Yao, M.; Tsay, W.; Wu, S.J.; Huang, S.Y.; et al. The prognostic impact and stability of Isocitrate dehydrogenase 2 mutation in adult patients with acute myeloid leukemia. Leukemia 2011, 25, 246–253. [Google Scholar] [CrossRef] [PubMed]
  15. Stein, E.M.; DiNardo, C.D.; Pollyea, D.A.; Fathi, A.T.; Roboz, G.J.; Altman, J.K.; Stone, R.M.; DeAngelo, D.J.; Levine, R.L.; Flinn, I.W.; et al. Enasidenib in mutant IDH2 relapsed or refractory acute myeloid leukemia. Blood 2017, 130, 722–731. [Google Scholar] [CrossRef]
  16. de Botton, S.; Montesinos, P.; Schuh, A.C.; Papayannidis, C.; Vyas, P.; Wei, A.H.; Ommen, H.; Semochkin, S.; Kim, H.J.; Larson, R.A.; et al. Enasidenib vs conventional care in older patients with late-stage mutant-IDH2 relapsed/refractory AML: A randomized phase 3 trial. Blood 2023, 141, 156–167. [Google Scholar] [CrossRef]
  17. Venditti, A.; Piciocchi, A.; Candoni, A.; Arena, V.; Palmieri, R.; Filì, C.; Carella, A.M.; Calafiore, V.; Cairoli, R.; de Fabritiis, P.; et al. Risk-adapted MRD-directed therapy for young acute myeloid leukemia adults: 6-year update of the GIMEMA AML1310 trial. Blood Adv. 2024, 8, 4410–4413. [Google Scholar] [CrossRef]
  18. Gottardi, M.; Simonetti, G.; Sperotto, A.; Nappi, D.; Ghelli Luserna di Rorà, A.; Padella, A.; Norata, A.; Giannini, M.B.; Musuraca, G.; Lanza, F.; et al. Therapeutic Targeting of Acute Myeloid Leukemia by Gemtuzumab Ozogamicin. Cancers 2021, 13, 4566. [Google Scholar] [CrossRef]
  19. Röllig, C.; Steffen, B.; Schliemann, C.; Mikesch, J.-H.; Alakel, N.; Herbst, E.; Hänel, M.; Noppeney, R.; Hanoun, M.; Kaufmann, M.; et al. Single or Double Induction With 7 + 3 Containing Standard or High-Dose Daunorubicin for Newly Diagnosed AML: The Randomized DaunoDouble Trial by the Study Alliance Leukemia. J. Clin. Oncol. 2025, 43, 65–74. [Google Scholar] [CrossRef]
  20. Mishra, S.K.; Millman, S.E.; Zhang, L. Metabolism in acute myeloid leukemia: Mechanistic insights and therapeutic targets. Blood 2023, 141, 1119–1135. [Google Scholar] [CrossRef]
  21. McCall, D.; Alqahtani, S.; Budak, M.; Sheikh, I.; Fan, A.E.; Ramakrishnan, R.; Nunez, C.; Roth, M.; Garcia, M.B.; Gibson, A.; et al. Cladribine-Based Therapy for Relapsed or Refractory Acute Myeloid Leukemia in Child, Adolescent, and Early Young Adult Patients: The MD Anderson Cancer Center Experience. Cancers 2024, 16, 3886. [Google Scholar] [CrossRef]
  22. Mosna, F.; Borlenghi, E.; Litzow, M.; Byrd, J.C.; Papayannidis, C.; Tecchio, C.; Ferrara, F.; Marcucci, G.; Cairoli, R.; Morgan, E.A.; et al. Long-term survival can be achieved in a significant fraction of older patients with core binding factor acute myeloid leukemia treated with intensive chemotherapy. Haematologica 2024, 110, 608–620. [Google Scholar] [CrossRef]
  23. George, B.M.; Luskin, M.R. Is age just a number? Intensive therapy for core-binding factor acute myeloid leukemia in older adults. Haematologica 2025, 110, 543–545. [Google Scholar] [CrossRef] [PubMed]
  24. Ge, S.; Wang, J.; He, Q.; Zhu, J.; Liu, P.; Wang, H.; Zhang, F. Auto-hematopoietic stem cell transplantation or chemotherapy? Meta-analysis of clinical choice for AML. Ann. Hematol. 2024, 103, 3855–3866. [Google Scholar] [CrossRef] [PubMed]
  25. Gangat, N.; Elbeih, A.; Ghosoun, N.; McCullough, K.; Aperna, F.; Johnson, I.M.; Abdelmagid, M.; Al-Kali, A.; Alkhateeb, H.B.; Begna, K.H.; et al. Risk Models for Newly Diagnosed Acute Myeloid Leukemia Treated With Venetoclax + Hypomethylating Agent. Am. J. Hematol. 2024, 100, 260–271. [Google Scholar] [CrossRef] [PubMed]
  26. Lachowiez, C.A.; Ravikumar, V.I.; Othman, J.; O’Nions, J.; Peters, D.T.; McMahon, C.; Swords, R.; Cook, R.; Saultz, J.N.; Tyner, J.W.; et al. Refined ELN 2024 risk stratification improves survival prognostication following venetoclax-based therapy in AML. Blood 2024, 144, 2788–2792. [Google Scholar] [CrossRef]
  27. Lachowiez, C.A.; Heiblig, M.; Requena, G.A.; Tavernier-Tardy, E.; Dai, F.; Ashango, A.B.; Peters, D.T.; Fang, J.; Kaempf, A.; Long, N.; et al. Genetic and Phenotypic correlates of clinical outcomes with Venetoclax in Acute Myeloid Leukemia: The GEN-PHEN-VEN study. Blood Cancer Discov. 2025, Online ahead of print. [Google Scholar] [CrossRef]
  28. 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]
  29. Lanza, F.; Rondoni, M.; Zannetti, B.A. New Horizons in Immunology and Immunotherapy of Acute Leukemias and Related Disorders. Cancers 2023, 15, 2422. [Google Scholar] [CrossRef]
  30. Rondoni, M.; Marconi, G.; Nicoletti, A.; Giannini, B.; Zuffa, E.; Giannini, M.B.; Mianulli, A.; Norata, M.; Monaco, F.; Zaccheo, I.; et al. Low WT1 Expression Identifies a Subset of Acute Myeloid Leukemia with a Distinct Genotype. Cancers 2025, 17, 1213. [Google Scholar] [CrossRef]
  31. Hiwase, D.; Hahn, C.; Tran, E.N.H.; Chhetri, E.; Baranwal, A.; Al-Kali, A.; Sharplin, K.; Ladon, D.; Hollins, R.; Greipp, P.; et al. TP53 mutation in therapy-related myeloid neoplasm defines a distinct molecular subtype. Blood 2023, 141, 1087–1091. [Google Scholar] [CrossRef] [PubMed]
  32. Sallman, D.A.; Stahl, M. TP53-mutated acute myeloid leukemia: How can we improve outcomes? Blood 2025, 145, 2828–2833. [Google Scholar] [CrossRef] [PubMed]
  33. Lane, D.P. How to lose tumor suppression. Science 2019, 365, 539–540. [Google Scholar] [CrossRef] [PubMed]
  34. Zhu, J.; Sammons, M.A.; Donahue, G.; Dou, Z.; Vedadi, M.; Getlik, M.; Barsyte-Lovejoy, D.; Al-awar, R.; Katona, B.W.; Shilatifard, A.; et al. Gain-of-function p53 mutants co-opt chromatin pathways to drive cancer growth. Nature 2015, 525, 206–211. [Google Scholar] [CrossRef]
  35. Wong, T.N.; Ramsingh, G.; Young, A.; Miller, C.A.; Touma, W.; Welch, J.S.; Lamprecht, T.L.; Shen, D.; Hundal, J.; Fulton, R.S.; et al. Role of TP53 mutations in the origin and evolution of therapy-related acute myeloid leukaemia. Nature 2015, 518, 552–555. [Google Scholar] [CrossRef]
  36. Usui, Y.; Endo, M.; Iwasaki, Y.; Iijima, H.; Nakagawa, H.; Matsuda, K.; Momozawa, Y. Clinical Significance of TP53-Mutant Clonal Hematopoiesis Across Diseases. Blood Cancer Discov. 2025, 6, 298–306. [Google Scholar] [CrossRef]
  37. Senapati, J.; Loghavi, S.; Garcia-Manero, G.; Tang, G.; Kadia, T.; Short, N.J.; Abbas, H.A.; Arani, N.; DiNardo, C.D.; Borthakur, G.; et al. Clinical interrogation of TP53 aberrations and its impact on survival in patients with myeloid neoplasms. Haematologica 2025, 110, 1304–1315. [Google Scholar] [CrossRef]
  38. Diamond, B.; Ziccheddu, B.; Maclachlan, K.; Taylor, J.; Boyle, E.; Ossa, J.A.; Jahn, J.; Affer, M.; Totiger, T.M.; Coffey, D.; et al. Tracking the evolution of therapy-related myeloid neoplasms using chemotherapy signatures. Blood 2023, 141, 2359–2371. [Google Scholar] [CrossRef]
  39. Platzbecker, U.; Kordasti, S. Natural born survivors: The inglorious TP53. Blood 2020, 136, 2727–2728. [Google Scholar] [CrossRef]
  40. Sallman, D.A.; McLemore, A.F.; Aldrich, A.L.; Komrokji, R.S.; McGraw, K.L.; Dhawan, A.; Geyer, S.; Hou, H.A.; Eksioglu, E.A.; Sullivan, A.; et al. TP53 mutations in myelodysplastic syndromes and secondary AML confer an immunosuppressive phenotype. Blood 2020, 136, 2812–2823. [Google Scholar] [CrossRef]
  41. Weinberg, O.K.; Siddon, A.; Madanat, Y.F.; Gagan, J.; Arber, D.A.; Dal Cin, P.; Narayanan, D.; Ouseph, M.M.; Kurzer, J.H.; Hasserjian, R.P. TP53 mutation defines a unique subgroup within complex karyotype de novo and therapy-related MDS/AML. Blood Adv. 2022, 6, 2847–2853. [Google Scholar] [CrossRef] [PubMed]
  42. Grob, T.; Al Hinai, A.S.A.; Sanders, M.A.; Kavelaars, F.G.; Rijken, M.; Gradowska, P.L.; Biemond, B.J.; Breems, D.A.; Maertens, J.; van Marwijk Kooy, M.; et al. Molecular characterization of mutant TP53 acute myeloid leukemia and high-risk myelodysplastic syndrome. Blood 2022, 139, 2347–2354. [Google Scholar] [CrossRef] [PubMed]
  43. Stengel, A.; Meggendorfer, M.; Walter, W.; Baer, C.; Nadarajah, N.; Hutter, S.; Kern, W.; Haferlach, T.; Haferlach, C. Interplay of TP53 allelic state, blast count, and complex karyotype on survival of patients with AML and MDS. Blood Adv. 2023, 7, 5540–5548. [Google Scholar] [CrossRef] [PubMed]
  44. Stengel, A.; Haferlach, T.; Baer, C.; Hutter, S.; Meggendorfer, M.; Kern, W.; Haferlach, C. Specific subtype distribution with impact on prognosis of TP53 single-hit and double-hit events in AML and MDS. Blood Adv. 2023, 7, 2952–2956. [Google Scholar] [CrossRef]
  45. Fontana, M.C.; Marconi, G.; Feenstra, J.D.M.; Fonzi, E.; Papayannidis, C.; Ghelli Luserna di Rorá, A.; Padella, A.; Solli, V.; Franchini, E.; Ottaviani, E.; et al. Chromothripsis in acute myeloid leukemia: Biological features and impact on survival. Leukemia 2018, 32, 1609–1620. [Google Scholar] [CrossRef]
  46. DiNardo, C.D.; Jonas, B.A.; Pullarkat, V.; Thirman, M.J.; Garcia, J.S.; Wei, A.H.; Konopleva, M.; Döhner, H.; Letai, A.; Fenaux, P.; et al. Azacitidine and Venetoclax in Previously Untreated Acute Myeloid Leukemia. N. Engl. J. Med. 2020, 383, 617–629. [Google Scholar] [CrossRef]
  47. Badar, T.; Atallah, E.; Shallis, R.M.; Goldberg, A.D.; Patel, A.; Abaza, Y.; Bewersdorf, J.P.; Saliba, A.N.; Sacchi De Camargo Correia, G.; Murthy, G.; et al. Outcomes of TP53-mutated AML with evolving frontline therapies: Impact of allogeneic stem cell transplantation on survival. Am. J. Hematol. 2022, 97, E232–E235. [Google Scholar] [CrossRef]
  48. Kim, K.; Maiti, A.; Loghavi, S.; Pourebrahim, R.; Kadia, T.M.; Rausch, C.R.; Furudate, K.; Daver, N.G.; Alvarado, Y.; Ohanian, M.; et al. Outcomes of TP53-mutant acute myeloid leukemia with decitabine and venetoclax. Cancer 2021, 127, 3772–3781. [Google Scholar] [CrossRef]
  49. Garcia-Manero, G.; Goldberg, A.D.; Winer, E.S.; Altman, J.K.; Fathi, A.T.; Odenike, O.; Roboz, G.J.; Sweet, K.; Miller, K.; Wennborg, A.; et al. Eprenetapopt combined with venetoclax and azacitidine in TP53-mutated acute myeloid leukaemia: A phase 1, dose-finding and expansion study. Lancet Haematol. 2023, 10, e272–e283. [Google Scholar] [CrossRef]
  50. Uy, G.L.; Aldoss, I.; Foster, M.C.; Sayre, P.H.; Wieduwilt, M.J.; Advani, A.S.; Godwin, J.E.; Arellano, M.L.; Sweet, K.L.; Emadi, A.; et al. Flotetuzumab as salvage immunotherapy for refractory acute myeloid leukemia. Blood 2021, 137, 751–762. [Google Scholar] [CrossRef]
  51. Zeidner, J.D.; Sallman, D.A.; Récher, C.; Daver, N.G.; Leung, A.Y.; Hiwase, D.K.; Subklewe, M.; Pabst, T.; Montesinos, P.; Larson, R.A.; et al. Magrolimab plus azacitidine vs physician’s choice for untreated TP53-mutated acute myeloid leukemia: The ENHANCE-2 study. Blood 2025, Online ahead of print. [Google Scholar] [CrossRef] [PubMed]
  52. Nawas, M.T.; Kosuri, S. Utility or futility? A contemporary approach to allogeneic hematopoietic cell transplantation for TP53-mutated MDS/AML. Blood Adv. 2024, 8, 553–561. [Google Scholar] [CrossRef] [PubMed]
  53. Ball, S.; Loghavi, S.; Zeidan, A.M. TP53-altered higher-risk myelodysplastic syndromes/neoplasms and acute myeloid leukemia: A distinct genetic entity with unique unmet needs. Leuk. Lymphoma 2023, 64, 540–550. [Google Scholar] [CrossRef] [PubMed]
  54. Shahzad, M.; Amin, M.K.; Daver, N.G.; Shah, M.V.; Hiwase, D.; Arber, D.A.; Kharfan-Dabaja, M.A.; Badar, T. What have we learned about TP53-mutated acute myeloid leukemia? Blood Cancer J. 2024, 14, 202. [Google Scholar] [CrossRef]
  55. Mill, C.P.; Fiskus, W.; Das, K.; Davis, J.A.; Birdwell, C.E.; Kadia, T.M.; DiNardo, C.D.; Daver, N.; Takahashi, K.; Sasaki, K.; et al. Causal linkage of presence of mutant NPM1 to efficacy of novel therapeutic agents against AML cells with mutant NPM1. Leukemia 2023, 37, 1336–1348. [Google Scholar] [CrossRef]
  56. Dohner, K.; Thiede, C.; Jahn, N.; Panina, E.; Gambietz, A.; Larson, R.A.; Prior, T.W.; Marcucci, G.; Jones, D.; Krauter, J.; et al. Impact of NPM1/FLT3-ITD genotypes defined by the 2017 European LeukemiaNet in patients with acute myeloid leukemia. Blood 2020, 135, 371–380. [Google Scholar] [CrossRef]
  57. Uckelmann, H.J.; Haarer, E.L.; Takeda, R.; Wong, E.M.; Hatton, C.; Marinaccio, C.; Perner, F.; Rajput, M.; Antonissen, N.J.C.; Wen, Y.; et al. Mutant NPM1 Directly Regulates Oncogenic Transcription in Acute Myeloid Leukemia. Cancer Discov. 2023, 13, 746–765. [Google Scholar] [CrossRef]
  58. Soto-Feliciano, Y.M.; Sanchez-Rivera, F.J.; Perner, F.; Barrows, D.W.; Kastenhuber, E.R.; Ho, Y.J.; Carroll, T.; Xiong, Y.; Anand, D.; Soshnev, A.A.; et al. A Molecular Switch between Mammalian MLL Complexes Dictates Response to Menin-MLL Inhibition. Cancer Discov. 2023, 13, 146–169. [Google Scholar] [CrossRef]
  59. Fleischmann, M.; Bechwar, J.; Voigtländer, D.; Fischer, M.; Schnetzke, U.; Hochhaus, A.; Scholl, S. Synergistic effects of the RARalpha agonist tamibarotene and the Menin inhibitor revumenib in acute myeloid leukemia cells with KMT2A rearrangement or NPM1 mutation. Cancers 2024, 16, 1311. [Google Scholar] [CrossRef]
  60. Dalle, I.A.; Labopin, M.; Khvedelidze, I.; Baron, F.; Brissot, E.; Bug, G.; Esteve, J.; Giebel, S.; Gorin, N.-C.; Lanza, F.; et al. Growing adoption of pharmacologic maintenance therapy after allogeneic hematopoietic cell transplantation in acute myeloid leukemia: A survey on behalf of the EBMT acute leukemia working party. Bone Marrow Transplant. 2025, 60, 921–923. [Google Scholar] [CrossRef]
  61. Marconi, G.; Rondoni, M.; Zannetti, B.A.; Zacheo, I.; Nappi, D.; Mattei, A.; Rocchi, S.; Lanza, F. Novel insights and therapeutic approaches in secondary AML. Front. Oncol. 2024, 14, 1400461. [Google Scholar] [CrossRef]
  62. Mehta, P.; Campbell, V.; Maddox, J.; Floisand, Y.; Kalakonda, A.J.M.; O’Nions, J.; Coats, T.; Nagumantry, S.; Hodgson, K.; Whitmill, R.; et al. CREST-UK: Real-world effectiveness, safety and outpatient delivery of CPX-351 for first-line treatment of newly diagnosed therapy-related AML and AML with myelodysplasia-related changes in the UK. Br. J. Haematol. 2024, 205, 1326–1336. [Google Scholar] [CrossRef] [PubMed]
  63. Rodríguez-Arbolí, E.; Rodríguez-Veiga, R.; Soria-Saldise, E.; Bergua, J.M.; Caballero-Velázquez, T.; Arnán, M.; Vives, S.; Serrano, J.; Bernal, T.; Martínez-Sánchez, P.; et al. A phase 2, multicenter, clinical trial of CPX-351 in older patients with secondary or high-risk acute myeloid leukemia: PETHEMA-LAMVYX. Cancer 2025, 131, e35618. [Google Scholar] [CrossRef] [PubMed]
  64. Cortes, J.E.; Lin, T.L.; Asubonteng, K.; Faderl, S.; Lancet, J.E.; Prebet, T. Efficacy and safety of CPX-351 versus 7 + 3 chemotherapy by European LeukemiaNet 2017 risk subgroups in older adults with newly diagnosed, high-risk/secondary AML: Post hoc analysis of a randomized, phase 3 trial. J. Hematol. Oncol. 2022, 15, 155. [Google Scholar] [CrossRef] [PubMed]
  65. de Botton, S.; Cluzeau, T.; Vigil, C.; Cook, R.J.; Rousselot, P.; Rizzieri, D.A.; Liesveld, J.L.; Fenaux, P.; Braun, T.; Banos, A.; et al. Targeting RARA overexpression with tamibarotene, a potent and selective RARalpha agonist, is a novel approach in AML. Blood Adv. 2023, 7, 1858–1870. [Google Scholar] [CrossRef]
  66. DeZern, A.E.; Thepot, S.; De Botton, S.; Patriarca, A.; Deeren, D.; Torregrose Diaz, J.M.; Marconi, G.; Bernal Del Castillo, T.; Bergua Burgues, J.M.; Xicoy, B.; et al. Pivotal Results of SELECT-MDS-1 Phase 3 Study of Tamibarotene with Azacitidine in Newly Diagnosed Higher-Risk MDS. Blood Adv. 2025, Online ahead of print. [Google Scholar] [CrossRef]
  67. Rungjirajittranon, T.; Siriwannangkul, T.; Kungwankiattichai, S.; Leelakanok, N.; Rotchanapanya, W.; Vittayawacharin, P.; Mekrakseree, B.; Kulchutisin, K.; Owattanapanich, W. Clinical Outcomes of Acute Myeloid Leukemia Patients Harboring the RUNX1 Mutation: Is It Still an Unfavorable Prognosis? A Cohort Study and Meta-Analysis. Cancers 2022, 14, 5239. [Google Scholar] [CrossRef]
  68. Schlenk, R.F.; Kayser, S.; Bullinger, L.; Kobbe, G.; Casper, J.; Ringhoffer, M.; Held, G.; Brossart, P.; Lübbert, M.; Salih, H.R.; et al. Differential impact of allelic ratio and insertion site in FLT3-ITD-positive AML with respect to allogeneic transplantation. Blood 2014, 124, 3441–3449. [Google Scholar] [CrossRef]
  69. Small, D. FLT3 mutations: Biology and treatment. Hematol. Am. Soc. Hematol. Educ. Program. 2006, 2006, 178–184. [Google Scholar] [CrossRef]
  70. Bazarbachi, A.; Bug, G.; Baron, F.; Brissot, E.; Ciceri, F.; Dalle, I.A.; Döhner, H.; Esteve, J.; Floisand, Y.; Giebel, S.; et al. Clinical practice recommendation on hematopoietic stem cell transplantation for acute myeloid leukemia patients with FLT3-internal tandem duplication: A position statement from the Acute Leukemia Working Party of the European Society for Blood and Marrow Transplantation. Haematologica 2020, 105, 1507–1516. [Google Scholar] [CrossRef]
  71. Capria, S.; Trisolini, S.M.; Torrieri, L.; Amabile, E.; Marsili, G.; Piciocchi, A.; Barberi, W.; Iori, A.P.; Diverio, D.; Carmini, D.; et al. Real-Life Management of FLT3-Mutated AML: Single-Centre Experience over 24 Years. Cancers 2024, 16, 2864. [Google Scholar] [CrossRef]
  72. Pratz, K.W.; Cherry, M.; Altman, J.K.; Cooper, B.W.; Podoltsev, N.A.; Cruz, J.C.; Lin, T.L.; Schiller, G.J.; Jurcic, J.G.; Asch, A.; et al. Gilteritinib in Combination With Induction and Consolidation Chemotherapy and as Maintenance Therapy: A Phase IB Study in Patients With Newly Diagnosed AML. J. Clin. Oncol. 2023, 41, 4236–4246. [Google Scholar] [CrossRef]
  73. Fan, S.; Hong, H.; Lu, S.; Wen, Q.; Hong, S.; Zhang, X.; Xu, L.; Wang, Y.; Yan, C.; Chen, H.; et al. Artificial intelligence-based predictive model for relapse in acute myeloid leukemia patients following haploidentical hematopoietic cell transplantation. J. Transl. Intern. Med. 2025, 13, 253–266. [Google Scholar] [CrossRef]
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Lanza, F.; Rondoni, M.; Marconi, G. Acute Myeloid Leukemia: Updates on Diagnosis, Treatment and Management. Cancers 2025, 17, 2387. https://doi.org/10.3390/cancers17142387

AMA Style

Lanza F, Rondoni M, Marconi G. Acute Myeloid Leukemia: Updates on Diagnosis, Treatment and Management. Cancers. 2025; 17(14):2387. https://doi.org/10.3390/cancers17142387

Chicago/Turabian Style

Lanza, Francesco, Michela Rondoni, and Giovanni Marconi. 2025. "Acute Myeloid Leukemia: Updates on Diagnosis, Treatment and Management" Cancers 17, no. 14: 2387. https://doi.org/10.3390/cancers17142387

APA Style

Lanza, F., Rondoni, M., & Marconi, G. (2025). Acute Myeloid Leukemia: Updates on Diagnosis, Treatment and Management. Cancers, 17(14), 2387. https://doi.org/10.3390/cancers17142387

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