ABSTRACT
Introduction
NPM1 mutated AML without FLT3‐ITD is considered “favorable” per the recent ELN 2022 criteria. However, our center has been challenged with treatment‐refractory patients, prompting a search for additional prognostic factors.
Methods
We reviewed records of NPM1 AML patients from 2015 to 2024. Factors associated with event‐free survival (EFS) and overall survival (OS) were evaluated using Cox regression.
Results
Among 141 patients with NPM1 AML, subtype A was the most common (N = 99), followed by subtype D (N = 10), subtype B (N = 6), subtype G/I/J/K/R (N = 3/5/3/2/1) and other subtypes (N = 12). Ninety patients received chemotherapy (chemo), 41 received hypomethylating agent +/− venetoclax (HMA/ven) and 10 did not receive specific anti‐AML therapy. At 12 months, EFS for subtypes A, D, B, G/I/J/K/R, and other subtypes were 49%, 58%, 50%, 49%, and 31%, and OS were 71%, 79%, 50%, 44%, and 56%, respectively. Fifty patients had allogeneic stem cell transplants: 33 in CR1 and 17 in CR2+. EFS at 12 months post‐HSCT was 72%.
On multivariable analysis, co‐mutation with KRAS (HR: 2.69, 95% CI: 1.20–6.00) or TET2 (HR: 1.99, 95% CI: 1.22–3.26) was associated with worse EFS. For each 50 k/mm3 increase in WBC at diagnosis, the risk of relapse or death increased by 21%. For OS, co‐mutation with IDH1/IDH2 (HR: 0.40, 95% CI: 0.21–0.74) was associated with better OS, whereas co‐mutation with SRSF2 (HR: 2.70, 95% CI: 1.35–5.40) was associated with worse OS.
Conclusion
We did not find a statistically significant difference in EFS and OS among the NPM1 subtypes. However, our results showed that the prognoses of NPM1 AML can be influenced by other co‐occurring mutations. A larger study is needed to confirm our findings.
Keywords: AML, co‐mutation, EFS, NPM1 subtype, OS
1. Introduction
The prognosis of acute myeloid leukemia (AML) is dictated by the underlying cytogenetic abnormalities and molecular mutation patterns, as reflected by the recent major revision from the World Health Organization and International Consensus Classification of Myeloid Neoplasms and Acute Leukemias in 2022 [1, 2]. In the absence of FMS‐like tyrosine kinase‐3 (FLT3) internal tandem duplication (ITD) mutation, nucleophosmin1 (NPM1) mutation is considered a favorable prognostic marker [3, 4, 5], but our center has been challenged with a few treatment‐refractory NPM1 AML patients, prompting a search for other overriding prognostic factors. As AML driven by NPM1 can be as prevalent in up to 30% of newly diagnosed AML [6], there remains a need to stratify those with truly favorable prognoses compared to those at high risk of relapse.
NPM1 protein mainly resides in the nucleolus and performs crucial tasks including ribosome biogenesis, DNA repair, histone chaperoning, and many other functions [7]. The most common NPM1 mutation occurs when the TCTG DNA sequence is inserted in exon 12 (previously exon 11 [8]) dubbed ‘subtype A' NPM1 [7] resulting in a conformational change of the C‐terminus nucleus that preferentially shuttles the NPM1 through the nuclear export protein (XPO1) into the cytoplasm; a mechanism proposed to incite leukemogenesis. Other subtypes of NPM1 in descending order of prevalence include subtypes D, B, G, I, J, K, R, and other subtypes that result from different variants of insertion mutations on exon 12 and sporadically on exon 11 [9] or 9 [10]. A few reports have noted distinctive clinical outcomes among the various subtypes of NPM1 [11, 12, 13], but the true clinical impact and natural course of the disease of other NPM1 subtypes remain to be explored.
By itself, the NPM1 alone is sufficient to initiate and sustain leukemogenesis but the effect of co‐occurring mutations can be variable, for example when coupled with a proliferating mutation such as FLT3‐ITD, the growth potential seems exponential, while the magnitude of the cellular proliferation when NPM1 co‐mutates with a downstream intracellular mutation such as PTPN11, WT1, or mutations in the RAS pathway [14] are less prominent. There is also limited data on the significance of co‐occurring age‐related clonal hematopoietic mutations [15] and splicing factor mutations [16]. We, therefore, aim to clarify whether the subtypes of NPM1 or the different co‐mutation patterns could influence event‐free survival (EFS) and overall survival (OS) among patients with NPM1 AML.
2. Methods
We retrospectively reviewed the medical records of patients age ≥ 18 diagnosed with NPM1 AML at the University of Iowa Health Care (UIHC) between 2015 and 2024. Patients provided informed consent for treatment and authorized the use of their personal information for research purposes. This study was approved by the University of Iowa Institutional Review Board.
2.1. Definitions
Bone marrow biopsies were reviewed by UIHC expert hematopathologists for morphology, including features of monocytic differentiation and % marrow blasts. NPM1 and 34 other AML‐related genes were identified by the UIHC institutional panel using a massively parallel next‐generation sequencing (NGS)‐by‐synthesis (Ion Torrent)‐based assay (list of genes provided in Table S2). Identified mutations were categorized using guidelines established by the Association for Molecular Pathology on interpreting somatic sequence variants, and the threshold for reporting a mutation is a variant allelic frequency (VAF) ≥ 4%.
The subtypes of NPM1 were classified by the definition from a prior report from Alpermann et al. [11] (details of insertion mutation variants are provided in Table S2). In patients diagnosed after 2020, we also incorporated quantification of the NPM1 transcript using multiplex reverse transcription in combination with digital droplet PCR technology (RT‐PCR). The limit of quantitation is 0.005% NPM1 Quant ratio.
Treatment consists of high‐intensity chemotherapy (chemo) including [17]: anthracycline and cytarabine “7 + 3” (with the addition of gemtuzumab ozogamicin (GO) or FLT3 inhibitors (FLT3i) per the treating physician), Fludarabine‐based chemo (FLAG‐Ida) or other high‐dose cytarabine‐based regimens. Low‐intensity therapy includes hypomethylating agents (HMA; azacytidine or decitabine) with or without venetoclax (ven).
Response assessment at the end of induction was based on European LeukemiaNet 2022 criteria [5]. Measurable residual disease (MRD) status was determined by 10‐color flow cytometry, UIHC NGS panel, and NPM1 RT‐PCR.
2.2. Statistical Analysis
Chi‐squared tests were used to compare categorical variables, and Wilcoxon rank sum tests were used to compare continuous variables between types. Firth‐penalized logistic regression models were utilized to estimate the effect of patient, disease, and treatment characteristics on the odds of achieving a complete response among patients who received treatment. Survival probabilities were estimated and plotted using the Kaplan–Meier method. Time was calculated from the date of diagnosis to progression, relapse, or death due to any cause for event‐free survival (EFS), and to death due to any cause for overall survival (OS). Otherwise, patients were censored at HSCT (if applicable) or the last follow‐up. Among patients receiving an HSCT, time was calculated from HSCT to relapse or death due to any cause for recurrence‐free survival (RFS). Cox regression models were used to estimate the effect of patient, disease, and treatment characteristics on EFS and OS. All statistical testing was two‐sided and assessed for significance at the 5% level using SAS v9.4 (SAS Institute, Cary, NC).
3. Results
3.1. Patient Characteristics
Among 141 patients with NPM1 AML, subtype A was the most common (N = 99), followed by subtype D (N = 10), subtype B (N = 6), subtype G/I/J/K/R (N = 3/5/3/2/1) and other subtypes (N = 12) (details of NPM1 subtypes in Table S2). The median age at diagnosis was 62 years.
When stratified between subtype A versus non‐A NPM1, only karyotype significantly differed between groups (p = 0.03, Table 1). Subtype non‐A more frequently had trisomy 8 and other abnormalities. Subtype A tended to present with a higher white blood cell (WBC) count at diagnosis (median 33.0 vs. 19.2 k/mm3, p = 0.08). A statistically significant difference was not noted for sex, % marrow blasts at diagnosis, monocytic differentiation, extramedullary involvement, or baseline NPM1 VAF between the two cohorts. There were also no significant differences in the distribution of co‐mutations for FLT3, IDH, RAS pathway, splicing factor mutations, PTPN11, WT1, and DTA mutations. One patient in the subtype A cohort harbored a concomitant TP53 mutation.
TABLE 1.
Patient characteristics.
| Type A (N = 99) | Other type (N = 42) | p | |
|---|---|---|---|
| Median age (range) | 62 (28–94) | 63 (19–80) | 0.76 |
| Female (%) | 54 (54.5%) | 17 (40.5%) | 0.13 |
| Initial WBC count (k/mm3) (range) | 33.0 (1.4–450) | 19.2 (0.1–400.0) | 0.08 |
| Median % marrow blast (range) | 66% (2%–100%) | 64% (5%–100%) | 0.90 |
| Monocytic differentiation | 45 (45.5%) | 17 (40.5%) | 0.59 |
| Extramedullary disease | 13 (13.1%) | 11 (26.2%) | 0.06 |
| Baseline NPM1 VAF | 0.77 | ||
| < 40% | 38 (38.8%) | 17 (41.5%) | |
| ≥ 40% | 60 (61.2%) | 24 (58.5%) | |
| Co‐mutation | |||
| FLT3 | |||
| FLT3‐ITD | 24 (25.0%) | 8 (19.5%) | 0.49 |
| FLT3‐TKD | 16 (16.7%) | 8 (19.5%) | 0.69 |
| IDH | |||
| IDH1 | 13 (13.5%) | 5 (12.2%) | 0.83 |
| IDH2 | 21 (21.9%) | 4 (9.8%) | 0.09 |
| RAS pathway | |||
| KRAS | 5 (5.2%) | 5 (12.2%) | 0.17 |
| NRAS | 11 (11.5%) | 6 (14.6%) | 0.61 |
| HRAS | 0 | 0 | |
| DTA | |||
| DNMT3A | 34 (35.4%) | 9 (22.0%) | 0.12 |
| TET2 | 28 (29.2%) | 8 (19.5%) | 0.24 |
| ASXL1 | 5 (5.2%) | 0 | 0.32 |
| Splicing factor | |||
| SRSF2 | 10 (10.4%) | 6 (14.6%) | 0.56 |
| ZRSR2 | 1 (1.0%) | 1 (2.4%) | 0.51 |
| SF3B1 | 0 | 0 | |
| WT1 | 6 (6.3%) | 3 (7.3%) | 1.00 |
| PTPN11 | 13 (13.5%) | 8 (19.5%) | 0.37 |
| TP53 | 1 (1.0%) | 0 | 1.00 |
| Karyotype | 0.03 | ||
| Normal | 85 (89.5%) | 30 (73.2%) | |
| Trisomy 8 | 6 (6.3%) | 4 (9.8%) | |
| Other abnormalities | 4 (4.2%) | 7 (17.1%) | |
| Treatment | 0.52 | ||
| Chemotherapy | 66 (66.7%) | 24 (57.1%) | |
| HMA +/− venetoclax | 27 (27.3%) | 14 (33.3%) | |
| No treatment | 6 (6.1%) | 4 (9.5%) | |
| Initial Response | 0.68 | ||
| CR/CRi MRD‐ by MFC | 57 (57.6%) | 22 (52.4%) | |
| CR/CRi MRD+ by MFC | 20 (20.2%) | 7 (16.7%) | |
| PR/Refractory disease | 12 (12.1%) | 6 (14.3%) | |
| Not evaluable | 10 (10.1%) | 7 (16.7%) | |
| Median follow‐up (months) (range) | 16.8 (0.0–108.3) | 11.6 (0.1–103.0) | |
| Median follow‐up for survivors (months) (range) | 34.2 (2.6–108.3) | 31.4 (2.1–98.7) |
Note: Bold values indicates the interpretation of the significance are mentioned in the texts, p–value is highlighted when < 0.05.
From both cohorts, 90 patients received chemo including 7 + 3 (N = 80; 29 with additional FLT3i and 5 with GO), FLAG‐Ida (N = 7), and a cytarabine‐based regimen (N = 3). Forty‐one received HMA +/− ven and 10 did not receive specific anti‐AML therapy. Ten patients were enrolled in clinical trials; each received the addition of uproleselan (N = 3), idasanutlin (N = 1), or vorinostat (N = 1) with chemo and tamibarotene (N = 1), magrolimab (N = 1), or alvodicib (N = 1) with HMA +/− ven.
3.2. Outcomes
EFS at 12 months was 58% (95% confidence interval (CI): 23%–82%) for subtype D, 50% (95% CI: 11%–80%) for subtype B, 49% (95% CI: 37%–60%) for subtype A, 49% (95% CI: 19%–74%) for subtype G/I/J/K/R, and 31% (95% CI: 8%–59%) for other subtypes (Figure 1). OS at 12 months was 79% (95% CI: 38%–94%) for subtype D, 71% (95% CI: 60%–79%) for subtype A, 56% (95% CI: 24%–79%) for other subtypes, 50% (95% CI: 11%–80%) for subtype B, and 44% (95% CI: 17%–68%) for subtype G/I/J/K/R (Figure 2). Collectively for subtype non‐A, EFS and OS at 12 months were 46% (95% CI: 29%–61%) and 57% (95% CI: 41%–71%), respectively (Figures S1 and S2).
FIGURE 1.
Event‐free survival stratified by NPM1 subtypes.
FIGURE 2.
Overall survival stratified by NPM1 subtypes.
On multivariable analysis, co‐mutation with KRAS and TET2 as well as the initial WBC at diagnosis was significantly associated with EFS (Table 2). Co‐mutation with KRAS (HR: 2.69, 95% CI: 1.20–6.00) or TET2 (HR: 1.99, 95% CI: 1.22–3.26) was associated with poorer EFS. For each 50 k/mm3 increase in WBC at diagnosis, the risk of progression, relapse, or death increased by 21%. For OS, co‐mutation with IDH1/IDH2 or SRSF2, initial WBC at diagnosis, and treatment were significant on multivariable analysis (Table 2). Co‐mutation with IDH1/IDH2 (HR: 0.40, 95% CI: 0.21–0.74) was associated with better OS, whereas co‐mutation with SRSF2 (HR: 2.70, 95% CI: 1.35–5.40) was associated with worse OS. For each 50 k/mm3 increase in WBC at diagnosis, the risk of death increased by 20%. Of note, 3 patients had a combination of NPM1/KRAS/TET2 mutations whose additive effects were not evaluable on the multivariate model.
TABLE 2.
Multivariable models for event‐free survival and overall survival.
| Covariate | Comparison | Event‐free survival | Overall survival | ||||
|---|---|---|---|---|---|---|---|
| HR | 95% CI | p | HR | 95% CI | p | ||
| WBC at diagnosis | Units = 50 k/mm3 | 1.21 | 1.04–1.40 | 0.01 | 1.20 | 1.02–1.42 | 0.03 |
| Treatment | HMA ± ven versus chemotherapy | 1.94 | 1.12–3.37 | < 0.01 | |||
| None versus chemotherapy | 167.87 | 42.31–666.03 | |||||
| KRAS | Yes versus No | 2.69 | 1.20–6.00 | 0.02 | |||
| TET2 | Yes versus No | 1.99 | 1.22–3.26 | < 0.01 | |||
| IDH1/IDH2 | Yes versus No | 0.40 | 0.21–0.74 | < 0.01 | |||
| SRSF2 | Yes versus No | 2.70 | 1.35–5.40 | < 0.01 | |||
Note: Bold values indicates the interpretation of the significance are mentioned in the texts, p–value is highlighted when < 0.05.
Among the 141 patients, 74 had MRD measured by NPM1 RT‐PCR. Negative results were obtained for 20 patients (treated with chemo N = 17, HMA/ven N = 3) at a median of 6.1 months (range: 1.4–29.1) from the time of diagnosis.
Fifty patients underwent allogeneic stem cell transplants (HSCT) at a median of 5.8 months (range 2.8–51.0) after diagnosis. Thirty‐three patients were in first remission (CR1) and HSCT was indicated by adverse cytogenetics or co‐mutations, and 17 patients were in second remission or a more advanced state (CR2+) (patient characteristics in Table S1). Thirty‐one patients had detectable MRD pre‐HSCT. Nineteen patients experienced a post‐HSCT relapse. RFS at 12 months post‐HSCT was 72% (95% CI: 57%–83%).
4. Discussion
There remains a need for further understanding of the pathogenesis of NPM1 AML. Our findings affirm the report from Alpermann et al. [11] that the EFS and OS outcomes were not impacted by the subtypes of NPM1 mutation (subtype A vs. other subtypes). However, we found that co‐mutations other than FLT3‐ITD can also influence the overall prognoses among NPM1 AML.
Among the different co‐mutations, the presence of TET2 or KRAS portends a worse EFS. Co‐mutation with SRSF2 is associated with worse OS, while the accompaniment of IDH1/IDH2 confers better OS. Current data show conflicting outcomes influenced by different co‐mutations [14, 16, 18, 19], but our study's striking finding is the adverse EFS outcomes when KRAS co‐occurs with NPM1. While we do not have a clear explanation for this finding, we speculate that KRAS may be a secondary event in the downstream signaling pathway that further propagates the clonal proliferation [20], but the absence of similar findings with NRAS or HRAS mutations could be secondary to the small patient population in our study. Our findings of the impact of TET2 co‐mutation echo that of the general population of AML patients [21] in that we found only worse EFS but not necessarily OS; this could be potentially from diverse TET2 mutation biology; some are driver mutations while others represent background clonal hematopoiesis. Only one of our patients harbored a TP53 mutation, which attests to a prior report that TP53 rarely co‐occurs in NPM1‐driven AML [22]. One striking finding from our study is that the FLT3‐ITD mutation did not confer adverse EFS or OS, but this could be secondary to the limited number of patients with co‐occurring NPM1 and FLT3‐ITD (N = 33) in our cohort.
Interestingly, not only can insertion mutations on exon 12 lead to abnormal cytoplasmic accumulation of NPM1. Studies from Matelli [23] and Yao [24] et al. discovered a non‐canonical NPM1 on exon 5 that is not detectable on a standard myeloid NGS panel, but ancillary NPM1 immunohistochemistry stain was able to illustrate abnormal intracytoplasmic NPM1 conglomeration and subsequent leukemic state.
Uniquely advantageous among NPM1‐driven AML is the emerging role of MRD dynamics. NPM1 RT‐PCR rises and falls synchronously with the AML disease status and has been shown to reliably predict an impending relapse. The original study from the UK AML 17 [25] reported a markedly higher risk of relapse (82% vs. 30%) for those with detectable MRD after 2 cycles of chemo, and a more recent study with HMA/ven‐based therapy [26] similarly suggests that failure of MRD clearance after cycle 4 of treatment may predict underlying resistant disease biology. Our institution's small number of patients, unfortunately, was not able to stratify the rate of MRD clearance based on different types of therapies.
Newer treatment strategies are on the horizon for NPM1 AML, such as menin inhibitors [27] that interfere with the ARF/p53 pathways [28], and XPO1 inhibitor [29] that aim to inhibit the aberrant NPM1 shuttling are actively being explored.
We acknowledge that our small and heterogeneous patient population may not have captured the true effect of the NPM1 subtypes and the co‐occurring mutations, but this data generates a basis for further study into the biological interplay of this complex malignancy.
5. Conclusion
NPM1 AML remains a disease with variable clinical outcomes; the subtypes and co‐mutations alone may not reliably predict the patient's overall prognosis, but the additional information from longitudinal MRD tracking may offer a stronger predictive power for NPM1 AML patients. A larger prospective trial is needed to confirm our findings.
Author Contributions
Data collection: Ratdanai Yodsuwan, Kathryn Crawford, and Sarah Hornberg. Data analysis and interpretation: Sarah Mott. Study concept and design: Kittika Poonsombudlert, Prajwal Dhakal, and Margarida Magalhaes‐Silverman. Manuscript preparation and review: Kittika Poonsombudlert, Sarah Mott, Ratdanai Yodsuwan, Prajwal Dhakal, Anthony N. Snow, Grerk Sutamtewagul, and Margarida Magalhaes‐Silverman. All authors reviewed the results and approved the final version of the manuscript.
Conflicts of Interest
The authors declare no conflicts of interest.
Supporting information
Figure S1: Event‐free survival stratified by NPM1 subtype A versus other subtypes.
Figure S2: Overall survival stratified by NPM1 subtype A versus other subtypes.
Table S1: Table of HSCT cohort patient characteristics.
Table S2: Table of NPM1 subtypes mutation details and list of genes in UIHC AML mutation panel.
Funding: The authors received no specific funding for this work.
Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.
References
- 1. Arber D. A., Orazi A., Hasserjian R. P., et al., “International Consensus Classification of Myeloid Neoplasms and Acute Leukemias: Integrating Morphologic, Clinical, and Genomic Data,” Blood 140, no. 11 (2022): 1200–1228, 10.1182/blood.2022015850. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2. Khoury J. D., Solary E., Abla O., et al., “The 5th Edition of the World Health Organization Classification of Haematolymphoid Tumours: Myeloid and Histiocytic/Dendritic Neoplasms,” Leukemia 36, no. 7 (2022): 1703–1719, 10.1038/s41375-022-01613-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3. Dohner K., Thiede C., Jahn N., et al., “Impact of NPM1/FLT3‐ITD Genotypes Defined by the 2017 European LeukemiaNet in Patients With Acute Myeloid Leukemia,” Blood 135, no. 5 (2020): 371–380, 10.1182/blood.2019002697. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4. Juliusson G., Jadersten M., Deneberg S., et al., “The Prognostic Impact of FLT3‐ITD and NPM1 Mutation in Adult AML Is Age‐Dependent in the Population‐Based Setting,” Blood Advances 4, no. 6 (2020): 1094–1101, 10.1182/bloodadvances.2019001335. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5. Dohner H., Wei A. H., Appelbaum F. R., et al., “Diagnosis and Management of AML in Adults: 2022 Recommendations From an International Expert Panel on Behalf of the ELN,” Blood 140, no. 12 (2022): 1345–1377, 10.1182/blood.2022016867. [DOI] [PubMed] [Google Scholar]
- 6. Sharma N. and Liesveld J. L., “NPM 1 Mutations in AML‐The Landscape in 2023,” Cancers 15, no. 4 (2023): 1177, 10.3390/cancers15041177. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7. Falini B., Brunetti L., Sportoletti P., and Martelli M. P., “NPM1‐Mutated Acute Myeloid Leukemia: From Bench to Bedside,” Blood 136, no. 15 (2020): 1707–1721, 10.1182/blood.2019004226. [DOI] [PubMed] [Google Scholar]
- 8. Duployez N., Chebrek L., Helevaut N., et al., “A Novel Type of NPM1 Mutation Characterized by Multiple Internal Tandem Repeats in a Case of Cytogenetically Normal Acute Myeloid Leukemia,” Haematologica 103, no. 12 (2018): e575–e577, 10.3324/haematol.2018.190959. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9. Albiero E., Madeo D., Bolli N., et al., “Identification and Functional Characterization of a Cytoplasmic Nucleophosmin Leukaemic Mutant Generated by a Novel Exon‐11 NPM1 Mutation,” Leukemia 21, no. 5 (2007): 1099–1103, 10.1038/sj.leu.2404597. [DOI] [PubMed] [Google Scholar]
- 10. Mariano A. R., Colombo E., Luzi L., et al., “Cytoplasmic Localization of NPM in Myeloid Leukemias Is Dictated by Gain‐Of‐Function Mutations That Create a Functional Nuclear Export Signal,” Oncogene 25, no. 31 (2006): 4376–4380, 10.1038/sj.onc.1209453. [DOI] [PubMed] [Google Scholar]
- 11. Alpermann T., Schnittger S., Eder C., et al., “Molecular Subtypes of NPM1 Mutations Have Different Clinical Profiles, Specific Patterns of Accompanying Molecular Mutations and Varying Outcomes in Intermediate Risk Acute Myeloid Leukemia,” Haematologica 101, no. 2 (2016): e55–e58, 10.3324/haematol.2015.133819. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12. Pigazzi M., Tregnago C., Ries R. E., et al., “Nucleophosmin (NPM1) Type D Genotype Is Associated With Distinct Outcome in Acute Myeloid Leukemia–An AIEOP–BFM and COG‐SWOG Intergroup Collaboration,” Blood 142, no. Supplement 1 (2023): 840, 10.1182/blood-2023-181872. [DOI] [Google Scholar]
- 13. Tregnago C., Benetton M., Padrin D., et al., “NPM1 Mutational Status Underlines Different Biological Features in Pediatric AML,” Cancers 13, no. 14 (2021): 3457, 10.3390/cancers13143457. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14. Hernández‐Sánchez A., Villaverde‐Ramiro Á., Elicegui J. M., et al., “S130: NPM1 Mutated AML: Impact of Co‐Mutational Patterns‐Results of the European Harmony Alliance,” HemaSphere 6 (2022): 31–32, 10.1097/01.HS9.0000843412.59637.1b. [DOI] [Google Scholar]
- 15. Cappelli L. V., Meggendorfer M., Baer C., et al., “Indeterminate and Oncogenic Potential: CHIP vs CHOP Mutations in AML With NPM1 Alteration,” Leukemia 36, no. 2 (2022): 394–402, 10.1038/s41375-021-01368-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16. Eckardt J. N., Bill M., Rausch C., et al., “Secondary‐Type Mutations Do Not Impact Outcome in NPM1‐Mutated Acute Myeloid Leukemia ‐ Implications for the European LeukemiaNet Risk Classification,” Leukemia 37, no. 11 (2023): 2282–2285, 10.1038/s41375-023-02016-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17. McCurdy S. R. and Luger S. M., “Dose Intensity for Induction in Acute Myeloid Leukemia: What, When, and for Whom?,” Haematologica 106, no. 10 (2021): 2544, 10.3324/haematol.2020.269134. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18. Lachowiez C. A., Reville P. K., Kantarjian H., et al., “Contemporary Outcomes in IDH‐Mutated Acute Myeloid Leukemia: The Impact of Co‐Occurring NPM1 Mutations and Venetoclax‐Based Treatment,” American Journal of Hematology 97, no. 11 (2022): 1443–1452, 10.1002/ajh.26694. [DOI] [PubMed] [Google Scholar]
- 19. Nibourel O., Kosmider O., Cheok M., et al., “Association of TET2 Alterations With NPM1 Mutations and Prognostic Value in De Novo Acute Myeloid Leukemia (AML),” Blood 114, no. 22 (2009): 163. [Google Scholar]
- 20. Rivera D., Kim K., Kanagal‐Shamanna R., et al., “Implications of RAS Mutational Status in Subsets of Patients With Newly Diagnosed Acute Myeloid Leukemia Across Therapy Subtypes,” American Journal of Hematology 97, no. 12 (2022): 1599–1606, 10.1002/ajh.26731. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21. Gaidzik V. I., Paschka P., Spath D., et al., “TET2 Mutations in Acute Myeloid Leukemia (AML): Results From a Comprehensive Genetic and Clinical Analysis of the AML Study Group,” Journal of Clinical Oncology 30, no. 12 (2012): 1350–1357, 10.1200/JCO.2011.39.2886. [DOI] [PubMed] [Google Scholar]
- 22. Scarpa F. J., Paul M., Daringer R., et al., “TP53/NPM1‐Mutated Acute Myeloid Leukemia as a Molecularly Distinct Disease Entity,” Wolters Kluwer Health (2021). [Google Scholar]
- 23. Martelli M. P., Rossi R., Venanzi A., et al., “Novel NPM1 Exon 5 Mutations and Gene Fusions Leading to Aberrant Cytoplasmic Nucleophosmin in AML,” Blood 138, no. 25 (2021): 2696–2701, 10.1182/blood.2021012732. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24. Yao Y., Lin X., Wang C., et al., “Identification of a Novel NPM1 Mutation in Acute Myeloid Leukemia,” Experimental Hematology & Oncology 12, no. 1 (2023): 87, 10.1186/s40164-023-00449-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25. Ivey A., Hills R. K., Simpson M. A., et al., “Assessment of Minimal Residual Disease in Standard‐Risk AML,” New England Journal of Medicine 374, no. 5 (2016): 422–433, 10.1056/NEJMoa1507471. [DOI] [PubMed] [Google Scholar]
- 26. Othman J., Potter N., Ivey A., et al., “Postinduction Molecular MRD Identifies Patients With NPM1 AML Who Benefit From Allogeneic Transplant in First Remission,” Blood 143, no. 19 (2024): 1931–1936, 10.1182/blood.2023023096. [DOI] [PubMed] [Google Scholar]
- 27. Fathi A., Wang E., Issa G., et al., “P504: Updated Data for Ziftomenib in Patients With NPM1‐Mutated Relapsed or Refractory Acute Myeloid Leukemia,” HemaSphere 7, no. S3 (2023): e19161da. [Google Scholar]
- 28. Issa G. C., Aldoss I., DiPersio J., et al., “The Menin Inhibitor Revumenib in KMT2A‐Rearranged or NPM1‐Mutant Leukaemia,” Nature 615, no. 7954 (2023): 920–924, 10.1038/s41586-023-05812-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29. Pianigiani G., Gagliardi A., Mezzasoma F., et al., “Prolonged XPO1 Inhibition Is Essential for Optimal Antileukemic Activity in NPM1‐Mutated AML,” Blood Advances 6, no. 22 (2022): 5938–5949, 10.1182/bloodadvances.2022007563. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Figure S1: Event‐free survival stratified by NPM1 subtype A versus other subtypes.
Figure S2: Overall survival stratified by NPM1 subtype A versus other subtypes.
Table S1: Table of HSCT cohort patient characteristics.
Table S2: Table of NPM1 subtypes mutation details and list of genes in UIHC AML mutation panel.
Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.