ABSTRACT
Frameshift mutations in exon 12 of nucleophosmin 1 (NPM1 mut) are among the most common mutations in acute myeloid leukemia (AML) and have historically been considered favorable‐risk in the absence of FLT3‐ITD. In the European LeukemiaNet (ELN) 2024 risk‐classification for patients treated with hypomethylating agents plus venetoclax (HMA + VEN), NPM1 mut is not considered favorable when co‐occurring with signaling gene (SG) mutations (i.e., FLT3‐ITD, NRAS, KRAS). However, due to limited numbers in the original analysis, the prognostic impact of SG mutations in NPM1‐mutant AML remains unclear. We evaluated the prognostic significance of NPM1 mut with and without SG mutations in two independent cohorts of patients ≥ 60 years with ELN 2024 favorable‐ or intermediate‐risk AML treated with HMA + VEN. Cohort 1 included 322 patients treated in the academic setting. NPM1 mut (n = 61) was associated with a nonsignificantly longer overall survival (OS) compared to NPM1 wild‐type (NPM1 wt) (median, 53.05 vs. 17.03 months, p = 0.10). In multivariable analysis (MVA), SG mutations were not independently prognostic within the NPM1 mut subgroup. Cohort 2 included 816 patients from a real‐world community‐treated cohort. NPM1 mut (n = 124) had a longer OS compared with NPM1 wt (median, 15.3 vs. 14.4 months, p = 0.03). In MVA, NRAS, KRAS, and FLT3‐ITD were independent unfavorable prognostic factors; NPM1 mut with, compared to without, SG co‐mutation had a shorter OS (median, 9.4 vs. 31.6 months, p = 0.001). These findings suggest SG mutations negate the favorable impact of NPM1 mut in older patients treated with HMA + VEN. Prospective clinical trials are needed to investigate the use of combination therapies to improve outcomes in this high‐risk subgroup.
1. Introduction
Frameshift mutations in exon 12 of nucleophosmin 1 (NPM1 mut) are among the most frequent molecular abnormalities in acute myeloid leukemia (AML), occurring in approximately 35% of all patients [1]. In both the World Health Organization (WHO) and the International Consensus Conference (ICC) classifications, NPM1 mut AML is recognized as a genetically defined AML subtype [2, 3]. However, due to the frequent co‐occurring mutation profiles and patient characteristics, clinical outcomes remain highly heterogeneous within this molecular subgroup.
Risk stratification based on the revised European LeukemiaNet (ELN) 2022 classification identifies NPM1 mut AML as conferring favorable‐risk in the absence of a co‐occurring FLT3 internal tandem duplication (FLT3‐ITD) or adverse risk karyotype [4]. However, ELN 2022 is primarily based on outcomes in younger patients (generally 60 years) receiving intensive chemotherapy (IC), whereas for older patients treated with IC, the prognosis is less clearly favorable [5, 6, 7].
Pooled analysis of 279 patients, including those from an open‐label phase 1b trial [8] and the phase 3 VIALE‐A trial [9, 10], evaluating azacitidine (AZA) plus VEN (AZA + VEN) versus AZA plus placebo in patients who were ineligible for standard induction therapy, assessed clinical outcomes of patients treated with AZA + VEN. Patients with NPM1 mut AML had a median OS of 39.0 months in the absence of FLT3‐ITD, KRAS and/or NRAS mutations, compared with 9.9 months in their presence. Based on these data, Döhner et al. [11] developed a four‐gene signature (molecular prognostic risk score, mPRS) that stratified patients into three risk groups (higher benefit: not classified as intermediate‐benefit or lower‐benefit, intermediate‐benefit: FLT3‐ITD, NRAS, or KRAS mutation, and lower benefit: TP53 mutation). It is now used to risk‐stratify clinical outcomes in patients treated with AZA + VEN. This four‐gene signature was further validated by Bataller et al. [12] in a cohort of 159 older (> 60 years) patients treated at the University of Texas MD Anderson Cancer Center. NPM1 mut is considered intermediate‐risk when co‐occurring with signaling gene (SG) mutations (i.e., FLT3‐ITD, NRAS, KRAS) and favorable‐risk in the absence of SG mutations. However, given the small number of patients with a co‐occurring NPM1 and RAS mutations (n = 8) or FLT3‐ITD (n = 16) in the initial cohort used to define the four‐gene prognostic risk molecular signatures, it remains unclear whether these patients truly have worse outcome compared with those without SG mutations.
We aimed to investigate the prognostic impact of NPM1 mut with and without SG mutations in two independent cohorts of patients aged ≥ 60 years who were treated in the first line (1L) with a hypomethylating agent with VEN (HMA + VEN), with favorable‐ or intermediate‐risk by ELN 2024, and a third cohort of patients treated with HMA + VEN in the second line (2L).
2. Methods
2.1. Data Source
This retrospective observational study used data from three different patient cohorts. Cohort 1 included AML patients enrolled on the Beat AML clinical trial (NCT03013998) who met the screening criteria for enrollment and provided consent before May 10, 2023, as well as patients included in the Myeloid Malignancy Association on Rapid Research Outcomes Working Group (MARROW) Consortium database. Informed consent was obtained following institutional guidelines and in accordance with the Declaration of Helsinki. Cohort 2 and Cohort 3 included patients from the US nationwide Flatiron Health research database. The Flatiron Health database contains structured and unstructured data curated via technology‐enabled abstraction from approximately 280 cancer clinics and 800 unique sites of care [13, 14]. Patients who were recorded as receiving treatment with HMA + VEN as both their 1L and 2L treatments were excluded from Cohort 3, to minimize the risk of misclassifying line‐of‐therapy sequencing and to avoid potential inaccuracies in subsequent treatment capture. Informed consent was obtained following institutional guidelines and in accordance with the Declaration of Helsinki.
Patients were included if they had newly diagnosed AML with favorable‐ or intermediate‐risk by ELN 2024 (i.e., patients with a TP53 mutation or unknown TP53 mutation status were excluded), had a known NPM1 mutation status, were aged ≥ 60 years at diagnosis and received treatment with HMA + VEN (Cohort 1 and 2, 1L HMA + VEN; Cohort 3, 2L HMA + VEN). Patients were excluded if they received HMA + VEN in combination with a clinical study drug, IDH or FLT3 inhibitor as 1L‐therapy, if they harbored the t(9;22)(q34;q11.2) (or were treated with a tyrosine kinase inhibitor) or if they were diagnosed with acute promyelocytic leukemia.
2.2. Molecular Analysis
Details of genomic analysis performed for patients enrolled on the Beat AML clinical trial have been reported previously [15]. Molecular testing was performed by next‐generation sequencing (NGS) using FoundationOne Heme (Foundation Medicine) with a limit of detection of 28 reads [16]. Molecular testing for patients included in the Marrow Consortium database was performed according to the internal guidelines of each participating academic center. The Flatiron Health research dataset captured molecular data that corresponded to a positive or negative result from specimens collected prior to the start of therapy from electronic health records, including results from fluorescence in situ hybridization (FISH), karyotyping, PCR analysis, and NGS. Patients were classified as normal karyotype only if karyotyping and/or FISH results were available and showed no abnormalities; patients without available cytogenetic data were classified as unknown.
2.3. Statistical Analysis
Patient characteristics are summarized using median (range) for continuous variables and frequency (percentage) for categorial variables. Student's t‐test or Wilcoxon rank sum test and Chi‐square or Fisher's exact test were used to compare continuous or categorial variables, respectively. Level of significance was defined as a p < 0.05. Birth year data for elderly patients in the Flatiron database were subject to a standard algorithmic transformation to mitigate their higher risk of patient re‐identification. Only birth year was captured and converted to the default date of December 31 (i.e., December 31, year of birth).
Overall survival (OS) was estimated using the Kaplan–Meier method from the date of trial inclusion (Cohort 1), time from 1L (Cohort 2) or 2L (Cohort 3) treatment initiation until death or last follow‐up. Group differences for censored outcomes were calculated using the log‐rank test. Univariable Cox proportional hazard models were used to describe the risk of each variable on death over time among patients with an NPM1 mutation. Multivariable analysis was performed using the backward elimination approach starting with all variables with a p < 0.2 on the univariable analysis and removing the variables with the highest p values from the model. Statistical analyses were conducted in RStudio, Version 4.2.3 and SAS 9.4.
3. Results
3.1. Baseline Patient Characteristic Cohort 1
Cohort 1 included 322 patients treated with HMA + VEN (Table 1). Among these, 237 (74%) were classified as having favorable‐risk by ELN 2024. Patients had a median age of 73 years (range, 61–89 years), with 126 (39%) being ≥ 75 years, and 127 (39%) being female.
TABLE 1.
Baseline characteristics of 322 patients included in Cohort 1 (n = 322).
| Variable, n (%) or median (range) | NPM1 mut (n = 61) | NPM1 wt (n = 261) | All (N = 322) | p |
|---|---|---|---|---|
| Age (years) | 73 (62–89) | 73 (61–87) | 73 (61–89) | 0.95 |
| Female sex | 27 (45) | 100 (39) | 127 (39) | 0.42 |
| ELN 2024 | ||||
| Favorable | 32 (52) | 205 (78) | 237 (74) | < 0.001 |
| Intermediate | 29 (48) | 56 (22) | 85 (26) | |
| RAS/MAPK mutations | ||||
| NRAS | 12 (20) | 31 (12) | 43 (13) | 0.11 |
| KRAS | 6 (10) | 17 (7) | 23 (7) | 0.37 |
| PTPN11 | 11 (18) | 22 (8) | 33 (10) | 0.03 |
| CBL | 4 (7) | 20 (7) | 24 (7) | 0.76 |
| NF1 a , b | 0 (0) | 10 (7) | 10 (5) | 0.09 |
| ≥ 1 mutation | 24 (39) | 81 (31) | 105 (33) | 0.21 |
| Tyrosine kinase receptor | ||||
| FLT3‐ITD | 27 (44) | 25 (10) | 52 (16) | < 0.001 |
| FLT3‐TKD | 7 (11) | 12 (5) | 19 (6) | 0.04 |
| KIT | 2 (3) | 7 (3) | 9 (3) | 0.68 |
| ≥ 1 mutation | 24 (39) | 31 (12) | 55 (17) | < 0.001 |
| JAK/STAT | ||||
| JAK2 | 2 (3) | 34 (13) | 36 (11) | 0.03 |
| MPL | 0 (0) | 9 (3) | 9 (3) | 0.14 |
| CSF3R | 1 (2) | 7 (3) | 8 (2) | 0.62 |
| ≥ 1 mutation | 3 (5) | 46 (18) | 49 (15) | 0.01 |
| Cytogenetics | < 0.001 | |||
| Normal karyotype | 43 (89) | 77 (42) | 120 (52) | |
| −5 or del(5q); −7; 17/abn(17p) | 0 (0) | 8 (4) | 8 (3) | |
| KMT2A‐rearrangement | 0 (0) | 13 (8) | 13 (6) | |
| Inversion (16) or t(8;21) | 0 (0) | 3 (2) | 3 (1) | |
| Complex karyotype | 3 (7) | 15 (8) | 18 (8) | |
| Inversion (3) | 0 (0) | 4 (2) | 4 (2) | |
| t(6;9) | 0 (0) | 0 (0) | 0 (0) | |
| Trisomy 8 | 1 (2) | 25 (14) | 26 (11) | |
| Other | 1 (2) | 36 (20) | 37 (17) | |
| Unknown | 13 | 80 | 93 | |
Note: Bolded values indicate a statistically significant p < 0.05.
Missing includes unknown or not documented in the database. Missing data were not considered in p value calculations.
Mutation frequencies are calculated among patients with known mutation status. NF1 mutation status was known for 190 patients.
Molecular data were available for all patients, and 61 (19%) patients had AML characterized by NPM1 mut. The median age did not differ between NPM1 mut patients and those with wild‐type NPM1 (NPM1 wt; p = 0.95). Patients with NPM1 mut AML more frequently had a co‐mutation in PTPN11 (18% vs. 8%, p = 0.03), FLT3‐ITD (44% vs. 10%, p < 0.001), or the FLT3‐tyrosine kinase domain (TKD) mutation (11% vs. 5%, p = 0.04) compared to NPM1 wt. JAK2 mutation was present in only 3% of the NPM1 mut patients compared to 13% in those with NPM1 wt (p = 0.03). The prevalence of KRAS, NRAS, CBL, NF1, KIT, MPL, and CSF3R mutations was not different between NPM1 mut and NPM1 wt patients with AML.
3.2. Outcomes of Patients With NPM1 mut AML Receiving HMA Plus VEN
At a median follow‐up of 18.2 months [95% confidence interval (CI), 15.6–25.2] for the entire cohort, the median OS was 18.0 months [95% CI, 15.5–25.2] (Figure S1A). Comparing the outcomes of patients with NPM1 mut (n = 61) and those with NPM1 wt (n = 261), NPM1 mut was associated with a trend toward longer OS compared to NPM1 wt (median, 53.1 [95% CI, 12.6‐NA]) vs. 17.0 [95% CI, 14.8–21.1] months, 2‐year OS rates 54% vs. 42%; p = 0.10 (Figure 1A). Similar results were obtained in patients aged ≥ 75 years (n = 126), with a median OS of 22.0 vs. 13.9 months (p = 0.35) for NPM1 mut (n = 24) and NPM1 wt patients (n = 102).
FIGURE 1.
Kaplan–Meier plots of overall survival (OS) of patients stratified by NPM1 mutation status in Cohort 1. (A) OS stratified by NPM1 mut and NPM1 wt. (B) OS among NPM1 mut in the presence or absence of signaling gene (SG) mutations (i.e., KRAS, NRAS, FLT3‐ITD, and PTPN11). [Color figure can be viewed at wileyonlinelibrary.com]
We next evaluated the impact of specific SG co‐mutations on survival among NPM1 mut patients. Using univariable analyses, we found that FLT3‐ITD (n = 27), FLT3‐TKD (n = 7), and mutations in PTPN11 (n = 11), and NRAS (n = 12) did not significantly impact survival (Table S1). Because of the small number of patients with NPM1 mut AML with KRAS (n = 6), NF1 (n = 0), KIT (n = 2), CBL (n = 4), or JAK–STAT co‐mutations (n = 3), their impact on outcome could not be assessed. FLT3‐ITD and PTPN11 mutations (both associated with a p < 0.2 in univariate analyses) were subsequently considered in multivariable modeling; however, neither emerged as an independent prognostic variable (Table S2).
The OS of NPM1 mut patients without SG mutations (PTPN11, FLT3‐ITD, NRAS, or KRAS) (n = 40) did not differ from that of NPM1 mut patients with any of those four mutations (n = 21) (median, 25.4 months vs. median not reached, p = 0.97) (Figure 1B). Moreover, the OS of patients with NPM1 and PTPN11 mutations (n = 11) was not statistically different from the OS of NPM1 mut patients with FLT3‐ITD or a mutation in NRAS or KRAS, but without PTPN11 (n = 28) (median, not reached vs. 25.9 months, p = 0.16) (Figure S2).
3.3. Baseline Patient Characteristics of Cohort 2
Next, we conducted similar analyses in a larger real‐world cohort (Cohort 2) of newly diagnosed AML patients. Patients had a median age of 76 years (range, 60–84 years) with 57% being aged 75 years or older, and 37% of the patients were female. Patient characteristics are shown in Table 2.
TABLE 2.
Baseline characteristics of 816 patients included in Cohort 2 (n = 816).
| Variable a , n (%) or median (range) | NPM1 mut (n = 124) | NPM1 wt (n = 692) | All (N = 816) | p |
|---|---|---|---|---|
| Age (years) | 75 (60–84) | 76 (60–84) | 76 (60–84) | 0.197 |
| Female sex | 60 (48) | 242 (35) | 302 (37) | 0.006 |
| ELN 2024, n (%) | 0.02 | |||
| Favorable | 38 (43) | 249 (58) | 287 (55) | |
| Intermediate | 50 (57) | 183 (42) | 233 (45) | |
| Unknown b | 36 | 260 | 296 | |
| RAS/MAPK mutations c | ||||
| KRAS | 8 (7) | 56 (8) | 64 (8) | 0.72 |
| NRAS | 16 (14) | 93 (14) | 109 (14) | 0.98 |
| NF1 | 9 (11) | 30 (7) | 39 (7) | 0.25 |
| ≥ 1 mutation | 28 (32) | 148 (31) | 176 (31) | 0.90 |
| Tyrosine kinase receptor c | ||||
| FLT3‐ITD | 31 (34) | 65 (16) | 96 (19) | < 0.001 |
| FLT3‐TKD | 14 (17) | 24 (6) | 38 (8) | 0.003 |
| KIT | 4 (3) | 16 (2) | 20 (3) | 0.52 |
| ≥ 1 mutation | 46 (54) | 94 (24) | 140 (29) | < 0.001 |
| JAK/STAT signaling c | ||||
| JAK2 | 2 (2) | 52 (8) | 54 (7) | 0.015 |
| MPL | 3 (3) | 10 (2) | 13 (2) | 0.419 |
| CSF3R | 1 (0.1) | 11 (2) | 12 (2) | 1.000 |
| ≥ 1 mutation | 6 (6) | 68 (12) | 74 (11) | 0.116 |
| Cytogenetics | < 0.001 | |||
| Normal karyotype | 99 (82) | 340 (51) | 439 (55) | |
| −5 or del(5q); −7; −17/abn(17p) | 4 (3) | 100 (15) | 104 (13) | |
| Trisomy 8 | 9 (7) | 77 (11) | 86 (11) | |
| KMT2A‐rearrangement | 0 (0) | 28 (4) | 28 (4) | |
| Inversion (16) or t(8;21) | 0 (0) | 20 (3) | 20 (3) | |
| Complex karyotype | 1 (1) | 16 (2) | 17 (2) | |
| Inversion (3) | 0 (0) | 15 (2) | 15 (2) | |
| t(6;9) | 0 (0) | (0.4) | 3 (0.4) | |
| Other | 8 (7) | 71 (11) | 79 (10) | |
| Unknown | 3 | 22 | 25 |
Note: Bolded values indicate a statistically significant p < 0.05.
Missing includes unknown or not documented in the database. Missing data were not considered in p value calculations.
Patients with missing mutational status for KRAS, NRAS, or FLT3‐ITD, but did meet criteria for favorable or intermediate risk based on the absence of a TP53 mutation.
Mutation status was available for the following number of patients: KRAS (n = 779), NRAS (n = 769), NF1 (n = 522), ≥ 1 RAS/MAPK mutations (n = 565), FLT3‐ITD (n = 496), FLT3‐TKD (n = 458), KIT (n = 776), ≥ 1 tyrosine kinase receptor (n = 484), JAK2 (n = 765), MPL (n = 676), CSF3R (n = 748), and > 1 JAK/STAT signaling mutation (n = 671). Mutation frequencies are calculated among patients with known mutation status.
NPM1 mut was present in 124 (15%) patients. The median age of NPM1 mut and NPM1 wt patients was similar (p = 0.20), with a higher percentage of the NPM1 mut patients being female (48% vs. 35%, p = 0.006). Patients with NPM1 mut AML more frequently had a FLT3‐ITD (34% vs. 16%, p < 0.001) or FLT3‐TKD (17% vs. 6%, p = 0.003) co‐mutation compared to NPM1 wt patients, whereas JAK2 was overrepresented in NPM1 wt patients (2% vs. 8%, p = 0.02). The proportions of mutations in KRAS, NRAS, NF1, KIT, MPL and CSF3R were not different between NPM1 mut and NPM1 wt AML patients. Mutational status for PTPN11 was unavailable.
3.4. Clinical Outcomes in Cohort 2
Among all 816 patients, the median OS was 14.7 months [95% CI, 13.4–16.2] at the time of last follow‐up (median follow‐up, 10.3 months [95% CI, 9.4–11.3]) (Figure S1B). The OS of NPM1 mut AML patients (n = 124) was significantly longer than OS of patients with NPM1 wt (n = 692; median 15.3 vs. 14.4 months, p = 0.03), with 2‐year OS rates of 42.3% vs. 31.8%, respectively (Figure 2A).
FIGURE 2.
Kaplan–Meier plots of overall survival (OS) of patients stratified by NPM1 mutation status in Cohort 2. (A) OS stratified by NPM1 mut and NPM1 wt. (B) OS among NPM1 mut in the presence or absence of signaling gene (SG) mutations (i.e., KRAS, NRAS, and FLT3‐ITD), and (C) stratified by the presence or absence of NPM1 mut and SGmut. [Color figure can be viewed at wileyonlinelibrary.com]
As in Cohort 1, we evaluated the impact of individual SG mutations in the NPM1 mut AML cohort of patients (n = 124) who received 1L HMA + VEN therapy. Using multivariable analysis, KRAS (n = 8) (HR 2.78 [95% CI, 0.95–8.10]) and NRAS (n = 16) (HR 3.04 [95% CI, 1.40–6.60]) mutations and FLT3‐ITD (n = 31) (HR 2.03 [95% CI, 1.10–3.76]) were all identified as independent unfavorable prognostic variables (Table 3, Table S3).
TABLE 3.
Multivariable analysis in NPM1 mut AML patients receiving HMA + VEN in the first line (n = 81/124).
| Variable | N a | HR | 95% CI | p |
|---|---|---|---|---|
| KRAS | 6 | 2.78 | 0.95–8.10 | 0.061 |
| NRAS | 12 | 3.04 | 1.40–6.60 | 0.005 |
| FLT3‐ITD | 30 | 2.03 | 1.10–3.76 | 0.024 |
Note: Bolded values indicate a statistically significant p < 0.05.
81/124 had available mutation status for KRAS, NRAS, and FLT3‐ITD and were included in the multivariable analysis.
Furthermore, because Zeidner et al. [17] recently showed that TET2 mutations were independently associated with an increased risk of death among NPM1 mut patients in a large retrospective cohort of older patients treated with IC or lower‐intensity therapy, we evaluated the impact of TET2 mutations in Cohort 2. Of the 124 NPM1 mut patients, 47 (38%) had a TET2 mutation. TET2 mutation was significantly associated with a shorter OS, with a median of 31.6 versus 8.9 months (p = 0.003) (Figure S3A). The adverse prognostic significance of TET2 mutations was also shown in the HARMONY study in patients without FLT3‐ITD and DNMT3A mutations in a cohort of intensively‐treated adults with NPM1 mut AML [18]. Thus, we assessed the impact of TET2 mutations in NPM1 mut patients with DNMT3A wt and no FLT3‐ITD, and found that those who harbored TET2 mutations (n = 12) had a shorter OS than those with TET2 wt (n = 20) (median, 5.2 vs. 31.6 months, p = 0.023) (Figure S3B).
3.5. Outcomes of Patients With NPM1 mut AML Stratified by the Co‐Occurrence of KRAS , NRAS Mutations, and/or FLT3 ‐ITD
Next, we investigated whether the co‐occurrence of KRAS, NRAS mutations, and/or FLT3‐ITD in NPM1 mut patients with AML impacted their survival. The presence of any of the three co‐occurring SG mutations (n = 50) was associated with a significantly shorter OS compared to NPM1 mut patients with wild‐type KRAS, NRAS and without FLT3‐ITD (n = 38) (median, 9.4 vs. 31.6 months, 2‐year rates, 30.0% vs. 50.1%; p = 0.01) (Figure 2B). Considering the entire cohort together, patients with NPM1 mut with a co‐occurring SG mutation (blue curve) had OS similar to that of NPM1 wt patients with an SG mutation (red curve) (median, 11.9 vs. 9.4 months, p = 0.67) (Figure 2C).
3.6. 2L HMA + VEN Cohort (Cohort 3)
We next investigated the prognostic impact of NPM1 mut in 220 patients aged ≥ 60 years receiving HMA + VEN as 2L therapy. Patients had a median age of 73 years (range, 60–84) and 40% were female (Table 4). Thirty‐one (13%) patients had an NPM1 mut (Table 4). Co‐mutations were largely similar between NPM1 mut and NPM1 wt patients, except for FLT3‐ITD, which was more commonly associated with NPM1 mut (35% vs. 12%, p = 0.01).
TABLE 4.
Baseline characteristics of 220 patients in Cohort 3.
| Variable a , n (%) or median (range) | NPM1 mut (n = 29) | NPM1 wt (n = 191) | All (N = 220) | p |
|---|---|---|---|---|
| Age (years) | 74 (61–84) | 73 (60–84) | 73 (60–84) | 0.29 |
| Female sex | 15 (52) | 72 (38) | 87 (40) | 0.22 |
| ELN 2024 | 0.80 | |||
| Favorable | 15 (62) | 92 (68) | 107 (67) | |
| Intermediate | 9 (38) | 44 (32) | 53 (33) | |
| Unknown b | 5 | 55 | 60 | |
| RAS/MAPK mutations c | ||||
| KRAS | 0 (0) | 16 (9) | 16 (8) | 0.14 |
| NRAS | 5 (18) | 28 (15) | 33 (16) | 0.96 |
| NF1 | 0 (0) | 7 (6) | 7 (5) | 1.00 |
| ≥ 1 mutation | 5 (33) | 44 (34) | 49 (34) | 1.00 |
| Tyrosine kinase receptor c | ||||
| FLT3‐ITD | 8 (35) | 15 (12) | 23 (15) | 0.01 |
| FLT3‐TKD | 3 (14) | 4 (3) | 7 (5) | 0.11 |
| KIT | 0 (0) | 4 (2) | 4 (2) | 1.00 |
| ≥ 1 mutation | 11 (46) | 23 (19) | 34 (23) | 0.008 |
| JAK/STAT signaling c | ||||
| JAK2 | 0 (0) | 18 (10) | 18 (9) | 0.14 |
| MPL | 2 (9) | 2 (1) | 4 (2) | 0.07 |
| CSF3R | 0 (0) | 7 (4) | 7 (3) | 0.60 |
| ≥ 1 mutation | 2 (9) | 26 (17) | 28 (16) | 0.54 |
| First line of therapy | 0.99 | |||
| Intensive chemotherapy | 11 (39) | 69 (37) | 80 (37) | |
| Lower intensity therapy | 17 (61) | 117 (63) | 134 (63) | |
| Unknown | 1 | 5 | 6 | |
| Cytogenetics | 0.002 | |||
| Normal karyotype | 27 (93) | 81 (43) | 108 (50) | |
| −5 or del(5q); −7; −17/abn(17p) | 2 (7) | 39 (1) | 41 (19) | |
| KMT2A‐rearrangement | 0 (0) | 7 (4) | 7 (3) | |
| Inversion (16) or t(8;21) | 0 (0) | 9 (5) | 9 (4) | |
| Complex karyotype | 0 (0) | 3 (2) | 3 (1) | |
| Inversion (3) | 0 (0) | 7 (4) | 7 (3) | |
| Trisomy 8 | 0 (0) | 25 (13) | 25 (12) | |
| Other | 0 (0) | 16 (9) | 16 (7) | |
| Unknown | 0 | 4 | 4 | |
Note: Bolded values indicate a statistically significant p < 0.05.
Missing includes unknown or not documented in the database. Missing data were not considered in p value calculations.
Patients with missing mutational status for KRAS, NRAS, or FLT3‐ITD, but did meet criteria for favorable or intermediate risk based on the absence of a TP53 mutation.
Mutation data was available for the following number of patients: KRAS (n = 209), NRAS (n = 210), NF1 (n = 130), ≥ 1 RAS/MAPK mutations (n = 144), FLT3‐ITD (n = 151), FLT3‐TKD (n = 142), KIT (n = 212), ≥ 1 tyrosine kinase receptor (n = 146), JAK2 (n = 204), MPL (n = 179), CSF3R (n = 202), and ≥ 1 JAK/STAT signaling mutation (n = 179). Mutation frequencies are calculated among patients with known mutation status.
Among the 220 patients, 39% had received IC treatment in the frontline, 61% had received lower intensity therapy, and six patients were treated with an unspecified regimen that included a clinical study drug. Eight patients had received prior treatment with midostaurin during the 1L, four patients had received ivosidenib, and one enasidenib. A summary of prior treatment regimens is shown in Table S4. Two patients received an allogeneic stem cell transplantation prior to 2L therapy.
3.7. Outcomes of Patients With NPM1 mut AML Receiving HMA Plus VEN in the 2L
At a median follow‐up of 9.7 months [95% CI, 7.9–11.3], the median OS from the start of 2L therapy was 13.0 months [95% CI, 10.3–15.6] (Figure S1C). Survival did not differ significantly between NPM1 mut (n = 29) and NPM1 wt (n = 191) patients (17.5 vs. 12.9 months, p = 0.16) (Figure 3A). When we further evaluated outcomes stratified by their 1L therapy, NPM1 mut (n = 17) was not associated with OS difference compared to NPM1 wt (n = 117) (median, 9.4 vs. 10.9 months; p = 0.59) in patients who received lower‐intensity therapy as their 1L‐therapy (n = 134) (Figure 3B). Although numbers were small, the OS of NPM1 mut patients who had received IC in the 1L was slightly longer (median, 14.6 months for NPM1 mut (n = 11) vs. 10.2 months for NPM1 wt (n = 69), 3‐year rates, 54.5% vs. 29.7%; p = 0.23) (Figure 3C).
FIGURE 3.
Kaplan–Meier plots of overall survival (OS) of patients stratified by NPM1 mutation status in Cohort 3. (A) OS stratified by NPM1 mut and NPM1 wt among all patients treated with 2LHMA + VEN, and for patients treated with (B) lower‐intensity therapy or (C) intensive chemotherapy in the 1L. (D) OS in NPM1 mut in the presence or absence of signaling gene (SG) mutations (i.e., KRAS, NRAS, and FLT3‐ITD). [Color figure can be viewed at wileyonlinelibrary.com]
Within the NPM1 mut cohort, univariable analysis did not identify any individual SG mutations associated with outcome (Table S5). Analysis was limited by the small sample size; only one patient had a KRAS mutation, and one had a mutation in the NF1 gene. OS of NPM1 mut cases did not differ based on the presence or absence of NRAS/KRAS mut and/or FLT3‐ITDpos (p = 0.79) (Figure 3D).
4. Discussion
We describe one of the largest cohorts of older patients with newly diagnosed NPM1 mut AML. The primary objective of this analysis was to assess the prognostic impact of co‐occurring SG mutations in older patients with NPM1 mut AML treated with HMA + VEN. Consistent with prior studies, NPM1 was frequently co‐mutated with FLT3‐ITD and FLT3‐TKD, and rarely with JAK2 [19, 20]. Overall, NPM1 mut was associated with improved OS, but the benefit was abrogated by the presence of SG mutations (FLT3‐ITD, KRAS, and NRAS), which is consistent with prior studies as well as ELN 2024 risk classification.
Our study included two separate cohorts of HMA + VEN in the frontline setting; Cohort 1 included patients treated in academic centers, whereas Cohort 2 included patients largely treated in a more real‐world community setting. The median OS for NPM1 mut was 53.1 and 15.3 months compared to 17.0 and 14.4 months for NPM1 wt in Cohorts 1 and 2, respectively. For NPM1 mut patients with SG mutations, in Cohort 1, the OS was not statistically different from NPM1 mut without SG mutations, whereas in Cohort 2, the median OS was 9.4 compared to 31.6 months without SG mutations. Although relapse data were not available for Cohort 1, relapse rates may have differed between patients with and without SG mutations despite similar OS outcomes, and access to salvage therapies at academic centers may have mitigated potential differences in survival outcomes.
These findings align with the four‐gene molecular risk signature, showing that although patients with NPM1 mut AML appear to be sensitive to VEN‐based treatment, favorable clinical outcomes are largely restricted to cases lacking activated SG co‐mutations [9, 10, 11]. Similarly, the recently developed PRISM score, derived from a large multicenter cohort of 2273 newly diagnosed AML patients, confirmed the negative prognostic impact of KRAS mutations and FLT3‐ITD, but not NRAS mutations, irrespective of NPM1 mutation status [21]. While our analysis was limited by the sample size of Cohort 1, and missing PTPN11 mutational data in Cohort 2, prior studies, including the PRISM score, also suggested that PTPN11 co‐mutations confer adverse outcomes in NPM1 mut AML [22, 23, 24]. PTPN11 mutations are relatively rare among all patients with AML (~8%) (24), but approximately 15%–20% of the NPM1 mut AML patients have a co‐mutation in PTPN11 [20, 25, 26]. Although PTPN11 mutation status is not incorporated in the ELN 2024, and patients with PTPN11 mutations are therefore considered “favorable‐risk,” their prognostic impact warrants further investigation and they should not be presumed to confer favorable‐risk.
Moreover, studies have also shown that TET2 mutation may be associated with worse outcomes in patients with NPM1 mut [17]. In cohort 2, we confirmed worse outcomes associated with TET2 among those with an NPM1 mutation. Due to the small number of patients in cohort 1 (n = 2), we were unable to assess the impact of TET2 in this cohort. Our data suggest that TET2 mutations may be an additional adverse‐risk factor when identified in combination with NPM1 mut in older patients receiving AZA + VEN frontline therapy.
Next, we investigated the effect on outcome of NPM1 mut on outcome in patients receiving HMA + VEN in the 2L. We found that NPM1 mut was not prognostic overall. However, in patients who received IC as frontline therapy, long‐term survival appeared higher in NPM1 mut patients though this was not statistically significant, and the sample size was small. We also found that the presence or absence of SG mutations was not prognostic in NPM1 mut AML patients treated with HMA + VEN in the 2L setting.
The observation that SG mutations in NPM1 mut are associated with shorter OS duration in patients treated with frontline HMA + VEN, due to either primary resistance or relapse due to acquisition or enrichment of clones with activated kinase signaling mutations [27, 28], underscores the need for new treatment options for this subset of patients. Recently, two menin inhibitors, revumenib and ziftomenib, have been FDA approved for patients with relapsed/refractory NPM1 mut AML [29, 30]. Menin‐inhibitors target the interaction between menin and KMT2A fusion proteins or mutant NPM1, leading to downregulation of HOX/MEIS, thereby reducing leukemic persistence and promoting differentiation [31, 32]. Although limited by small numbers, both the AUGMENT‐101 and the KOMET‐001 showed activity of menin inhibitors across NPM1 mut patients with co‐signaling gene mutations (e.g., in KRAS/NRAS, FLT3‐ITD).
The Beat AML substudy evaluated the triplet combination of AZA + VEN + revumenib for newly diagnosed older AML patients with NPM1 mut or KMT2A‐rearrangement and demonstrated encouraging clinical outcomes with overall response rates and complete remission rates of 88% and 67%, respectively [33]. Further, in NPM1 mut AML patients with SG mutations, the combination of AZA + VEN + revumenib demonstrated a composite remission rate of 77% and median OS of 15.5 months suggesting that the addition of revumenib may abrogate the poor outcomes associated with SG mutations [33]. Ziftomenib and bleximenib have also demonstrated encouraging clinical activity in combination with AZA + VEN in this patient population [34, 35]. These findings have led to three ongoing randomized phase 3 studies (KO‐MEN‐017 [NCT07007312], EVOLVE‐2: HOVON [NCT06652438], cAMeLot‐2 [NCT06852222]) investigating AZA + VEN+ menin inhibitor or placebo for newly diagnosed older/unfit AML patients with NPM1 mut. Our data corroborate prior findings that SG co‐mutations lead to worse outcomes in patients with NPM1 mut. Further data from these ongoing randomized phase 3 studies is necessary to determine whether the addition of menin inhibitors to AZA + VEN improves clinical outcomes in patients with NPM1 mut with SG mutations.
Combinational therapies incorporating FLT3 inhibitors are also under investigation and may be effective in this higher‐risk subset. A phase 1/2 study of gilteritinib, VEN, and AZA in relapsed/refractory (n = 22) and newly diagnosed AML (n = 30) patients unfit for IC demonstrated high remission and measurable residual disease negativity rates; approximately 40% of patients harbored both an NPM1 mutation and FLT3‐ITD [36]. Additional ongoing studies evaluating FLT3 inhibitor‐based triplet regimens include the phase 1/2 VICEROY trial (NCT05520567) in newly diagnosed AML with FLT3‐ITD or FLT3‐TKD, MyeloMATCH MM10A‐EA02 (NCT05564390), and a phase 1/2 trial with ASTX727 (decitabine/cedazuridine), VEN, and gilteritinib (NCT05010122).
Our study is limited by its retrospective nature and inclusion of real‐world patient data captured from electronic health records. Documentation can be incomplete, treatment sequences can be misclassified, and certain practice types or geographic regions may be overrepresented (e.g., community practices are more likely to provide data to the Flatiron database). Further, we did not have information regarding overall response rates to HMA + VEN and thus our data are only applicable to OS estimates, nor did we have data regarding subsequent therapies in Cohort 1.
In conclusion, we demonstrated that SG mutations negate the favorable prognostic impact of NPM1 mut in patients ≥ 60 years with newly diagnosed AML treated with HMA + VEN in the 1L setting. Given the poor outcomes in this subgroup, prospective clinical trials are needed in these patients with NPM1 mut and SG mutations. Menin inhibitors are being investigated in combination with AZA + VEN in three ongoing randomized phase 3 trials for newly diagnosed older/unfit AML patients with NPM1 mut, whereas FLT3 inhibitors are under investigation in FLT3‐ITD‐positive and FLT3‐TKD‐mutated AML, including subsets with co‐occurring NPM1 mutations. It is imperative to assess clinical outcomes of NPM1 mut AML patients with and without SG mutations as separate subgroups in clinical trials.
Author Contributions
F.W.H., J.F.Z., G.T., D.N., and Y.F.M. analyzed the data. K.M., Y.H., A.L., R.L.W., R.T.S., E.T., E.M.S., T.L.L., M.R.B., V.H.D., W.G.B., M.L.A., W.S., O.O., R.L.O., C.C.S., G.J.S., E.K.C., O.C., C.M., M.H., K.S., C.F., J.G.‐L., B.K.R., S.V.H., N.A.H., T.C., M.M., M.S., S.G.M., L.R., B.J.D., R.L.L., A.S.M., A.O.Y., U.M.B., A.S.M., A.‐K.E., J.C.B., and Y.F.M. collected and assembled data, and/or were involved in patient care. F.W.H., J.F.Z., K.M., and Y.F.M. wrote the paper. All authors reviewed the manuscript and approved the final version.
Funding
The study was sponsored by Blood Cancer United. Funding for the trial was made possible by the Harry T. Mangurian Foundation, many other donors, and the sites that enabled resources for rapid turnaround for cytogenetic analysis and other monitoring requirements for patients. Sub‐studies in this trial were supported by pharmaceutical sponsors. We thank the pharmaceutical sponsors who paid the cost of performing the specific sub‐studies with their investigational drugs.
Ethics Statement
The study was approved by a central institutional review board (IRB) and MARROW consortium‐associated IRBs. The study was conducted in accordance with the Declaration of Helsinki and the International Council for Harmonization of Good Clinical Practice guidelines.
Consent
All patients provided written informed consent.
Conflicts of Interest
E.T. has participated in advisory boards and/or consulting for Abbvie, Astellas, Daiichi‐Sankyo, Servier, and Rigel. He has received research funding from Prelude Therapeutics, Schrodinger, Incyte, and Astra‐Zeneca. E.M.S. has served on the advisory boards of Astellas Pharma, AbbVie, Genentech, Daiichi Sankyo, Novartis, Amgen, Seattle Genetics, Syros Pharmaceuticals, Syndax Pharmaceuticals, Agios Pharmaceuticals, and Celgene. He is an equity holder in Auron Therapeutics. T.L.L. has received research funding from Bio‐Path Holdings, Astellas Pharma, Celyad, Aptevo Therapeutics, Cleave Biosciences, Ciclomed, Jazz Pharmaceuticals, and Kura Oncology and serves on the advisory board of Servier, Syndax, and Daiichi Sankyo. M.R.B. has institutional funding from AbbVie, Ascentage, Astellas, Gilead, Kura, Sumitomo, and Takeda. W.G.B. has served on advisory boards of AbbVie and Syndax and has research funding from ImmuneOnc, Meryx, and Nkarta. O.O. has served on the advisory boards of Servier, Rigel, ABBVIE, Incyte, and data safety monitoring board for Threadwell therapeutics. J.F.Z. has received honoraria from consulting and/or advisory fees from AbbVie, Astellas, AstraZeneca, Crossbow Therapeutics, Daiichi Sankyo, Foghorn, Genentech, Genmab, Geron, Ipsen, Jazz, Johnson & Johnson, Kura Oncology, Neogenomics, Novartis, Relmada Therapeutics, Rigel, Sellas, Servier, Shattuck Labs, Sumitomo Pharma, and Syndax; has received research funding from AbbVie, Akesobio, Aptevo, Arog, Ascentage, Auron, Daiichi Sankyo, Faron, Jazz, Kura Oncology, Lin Biosciences, Loxo, Merck, Novartis, Sellas, Shattuck Labs, Stemline, Sumitomo Pharma, and Zentalis. R.L.O. has received research funds for Cellectis and consulted for Syndax. C.C.S. has received research funds from Abbvie, BMS, Erasca, Revolution Medicines and Zentalis and served on advisory boards for Abbvie, Genentech and Astellas. G.J.S. has commercial interests in BMS, Amgen, and J&J. He has received fees from AbbVie, Agios, Amgen, Astellas, BMS, Incyte, Janssen, Jazz, Karyopharm, Kite, Pharmacyclics, Sanofi/Genzyme, and Stemline. He has received research funds from AbbVie, Actinium, Actuate, Arog, Astellas, AltruBio, AVM Bio, BMS/Celgene, Celator, Constellation, Daiichi‐Sankyo, Deciphera, Delta‐Fly, Forma, FujiFilm, Gamida, Genentech‐Roche, Glycomimetics, Geron, Incyte, Karyopharm, Kiadis, Kite/Gilead, Kura, Marker, Mateon, Onconova, Pfizer, PrECOG, Regimmune, Samus, Sangamo, Sellas, Stemline, Syros, Takeda, Tolero, Trovagene, Agios, Amgen, Jazz, Orca, Ono‐UK, and Novartis. M.S. has been a consultant for Eilean Therapeutics. B.J.D. has the following conflicts of interest: Cepheid, Labcorp, Nemucore Medical Innovations, Novartis, RUNX1 Research Program; SAB & Stock: Aptose Biosciences, Blueprint Medicines, Enliven Therapeutics, Iterion Therapeutics, GRAIL, Recludix Pharma; Board of Directors & Stock: Amgen, Vincerx Pharma; Board of Directors: Burroughs Wellcome Fund, CureOne (inactive); Joint Steering Committee: Beat AML Blood Cancer United; Advisory Committee: Multicancer Early Detection Consortium; Founder: VB Therapeutics; Sponsored Research Agreement: Astra‐Zeneca, DELiver Therapeutics, Immunoforge, Terns, Enliven Therapeutics (inactive), Recludix Pharma (inactive); Clinical Trial Funding: Novartis, Astra‐Zeneca; Royalties from Patent 6958335 (Novartis exclusive license) and OHSU and Dana‐Farber Cancer Institute (one Merck exclusive license, one CytoImage Inc. exclusive license, one DELiver Therapeutics nonexclusive license, and one Sun Pharma Advanced Research Company nonexclusive license); US Patents 4326534, 6958335, 7416873, 7592142, 10473667, 10664967, and 11049247. R.L.L. is on the supervisory board of Qiagen and is a scientific advisor to Imago, Mission Bio, Syndax. Zentalis, Ajax, Bakx, Auron, Prelude, C4 Therapeutics and Isoplexis for which he receives equity support. B.K.R. serves on the advisory boards for Astellas, BMS, and Syndax. R.L.L. receives research support from Ajax and Abbvie and has consulted for Incyte, Janssen, Morphosys, and Novartis. He has received honoraria from Astra Zeneca and Kura for invited lectures and from Gilead for grant reviews. U.M.B. has been a consultant for Genentech, Daiichi Sankyo, Takeda, Pfizer, AbbVie/Genentech, and Novartis. A.S.M. has served on the advisory boards of AbbVie/Genentech, Novartis, Ryvu Therapeutics, Rigel Therapeutics, Treadwell Therapeutics, and Foghorn Therapeutics. J.C.B. is a current equity holder in Lomond Therapeutics Inc. (a publicly traded company) and Eilean Therapeutics. J.C.B. holds membership on the Board of Directors or advisory committees of Lomond, Newave, Eilean, and Kartos, and Orange Grove. Y.F.M. has received honoraria/consulting fees from BMS, Kura Oncology, BluePrint Medicines, Geron, OncLive and MD Education, VJHemOnc, and Medscape Live. Y.F.M. participated in advisory boards and received honoraria from Sierra Oncology, Stemline Therapeutics, Blueprint Medicines, Morphosys, Taiho Oncology, SOBI, Rigel Pharmaceuticals, Geron, Cogent Biosciences, and Novartis. Y.F.M. received travel reimbursement from Blueprint Medicines, MD Education, and Morphosys. None of these relationships were related to this work. M.L.A. participated in advisory board of Syndax Pharmaceuticals. The other authors declare no conflicts of interest.
Supporting information
Table S1: Univariate analysis of overall survival at last follow‐up for full Cohort 1 (n = 322) and NPM1‐mutated (n = 61).
Table S2: Multivariate analysis in Cohort 1.
Table S3: Univariate analysis of overall survival at last follow‐up for full Cohort 2 (n = 816) and NPM1‐mutated (n = 124).
Table S4: First line treatment regimens of patients in Cohort 3 receiving HMA + VEN in the second line (n = 220).
Table S5: Univariate analysis of overall survival at last follow‐up for full Cohort 3 (n = 220) and NPM1‐mutated (n = 29).
Figure S1: Overall survival of all patients included in (A) Cohort 1, (B) Cohort 2, and (C) Cohort 3.
Figure S2: Kaplan–Meier curves depicting overall survival of patients with NPM1 mut AML who also harbored mutations in the PTPN11 gene versus overall survival of NPM1 mut patients with wild‐type PTPN11 who harbored FLT3‐ITD, KRAS and/or NRAS mutations.
Figure S3: Overall survival of patients with NPM1 mut AML (A) with and those without TET2 mutations. (B) Overall survival of patients with NPM1 mut AML, no FLT3‐ITD, and wild‐ type DNMT3A who harbored TET2 mutations versus those who did not.
Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Table S1: Univariate analysis of overall survival at last follow‐up for full Cohort 1 (n = 322) and NPM1‐mutated (n = 61).
Table S2: Multivariate analysis in Cohort 1.
Table S3: Univariate analysis of overall survival at last follow‐up for full Cohort 2 (n = 816) and NPM1‐mutated (n = 124).
Table S4: First line treatment regimens of patients in Cohort 3 receiving HMA + VEN in the second line (n = 220).
Table S5: Univariate analysis of overall survival at last follow‐up for full Cohort 3 (n = 220) and NPM1‐mutated (n = 29).
Figure S1: Overall survival of all patients included in (A) Cohort 1, (B) Cohort 2, and (C) Cohort 3.
Figure S2: Kaplan–Meier curves depicting overall survival of patients with NPM1 mut AML who also harbored mutations in the PTPN11 gene versus overall survival of NPM1 mut patients with wild‐type PTPN11 who harbored FLT3‐ITD, KRAS and/or NRAS mutations.
Figure S3: Overall survival of patients with NPM1 mut AML (A) with and those without TET2 mutations. (B) Overall survival of patients with NPM1 mut AML, no FLT3‐ITD, and wild‐ type DNMT3A who harbored TET2 mutations versus those who did not.
Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.