Genomic Profile and Clinical Outcomes in Acute Myeloid Leukemia with Monosomal Karyotype
by
, , and
Collins Wangulu
1,2,
Ehsan Bahrami Hezaveh
3,
Mojgan Zarif
3,
Qianghua Zhou
2,3,
Winnie Lo
2,4,
Cuihong Wei
2,4,
Hassan Sibai
5 and
Hong Chang
2,3,* 
1
Princess Margaret Cancer Biobank (PMCB), University Health Network, Toronto, ON M5G 2C4, Canada
2
Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON M5S 1V4, Canada
3
Department of Laboratory Hematology, University Health Network, Toronto, ON M5G 2C4, Canada
4
Laboratory Medicine Program, Clinical Laboratory Genetics, University Health Network, Toronto, ON M5G 2C4, Canada
5
Department of Medical Oncology and Hematology, Princess Margaret Cancer Centre, University of Toronto, Toronto, ON M5G 2C4, Canada
*
Author to whom correspondence should be addressed.
Int. J. Mol. Sci. 2025, 26(12), 5845; https://doi.org/10.3390/ijms26125845
Submission received: 5 May 2025
/
Revised: 3 June 2025
/
Accepted: 16 June 2025
/
Published: 18 June 2025
(This article belongs to the Special Issue Leukemia and Lymphoma: A Focus on Molecular Genetics Research)
Abstract
The biology of Monosomal Karyotype Acute Myeloid Leukemia (MK AML) remains unclear, and its mutational profile has not been exclusively assessed. We sought to determine the genomic profile of MK AML patients and its correlation with overall survival (OS). We conducted a retrospective study involving 664 AML patients, identifying 156 (23.5%) with MK AML. The most common monosomies were -17 (41%) and -7 (37%), with 149 (95%) and 138 (88%) having myelodysplasia-related (MR) cytogenetics and complex karyotype (CK), respectively. Frequent mutations included TP53 (69%), DNMT3A (19%), TET2 (13%), and IDH1 (7%). Patients with MK AML with TP53 mutation (TP53 Mut) had shorter OS compared to those with TP53 wild-type (WT) (median OS, 3.9 versus 9.2 months, p = 0.002). Our validation study further supports this finding. There was no significant difference in OS related to the presence or absence of CK (p = 0.252), MR mutations (p = 0.252), DNMT3A (p = 0.264), TET2 (p = 0.264), and IDH1 (p = 0.183) alterations. Co-mutation with novel EPI6 and TAZI signature alterations did not significantly impact OS among MK AML TP53 Mut patients, suggesting that TP53 Mut remains the dominant driver of outcome in this subgroup. In conclusion, MK AML is a genotypically diverse and high-risk group, with MK AML TP53 Mut indicating worse prognosis.
1. Introduction
Monosomal Karyotype (MK) is defined by the presence of a single autosomal monosomy, along with at least one additional autosomal monosomy or a structural chromosome abnormality, other than those associated with defining core binding factor (CBF) Acute Myeloid Leukemia (AML) [t (8; 21) (q22; q22), inv (16) (p13.1q22)/t(16; 16) (p13.1; q22)] or acute promyelocytic leukemia [t (15; 17) (q22; q12)]. MK has been observed in 5–10% of newly diagnosed AML patients, increases with age [1,2,3,4], and has no biological sex disparity [5]. These patients have a poor prognosis [2,4,6], showing limited response to conventional chemotherapy [1,2,7] and allogeneic hematopoietic stem cell transplantation (allo-HCT) [1,8], which explains their adverse risk status according to the European LeukemiaNet 2022 (ELN 2022) risk stratification [9].
The cytogenetic profile of MK AML frequently features -5 and -7 as the two most commonly reported monosomies [1,6,10]. Previous studies, however, document various types and frequencies of these lesions [4,6,7]. Other cytogenetic abnormalities associated with MK AML include inv (3) or t (3; 3), abnormal(12p), abnormal(17p), complex karyotype (CK), and myelodysplasia-related (MR) cytogenetic changes [4,7,11]. A relatively high frequency of TP53 mutation (TP53 Mut) [12,13] has been reported among MK AML patients, along with underrepresentation of NPM1 and FLT3-ITD mutations [7,12]. Previous MK AML studies have been limited by low patient numbers [5,12], limited access to molecular genomic analysis that restricted targeted mutational profile [5] and lack of an exclusively MK AML patient population [12]. In fact, as far as we know, no previous study has evaluated the mutational profile of exclusively MK AML patients.
Understanding the cytogenetic and molecular profiles of various types of AML helps predict prognosis and guide optimal therapy to enhance outcomes in the evolving field of science [9,14]. Different cytogenetic abnormalities [1,4,7,13,15] and some co-occurring mutations [5,12,16] in MK AML patients have been demonstrated to confer varying clinical outcomes, making them a heterogeneous group that may benefit from characterization based on their clinical outcomes. The poor prognosis of TP53 Mut in AML, including MK AML, has been described [17,18,19,20,21,22,23]. However, other mutational changes underlying MK AML and their impact on clinical outcomes are yet to be established.
Our study aims to determine the cytogenetic and mutational profiles of MK AML patients and seeks to correlate these genomic characteristics with overall survival (OS) in a real-world setting.
2. Results
2.1. Patient Characteristics
We examined 664 patients diagnosed with AML, of whom 156 (23.5%) had MK AML. The median age for patients with MK AML was 71 years (range, 19–94), with the majority (n = 82, 52.6%) being male. At the time of diagnosis, they had a median white blood cell (WBC) count of 3.4 (range, 0.1–162.3) × 109 cells/L, hemoglobin levels 8.4 (range, 5.7–14.2) g/dL, platelet count 43 (range, 9–782) × 109 cells/L and BM blast percentage 38.5% (range, 20–95%) (Table 1).
MK AML patients were older compared to their non-MK AML counterparts (p = 0.033) and had lower WBC (p < 0.001) and platelet (p < 0.001) counts. In addition, they showed a greater incidence of CK (p < 0.001) and lower rates of allo-HCT (p = 0.023) (Table 1).
2.2. Genomic Profile
The most common monosomies observed in the study cohort were -17 (n = 64, 41%), -7 (n = 58, 37%), -13 (n = 29, 18%), and -5 (n = 21, 13%) (Figure 1A). In comparison to their non-MK AML counterparts, each of these monosomies was more prevalent in patients with MK AML (Table 1). A total of 149 (95%) and 138 (88%) patients had MR cytogenetics and CK, respectively (Figure 1A). MR mutations were observed in 37 (24%) patients, whereas two recently described mutation signatures, EPI6 (CUX1, U2AF1, EZH2, TET2, CBL, or KRAS) [24,25] and TAZI (DNMT3A, SETBP1, CUX1, TET2, ASXL1, BCOR, EZH2, PHF6, RUNX1, SF3B1, SRSF2, STAG2, U2AF1 or ZRSR2) [25,26] were seen in 33 (21%) and 71 (45%) patients, respectively.
Forty-two (77.8%) of the 54 individual genes targeted for analysis were mutated in 150 (96.2%) MK AML patients. A total of 313 mutations were present, with a median of 2 and a range of 0 to 8 mutations per patient across the 42 genes. Nine genes were mutated in more than 5% of the patients, including TP53 Mut (n = 108, 69%), DNMT3A (n = 29, 19%), TET2 (n = 20, 13%), IDH1 (n = 11, 7%), RUNX1 (n = 10, 6%), BCOR (n = 9, 6%), CEBPA (n = 8, 5%), NRAS (n = 8, 5%), and U2AF1 (n = 8, 5%) as illustrated in Figure 1A. Among these genes, BCOR, TP53, and RUNX1 had a median variant allele frequency (VAF) greater than 50% (Figure 1B). Thirty-one pairs of gene mutations demonstrated a significant correlation. We identified a significant negative correlation between the TP53 Mut and six genes: NRAS, RUNX1, BCOR, CEBPA, NPM1 and U2AF1. In addition, NPM1—CEBPA, SF3B1—NRAS and SRSF2 -TET2 exhibited the strongest positive correlations among these patients (Figure 1C).
2.3. Overall Survival (OS) and Impact of Allo-HCT on MK AML Patients
MK AML patients had significantly shorter OS compared to their non-MK AML counterparts (median OS, 5.5 months versus 24 months, p < 0.001) (Figure 2A). Regarding their treatment, 47 (30.1%) MK AML patients received only supportive therapy. Meanwhile, 66 (42.3%) and 43 (27.6%) underwent intensive and low-intensive induction chemotherapy, leading to 30 (45.4%) and 9 (20.9%) achieving CR after the first cycle of induction therapy, respectively. In total, 23 (14.7%) patients received allo-HCT while in CR following different cycles of chemotherapy. In contrast, 21 (13.7%) who also reached CR during different cycles did not receive transplantation (Table A2). Overall, recipients of allo-HCT had significantly better OS compared to those who reached CR but were not transplanted (median OS, 16.2 months versus 11.3 months, p = 0.016) (Figure 2B).
2.4. Impact of TP53 Mutation on OS
We categorized MK AML patients in our study based on their TP53 Mut status. Among all MK AML patients in the study, 108 (69.2%) had TP53 Mut (MK AML TP53 Mut), while 48 (30.8%) were MK AML TP53 wild-type (MK AML TP53 WT). MK AML TP53 Mut patients were older (p = 0.008) and had a higher frequency of CK (p < 0.001) compared to their MK AML TP53 WT counterparts. In addition, fewer of these patients underwent allogeneic transplantation (allo-HCT) (p = 0.004) (Table 2). Kaplan–Meier analysis showed significantly shorter OS among MK AML TP53 Mut compared to the MK AML TP53 WT group in the study (median OS, 3.9 versus 9.2 months, p = 0.002) (Figure 2C).
We separately analyzed how the presence or absence of CK, monosomies, ICC MR mutations, and the most frequent mutations within our study cohort affect OS. Our findings indicated inferior OS related to the presence of monosomy 17 (p = 0.009). We found no significant difference in OS related to the presence or absence of CK (p = 0.252), ICC MR mutations (p = 0.252), DNMT3A (p = 0.264), TET2 (p = 0.264), and IDH1 (p = 0.183) among MK AML patients (Table 3).
We further conducted Cox proportional hazards regression analysis, incorporating covariates known to affect outcomes in AML. We excluded complex karyotype (CK) from our analysis due to its overrepresentation in MK AML [5,7,27]. Our study comprised 138 (88.5%) MK AML patients with CK (Table 1). In addition, CK is also strongly associated with TP53 Mut [19,28,29] and did not show significance in the univariate analysis. Our multivariate analysis revealed that allo-HCT (p < 0.001), low-intensity (p < 0.001), and intensive induction chemotherapy (p < 0.001) significantly lowered the risk of death among MK AML patients. Conversely, the presence of TP53 Mut was associated with a higher risk of mortality. Age and WBC count showed no significant correlation (Table 4).
2.5. Impact of Co-Alterations on MK AML in TP53 Mut and WT Patients
Two co-mutation signatures, EPI6 [25] and TAZI [25,26], have recently been identified and shown to predict adverse clinical outcomes among TP53 Mut patients with myeloid neoplasia (MN) [25]. In our study population, there was no difference in OS among MK TP53 Mut patients when categorized based on the presence or absence of TAZI (p = 0.232) (Figure A1a) and EPI6 (p = 0.563) mutation signatures (Figure A1b). In addition, no difference in OS was observed among the AML MK TP53 WT group based on the presence or absence of CK (p = 0.771), MR cytogenetics (p = 0.135) and MR mutations (p = 0.922) and (Table A1).
2.6. Validation Cohort
To validate our findings, we utilized a publicly available dataset from the BEAT AML 2.0 study [30]. We analyzed 100 AML MK patients with a median age of 65 (21–83) years, whose clinical and genetic analysis data were accessible. The distribution of biological sex (p = 0.394) and TP53 Mut status (p = 0.129) was comparable to our cohort, although they represented a relatively younger (p = 0.002) population (Table A3).
Similar to the approach used in our study population, we categorized them according to their TP53 Mut status, with 60 (60%) being AML MK TP53 Mut and 40 (40%) AML MK TP53 WT. Kaplan–Meier analysis of OS among AML MK TP53 Mut patients and their MK TP53 WT counterparts demonstrated a significant difference in OS (median OS of 5 versus 12.5 months, p < 0.001) (Figure 2D).
3. Discussion
Describing the genomic landscape of the heterogeneous MK AML patient group undoubtedly enhances our understanding of the disease biology, potential prognostic classification, and the development of treatment strategies in this era of precision medicine and highly personalized care. MK AML patients in our study cohort represented 23.5% of all AML patients, which is comparable to those described previously [1,7], especially considering our older study population (Table 1). Similar to earlier studies, they were older [2,4,7] with associated lower WBC counts [5,6,12] as compared to their non-MK AML counterparts. We describe their genomic profile in the context of the few existing studies [5,12] and our correlation with clinical outcomes identifies an ultra-adverse risk subgroup based on their OS in a real-world setting.
Our study identifies -17 and -7 as the two most frequent monosomies, similar to Weinberg et al. [5], which contrasts other studies that found -5 and -7 as the most frequent [2,6,10]. Variations in these frequencies can be attributed to differences in study geographical settings [1]. Most importantly, it has previously been established that there is no difference in prognosis resulting from the presence of any specific monosomy within the context of the MK AML [1,4]. Monosomy 17 is part of the spectrum of abnormalities linked to the loss of function or deletion of the TP53 gene found on chromosome 17p13.1 [31]. In our study, 58 (90.6%) MK AML patients with monosomy 17 had TP53 Mut, which supports our findings of an inferior survival among these patients (Table 3). Co-occurrence of unfavourable cytogenetics, such as CK and MR cytogenetic abnormalities in MK AML is not uncommon [4,13] and has been shown to worsen clinical outcomes [7]. In our cohort, 88.5% and 95% of MK AML patients had CK and MR cytogenetic abnormalities, respectively, which is comparable to other studies [4,10,32] and could partly explain the overall poor prognosis in this group of patients.
The association and adverse impact of TP53 Mut on MK AML has been previously described [1,13], along with its relatively high prevalence in a subset of CK MK patients [12]. With a frequency of 69%, TP53 Mut was the most common mutation in our study cohort. Indeed, the ineffective DNA repair mechanisms and impaired apoptosis induced by TP53 Mut in leukemic cells has been suggested as the cause of the karyotype complexity and adverse chromosomal alterations observed in TP53 Mut AML [17,18]. This is in addition to being a potential mechanism for MK AML and the presence of co-occurring adverse cytogenetics among these patients [1]. Our study also identifies DNMT3A (19%), TET2 (13%), IDH1 (7%), and RUNX1 (6%) as the other most frequent altered genes in this group of patients. Leung et al. found RUNX1 (18%), DNMT3A (16%), BCOR (14%), NRAS (13%) as the most frequent mutations among MK AML patients with CK [12]. Differences in the frequency and types of mutations are likely due to their specific cohort consisting exclusively of CK MK AML patients. MK AML has been found to have a lower representation of NPM1 and CEBPA mutations [5], which is similar to the findings in our study and potentially explains the adverse clinical outcomes observed in this group of patients.
We identify MK AML TP53 Mut as a distinct entity associated with poorer clinical outcomes within the heterogeneous MK AML group. Compared to their MK AML TP53 WT counterparts, they are older and have a significantly shorter OS (p = 0.002). We observed similarly worse OS among this group of patients in our validation dataset from the Beat AML 2.0 cohort [30], which represents a robust, contemporary, and multicenter dataset. In addition, there was no significant difference in OS related to the presence or absence of CK (p = 0.252), ICC MR mutations (p = 0.252), DNMT3A (p = 0.264), TET2 (p = 0.264), and IDH1 (p = 0.183) among AML MK patients. TP53 Mut also maintained its independent prognostic significance in our Cox proportional hazards regression analysis that included covariates known to affect clinical outcomes in AML (Table 4). Other studies indicate a poorer prognosis for MK AML when there is an additional structural chromosomal abnormality or monosomy [1,4] or the presence of CK [13]. However, TP53 Mut in AML strongly explains the underlying genetic predisposition to these frequently co-occurring adverse cytogenetic abnormalities [33,34].
Recently, two novel co-mutation signatures, EPI6 mutations that comprise six genes [24,25] and a 14-gene Tazi signature mutation [25,26] have been shown to have predictive ability for inferior clinical outcomes among TP53 Mut patients with Myeloid Neoplasia (MN) [24,25,26]. Considering the previously observed high incidence of TP53 Mut among MK AML patients [12], we assessed these signature mutations in our TP53 Mut MK AML cohort, as no studies, to the best of our knowledge, have been conducted to determine their incidence and prognostic utility among these patients. There was no difference in OS among TP53 Mut MK AML patients based on the presence or absence of these two signature mutations in our study. Potential reasons could be due to the fact that TAZI signature was developed outside the context of TP53 Mut AML [26], whereas EPI6 was specifically designed within a TP53 Mut MN cohort [24]. Additionally, the two signature mutations share overlapping genes. This finding, however, further suggests that TP53 Mut remains the dominant driver of outcome among TP53 Mut MK AML patients in the context of OS.
Our study cohort comprised a relatively large number of MK AML patients across a wide age range who received either intensive or non-intensive treatment that reflects the “real-world” patient scenario. However, the single-centre nature of our study limits the generalizability of its findings to other settings. Regional treatment protocols or referral bias may also influence outcomes. Notably, treatment protocols in this setting are more uniform than in multicenter studies. Lastly, we used OS as the primary predicted outcome, which is comparable with other studies, but it is acknowledged that patient mortality may result from treatment toxicity or other causes unrelated to leukemic biology itself. Future multicenter prospective studies with larger patient cohorts of MK AML are needed to confirm our data and comprehensively evaluate our proposed genomic categorization of MK AML patients.
4. Materials and Methods
4.1. Patients and Samples
We carried out a single-centre retrospective cohort study focusing on MK AML patients. These were selected from a group of AML patients diagnosed from 2016 to 2022, all of whom had comprehensive clinical and diagnostic data, including cytogenetic and molecular testing. The AML diagnoses were reviewed and reclassified according to the 2022 International Consensus Classification (ICC) and subsequently categorized as MK AML based on the cytogenetic results. Furthermore, we utilized a publicly available dataset from the BEAT-AML 2.0 study [30] to validate our findings on defining a worse outcome category. This study received approval from the University Health Network (UHN) Research Ethics Board, and the study procedures adhered to the principles outlined in the Declaration of Helsinki. Patients in the study underwent baseline laboratory testing at diagnosis for Complete Blood Count, bone marrow (BM) blast percentage as well as conventional cytogenetics and molecular testing in accordance with established guidelines. Clinical data, encompassing the age at diagnosis, biological sex, administered chemotherapy, allogeneic hematopoietic stem cell transplantation (allo-HCT) status, conventional karyotype analysis, next-generation sequencing (NGS) results, and survival status, were collected. Individuals with incomplete clinical and laboratory data were excluded from the study.
4.2. Treatment
Patients eligible for intensive induction chemotherapy (IC) received regimens such as 7 + 3 (cytarabine plus daunorubicin), 7 + 3 plus midostaurin for FLT3-mutated AML or FLAG-IDA (fludarabine, cytarabine, filgrastim, and idarubicin). Those who were ineligible received low-intensity therapy (LIT) regimens, which included hypomethylating agents (azacitidine) alone or in conjunction with the BCL2 inhibitor (venetoclax). Patients with intermediate and high-risk disease in their first complete remission (CR) underwent allo-HCT, as did those with refractory or relapsed disease who achieved remission after salvage chemotherapy, provided an available donor was identified. The best supportive care was provided to patients deemed unsuitable for IC or LIT.
4.3. Cytogenetic Analysis
Cytogenetic analysis was performed on diagnostic bone marrow samples using standard chromosome banding techniques, and nomenclatures were provided following the International System for Human Cytogenomic Nomenclature (ISCN) recommendations [35]. Each patient was evaluated for a minimum of 20 metaphases. Monosomal and complex karyotypes were identified in accordance with the European LeukemiaNet (ELN) guidelines.
4.4. Molecular Testing
Molecular analysis utilized total cellular DNA extracted from samples of peripheral blood and BM. In patients diagnosed prior to 2018, targeted sequencing (TAR-SEQ) was conducted using a 54-gene next-generation sequencing (NGS) myeloid panel [36]. NGS was performed in patients diagnosed after 2018 using a custom hybrid-capture–based myeloid panel consisting of 49 genes [37]. The detection limit for variant calling was set at 2%, and only pathogenic mutations were considered. Variants of uncertain significance were excluded from the analysis.
4.5. Statistical Analysis
Categorical variables were expressed as counts and percentages, while continuous variables were summarized using median and range. Association between variables was assessed using Pearson’s chi-square test and Fisher’s exact test for categorical variables, as well as the Kruskal–Wallis test and Mann–Whitney U test for continuous variables. OS was measured from the initial diagnosis to death from any cause or the last follow-up and analyzed by the Kaplan–Meier method. Differences in OS among the risk groups were established using log-rank test. Pairwise comparison of survival between two groups was also performed using log-rank test reporting the statistical significance, hazard ratios (HRs) and 95% confidence intervals (CIs). Multiple comparisons were controlled for false discovery using the Benjamini–Hochberg procedure to adjust the p values [38]. We conducted a multivariable Cox proportional hazards regression analysis that included covariates known to affect clinical outcomes in AML. p values <0.05 were considered statistically significant. Statistical analyses were executed using R software version 4.4.1, and GraphPad Prism software version 10.3.1.
5. Conclusions
In conclusion, MK AML represents a genotypically and clinically diverse group of patients in the ELN 2022 adverse risk category. MK AML TP53 Mut indicates worse outcomes under the current standard of care.
Author Contributions
C.W. (Collins Wangulu) collected, analyzed the data, and wrote the manuscript; E.B.H., M.Z. and Q.Z. collected data and revised the manuscript; C.W. (Cuihong Wei), W.L., and H.S. reviewed and provided critical revisions to the manuscript; H.C. designed the study, analyzed the data, and revised the manuscript. All authors have read and agreed to the published version of the manuscript.
Funding
This research received no external funding.
Institutional Review Board Statement
The study was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Review Board of University Health Network (UHN) Research Ethics Board, approval code: 21-5206.6, 24 September 2024.
Informed Consent Statement
Patient consent was not required because of the retrospective nature of the study.
Data Availability Statement
The data presented in this study are available on request from the corresponding author.
Acknowledgments
The authors acknowledge the dedication and service to patients with Acute Myeloid Leukemia by all health professionals at the University Health Network—Princess Margaret Cancer Centre. The authors have reviewed and edited the output and take full responsibility for the content of this publication.
Conflicts of Interest
The authors declare no conflicts of interest.
Abbreviations
The following abbreviations are used in this manuscript:
| Allo-HCT | Allogeneic hematopoietic stem cell transplantation |
| AML | Acute Myeloid Leukemia |
| BM | Bone marrow |
| CK | Complex karyotype |
| CR | Complete remission |
| ELN 2022 | European LeukemiaNet 2022 |
| FLAG-IDA | Fludarabine, Cytarabine, Filgrastim, and Idarubicin |
| IC | Induction chemotherapy |
| ICC | International Consensus Classification |
| ISCN | International System for Human Cytogenomic Nomenclature |
| LIT | Low-intensity therapy |
| MK | Monosomal Karyotype |
| MK AML | Acute Myeloid Leukemia with Monosomal Karyotype |
| MN | Myeloid Neoplasia |
| MR | Myelodysplasia-Related |
| NGS | Next-generation sequencing |
| NK | Normal karyotype |
| Nove-HiDAC | Mitoxantrone, Etoposide, and modified high-dose cytarabine) |
| OS | Overall survival |
| SPSS | IBM Statistical Package for the Social Sciences |
| TAR-SEQ | Targeted sequencing |
| TP53 Mut | TP53 mutation |
| UHN | University Health Network |
| VAF | Variant allele frequency |
| WBC | White blood cell |
| WT | Wild-type |
Appendix A
Table A1.
Analysis of overall survival in AML MK TP53 WT patients based on complex karyotype (CK), myelodysplasia-related (MR) mutations, and MR cytogenetics.
Table A1.
Analysis of overall survival in AML MK TP53 WT patients based on complex karyotype (CK), myelodysplasia-related (MR) mutations, and MR cytogenetics.
| Variable | MK AML TP53 WT (n = 48) | Median OS (Months) | HR | 95% CI | p Value | |
|---|---|---|---|---|---|---|
| CK | Present | 31 (64.5%) | 7.1 | 1.112 | 0.55–2.25 | 0.771 |
| Absent | 17 (35.4%) | 9.2 | ||||
| MR Cytogenetics | Present | 40 (83.3%) | 7.2 | 0.419 | 0.177–1.99 | 0.135 |
| Absent | 8 (16.7%) | 9.2 | ||||
| MR mutations | Present | 26 (54.1%) | 9.2 | 1.034 | 0.53–2.03 | 0.922 |
| Absent | 22 (45.8%) | 8.7 | ||||
NOTE: The table presents a summary of findings from the Kaplan–Meier analysis of Overall Survival (OS) for study patients.
The table is based on the presence or absence of Complex Karyotype (CK), MR (myelodysplasia-related mutations) as defined by the International Consensus Classification, and MR cytogenetics observed among AML MK TP53 WT patients in the study. The median OS, hazard ratio (HR), 95% confidence interval (CI), and p-values are all provided.
Table A2.
Treatment profile of patients in the study.
| Variable | MK + (n = 156) | CR | MK + TP53 + (n = 108) | MK + TP53 − (n = 48) | |
|---|---|---|---|---|---|
| Induction Chemotherapy | Supportive | 47 (30.1%) | 33 (30.6%) | 14 (29.2%) | |
| Intensive | 66 (42.3%) | 30 (45.4%) a | 43 (39.8%) | 23 (47.9%) | |
| Less Intensive | 43 (27.6%) | 9 (20.9%) a | 32 (29.6%) | 11 (22.9%) | |
| Allo-HCT | Transplanted | 23 (14.7%) | 23 (14.7%) b | 10 (9.3%) | 13 (27.1%) |
| Not Transplanted | 133 (85.3%) | 21 (13.7%) b | 14 (13%) | 7 (14.6%) | |
Abbreviations: MK, monosomal karyotype; CR, complete remission; Allo-HCT, allogeneic hematopoietic transplantation. a—CR after the first cycle of induction chemotherapy, b—CR during different cycles of chemotherapy.
Table A3.
Comparison of baseline characteristics between the study and validation cohorts.
| Variable | Study Cohort (n = 156) | Validation Cohort (n = 100) | p-Value | |
|---|---|---|---|---|
| Age (years) | Median (min-max) | 71 (19–94) | 65 (21–83) | 0.002 a |
| Sex | Male Female | 82 (52.6%) 74 (47.4%) | 58(52%) 42 (42%) | 0.394 b |
| TP53 Mut Status | AML MK TP53 Mut | 108 (69%) | 60 (60%) | |
| AML MK TP53 WT | 48 (31%) | 40 (40%) | 0.129 b | |
| Transplant Status | Allo-HCT | 23 (14.7%) | 21 (21%) | 0.196 b |
Abbreviations: AML, Acute Myeloid Leukemia; MK, monosomal karyotype; TP53 Mut, mutated TP53 gene; allo-HCT, allogeneic hematopoietic transplantation. a—Mann–Whitney U Test, b—Pearson’s Chi Square.
Appendix B
Figure A1.
Kaplan–Meier survival plots of OS among AML MK TP53 Mut patients based on their TAZI and EPI6 signature mutation status. (a) Kaplan–Meier survival plots of OS among AML MK TP53 Mut patients based on their TAZI signature mutation status. (b) Kaplan–Meier survival plots of OS among AML MK TP53 Mut patients based on their EPI6 signature mutation status.
Figure A1.
Kaplan–Meier survival plots of OS among AML MK TP53 Mut patients based on their TAZI and EPI6 signature mutation status. (a) Kaplan–Meier survival plots of OS among AML MK TP53 Mut patients based on their TAZI signature mutation status. (b) Kaplan–Meier survival plots of OS among AML MK TP53 Mut patients based on their EPI6 signature mutation status.
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Figure 1.
Genomic landscape of the study population. (A) Genomic oncoprint of the study cohort. Each column represents a patient, while each row signifies a genomic alteration. The first section is a bar graph showing the number of mutations per patient, followed by the mutations and cytogenetic aberrations examined in the study. The bar plot on the right shows both the percentage and the number of patients with alterations ordered in descending frequency. (B) Analysis of variant allele frequencies (VAFs) for the common mutations in the study cohort. The boxplot shows the median (solid line), 25th, 75th percentiles, and minimum and maximum VAF. Values outside the range are indicated as outliers (dots). The order is sorted by median VAF from high to low. (C) Correlation plot of the most frequently mutated genes. Blue colour indicates positive correlation and red colour indicates negative correlation. Values represent the coefficients. Only significant pairs are shown.
Figure 1.
Genomic landscape of the study population. (A) Genomic oncoprint of the study cohort. Each column represents a patient, while each row signifies a genomic alteration. The first section is a bar graph showing the number of mutations per patient, followed by the mutations and cytogenetic aberrations examined in the study. The bar plot on the right shows both the percentage and the number of patients with alterations ordered in descending frequency. (B) Analysis of variant allele frequencies (VAFs) for the common mutations in the study cohort. The boxplot shows the median (solid line), 25th, 75th percentiles, and minimum and maximum VAF. Values outside the range are indicated as outliers (dots). The order is sorted by median VAF from high to low. (C) Correlation plot of the most frequently mutated genes. Blue colour indicates positive correlation and red colour indicates negative correlation. Values represent the coefficients. Only significant pairs are shown.
Figure 2.
Kaplan–Meier survival plots of OS of the study and validation cohorts. (A) Kaplan–Meier plot of OS based on the presence or absence of MK among all AML patients. (B) Kaplan–Meier plot of OS based on allogeneic hematopoietic transplant (allo-HCT) status of AML MK patients in the study. (C) Kaplan–Meier plot of OS based on TP53 mutation (TP53 Mut) status of MK AML patients in the study. (D) Kaplan–Meier plot of OS based on TP53 Mut of the validation cohort.
Figure 2.
Kaplan–Meier survival plots of OS of the study and validation cohorts. (A) Kaplan–Meier plot of OS based on the presence or absence of MK among all AML patients. (B) Kaplan–Meier plot of OS based on allogeneic hematopoietic transplant (allo-HCT) status of AML MK patients in the study. (C) Kaplan–Meier plot of OS based on TP53 mutation (TP53 Mut) status of MK AML patients in the study. (D) Kaplan–Meier plot of OS based on TP53 Mut of the validation cohort.
Table 1.
Demographic and clinical characteristics of the study cohort.
| Variable | AML (n = 664) | MK − AML (n = 508) | MK + AML (n = 156) | MK − AML vs. MK + AML |
|---|---|---|---|---|
| Male:Female Sex | 377:287 | 295:213 | 82:74 | 0.231 |
| Age (y), median [range] | 69 [18–95] | 69 [18–95] | 71 [19–94] | 0.033 a |
| WBC Count × 109/L, median [range] | 5.9 [0.1–328.7] | 8.0 [0.3–328.7] | 3.4 [0.1–162.3] | <0.001 a |
| Hemoglobin, g/dL, median [range] | 8.6 [3.7–19.7] | 8.6 [3.7–19.7] | 8.4 [5.7–14.2] | 0.598 a |
| Platelet × 109/L, median [range] | 55 [9.0–2726] | 64 [10–2726] | 43 [9–782] | <0.001 a |
| BM Blast percentage, n (%) | 45 (13–97) | 48 (13–97) | 38.5 (20–95) | 0.002 a |
| Complex Karyotype, n (%) | 192 (28.9%) | 54 (10.6%) | 138 (88.5%) | <0.001 b |
| Monosomy 7 | 76 (48.7%) | 18 (3.5%) | 58 (37.2%) | <0.001 b |
| Monosomy 17 | 64 (9.6%) | 0 | 64 (41%) | <0.001 b |
| Monosomy 13 | 28 (4.2%) | 0 | 28 (17.9%) | <0.001 b |
| Monosomy 5 | 21 (3.2%) | 0 | 21 (13.5%) | <0.001 b |
| Transplant, n (%) | 141 (21.2%) | 118 (23.2%) | 23 (14.7%) | 0.023 b |
Abbreviations: AML, Acute Myeloid Leukemia; MK, monosomal karyotype; WBC, white blood cell; BM, bone marrow. a—Mann–Whitney U test. b—Pearson’s Chi-Square test.
Table 2.
Clinical characteristics of MK AML patients based on their TP53 mutation status.
| Variable | MK + AML TP53 + (n = 108) | MK + AML TP53 − (n = 48) | MK + AML TP53 + vs. MK + AML TP53 − |
|---|---|---|---|
| Male:Female Sex | 53:55 | 29:19 | 0.190 a |
| Age (y), median [range] | 73 [36–94] | 65 [19–91] | 0.008 a |
| WBC Count × 109/L, median [range] | 3.1 [0.1–76.9] | 3.8 [0.1–162.3] | 0.184 a |
| Hemoglobin, g/dL, median [range] | 8.3 [5.7–12.3] | 8.9 [6.4–14.2] | 0.018 a |
| Platelet × 109/L, median [range] | 42 [9–782] | 44 [9–408] | 0.586 a |
| BM Blast percentage, n (%) | 35 (20–91) | 46 (20−95) | 0.070 a |
| Complex Karyotype, n (%) | 107 (99.1%) | 31 (64.6%) | <0.001 b |
| Transplant, n (%) | 10 (9.3%) | 13(27.1%) | 0.004 b |
Abbreviations: AML, Acute Myeloid Leukemia; MK, monosomal karyotype; WBC, white blood cell; BM, bone marrow. a—Mann–Whitney U test. b—Pearson’s Chi-Square test.
Table 3.
Analysis of overall survival in AML MK patients based on their frequent genomic alterations, excluding TP53 mutation.
Table 3.
Analysis of overall survival in AML MK patients based on their frequent genomic alterations, excluding TP53 mutation.
| Variable | MK AML (n = 156) | Median OS (Months) | HR | 95% CI | p Value | |
|---|---|---|---|---|---|---|
| CK | Present | 138 (88.5%) | 4.9 | 0.64 | 0.39–1.05 | 0.252 |
| Absent | 18 (11.5%) | 9.2 | ||||
| Monosomy 17 | Present | 64 (41.0%) | 3.3 | 1.77 | 1.22–2.57 | 0.009 |
| Absent | 92 (59.0%) | 7.9 | ||||
| Monosomy 7 | Present | 58 (37.2%) | 4.9 | 1.30 | 0.91–1.88 | 0.382 |
| Absent | 98 (62.8%) | 6.6 | ||||
| Monosomy 13 | Present | 29 (18.6%) | 3.3 | 1.20 | 0.73–1.95 | 0.439 |
| Absent | 127 (81.4%) | 5.9 | ||||
| Monosomy 5 | Present | 21 (13.5%) | 3.5 | 1.55 | 0.90−2.69 | 0.183 |
| Absent | 135 (86.5%) | 6.0 | ||||
| ICC MR Mutations | Present | 37 (23.7%) | 7.2 | 1.36 | 0.93–1.99 | 0.252 |
| Absent | 119 (76.3%) | 4.7 | ||||
| DNMT3A | Present | 29 (18.6%) | 3.5 | 0.76 | 0.47–1.22 | 0.264 |
| Absent | 127 (81.4%) | 5.9 | ||||
| TET2 | Present | 20 (12.8%) | 2.3 | 0.72 | 0.41–1.27 | 0.264 |
| Absent | 136 (87.2%) | 5.9 | ||||
| IDH1 | Present | 11 (7.1%) | 8.7 | 1.88 | 1.11−3.18 | 0.183 |
| Absent | 145 (92.9%) | 5.2 | ||||
NOTE: The table presents a summary of findings from the Kaplan–Meier analysis of Overall Survival (OS) for study patients based on the presence or absence of Complex Karyotype (CK), Monosomies, MR (myelodysplasia-related mutations) as defined by the International Consensus Classification), and the most frequent mutations observed in the study cohort. The median overall survival (OS), hazard ratio (HR), 95% confidence interval (CI), and p-values are reported. To control for false discovery in multiple comparisons, the Benjamini–Hochberg procedure was used for adjusting the p values.
Table 4.
Cox proportional hazards regression analysis of variables among MK AML patients.
| Variable | Hazard Ratio | 95% CI | p Value | |
|---|---|---|---|---|
| Age [Years] | 1.01 | 0.66–1.54 | 0.965 | |
| WBC Count | 1.00 | 0.99–1.01 | 0.949 | |
| TP53 Mut | 1.61 | 1.06–2.46 | 0.026 | |
| Induction Chemotherapy | Low-Intensity | 0.25 | 0.16–0.41 | <0.001 |
| Intensive | 0.32 | 0.2–0.52 | <0.001 | |
| Allo-HCT | 0.25 | 0.14–0.47 | <0.001 | |
Abbreviations: Allo-HCT, Allogeneic hematopoietic stem cell transplantation; CI, confidence interval; TP53 Mut, TP53 mutation; WBC, white blood cell.
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Wangulu, C.; Bahrami Hezaveh, E.; Zarif, M.; Zhou, Q.; Lo, W.; Wei, C.; Sibai, H.; Chang, H. Genomic Profile and Clinical Outcomes in Acute Myeloid Leukemia with Monosomal Karyotype. Int. J. Mol. Sci. 2025, 26, 5845. https://doi.org/10.3390/ijms26125845
AMA Style
Wangulu C, Bahrami Hezaveh E, Zarif M, Zhou Q, Lo W, Wei C, Sibai H, Chang H. Genomic Profile and Clinical Outcomes in Acute Myeloid Leukemia with Monosomal Karyotype. International Journal of Molecular Sciences. 2025; 26(12):5845. https://doi.org/10.3390/ijms26125845
Chicago/Turabian StyleWangulu, Collins, Ehsan Bahrami Hezaveh, Mojgan Zarif, Qianghua Zhou, Winnie Lo, Cuihong Wei, Hassan Sibai, and Hong Chang. 2025. "Genomic Profile and Clinical Outcomes in Acute Myeloid Leukemia with Monosomal Karyotype" International Journal of Molecular Sciences 26, no. 12: 5845. https://doi.org/10.3390/ijms26125845
APA StyleWangulu, C., Bahrami Hezaveh, E., Zarif, M., Zhou, Q., Lo, W., Wei, C., Sibai, H., & Chang, H. (2025). Genomic Profile and Clinical Outcomes in Acute Myeloid Leukemia with Monosomal Karyotype. International Journal of Molecular Sciences, 26(12), 5845. https://doi.org/10.3390/ijms26125845
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