Post-cytotoxic myeloid neoplasms: a comprehensive analysis of clinicopathologic, genetic profile, latency determinants, and potential prognostic predictors- a single centre study.

Introduction

Myeloid neoplasms-post Cytotoxic (MN-pCTs), also known as therapy-related myeloid neoplasms (t-MN), refer to a category of myeloid neoplasms that develop in patients with a history of prior DNA-damaging cytotoxic chemotherapy, which includes alkylating agents, Topoisomerase II inhibitor, antimetabolites, antitubulin agents and/or large field ionizing radiotherapy, for an unrelated disease [ 1 ]. It signifies a heterogenous pool of MN, encompasses myelodysplastic syndrome (t-MDS), acute myeloid leukemia (t-AML) and myelodysplastic/myeloproliferative neoplasms (t-MDS/MPN) occurring post exposure to cytotoxic or radiation therapy for an unrelated neoplastic or non-neoplastic disorder [ 2 ].

In the most recent evolution of the current World Health Organization (WHO) classification of hematologic neoplasms (2022), MN-pCTs are listed under the umbrella of the newly set apart entity of “secondary myeloid neoplasms”, replacing the former term of t-MN [ 3 ]. The International Consensus Classification system of MN (ICC) goes further by eliminating t-MN as a distinct subgroup, adopting a genetically informed pathologic diagnosis for MN and identifying therapy relatedness as a diagnostic qualifier rather than a specific disease category [ 4 ]. This significant change underscores the growing acknowledgment of the genetic role in the pathogenesis and prognostication of MNs. The pathogenesis of MN-pCT is attributed to the complex interplay among the effects of cytotoxic therapies, genetic instability (both somatic and hereditary), clonal expansion of a pre-existing malignant clone and the inflammatory microenvironment [ 5 , 6 ]. The incidence of MN- pCTs varies widely, reported as 7% to approximately 15–20% among AML and MDS/MPN patients [ 7 , 8 ]. The incidence has increased from 0.04/10,000 new cases (2001–2007) to 0.20/100,000 (2008–2014) [ 9 ], likely due to more cancer survivors, possibly as a result of enhanced diagnostics and modernized therapies. Outcomes of MN-pCT patients are universally dismal, with unsuccessful therapies, and lack of consensus on prognostic indicators. This is attributed to various patient-related factors including the tendency for MN-pCT to be diagnosed primarily in older individuals, the relapse/persistence of the original disease, cumulative toxicity from both primary and secondary therapies and increased burden of molecular mutations induced or exacerbated by cytotoxic therapies [ 1 , 10 ]. In addition to its aggressive biology with higher prevalence of complex karyotypes, TP53 mutations and treatment refractoriness to standard therapies [ 11 – 13 ]. Despite their aggressive biology, studies focusing on the prognostic predictors within this entity remain limited and lack consensus, primarily due to the heterogenous nature of the disease spectrum. Most published data have predominantly explored either MDS-pCT or AML-pCT, thus hindering comprehensive risk stratification and informed therapeutic decision-making. It is crucial to understand the risk factors and prognostic indicators associated with MN-pCT, in order to anticipate and potentially reduce their incidence in the long term. New therapies, such as CPX-351/Vyxeos, a liposomal formulation of cytarabine and daunorubicin, have demonstrated remarkable outcomes in patients with t-AML who are suitable for intensive chemotherapy [ 14 ].

This is a retrospective single-center study aiming to analyze the demographics, clinicopathologic, genetic characteristics of patients with MN-pCT and assess their association with MN- pCT (t-MN) survival, OS and median latency determinants. Literature still lacks data on therapy related myeloid neoplasms in the Middle East and North Africa (MENA) regions. Consequently, this region remains underrepresented in the international data literature regarding its prevalence, primary disease characterization, contributing cytotoxic agents, clinicopathologic profile, genetic make-up, disease outcome and prognostic predictors.

Method

Patients and data collection

The current retrospective study was carried out in our cancer hospital for patients with myeloid neoplasms who had a prior history of exposure to an alkylating agent, Topoisomerase II inhibitor, antimetabolites, radiotherapy (including brachytherapy and radioactive iodine (RAI)), without restricting eligibility based on minimum or maximum latency period before development of t-MN. The diagnosis of MN-pCT (or t-MN) was made on bone marrow (BM) according to WHO 2016 diagnostic criteria with AML defined by ≥ 20% blasts in peripheral blood and/or bone marrow and MDS and MDS/MPN with blasts < 20%. All patients were diagnosed at National centrer for cancer care and research (NCCCR), a member of Hamad Medical Corporation (HMC) in Doha, Qatar between January 2010 and December 2020. The NCCCR is the only cancer treating center in Qatar and is part of the government funded national health system. The study had an ethical approval from Hamad Medical Research Center under the protocol number # MRC-01–19-256. The informed consent is waived in this study due to retrospective nature and the study involves minimal or no risk with de-identified subjects.

Study design

The primary objective of this research study was to analyze MN-pCT characteristics in our center, identify latency duration determinants and identify the most important prognostic predictors of MN-pCT. The parameters studied include demographic data, characteristics of original disease, causative cytotoxic agents, mean & median latency period before developing MN-pCT, hematological parameters, pathological characteristics of MN (including assessment of multilineage dysplasia, BM cellularity, degree of fibrosis, blasts count, immunophenotyping (IPT) by flow cytometry &/or immunohistochemistry (IHC)) and conventional cytogenetics. These parameters were extracted and reviewed individually by the research team. In this article therapy related myeloid neoplasms (t-MN) and myeloid neoplasms post cytotoxic (MN-pCT) will be used interchangeably to convey the same meaning. MN-pCT were subclassified according to WHO 2016 compiling morphologic and genetic data. Latency period was calculated as time in months/years from the date of primary diagnosis of original cancer/disease to the date of diagnosis of MN-pCT. Patients who developed MN-pCTs post Methotrexate therapy were not excluded. P53 protein expression by IHC was performed and assessed for all patients with available BM biopsy at time of diagnosis. A cutoff of > 1% p53 strongly positive (3+)‏ cells was used to define p53-positive cells. A subset of patients in this cohort underwent next-generation sequencing (NGS)with a panel for myeloid neoplasms particularly p53 mutation.

NGS methodology

DNA and RNA underwent NGS analysis using an Oncomine Myeloid targeted amplicon panel together with the Ion Torrent semiconductor sequencing platform, the Ion S5 to analyses specific full genes ( ASXL1 , CALR , CEBPa , ETV6 , EZH2 , PHF6 , RUNX1 , TET2 , TP53 , ZRSR2) and targeted hotspot regions ( ABL1 (Exons 1–11), BRAF (Exons 1–4, 6, 8, 11, 15, 17–18), CBL , CSF3R , DNMT3A ( Exon 11–23), FLT3 (Exons 8,11,13–16,20,23–24), GATA2 (Exons 4–5), HRAS (Exons 2–3), IDH1 (Exon 4), IDH2 (Exon 4), JAK2 (Exon 12–15), KIT ( Exons 1–2, 8–11, 13, 17), KRAS (Exons 2–6), MPL (Exons 3–4, 10, 12), MYD88 (Exons 3,5), NPM1 (Exon11), NRAS (Exons2-4), PTPN11 (Exons 3,12–13), SETBP1 (Exon4) , SF3B1 ( Exons 14–21), SRSF2 (Exon1) , U2AF1 (Exons 2 , 6) , WT1 (Exons 7 , 9)) in thirty-three genes associated with myeloid neoplasia and forty three myeloid fusion driver genes ( ABL1 , ABL2 , ALK , BCL2 , BRAF , CCND1 , CREBBP , CSF1R , EGFR , ETV6 , FGFR1 , FUS , GUS2 , HMGA2 , JAK2 , KAT6A , KAT6B , KMT2A , KMT2APTD , MECOM , MLLT10 , MRTFA , MYBL1 , MYH11 , NOTCH1 , NTRK1 , NTRK2 , NTRK3 , NUP214 , NUP98 , PAX5 , PDGFRA , PDGFRB , RARA , RARB , RARG , RET , RUNX1 , TAL1 , TCF3 , TCR4 , TFE3 , ZNF384 ). Sequence alignment and variant calling was performed using the integral Ion Reporter software (version 5.18) against human genome reference hg19. Pathogenicity and clinical actionability of somatic variants were established using AMP guidance [ 15 ].

Statistical analysis

Preliminary statistical analysis was conducted to examine the distribution of the data variables using the Shapiro–Wilk test. The normally distributed data and results were reported with mean and standard deviation (SD) whereas median and interquartile range (IQR) were used for skewed data distribution. Categorical data were summarized using frequencies and percentages. Associations between two or more qualitative data variables were assessed using Pearson Chi-square (χ2) test, Fisher Exact or Yates corrected Chi-square tests as appropriate. Quantitative data and outcomes between the two independent groups were analyzed using unpaired t or Mann Whitney U tests as appropriate. MN-pCT (t-MN) survival was calculated from the date of t-MN diagnosis to date of death (uncensored) or last FU (censored). Overall survival (OS) was calculated from the date of initial diagnosis of the primary disease to date of death (uncensored) or last follow-up (FU) (censored). Median latency period is also expressed as t-MN-free survival, was calculated from the date of receiving cytotoxic therapy to date of development of MN-pCT. The cumulative probability of MN-pCT (t-MN), OS, and t-MN-free survival were estimated using the Kaplan-Meier (KM) curves method and differences between the groups were compared using a Log-Rank test. Univariate and multivariate Cox regression analysis were performed (exploratory statical analysis) conducted to assess potential risk factors and predictors associated with MN-pCT survival and OS and the results were presented using respective hazard ratios (HR) and 95% confidence intervals (CI). Cox regression was employed to evaluate time-dependent risk factors for mortality, as it accounts for varying follow-up times and provides estimates of hazard ratios for potential predictors. After identifying the covariates that were significantly associated with mortality (considering both statistical and clinical significance), they were incorporated into a multivariate Cox regression model to establish independent associations. Statistical significance was defined as a two-sided P-value < 0.05. All Statistical analyses were performed using the statistical packages SPSS version 29.0 (Armonk, NY, IBM Corp) and STATA version 16, and Epi Info 2000 (Centers for Disease Control and Prevention, Atlanta, GA).

Results

A total of 42 patients with MN-pCTs were identified, among 288 AML patients (excluding APL) with an overall incidence of (14.5%). Among MN-pCTs, 42.9% presented as AML; 35.7% classified as MDS and 21.4% as MDS/MPN. Leukocytosis was observed in 30.8% of the cohort, including 7 patients with monocytic leukaemia and 5 patients with MDS/MPN (including CMML). Conventional cytogenetic analysis was performed for 38/42 patients. Detailed clinicopathologic and genetic characteristics of MN-pCT are listed in (Table 1 ). The median latency period before development of MN-pCTs in our cohort was 57.8 months (4.8 years) +/- 2SD, mean latency of 7.2 years, ranging between1.06–37.82.82. 21 patients (51.2%) had a latency of < 5 years. Determinants of shorter latency period (< 5 years) were illustrated in (Fig. 1 ). Molecular genetics testing using next-generation sequence (NGS) was performed for 28/42 cases (66.6%). The most frequently mutated gene was TP53, detected in 8/28 cases (28.6%) cases, followed by ASXL-1 in 5/28 cases (17.8%). Other mutated genes detected with a frequency of greater than 5% include NRAS , NPM1 and FLT3 (detected in 4 cases), TET2 , EZH2 and IDH1/IDH2 (observed in three cases), SF3B1 , RUNX-1 , D NMT3 , NF-1 (noted in two cases) and U2AF1 , SRSF1 , SETBP1 , PTPN1 and STAG were detected in a single case each. P53 protein positive expression (by IHC) was detected in 11/33 (33.3%) of patients. Upon comparing the two methods (NGS and IHC) for assessing P53 expression status, we observed that the concordance accuracy between p53 IHC and TP53 NGS analysis was 95.8% (95% CI 79.8–99.3%), with a sensitivity 85.7% (48.7–97.4%), specificity 100% (81.6–100%), positive predictive value 100% (61–100%) and negative predictive value 94.4% (74.2–99.01.2.01%).

Original (primary disease) characteristics (Table 2 )

According to the type of the original disease, three groups were identified; 18 patients (42.8%) had solid cancers with breast cancer being the most represented (6 cases). 10 patients (23.8%) had prior lymphoid malignancies, and the third group of 13 patients (30.9%) had been treated for prior autoimmune disorder (AID)/immunosuppressive history. Cytotoxic agents given for the primary disease were grouped into three groups alkylating agents, Topoisomerase II inhibitor and antimetabolite agents which include Azathioprine, Gemcitabine, Cytarabine, Fludarabine and Methotrexate. A combination of two or more chemotherapeutic agents was documented in 14 (33.3%) patients. Localized (limited field) radiation monotherapy was administered in three patients.

Survival data

Treatment was deemed appropriate for 33 out of 42 cases (78.5%). The available therapeutic options ranged from standard (Intensive therapy) (Daunorubicin and Cytarabine (DA; 3 + 7) or FLAG-IDA), to less intensive therapy (hypomethylating agents with or without Venetoclax), or supportive measures (transfusion and/or cytoreductive therapy). Four of the 33 patients received bone marrow transplants (Table 1 ). CPX-351 was not available in our center at the time when the study was conducted. The median follow -up duration from diagnosis of original disease is 7.28 years (IQR 3.76–11.58). The median FU time following developments of MN-post CT is 1.03 years (IQR 0.43, 2.70). Three survival analyses were conducted (MN-Pct (t-MN) survival, OS and MN-Pct free survival, in addition to cox regression analysis and multivariate analysis. For cytogenetics correlation with survival and due to low number of cases, we have merged the results into two subgroups one with “good cytogenetics” including recurrent genetic translocation s (RT) and normal KT and the other group with “poor cytogenetics” combining those with abnormalities in chromosome 5 and 7 &/or complex KT.

Median survival post development of MN-pct (t-MN survival) (Fig. 2 )

The median survival following t-MN diagnosis was 14.16 months (1.18 years; 95% CI 0.71,1.65). Age, dyserythropoiesis, expression of MPO, CD36, P53 mutation/protein expression, and achievement of CR (post first induction) were identified as potential significant predictors of MN-pct survival ( P < 0.050). Patients with prior AID showed longer MN-pct survival compared to solid cancers and lymphoid malignancies ( P = 0.056). Patients receiving intensive therapy had significantly higher median t-MN survival than those given best supportive care or less intensive therapy ( P = 0.041).

MN-pCT (t-MN survival) survival: univariate and multivariate cox regression analysis

Univariate Cox regression ( Table 3 ) identified 5 parameters that served as potential predictors of MN-pCT survival. These parameters include age, dyserythropoiesis, positive P53 (NGS), achievement of complete remission (CR) following the initial induction treatment and expression of MPO on leukemic cells. Multivariate Cox regression analysis (Table 4 ) identified dyserythropoiesis (adjusted HR 5.19) and dysmegakaryopoiesis (adjusted HR 3.78) as the most significant independent predictors associated with decreased t-MN survival and increased mortality risk ( P < 0.05).

Median overall survival

OS calculated from the time of diagnosis of the original (primary) disease till last FU is 8.78 years, (95% CI 6.1,11.4). The most significant predictors affecting OS are demonstrated in Fig. 3 . Univariate and multivariate cox regression analysis on OS (Tables 3 and 4 B).

Multivariate Cox regression identified both a latency period of ≥ 5 years and TP53 positivity (detected by NGS or IHC) as statistically significant independent factors associated with reduced (OS) ( P < 0.05).

Median latency (t-MN free survival data) and latency determinants

The most important parameters that affected the duration of latency period before development of MN-pCT are summarized in Table 5 .

Discussion

An improved understanding of MN-Pct characteristics, prognostic markers and their optimal treatment options is important to help improve outcomes for this challenging entity. MN-pCT are typically diagnosed in older populations, with a mean age reported in the literature of 64–67 years [ 11 , 16 ]. In contrast, we noticed that our cohort shows a ten-year younger mean age at diagnosis, (53.2 years). Notably, four patients were diagnosed with MN-PCT prior to the age of 30 years (at 10, 16, 25, and 27 years). Among these, two individuals had a history of AID, whereas the other two had a prior diagnosis of lymphoid neoplasms: B-ALL and MM.

We observed that the prevalence of AID as a primary condition is notably higher than that reported in the literature (31.7%). This finding contrasts with the data concluded by Fianchi et al. [ 17 ], who reported a significantly lower prevalence of AID at 11/277 (4%). Similarly, Guerra et al. [ 18 ] showed that the primary diseases were largely dominated by solid cancers, followed by non-Hodgkin lymphomas, and did not report any cases with prior AID.

The median latency period before the development of MN-pCTs in our cohort was 57.8 months (4.8 years), which is comparable to literature data of approximately 5 years [ 19 , 20 ]. Several studies imply that the latency period following cytotoxic chemotherapy is shortest in patients who have been treated with combined chemotherapies; implying that leukemogenic effect is augmented with increased cytotoxic therapies [ 17 ].

BM fibrosis and an inflammatory BM microenvironment are well described in context of MN and are associated with poor prognosis [ 5 ]. We noticed in our cohort a high prevalence of BM fibrosis (MF 1–3), detected in 47.2% of cases. Similarly, prominent cytoplasmic and chromatin vacuolization of granulocytic and/or erythroid precursors was also appreciated as a frequent morphologic feature detected in most cases ( Fig. 4 ) . These morphologic characteristics were not highlighted before in the literature in context of MN-pCT. Whether the abnormal marrow microenvironment is the cause or effect of MN development is debatable. Malignant clones can alter the BM microenvironment to favor their expansion while inhibiting normal hematopoietic stem cells. Conversely, recent literature has proposed that an aberrant BM microenvironment can also contribute to the development of MN [ 21 , 22 ]. In this study, megakaryoblastic differentiation (demarcated by CD41-expression) was frequently detected in 4 cases (16.7%) cases, three of which have complex KT and TP53 mutation&/or protein expression and found to confer poor prognosis and shorter OS. Mutations of TP53 are significantly enriched (33%- 50%) of MN-pCT cases compared to 5–20% in de novo myeloid neoplasms [ 13 ]. A comprehensive analysis of TP53 mutation within MN-pCT [ 16 , 23 ] has recently provided evidence of the poor outcome of TP53-mutated t-MN regardless of the blast or VAF percentage and emphasizing that TP53 VAF of 10% is a reliable threshold to stratify patients with poor survival. TP53 gene is the most frequently mutated gene in our cohort, detected in 28.6% of tested cases. Only the group of patients with strong p53 positivity ( 3+ ) was well correlated with P53 somatic mutation detected by NGS and strongly associated with a complex karyotype and poor survival.

MN-post local field radiation monotherapy (without chemotherapy)

While the WHO classifications clearly recognize large field radiotherapy as a causative agent for MN-pCT, rather than local field radiotherapy. We have shown some evidence that even with a local field radiotherapy, a significant portion of the active BM can receive a significant dose of radiation, potentially sufficient to induce myeloid neoplasms or cause remarkable myelosuppression [ 24 ]. In our cohort, three patients (4.7%) developed MN-pCT after exposure to local field radiation monotherapy within a short latency period of less than 2 years (15.8–21.5 months).

The first case is a 53-year-old male with a vocal cord tumor who developed APL with PML::RARA and myelofibrosis 15.8 months after local radiotherapy. The second patient is a 63-year-old female with endometrial cancer, who received a 21 Gy dose of brachytherapy and subsequently developed MDS with complex KT and a TP53 mutation 22 months later and the third case is a 32-year-old female who developed MN-pCT with CBFB::MYH11 and NRAS mutation, 18 months after radioactive iodine (RAI) therapy for thyroid cancer. Patel et al. [ 5 ] reported a similar occurrence of MN-pCT with PML::RARA after radiation monotherapy in four patients (3.5% of their cohort). RAI therapy for thyroid cancer and radiotherapy for prostate and uterine cancers are associated with a three- to fivefold increased risk of t-MN [ 5 , 25 ] and CML [ 26 ].

Latency determinants

The current hematologic neoplasms classification systems do not specify a particular latency period for categorizing a case as MN-pCT, with literature reporting a wide range of latency periods, from very short (< 1 year) to extended (>10 years) [ 27 ]. It is unclear if these MN-pCT with unusual latencies are phenotypically and genetically similar to the remaining t-MNs. The mean latency in our cohort of 7.2 years, is comparable to published data of 8.5 years [ 27 ] and the longest latency observed was approximately 302 months (~ 25 years). In our cohort, the most significant determinants associated with shorter latency period (< 5 years), were prior exposure to alkylating agents and positivity for TP53 (either by IHC &/or NGS). In contrast, patients with primary AID demonstrated a longer latency period compared to those with prior solid tumors or lymphoid neoplasms, with a near significant p-value (0.056). Additionally, female gender was associated with a longer latency period, although this difference was statistically insignificant (Fig. 1 and Table 5 ).

In contrast to recently published data [ 27 ], our cohort of MN-pCT is notably enriched with recurrent genetic abnormalities (23.7%) which are not limited to cases with prior exposure to Topoisomerase II inhibitors. In line with Smith et al. [ 28 ], we found that MN-pCT presenting as AML is more likely to have balanced chromosomal rearrangements (i.e., translocations, inversions) compared with patients with MDS. Despite receiving comparable therapies, the OS for CBF t-AML was shorter than that of its primary counterpart (69 versus. 190 months; P = 0.038; [ 29 ].

Prognostic indicators

The outcome of MN-pCT patients is universally dismal with survival in our cohort at approximately 14 months, aligning with literature reports of 10–14 months [ 12 , 17 , 30 , 31 ]. In a large study performed by Fianchi et al. [ 17 ], it was demonstrated that age, degree of anemia, and unfavorable KT, had a significant impact on survival. Another study performed by Kuendgen et al. [ 32 ] on MDS-pCT, cytogenetics was identified as significant predictors of survival. Several studies performed on AML-pCT, have revealed various prognostic indicators, including advanced age, unfavorable cytogenetics, and thrombocytopenia [ 33 ]. Our results showed that younger patients (≤ 50 years) exhibited significantly longer t-MN survival. This observation may, in part, be explained by the greater proportion of individuals in this age group who received intensive chemotherapy. Specifically, among the 18 cases aged 50 years or younger, approximately half (9 patients) underwent intensive therapy, whereas only four patients above 50 years received comparable treatment. Furthermore, the analysis identified dyserythropoiesis, TP53 mutation, MPO downregulation, and failure to achieve CR post first induction as adverse prognostic factors. Multivariate Cox regression analysis identified dyserythropoiesis and dysmegakaryopoiesis as the most significant independent predictors of inferior t-MN survival. Although age >50 years and TP53 positivity (by NGS or IHC) were also linked to lower t-MN survival, these associations were statistically insignificant ( P >0.05).

Our results are consistent with previous reports, in which age over 50 years has been recognized as a significant predictor of poor survival in t-MN multivariate analyses [ 34 , 35 ]. In an analysis from a study on MDS-pCT [ 36 ], seven factors, age, ECOG performance status, cytogenetics, WHO MDS subtype, hemoglobin level, platelet count, and transfusion dependence, were identified as independent predictors of survival. In the current study, we also analyzed (OS) from the time of primary disease diagnosis, assessing the impact of patient-related factors such as age, and pathologic/genetic factors associated with the primary neoplasm influence the outcomes in t-MN and contribute to their aggressive clinical behaviour. Interestingly, we found that short latency period (< 5 years), prior exposure to alkylating agents &/or combined chemotherapy and P53 mutation/expression were strong predictors of inferior OS (Fig. 3 ). It is important to highlight that P53 mutation by NGS was a common parameter identified by the multivariate analysis that adversely impacted both MN-Pct survival and OS. One of the interesting observations is the association between TP53 mutation/protein expression and shorter latency period and consequently shorter OS. This finding may warrant screening for TP53 mutation particularly in tumors with higher risk of developing MN-pCT, such as breast cancer and lymphoid neoplasms. Such screening could aid in the detection of TP53 clonal hematopoiesis of indeterminate potential (CHIP) and allow for more tailored chemotherapeutic strategies aimed at reducing the risk of developing MN-pCT.

Limitations, strengths and conclusion

This study has several limitations that warrant consideration: its retrospective design may introduce potential selection bias, and the relatively small sample size (42 patients), combined with the single-center approach, could affect the external validity of our findings. The study is further constrained by missing the full molecular data results; with information accessible for only 28 out of 42 cases (66.6%). A comprehensive analysis of molecular mutations beyond TP53 will be presented in a separate publication. Despite its limitations, this study is especially valuable as it originates from the only major cancer centre in a country with a relatively small population, characterized by predominantly young demographics. To the best of our knowledge, the current study provides the first and most comprehensive 10-year dataset on therapy-related myeloid neoplasms in the MENA region. In addition, exploring original disease characteristics prior to MN-pCT and its influence on (OS) has not yet been studied. We believe that our results shed light on additional factors that can significantly impact the course of MN-pCT, particularly in relation to the classification of the original disease, prior therapies and patient-related factors. This research provides valuable insights for advancing our understanding of the risk factors and behavior of these aggressive neoplasms within this understudied ethnic population, predominantly composed of Asian and Arab individuals, paving the way for future investigations and enhances the potential for improved clinical management. Our results also underscore the existence of additional adverse prognostic factors within MN-pCT, extending beyond the genetic influences and emphasizing the necessity of keeping MN-pCT as a distinct entity in the future classification systems. We believe this distinction is crucial for further characterization and acknowledgment of MN-pCT as a more complex group, which should be set apart from de novo counterparts that share similar morphologic and/or genomic profile.

Acknowledgements

We would like to acknowledge the great contribution of clinical hematology team and technical staff in hematology, histopathology & flow cytometry laboratories for their hard work and continuous support. We would also like to acknowledge the crucial role and the great contribution of cytogenetics and molecular genetics laboratory staff.

Abbreviations

Myeloid neoplasms-Post cytotoxic

Therapy related myeloid neoplasms

World Health Organization

International Consensus Classification system of MN

myelodysplastic syndrome

acute myeloid leukemia

myelodysplastic/myeloproliferative neoplasms

Overall survival

bone marrow

complete remission

Author contributions

Authorship Contributions: Everyone listed as an author has agreed to authorshipD.S, S.F and H.O conducted the study design, D.S and S.F conducted the methodologyD.S, S.F, S.A and S. E participated in data acquisition, P.C performed the statistical analysis, D.S drafted the manuscript, E.A, A.A, M.Y and FI revised the manuscript for intellectual content.All authors have read and agreed to the published version of the manuscript.

Funding

The study was supported by a grant for research from Hamad Medical Corporation - Medical Research Center (MRC) - for the research protocol number # MRC-01-19-256.

Data availability

The datasets used and/or analyzed during the current study are available from the first and corresponding author, based on reasonable requests.

Declarations

Ethics

The study had an ethical approval from Hamad Medical Research Center under the protocol number # MRC-01-19-256.

Consent for publication

The informed consent is waived in this study due to retrospective nature and the study involves minimal or no risk with de-identified subjects and the analysis utilized only publicly accessible data.

Competing interests

The authors declare no competing interests.

Footnotes

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

References

1. Granfeldt Østgård LS, Medeiros BC, Sengeløv H, Nørgaard M, Andersen MK, Dufva IH et al (2015) Epidemiology and clinical signifcance of secondary and therapy-related acute myeloid leukemia: a national population-based cohort study. J Clin Oncol 33(31):3641–3649

2. Arber DA, Orazi A, Hasserjian R, Thiele J, Borowitz MJ, Le Beau MM et al (2016) The 2016 revision to the World Health Organization classification of myeloid neoplasms and acute leukemia. Blood 127(20):2391–2405

3. Khoury JD, Solary E, Abla O, et al (2022) The 5th edition of the world health organization classification of haematolymphoid tumours: myeloid and histiocytic/dendritic neoplasms. Leukemia 36:1703–1719

4. Arber DA, Orazi A, Hasserjian RP, Borowitz MJ, Calvo KR, Kvasnicka HM et al (2022) International consensus classification of myeloid neoplasms and acute leukemias: integrating morphologic, clinical, and genomic data. Blood 140:1200–1228

5. Patel AA, Rojek AE, Drazer MW, Weiner H, Godley LA, Le Beau MM et al (2021) Therapy-related myeloid neoplasms in 109 patients after radiation monotherapy. Blood Adv 5:4140–4148

6. Travaglini S, Marinoni M, Visconte V, Guarnera L (2024) Therapy-related myeloid neoplasm: biology and mechanistic aspects of malignant progression. Biomedicines 12(5):1054. 10.3390/biomedicines12051054

7. Hulegardh E, Nilsson C, Lazarevic V, Garelius H, Antunovic P, Rangert Derolf A et al (2015) Characterization and prognostic features of secondary acute myeloid leukemia in a population-based setting: a report from the Swedish acute leukemia registry. Am J Hematol 90(3):208–214

8. Abou Zahr A, Kavi AM, Mukherjee S (2017) Therapy-related myelodysplastic syndromes, or are they? Blood Rev 31(3):119–128. 10.1016/j.blre.2016.11.002

9. Morton LM, Dores GM, Schonfeld SJ, Linet MS, Sigel BS, Lam CJK et al (2019) Association of chemotherapy for solid tumors with development of therapy-related myelodysplastic syndrome or acute myeloid leukemia in the modern era. JAMA Oncol 5:318–325

10. Ganser A, Heuser M (2017) Therapy-related myeloid neoplasms. Curr Opin Hematol 24:152–158

11. Mcnerney ME, Godley LA, Le Beau MM (2017) Therapy-related myeloid neoplasms: when genetics and environment collide. Nat Rev Cancer 17(9):513–527

12. Kayser S, Döhner K, Krauter J, Köhne CH, Horst HA, Held G et al (2011) The impact of therapy-related acute myeloid leukemia (AML) on outcome in 2853 adult patients with newly diagnosed AML. Blood 117:2137–2145

13. Wong TN, Ramsingh G, Young AL, Miller CA, Touma W, Welch JS et al (2015) Role of TP53 mutations in the origin and evolution of therapy-related acute myeloid leukaemia. Nature 518:552–555

14. Sallman DA, DeZern AE, Garcia-Manero G et al (2021) Eprenetapopt (APR-246) and azacitidine in TP53-mutant myelodysplastic syndromes. J Clin Oncol 39:1584–1594

15. Li MM, Datto M, Duncavage EJ, Kulkarni S, Lindeman NI, Roy S, Tsimberidou AM, Vnencak-Jones CL et al (2017) Standards and guidelines for the interpretation and reporting of sequence variants in cancer: A joint consensus recommendation of the association for molecular Pathology, American society of clinical Oncology, and college of American pathologists. J Mol Diagn 19(1):4–23

16. Hiwase D, Hahn C, Tran ENH, Chhetri R, Baranwal A, Al-Kali A et al (2023) TP53 mutation in therapy-related myeloid neoplasm defines a distinct molecular subtype. Blood 141(9):1087–1091. 10.1182/blood.2022018236

17. Fianchi L, Pagano L, Piciocchi A et al (2015) Characteristics and outcome of therapy-related myeloid neoplasms: report from the Italian network on secondary leukemias. Am J Hematol 90(5):E80–E85

18. Guerra VA, Yuanqing Y, Hsu J, Wang F, Alfayez M, Morita K et al (2019) Comprehensive analysis of genotype and prior exposures in therapy-related myeloid neoplasms (t-MNs). Blood 134(Suppl 1):458

19. Ha H, Kim HJ, Park JH (2022) Epidemiologic outlook of therapy-related myeloid neoplasms and selection of high-risk patients: a Korean nationwide study. Cancer 128(21):3888–3896

20. Maung SW, Burke C, Hayde J et al (2017) A review of therapy-related myelodysplastic syndromes and acute myeloid leukaemia (t-MDS/AML) in Irish patients: a single centre experience. Hematology 22(6):341–346

21. Medyouf H, Mossner M, Jann J-C, Nolte F, Raffel S, Herrmann C et al (2014) Myelodysplastic cells in patients reprogram mesenchymal stromal cells to establish a transplantable stem cell niche disease unit. Cell Stem Cell 14:824–837

22. Raaijmakers MHG, Mukherjee S, Guo S, Zhang S, Kobayashi T, Schoonmaker JA et al (2010) Bone progenitor dysfunction induces myelodysplasia and secondary leukaemia. Nature 464:852–857

23. Shah MV, Tran ENH, Shah S, Chhetri R, Baranwal A, Ladon D, Shultz C et al (2023) TP53 mutation variant allele frequency of ≥ 10% is associated with poor prognosis in therapy-related myeloid neoplasms. Blood Cancer J 13(1):51

24. Soliman DS, Al-Sabbagh A, Ibrahim F, El-Omri H, Yassin M et al (2019) Local field radiotherapy induced therapy related myeloid neoplasms and bone marrow suppression. Blood 134(Supplement1):5113

25. Teepen JC, Curtis RE, Dores GM, Berrington de Gonzalez A, van den Heuvel-Eibrink MM, Kremer LCM et al (2018) Risk of subsequent myeloid neoplasms after radiotherapy treatment for a solid cancer among adults in the United States, 2000–2014. Leukemia 32:2580–2589

26. Molenaar RJ, Sidana S, Radivoyevitch T et al (2018) Risk of hematologic malignancies after radioiodine treatment of well-differentiated thyroid cancer. J Clin Oncol 36(18):1831–1839

27. Liu YC, Illar GM, Al Amri R, Canady BC, Rea B, Yatsenko SA et al (2022) Therapy-related myeloid neoplasms with different latencies: a detailed clinicopathologic analysis. Mod Pathol 35(5):625–631

28. Smith SM, Le Beau MM, Huo D, Karrison T, Sobecks RM, Anastasi J et al (2003) Clinical-cytogenetic associations in 306 patients with therapy-related myelodysplasia and myeloid leukemia: the university of Chicago series. Blood 102(1):43–52

29. Rogers HJ, Wang X, Xie Y, Davis AR, Thakral B, Wang SA et al (2020) Comparison of therapy-related and de novo core binding factor acute myeloid leukemia: a bone marrow pathology group study. Am J Hematol 95:799–808

30. Samra B, Richard-Carpentier G, Kadia TM, Ravandi F, Daver N, DiNardo CD et al (2020) Characteristics and outcomes of patients with therapy-related acute myeloid leukemia with normal karyotype. Blood Cancer J 10(5):47

31. Chantadisai M, Kulkarni HR, Baum RP (2021) Therapy-related myeloid neoplasm after peptide receptor radionuclide therapy (PRRT) in 1631 patients from our 20 years of experiences: prognostic parameters and overall survival. Eur J Nucl Med Mol Imaging 48(5):1390–1398

32. Kuendgen A, Nomdedeu M, Tuechler H et al (2021) Therapyrelated myelodysplastic syndromes deserve specifc diagnostic Sub-classification and risk-stratification-an approach to classification of patients with MDS-pCT. Leukemia 35(3):835–849

33. Strickland SA, Vey N (2022) Diagnosis and treatment of therapy-related acute myeloid leukemia. Crit Rev Oncol Hematol 171:103607

34. Khalife-Hachem S, Saleh K, Pasquier F, Willekens C, Tarabay A et al (2021) Molecular landscape of therapy-related myeloid neoplasms in patients previously treated for gynecologic and breast cancers. Hemasphere 5(9):e632. 10.1097/HS9.0000000000000632

35. Kida M, Usuki K, Uchida N, Fukuda T, Katayama Y, Kondo T et al (2020) Outcome and risk factors for therapy-related myeloid neoplasms treated with allogeneic stem cell transplantation in Japan. Biol Blood Marrow Transplant 26(8):1543–1551. 10.1016/j.bbmt.2020.04.004

36. Quintás-Cardama A, Daver N, Kim H, Dinardo C, Jabbour E, Kadia T, Borthakur G et al (2014) A prognostic model of therapy-related myelodysplastic syndrome for predicting survival and transformation to acute myeloid leukemia. Clin Lymphoma Myeloma Leuk 14(5):401–410

Associated Data

Data Availability Statement

The datasets used and/or analyzed during the current study are available from the first and corresponding author, based on reasonable requests.