Bejar, Rafael

Abstract Myelodysplastic syndromes (MDS) are clinically and biologically diverse disorders, emphasizing the need for personalized treatment approaches. The International Working Group for Prognostication of MDS (IWG_PM) recently introduced a molecular classification, referred to as the MDS taxonomy, that categorizes patients into 16 subgroups based on 21 gene mutations, 6 cytogenetic abnormalities, and loss of heterozygosity (LOH) at TP53 and TET2 loci. This study sought to validate and enhance the clinical relevance of the MDS taxonomy by analyzing a large retrospective cohort ( n = 5136) and transcriptomic data from a prospective cohort ( n = 477). The taxonomy successfully identified subgroups with distinct clinical characteristics and disease progression patterns. However, incorporating gene interactions from taxonomy subgroups did not improve the prognostic performance of the Molecular International Prognostic Scoring System (IPSS‐M). We further assessed whether the taxonomy could guide management in patients receiving disease‐modifying therapies. Except for the “ TP53 ‐complex” subgroup, taxonomy classifications were not predictive of hypomethylating agent response or transplant outcomes. Nonetheless, they correlated with overall survival, suggesting that while both IPSS‐M and the taxonomy capture disease biology, other non‐genetic factors may influence treatment response. RNA sequencing confirmed the biological distinctiveness of the taxonomy groups. Transcriptomic profiling of CD34+ bone marrow cells revealed unique, homogeneous gene expression patterns, particularly within the AML‐like, bi TET2 , SF3B1 , and TP53 ‐complex subgroups. Further integration of multi‐omics data may refine MDS classification, improving clinical decision‐making and guiding the development of targeted therapies.

ABSTRACT The epidemiology of myelodysplastic syndromes/neoplasms (MDS) is challenging to define due to inconsistent reporting, complex diagnostic procedures, and evolving diagnostic criteria. Using the National MDS Natural History Study—a prospective cohort with centrally adjudicated histopathology and genetic variant review—we characterized the landscape of MDS across the United States and identified differences across demographics. Among 2115 participants, 64% (1346) had an MDS spectrum condition, including MDS (24%), MDS/myeloproliferative neoplasm (5%) and precursor conditions—clonal cytopenia of undetermined significance (22%) and idiopathic cytopenia/dysplasia of undetermined significance (13%). The median age was 74 years, and participants were predominantly male (66%), White (91%), and Non‐Hispanic (92%). Myeloid‐associated variants were detected in 68% of participants, most commonly in TET2, DNMT3A, ASXL1, SF3B1, and SRSF2 . Black, compared to White, participants were younger at diagnosis (69 vs. 74 years, p = 0.01), had equal or increased prevalence of higher‐risk MDS, lower hemoglobin, and higher peripheral blood blasts, yet were less likely to receive MDS‐directed therapy (14% vs. 42%, p = 0.008). Black and Hispanic participants had fewer detectable gene mutations than White participants. Females had lower variant allele frequencies and fewer RNA splicing gene mutations than males. After multivariable adjustment, TP53 mutations, MDS diagnosis, and higher‐risk disease were associated with worse progression‐free and overall survival; age was also associated with overall survival. Black race trended toward improved progression‐free survival. These findings highlight the need for enhanced understanding of MDS pathogenesis across patient groups and refined prognostic tools to improve personalized management of MDS spectrum conditions. Trial Registration: ClinicalTrials.gov identifier: NCT02775383

PURPOSE Chronic myelomonocytic leukemia (CMML) is a rare myeloid neoplasm characterized by clinical heterogeneity and is associated with poor outcomes. To date, limited molecular information has been incorporated into disease classification and risk stratification. We aimed to integrate genomic features into the clinical decision-making process for CMML. PATIENTS AND METHODS We analyzed a retrospective cohort of 3013 patients with CMML (training set) and a prospective population of 516 patients (validation set). Using an innovative framework for multimodal data analysis, we developed molecular-based disease taxonomy and prognostication. RESULTS Unsupervised clustering identified nine entities with distinct genomic features and outcomes ( P < .001), including splicing machinery, transcription factors, signal transduction and tyrosine kinase pathways aberrations, and high-risk molecular signatures. Notably, 15% of patients showed molecular/clinical overlap with other myeloid neoplasms. We integrated molecular and clinical information to build the international CMML Prognostic Scoring System (iCPSS), incorporating mutations in nine genes together with hematologic parameters and cytogenetic abnormalities. The iCPSS identified five groups with distinct probability of overall and leukemia-free survival in both training and validation cohorts ( P < .001), outperforming existing prognostic models. Importantly, 55% of patients were reassigned to higher or lower risk groups by the iCPSS. Decision analysis demonstrated that iCPSS could refine the optimal timing of allogeneic transplantation at the individual level; compared with conventional prognostic tools, iCPSS-based decision modeling changed transplantation strategy in 31% of cases, resulting in a significant gain-in-life expectancy for eligible patient population ( P < .001). A federated learning platform was implemented to enable continuous, privacy-preserving model update across multiple centers. CONCLUSION Molecular information improves CMML classification and prognostication, supports more effective clinical decision making, and potentially refines the design of clinical trials.

Abstract Patients at risk for progression from myeloid precursor states (idiopathic cytopenia of undetermined significance [ICUS] and clonal cytopenia of undetermined significance [CCUS]) to myelodysplastic syndrome (MDS) are not well defined. Epidemiologic risk factors, clonal changes for MDS development, and evolution from one MDS state to another were available in the MDS Natural History Study (NHS), a prospective cohort enrolled at diverse US sites. Extensive clinical data and biospecimens were collected at baseline and follow-up. A total of 1177 (56%) individuals with MDS or MDS-related precursor conditions (ICUS/idiopathic dysplasia of undetermined significance [IDUS], CCUS, and MDS/myeloproliferative neoplasm overlap) were enrolled and diagnosed in the MDS NHS. The median age was 74 years, with 89% aged ≥60 years, and most were male patients. Median follow-up time was 1.6 years and was similar among ICUS/IDUS, CCUS, and MDS. During follow-up period, 68% of participants terminated the study, 35% died, and 38% had disease progression. Using a refined clinical definition of progression, the greatest proportion of progression was observed among higher-risk-MDS (116 [73%]), followed by lower-risk-MDS (170 [52%]); fewer progression events were observed among participants with CCUS (65 [22%]) and ICUS/IDUS (46 [17%]). Predictors of progression are delineated, including female sex, higher quantity of mutations, the presence of TP53 mutation, and poor/very poor cytogenetic score. Based on these prospective data, guidelines for clinical management including monitoring and surveillance are outlined. The MDS NHS provides real-world data to illustrate how clinical and genotypic differences inform the classification, disease course, and approach to therapy, with informed monitoring guidelines for patients. This trial was registered at www.ClinicalTrials.gov as NCT02775383.

Abstract Introduction: Standardized reporting of clinical trials results for MDS is essential to improve clinical interpretation and cross-study comparison. However, reporting of patient characteristics, response criteria, and endpoints in publications is often inconsistent; there is no systemic analysis of MDS trial reporting available. We conducted a systematic review of published MDS trial manuscripts on behalf of the international consortium for MDS (icMDS) to assess variability in reporting practices. Methods We searched ClinicalTrials.gov to identify all clinical trials registered for adults (≥18 years) with MDS that reported results between 2015-2024. Clinical trials that included acute myeloid leukemia (AML) or MDS/myeloproliferative neoplasms (MPN) were included if they enrolled ≥5 MDS patients. We excluded trials without an MDS cohort; non-therapeutic trials; trials focused on transplant interventions; or those which enrolled solid malignancies or other hematologic malignancies (chronic myeloid leukemia or lymphoid diseases). Finally, trials were required to have a manuscript available on Larvol, PubMed, or Google Scholar. Trials were categorized by disease risk (lower-risk [LR] vs. higher-risk [HR]) and trial phase (early phase [EP] vs. late phase [LP]). Results We identified 502 MDS trials on ClinicalTrials.gov, of which 351 did not meet inclusion criteria and 79 lacked a manuscript. A total of 72 trials (32 EP, 40 LP) with 80 publications (34 EP, 46 LP) were analyzed. Frequently reported baseline characteristics included age (100% EP, 100% LP), disease risk (74% EP, 74% LP), Eastern Cooperative Oncology Group performance status (85% EP, 72% LP), prior treatments (71% EP, 67% LP), and RBC transfusion dependency (32% EP, 70% LP). Less frequently reported characteristics included blood counts (hemoglobin [Hb; 38% EP, 54% LP], platelet count [38% EP, 54% LP], neutrophil count [24% EP and LP]) and bone marrow blasts (29% EP, 43% LP). Although disease risk was widely reported, definitions varied: IPSS and IPSS-R were each reported in 54% of manuscripts, while IPSS-M appeared in only 3%. Cytogenetic risk was separately reported in 39% of manuscripts (38% EP, 39% LP), and mutational data in 45% (47% EP, 43% LP). Responses per IWG 2006 criteria were reported in 84% of manuscripts. The primary endpoint involved safety/tolerability in 85% of EP manuscripts, though definitions were variable; recommended phase 2 dose was the most common (26% of EP manuscripts). In LP trials, primary endpoints were risk-specific: transfusion independence (TI) in 77% of LR, overall response rate (ORR) in 28% of HR, and complete remission (CR) or overall survival (OS) in 22% of HR. In HR manuscripts, CR was reported in 100%, ORR in 73%, hematologic improvement (HI) in 48%, RBC-TI in 23%, and OS in 80%. However, seven different definitions were used for ORR: CR + marrow CR + partial remission + HI per IWG 2006 was most common (35%). Event-free survival was reported in 25%; progression-free survival and relapse-free survival in 13%; and leukemia-free survival in 5%. Early mortality rate was reported in 35% (18% EP, 56% LP) and transplant rate in 58% (50% EP, 67% LP). Only 47% of HR and 90% of LR manuscripts identified HI-eligible patients. In LR-MDS, RBC-TI was reported in 72% of manuscripts but used six definitions. The most common were RBC-TI ≥8 weeks at any time during treatment (24%), ≥8 weeks within 28 weeks of treatment (13%), ≥8 weeks with Hb increase ≥1.0 (4%), ≥12 weeks with Hb increase ≥1.5 (4%), and ≥16 weeks within 24 weeks of treatment (12%). The remainder did not report RBC-TI, did not define it, or used a custom definition not used in another trial. HI was reported in 80% of LR papers with most of those reporting HI using IWG 2006 criteria (90%). Conclusion Reporting of baseline characteristics, response criteria, and outcomes is inconsistent in MDS clinical trials, with wide variability in response definitions, including ORR and TI. This heterogeneity limits interpretability, hampers historical comparisons and may obscure efficacy signals. Our findings highlight the need for standardized reporting guidelines to ensure clarity and consistency in MDS trial publications. As a next phase of this effort, we will conduct a formal Delphi process among icMDS experts to establish consensus recommendations for minimal and optimal MDS clinical trial reporting in manuscripts by disease risk (LR/HR) and trial phase (EP/LP).

Abstract Background Myelodysplastic syndromes (MDS) develop from the acquisition of somatic mutations over years or decades. While some mutations are random stochastic events, others derive from extrinsic agents that promote genomic instability, including environmental exposures. Agent Orange (AO) is a phenoxy herbicide used by the U.S. military as a defoliant during the Vietnam War (1962-71), often diluted with gasoline to promote aerosolization, contaminated with the carcinogen dioxin during the manufacturing process, and linked to various cancers. We studied AO as a risk factor for MDS. Methods The prospective National Heart, Lung, and Blood Institute National MDS Natural History Study includes patients (pts) with suspected or recently diagnosed MDS enrolled from 6/2016-6/2024. Bone marrow samples underwent central pathology review, resulting in diagnoses including MDS, MDS/myeloproliferative neoplasm overlap (MDS/MPN), or clonal cytopenia of undetermined significance (CCUS). Pts completed detailed assessment for AO exposure and other risk factors for MDS development. Associations between AO exposure, mutation prevalence, and key covariates (demographics, diagnosis, military service, clinical history, cytogenetics and smoking) were assessed using univariate tests of association, multivariable regression and Cox regression models for survival and progression. Results Among 2115 enrolled pts, 1191 (56%) had a myeloid malignancy or precursor condition and 130 (6.1%) reported AO exposure, the majority (96%) male. Compared to unexposed pts, AO exposed pts were more likely to derive from the 1945-54 birth cohort (p&lt;.001), of age to serve in Vietnam, and to have an ultimate diagnosis of MDS or CCUS vs. a non-clonal diagnosis (57% vs. 44%, p=.046). AO exposure was more common among Blacks (12% vs 6%, p=.02), specifically Black males (21% vs 9%, p=.006). AO exposure was marginally associated with International Prognostic Scoring System (IPSS)-R poor-risk cytogenetics (p=.066) and lower baseline platelet count (p=.072). In multiple regression analyses, risk of AO exposure was significantly higher for the 1945-1954 birth cohort (OR [95% CI]=10.3 [4.4-30.6], p&lt;.001), among those with military service (OR=24.1 [11.9-55.8], p&lt;.0001), and for Blacks vs Whites (OR=2.6 [1.2-5.5], p=.017). The crude risk of AO exposure trended higher for patients with MDS compared to idiopathic cytopenia of undetermined significance (ICUS; OR=2.1 [0.9-6.0],p=.13), but not in multivariable analysis (OR=1.3 [0.5-4.4, p=.60]). AO exposure trended toward an association with younger age at MDS diagnosis (p=.06) and toward having a prior primary malignancy (49% vs. 41%, p=.09): Compared to non-AO exposed pts, AO exposed pts had higher rates of prior prostate cancer (16% vs. 8%), notable given its documented association with AO exposure. AO exposure was not associated with a history of or intensity of cigarette smoking (p=.67). After accounting for age, diagnosis, sex, and military service, AO exposure was significantly associated with increased numbers of pathogenic variants in 53 genes (OR=1.2 [1.0-1.4], p=.02) and with having Very Poor/Poor risk IPSS-R cytogenetics (OR=3.7 [1.2-11.1], p=.02). AO exposed and non-exposed pts had similar overall survival (HR=1.1 [0.8-1.7], p=.50), but those exposed to AO had a higher risk of disease progression in the first two years following diagnosis (HR =1.9 [1.2-2.8], p=.004). AO exposed pts appeared more likely to have del (5q) (15% vs. 8%) and del (20q) (13% vs. 5%) karyotypic abnormalities, and TP53 (7.7% vs. 4.5%), STAG2 (5.1% vs. 2.8%), and NRAS mutations (3.4% vs. 1.7%), although sample sizes were small. Focusing on gene pathways, AO exposed pts appeared more likely to have abnormalities in RAS signaling (10.3% vs. 5.7%), cell cycle (7.7% vs. 4.5%), and cohesion complex pathways (6.0% vs. 3.1%), but less likely to have abnormalities in cytokine receptor pathways (0% vs. 4.5%). ConclusionsIn our representative national cohort of pts with at least one cytopenia, and for the first time, we demonstrated that AO exposure is associated with younger age at MDS diagnosis, ultimate MDS diagnosis, genetic complexity of MDS, increased risk of disease progression, and with Black race, despite Black individuals comprising just 16% of men who served in the Vietnam War and being less likely to have MDS than white individuals. AO should formally be recognized as a risk factor for the development of MDS.

Background. Study of myeloid neoplasms (MN) has been rapidly transformed by genome characterization. Gene mutations have been reported to influence disease phenotype and risk of disease progression, and the evaluation of mutational status can provide valuable insights to improve the decision-making process. In this international study, we evaluated the clinical impact of mutational screening in patients with CMML, which is characterized by significant clinical and genomic heterogeneity, including a substantial proportion of patients with poor outcomes and unmet needs. Currently, only limited molecular information has been incorporated into CMML classification and prognostication. Methods. We retrospectively collected 3182 CMML patients. We used MOSAIC, an AI-based framework for multimodal analysis in rare cancers (PMID: 38875514) to develop innovative, molecular-based tools for classification and prognostication. An independent validation of the results on 516 prospectively collected patients was performed. Results. Bayesian Networs and Hierarchical Dirichlet Processes were used to identify genomic associations and define a CMML molecular classification. We identified 11 clusters with distinct clinical and genomic features, including splicing machinery, signal transduction and tyrosine kinase pathways aberrations, and high-risk molecular signatures (i.e., AML-like and TP53 mutations). Up to 15% of patients showed clear genomic overlap with other MN. Importantly, extensive multi-color flow cytometry on T lymphocytes, NK and myeloid cells (BD FACSymphony A5 Cell Analyzer) revealed specific immunologic and inflammation signatures associated with molecular subgroups. We then integrated molecular and clinical information to build an international CMML Prognostic Scoring System (iCPSS). We assessed the performance of different statistical and AI-based methods; L1-penalized Cox Model resulted as the best performing method. Selected features included hematological parameters (WBC, Hb, PLT and marrow blasts), cytogenetic abnormalities, and mutations in 10 genes (ASXL1, DNMT3A, EZH2, NRAS, RUNX1, SETBP1, STAG2, TET2, TP53, U2AF1). By Bayesian thresholds optimization, we identified 5 risk classes (i.e., very-low, low, intermediate, high and very-high) with median overall survival (OS) ranging from 99 to 9 months (P&lt;.001), and median leukemia-free survival (LFS) ranging from 210 to 18 months (P&lt;.001). iCPSS provided better patient discrimination across all clinical endpoints compared to currently available prognostic tools, with a Concordance Index (CI) for OS of 0.75 versus 0.62-0.64, respectively. Notably, compared to available scoring systems, up to 40% of patients were reassigned to higher or lower risk classes by the iCPSS. External validation on an independent prospective cohort confirmed that the performance of iCPSS is superior to existing prognostic models (CI for OS 0.71 vs 0.54-0.61, respectively) To demonstrate the clinical utility of iCPSS, we focused on 753 patients who underwent allogeneic stem cell transplantation (HSCT). In multivariable analysis, iCPSS stratified the probability of OS post-HSCT (P&lt;.001) and identified groups of patients with different probabilities of disease relapse, ranging from 9% to 62% (P&lt;.001). We employed a clinical- and genomic-based decision support system (PMID: 38723212) to determine the optimal timing of HSCT. Preliminary analyses indicated that higher-risk patients according to iCPSS (i.e., intermediate, high, and very high) benefit from an immediate HSCT strategy. Lower-risk patients (i.e., very low and low) had life expectancy maximized with delayed HSCT. Modeling decision analysis using iCPSS compared to conventional scores, resulted in a change in transplantation policy for a significant proportion of patients (up to 25%). Conclusion. Molecular information significantly improves the classification of CMML patients, providing a basis for refining diagnostic boundaries with other MN and for a more rational inclusion of patients in clinical trials. The iCPSS demonstrated superior performance over currently available scoring systems and improved HSCT decision making process.

Introduction Knowledge of epidemiologic risk factors, clonal changes associated with MDS development from precursor states, and evolution from one MDS state to another (lower- (LR) or higher-risk (HR) disease or leukemia (AML)) are largely limited to retrospective studies, which may not reflect the true MDS spectrum. The MDS NHS is an established prospective cohort of patients (pts) with suspected MDS enrolled at diverse US sites. Extensive clinical data and biospecimens are collected at baseline and throughout follow-up (F/U), in real time, as pts are followed for life. Here, we assess rates and potential predictors of progression providing a foundation for precise stratification across the MDS spectrum, which may ultimately guide intervention. Methods At baseline, all MDS NHS pts have central pathology review and those assigned to MDS, MDS/MPN overlap, AML&lt;30% blasts, or at-risk of MDS (AR-MDS: CCUS and other at-risk) are followed prospectively. We compared AR-MDS with LR-MDS (MDS and MDS/MPN overlap with IPSS-R ≤ 3.5) and HR-MDS (MDS and MDS/MPN overlap with IPSS-R &gt; 3.5). We defined disease progression as any F/U diagnosis of worsening disease or documented disease-related death. Rates of disease progression were compared between groups using survival analysis methods for cumulative incidence incorporating non-disease death as a competing risk. Associations between progression and predictor variables were explored using univariate tests of association and multivariable survival (Cox regression) models for time-to-progression and logistic models for probability of progression (yes/no). Results The MDS NHS enrolled 2051 pts during June 2016-February 2024, with 54% (1111, above categories) followed prospectively. Median F/U is 1.7 yrs (IQR: 0.8-3.1 yrs, max: 7.9 yrs). For the current analysis, 582 MDS and 505 AR-MDS pts were included. Compared to AR-MDS, MDS patients were more often male (70% v 61%, p&lt;0.01), older (median age: 75 v 72 years, p&lt;0.01), and had lower baseline hemoglobin (median: 10.1 v 11.9 g/dL, p&lt;0.001), platelets (median: 124 x109 v 146 x109 cells/L, p&lt;0.001), and absolute neutrophil counts (median: 1.9 x109 vs 2.8 x109 cells/L, p&lt;0.001). F/U time was similar among AR-MDS and MDS (median: 1.9 vs 1.6 yrs), with both groups having a 75th percentile of 3 yrs and maximum of 7 yrs. A total of 331 deaths were observed (30%), with 145 (44%) of these due to causes related to MDS (myeloid disease and/or cardiovascular disease). Overall, 18.5% had disease progression, with annual rates of 8% (MDS) and 2% (AR-MDS) (p&lt;0.01). Among HR-MDS, progression rates were greatest in the 1st year following diagnosis (33%) and declined thereafter, whereas progression rates remained between 5-8% for LR-MDS and 1-3% for AR-MDS over 5 yrs of F/U. AR-MDS had similar rates of progression within the first 3 yrs from diagnosis as MDS with the lowest IPSS-R category. Among AR-MDS, low hemoglobin (hazard ratio, HR [95% CI]=3.2 [1.4-7.3], p&lt;0.01) was significantly associated with progression. Among MDS, low hemoglobin (HR=4.0 [2.2-7.0], p&lt;0.001), low platelet count (HR=3.1 [1.7-5.6], p&lt;0.001) and higher numbers of mutations (HR=1.13 [1.0-1.2], p&lt;0.01) were significantly associated with progression. Due to the low rate of progression in AR-MDS, meaningful comparisons of mutations could not be completed. In MDS, univariate analyses showed that somatic mutation prevalence in gene pathways for transcription, cell cycle and RAS signaling, and in genes TP53, BCOR, SF3B1, DDX41, PTPN11, SETBP1, and JAK2 were significantly associated with the probability of progression (p&lt;0.05 in all). In multivariable models, adjusting for patient age, sex, and MDS risk level, the probability of progression (PP) was significantly higher among those with vs without somatic mutations in BCOR (PP=63% vs 29%, p=0.004), PTPN11 (PP=67% vs 29%, p=0.009), SETBP1 (PP=61% vs 30%, p=0.02), JAK2 (PP=59% vs 30%, p=0.02), DDX41 (PP=56% vs 30%, p=0.03) and TP53 (PP=43% vs 29%, p=0.04). Conclusions In this large prospective cohort of MDS and pts at risk for MDS, the annual rate of any disease progression was 8% among MDS and 2% among AR-MDS, lower than some retrospective series. Specific cytopenias and genetic factors associated with progression were identified. The MDS NHS provides an incomparable opportunity to address the critical clinical challenges of management and prevention of MDS progression across its spectrum.

Introduction: Myelodysplastic syndromes (MDS) occur due to the acquisition of mutational events over time. Tobacco smoking is a risk factor for MDS and has been associated with distinct genetic mutations in solid cancers. We investigated the association between smoking intensity and duration and the number and types of genetic mutations in MDS using a large prospective cohort. Methods: The prospective NHLBI/NCI National MDS Natural History Study includes individuals with suspected or recently diagnosed MDS enrolled between June 2016-August 2023. Patient (Pt) bone marrow samples underwent central pathology review, resulting in diagnoses including MDS, MDS/myeloproliferative neoplasm overlap (MDS/MPN), or precursor conditions, such as clonal cytopenia of undetermined significance (CCUS). Self-reported smoking data were collected at enrollment. Smoking intensity (i.e., light, medium, and heavy) was defined per CDC definitions. Included mutations were those manually annotated to be pathogenic for MDS. Mutation frequency and prevalence, as well as associations with smoking history and other key covariates, were assessed using univariate tests of association and multivariable regression models for counts and proportions. Rates of disease progression were compared between groups using survival analysis methods for cumulative incidence incorporating non-disease death as a competing risk. Results: Of 1898 evaluable pts, 52% (N=979) had a history of cigarette smoking [MDS: 58% (252/436), MDS/MPN: 57% (52/91), CCUS: 57% (230/405)], and 18% still smoked at diagnosis. The mean ± SD cigarettes per day was 15.8 ± 12.5 and the mean ± SD smoking years was 29.8 ± 16.9 years. Compared to non-smokers, smokers were more often males (68% v 54%, p&lt;0.001) in the 70-79 year age group (45% v 34%, p&lt;0.001). Similar proportions of those with and without a smoking history had MDS (41% v 37%, respectively). Within MDS, there was no association between smoking and MDS prognostic risk per revised international prognostic scoring system. Compared to light smokers [1-10 pack-years (PY)], heavy smokers (30+ PY) were more often male (81% v 62%, p&lt;0.001) and had higher rates of cardiovascular disease (38% v 20%, p&lt;0.001). In univariate analyses, smokers and non-smokers had similar numbers of mutations (mean ± SD: 2.0 ± 2.7 in both groups). Pts with CCUS had the least number of mutations (1.5 ± 1.2), followed by MDS (2.3 ± 1.8), and MDS/MPN overlap (3.3 ± 1.8). Within disease groups, smokers and non-smokers had similar numbers of mutations. Mutation prevalence was higher among smokers v non-smokers in gene pathways for chromatin modification (15% v 11%, p&lt;0.01) and RNA splicing (26% v 19%, p&lt;0.001) and for individual genes ASXL1 (12% v 8%, p&lt;0.01), SF3B1 (9% v 6%, p&lt;0.05), U2AF1 (6% v 3%, p&lt;0.05) and ZRSR2 (2% v 1%, p&lt;0.05). In multivariable regression models, after adjustment for sex, age and disease group, smokers had significantly more mutations on average than non-smokers (2.0 v. 1.4, p=0.04). Moreover, the number of mutations increased significantly with PY smoked (p=0.006), and those at the 75th and 90th percentiles of PY had 1.8 and 3.5 times the number of mutations, respectively, compared to non-smokers, indicating a dose-response relationship. After adjustment, mutation prevalence increased with PY smoked in the gene pathways for chromatin modification and RNA splicing (p&lt;0.03 for both) and for the genes ASXL1 and ETNK1 (p&lt;0.05 in both cases). The five-year cumulative incidence of disease progression was significantly higher among long-term smokers compared to non-smokers/those with shorter smoking history (mean [95% CI] proportion progressed, 20+ years vs &lt;20 years smoking: 27% [19%-36%] vs 18% [13%-24%], p &lt; 0.05). Overall survival was significantly lower for smokers compared to non-smokers for CCUS pts [HR 1.91, 95% CI (1.03-3.55), p=0.04] but not for MDS [HR 1.21, 95% CI (0.53-1.30), p=0.41]. Conclusions: In this prospective, national cohort, tobacco smoking was associated with distinct genetic mutations related to MDS, suggesting smoking potentially contributes to its multi-step molecular pathogenesis. A dose-response relationship was also demonstrated, as was an association with progression and survival. Our data suggest that pts with a new MDS diagnosis who are also smokers should be counseled to stop smoking, as it appears to contribute to the acquisition of new genetic mutations that can lead to progression.