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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

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: Despite advent of multiple tyrosine kinase inhibitors (TKIs) and newer treatment methods for AML and ALL, the outcomes of patients (pts) with chronic myeloid leukemia in blast phase (CML-BP) remain poor. Consensus guidelines on treatment of CML-BP are scarce. A recent study from the European leukemia network blast phase registry on 240 pts reported marked heterogeneity in treatment patterns and lack of an accepted standard. Hence, we undertook this study through the H Jean Khoury Cure CML Consortium (HJKC3) to describe the treatment patterns and outcomes of pts with CML-BP in the US. Methods: This is a multi-institution, retrospective study. IRB approval was obtained at each institution and data sharing agreements were executed. All pts diagnosed with CML-BP based on modified MD Anderson Criteria (≥30% blasts in the blood or bone marrow or extramedullary (EM) disease) from 2010 to 2025 were included. Categorical variables were compared using Chi-square test. Overall survival (OS) was calculated from time of diagnosis of CML BP to death from any cause. Event free survival (EFS) was calculated from date of best response to event (death or relapse). Results: Of the 283 pts with CML-BP, 96 (33.9%) were female and 187 (66.1%) were males. At the time of diagnosis, 183 (64.6%) had CML-CP, 21 (7.4%) pts had CML-AP and 79 (27.9%) pts had de-novo CML-BP. For the 204 pts that were initially diagnosed with CML-CP or CML-AP, the median time to progression to CML-BP was 22.5 months (1-207 months). Median age at diagnosis of CML-BP was 50 years (range 16-86 years). EM disease was present in 78 (27.6%) pts (38 myeloid sarcoma, 30 central nervous system and 10 skin). Blasts were of myeloid phenotype in 168 (59.4%), lymphoid in 103 (36.4%) and mixed in 9 (3.2%) pts. The bcr-abl protein was p210 in 229 (80.9%), p190 in 8 (2.8%) and p230 in 2 (0.7%) pts. ABL kinase domain mutation was seen in 42.1% (80/190) pts, with T315I being the most common (n=32), followed by E255K (n=16). Next generation sequencing was performed in 117 pts. The most common mutations were ASXL1 (n=27), RUNX1 (n=14), BCOR (n=4), DNMT3A (n=4) and BCORL1 (n=3). Of the 283 pts, 269 underwent CML-BP directed therapy. 63 (23.4%) pts were treated with TKI monotherapy, 184 (68.4%) pts were treated with a combination of chemotherapy (chemo) and TKI and 22 (8.2%) pts were treated with chemo alone. Response rate after CML-BP directed therapy was 75.3% (n=213). Best response was return to CML-CP in 49 pts, CHR with PCyR in 18 pts, CCyR in 31 pts, MMR in 31 pts, MR4 in 18 pts, MR4.5 in 19 pts and MR5 in 47 pts. Rate of response with 2G and ponatinib was significantly better than imatinib (85.3% and 77.3% vs 63.6%; p=0.04). 149 (55.4%) pts proceeded to alloSCT. Of the 213 pts that responded, 59 (27.7%) relapsed. At a median follow-up of 47 months, the median OS for all pts was 19.7 months (95% CI: 16.3-40.2 months), with 5-year OS rate of 38% (95% CI: 32-45%). Pts with myeloid phenotype had a significantly lower OS compared to lymphoid and mixed phenotype (Median OS 14.9 vs 45.9 and 31.1 months respectively; p=0.02). OS of pts that were treated with a combination of TKI and chemo was significantly longer compared to pts treated with TKI or chemo alone (52.9 vs 16.1 or 7.5 months; p<0.0001). Dasatinib (n=99; 34.9%) and ponatinib (n=97; 34.3%) were the most used TKIs followed by imatinib (n=23; 8.1%), nilotinib (n=21; 7.4%), bosutinib (n=8; 2.8%) and asciminib (n=3; 1.1%). Pts treated with ponatinib had a numerically longer OS compared to 2G-TKI and imatinib, however this was not statistically significant (40.1 vs 30.6 and 20.3 months; p=0.52). EFS for pts treated with ponatinib was significantly longer compared to 2G-TKI or imatinib (25.9 vs 17.6 and 15.9 months; p=0.03). In a landmark analysis, pts that underwent alloSCT within 6 months of diagnosis had a significantly longer OS compared to those who did not (69.3 vs 16.0 months; p=0.006). Conclusion: CML-BP continues to have poor prognosis. Treatment is heterogenous involving various combinations of TKI and chemo. In our analysis, treatment with 2G-TKI or ponatinib led to better responses. CML-BP with myeloid phenotype had worse OS. Treatment with ponatinib was associated with a numerically longer OS and significantly longer EFS compared to 2G-TKI and imatinib. In addition, treatment with chemo in combination with TKI and alloSCT led to improved OS.

Abstract Introduction Defining the epidemiology of myelodysplastic syndromes/neoplasms (MDS) and precursor conditions, such as clonal cytopenia of undetermined significance (CCUS), is challenging due to inconsistent reporting, complex diagnostics, and evolving criteria. The National MDS Natural History Study (NHS) overcomes these challenges through central pathology review, prospective follow-up, and a nationally representative cohort enrolled at the time of suspected MDS, enabling robust analysis across the myeloid disease spectrum. We analyzed clinical, genetic, and pathologic features in NHS participants by race, ethnicity, and sex to characterize disease variation across populations. Methods The NHS (NCT02775383) enrolled individuals undergoing evaluation for suspected MDS from June 2016–July 2024 at 102 US sites. Participants underwent bone marrow assessment with centralized, adjudicated histopathology review. Those meeting WHO 2016 criteria for MDS, MDS/myeloproliferative neoplasm (MPN), CCUS, idiopathic cytopenia/dysplasia of undetermined significance (ICUS/IDUS), or oligoblastic AML were followed longitudinally. Demographics, comorbidities, exposures, and clinical data were collected at baseline and every 6 months. Deep DNA sequencing was performed on baseline marrow, with pathogenic variants manually curated (53 genes). Statistical analyses assessed associations using chi-squared, Fisher's exact, Kruskal-Wallis, logistic regression, and Cox models. A p-value <0.05 was considered significant. Results Among 2,021 participants, 1,174 (58%) were diagnosed with MDS or precursor conditions. Median age was 74 years (yrs) and 66% were male. Most identified as Non-Hispanic White (NHW, 92%), with 4% Black and 4% Hispanic. The most common diagnoses were MDS (42%) and CCUS (37%). Pathogenic somatic mutations were identified in 84% (774/918) of MDS/CCUS, with TET2 (26% of 918), DNMT3A (21%), and ASXL1 (16%) most frequent. Median follow-up was 1.8yrs and consistent across race, ethnicity, and sex (p≥0.6). Black, compared to NHW, participants were younger (69 vs 74 yrs, p=0.006) and trended toward more females (47% vs 34%, p=0.09) and more MDS diagnoses (51% vs 41%, p=0.07). Black participants showed more advanced disease (e.g., lower hemoglobin, higher peripheral blood blasts, higher variant allele frequencies (VAFs) of pathogenic mutations), yet received less MDS-directed treatment (14% vs 41%, p=0.01). Black, compared to NHW, participants had more mutations in RUNX1, TP53, BCOR, and DNMT3A, but fewer in TET2 and ASXL1. Hispanic, compared to Non-Hispanic, participants had fewer known pathogenic mutations, leading to more ICUS (19% vs 5%, p=0.02). Females, compared to males, were younger at diagnosis (72 vs 75yrs, p<0.001), had more ICUS/IDUS (20% vs 10%, p<0.001), fewer pathogenic mutations, especially in splicing/chromatin modifier genes (U2AF1, SRSF2, ASXL1, ZRSR2), more DNMT3A mutations, and lower VAFs (0.27 vs 0.33, p<0.001). Median overall survival (OS) was 6.4yrs, and shorter in MDS (4.2yrs) than CCUS (not reached). Worse OS was associated with age (adjusted hazard ratio (aHR) 1.06), MDS (vs CCUS; aHR 1.89), higher-risk disease by IPSS-R/CCRS (aHR 2.15), and TP53 mutations (aHR 2.17) (all p<0.001). A trend toward improved OS in Black participants was attenuated after adjustment (aHR 0.79, p=0.6). Progression (e.g., worsening of disease, increase in transfusion dependency, death) occurred in 53% of participants. Worse progression-free survival (PFS) was associated with MDS diagnosis (aHR 2.59), higher-risk disease by IPSS-R/CCRS (aHR 2.17), and TP53 mutations (aHR 1.86) (all p<0.001). Despite more advanced disease and less MDS therapy, Black participants trended toward improved PFS (aHR 0.62, p=0.14), while age was borderline significant (aHR 1.01, p=0.05). Conclusions For the first time, we show that among individuals evaluated for suspected MDS at sites across the US, 58% had MDS or precursor conditions. Differences across demographics underscore the heterogeneity of MDS. Black participants presented with more advanced MDS, received less treatment, but trended toward improved outcomes, particularly PFS, even after adjustment, suggesting biological rather than access-to-care differences driving disparities. These findings highlight the complex interplay of sex, race, and genetics in shaping MDS outcomes and reinforce the need for diverse, large-scale studies to improve risk stratification and personalized care.

Abstract Post-translational modifications (PTM) of tau are implicated in Alzheimer disease (AD) progression and are established biomarkers in cerebrospinal fluid and plasma; however, the labor-intensive nature of conventional proteomics limits their investigation in histology-specific contexts. We describe the findings of an artificial intelligence-guided laser capture microdissection (LCM) pipeline for harvesting neurofibrillary tangles (NFTs) by maturation level into pretangles (pre-NFTs), mature tangles (iNFTs), and ghost tangles (eNFTs) using 38 cases obtained from 2 independent biobanks. We evaluated the performance characteristics of proprietary machine learning algorithms for the subclassification of these NFT categories in anti-pTau217-stained whole slide images of entorhinal cortex, hippocampus, frontal, and parietal cortex sections. Overall precision/recall/F1 scores were highest for Classifier A (0.6/0.46/0.5). The best performing algorithm was used to guide LCM capture and inform NFT enrichment. Targeted proteomics on tau signature peptides (pTau181, pTau217, and TauMTBR) was performed on approximately 1250 NFT collections. The results demonstrated that their abundance increased from pretangles to mature tangles (∼2-11-fold increase), and that this was followed by a sharp reduction in ghost tangles (∼3-116-fold decrease), with pTau217 showing the most drastic change. Pathologist-trained NFT classifiers represent an objective albeit imperfect means to enrich specific morphologic forms permitting coupled LCM-MS (mass spectrometry) to investigate AD-associated PTM.

Abstract The prevalence of steatotic liver disease (SLD) is rising globally, presenting a significant public health challenge. While non-contrast computed tomography (CT) scans hold promise for the opportunistic detection of SLD, their full potential has not been systematically explored. Clinical indicators, such as serum data, are crucial for monitoring the progression of SLD. We introduce a novel Multimodal AI for Opportunistic Steatotic Liver Disease Screening (MAOSS), which integrates demographic data, serum tests, conventional CT biomarkers, and deep learning-derived CT image features to enhance model performance and explainability. MAOSS employs an innovative learning strategy, trained on a large-scale dataset (n = 1,783) encompassing both histopathologically-confirmed SLD and radiologically-reported steatosis cases. The model underwent extensive retrospective validation using steatosis grades derived from both histology and MRI-PDFF across internal and external datasets (n = 913), as well as real-world patient data (n = 18,504). It accurately detected mild to severe steatosis (≥ S1) with AUCs ranging from 0.903 to 0.929. Notably, MAOSS significantly improved the overall AUC for radiologists (n = 11) from 0.709 to 0.798 (p < 0.001). Furthermore, MAOSS was applied to optimize the standard clinical pathway for a simulated primary risk screening of SLD patients (n = 1,192), resulting in the identification of 31% more patients at risk of steatohepatitis and liver fibrosis progression, highlighting its potential to enhance SLD detection and management.

Introduction: Despite advent of multiple tyrosine kinase inhibitors (TKIs) and newer treatment methods for both AML and ALL, the outcomes of patients (pts) with chronic myeloid leukemia in blast phase (CML-BP) remain poor. Consensus guidelines on treatment of CML-BP are scarce. A recent study from the European leukemia network (ELN) blast phase registry reported outcomes of 240 CML-BP pts. They also reported marked heterogeneity in treatment patterns and lack of an accepted standard. Hence, we are undertaking this study through the H Jean Khoury Cure CML Consortium (HJKC3) to study the treatment patterns and outcomes of pts with CML-BP in the US. Methods: This is a multi-institution, retrospective study. IRB approval was obtained at each institution separately and data sharing agreements were executed. All pts diagnosed with CML-BP based on modified MD Anderson Criteria (≥30% blasts in the blood or bone marrow or extramedullary (EM) disease) from 2010 to 2024 were included. Categorical variables were compared using the Chi-square test. Overall survival (OS) was calculated from the time of diagnosis to death from any cause. Survival probabilities were computed using the Kaplan-Meier method and compared with the log-rank test. Results: Of the 72 pts with CML-BP included in this analysis, 29 (40.3%) were female and 43 (59.7%) were males. At the time of diagnosis, 36 (50%) had CML-CP (chronic myeloid leukemia in chronic phase), 11 (15.3%) pts were diagnosed with CML-AP (accelerated phase CML) and 25 (34.7%) pts with de-novo CML-BP. For the 47 pts that were initially diagnosed with CML-CP or CML-AP, the median time to progression to CML-BP was 26 months (1-207 months). Median age at diagnosis of CML-BP was 54 years (range 21-86 years). EM disease was present in 17 (23.6%) pts (7 myeloid sarcoma, 5 central nervous system and 5 skin) with 3 pts presenting with EM disease only. Blasts were of myeloid phenotype in 41 (56.9%), lymphoid in 29 (40.3%) and mixed in 2 (2.8%) pts. The bcr-abl protein was p210 in 59 (81.9%), p190 in 5 (6.9%) and p230 in 1 (1.4%) pt. Four pts had prior allogeneic stem cell transplant (alloSCT) for CML-CP. Of the pts who had an ABL kinase domain mutation tested, 42.9% (18/42) pts were found to have an ABL kinase domain mutation. The most common TKD mutation was T315I (n=6). Next generation sequencing was performed in 32 pts. The most common mutations were ASXL1 (n=10), RUNX1 (n=4), BCOR (n=2), BCORL1 (n=2), DNMT3A (n=2) and 1 each in CSF3R, KMT2A, EZH2, NF1 and TP53. Of the 72 pts, 68 underwent CML-BP directed therapy. While only 9 (13.2%) pts were treated with TKI alone (4 dasatinib, 2 imatinib, 2 ponatinib and 1 asciminib), 54 (79.4%) pts were treated with a combination of chemotherapy with TKI (24 dasatinib, 13 ponatinib, 9 imatinib, 6 nilotinib, 1 bosutinib and 1 asciminib), and 5 (7.4%) pts were treated with chemotherapy alone. The response rate after CML-BP directed therapy was 72.1% (n=49). Best response was return to CML-CP in 17 pts, CHR with PCyR in 1 pt, CCyR in 11 pts, MMR in 5 pts, MR4 in 4 pts, MR4.5 in 5 pts and MR5 in 6 pts. Rate of response with third and second generation TKI was significantly better than first generation TKI (80% and 77.1% vs 36.3%; p=0.02287). 30 (44.1%) pts proceeded to alloSCT. Of the 49 pts that responded, 16 (32.6%) relapsed. The median time to relapse was 5 months (range 1-46 months). At a median follow up of 57 months, the median OS for all pts was 18 months. There was no difference in OS based on blast phenotype (14 months for myeloid, 21 for lymphoid and 7.5 for mixed; p=0.1185), initial diagnosis (38 months CP-CML, 13 for CML-AP and 16 for de-novo BP pts; p=0.6380), or TKI (13 months for first generation, 20 for second and not reached for third generation TKI; p=0.1729). The OS of pts that were treated with a combination of TKI and chemotherapy was significantly longer compared to pts treated with TKI or chemo alone (28 vs 13 or 4.5 months; p=0.0003). Of the 32 pts that responded, OS for pts that underwent alloSCT was significantly longer compared to pts that did not (not reached vs 14 months; p= 0.0022). Conclusion: CML-BP continues to have a dismal prognosis. Treatment is heterogenous involving various combinations of TKI and chemotherapy. In our analysis, treatment with second or third generation TKI led to better responses. In addition, treatment with chemotherapy in combination with TKI and alloSCT led to improved OS. Updated results from further multi-institution analysis will be presented at the meeting.

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.

Abstract Despite advances in understanding the genetic abnormalities in myeloproliferative neoplasms (MPN) and the development of JAK2 inhibitors, there is an urgent need to devise new treatment strategies, particularly for patients with triple-negative (TN) myelofibrosis (MF) who lack mutations in the JAK2 kinase pathway and have very poor clinical outcomes. Here we report that MYC copy number gain and increased MYC expression frequently occur in TN-MF and that MYC-directed activation of S100A9, an alarmin protein that plays pivotal roles in inflammation and innate immunity, is necessary and sufficient to drive development and progression of MF. Notably, the MYC-S100A9 circuit provokes a complex network of inflammatory signaling that involves numerous hematopoietic cell types in the bone marrow microenvironment. Accordingly, genetic ablation of S100A9 or treatment with small molecules targeting the MYC-S100A9 pathway effectively ameliorates MF phenotypes, highlighting the MYC–alarmin axis as a novel therapeutic vulnerability for this subgroup of MPNs. Significance: This study establishes that MYC expression is increased in TN-MPNs via trisomy 8, that a MYC-S100A9 circuit manifest in these cases is sufficient to provoke myelofibrosis and inflammation in diverse hematopoietic cell types in the BM niche, and that the MYC-S100A9 circuit is targetable in TN-MPNs.