Bejar, Rafael

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<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 > 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<0.01), older (median age: 75 v 72 years, p<0.01), and had lower baseline hemoglobin (median: 10.1 v 11.9 g/dL, p<0.001), platelets (median: 124 x109 v 146 x109 cells/L, p<0.001), and absolute neutrophil counts (median: 1.9 x109 vs 2.8 x109 cells/L, p<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<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<0.01) was significantly associated with progression. Among MDS, low hemoglobin (HR=4.0 [2.2-7.0], p<0.001), low platelet count (HR=3.1 [1.7-5.6], p<0.001) and higher numbers of mutations (HR=1.13 [1.0-1.2], p<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<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<0.001) in the 70-79 year age group (45% v 34%, p<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<0.001) and had higher rates of cardiovascular disease (38% v 20%, p<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<0.01) and RNA splicing (26% v 19%, p<0.001) and for individual genes ASXL1 (12% v 8%, p<0.01), SF3B1 (9% v 6%, p<0.05), U2AF1 (6% v 3%, p<0.05) and ZRSR2 (2% v 1%, p<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<0.03 for both) and for the genes ASXL1 and ETNK1 (p<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 <20 years smoking: 27% [19%-36%] vs 18% [13%-24%], p < 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.

INTRODUCTION: Luxeptinib (CG-806; LUX) is an orally active noncovalent kinase inhibitor of Bruton's tyrosine kinase (BTK), wild type and mutant forms of Fms-like tyrosine kinase 3 (FLT3) (including the internal tandem duplicates (ITD), tyrosine kinase domain (TKD), and F691L mutant forms), and growth receptors like KIT, CSF1R, PDGFRα, and TRKs. In prior studies, LUX has been shown to suppress aberrant proliferative signaling in B cell malignancies and acute myeloid leukemia (AML) via regulation of BTK, LYN, SYK, AKT, ERK, and MAPK. LUX is cytotoxic to primary AML cells insensitive to other FLT3 inhibitors and to malignant B-cells insensitive to ibrutinib, at pM and nM concentrations, respectively. AIMS: The primary objectives of these studies are to assess the safety, tolerability, and pharmacokinetics (PK) of LUX and determine recommended phase 2 doses for relapsed or refractory (R/R) AML and B cell malignancy patients. METHODS: In two studies (NCT04477291; NCT03893682), LUX (original formulation, G1) was administered continuously as oral capsules BID in 28-day cycles of ascending cohorts (relapsed or refractory de novo, secondary, or therapy-related AML or higher risk myelodysplastic syndrome (MDS), and relapsed and refractory for B cell lymphoma and chronic lymphocytic/small lymphocytic leukemia). A novel generation 3 (G3) formulation of LUX designed to increase bioavailability was tested at a single-dose (sub-study) for relative bioavailability (RBA), followed by continuous dosing in subsequent R/R AML patients. RESULTS: In the B-cell study (as of 15 th May 2023), LUX has been administered to 36 patients at dose levels from 150 mg to 900 mg BID in patients with a median of 3 lines of prior treatment, with 47.2% having received a BTK-inhibitor. Only one (2.8%) patient had a DLT of hypertension and 14 (38.9%) experienced at least one drug related ≥Grade3 treatment emergent adverse event (TEAE). Two patients (900 mg) are currently on study with no DLT and no ≥Grade 3 related TEAEs. A Follicular lymphoma patient is at cycle 28, and achieved a best response as partial response (PR) with a decrease in lesion size of 76.2%; an SLL patient is at cycle 13, and achieved stable disease (SD) showing a decrease in lesion size of 43.1% (Figure A). The overall best response achieved among the 17 patients who have been on treatment for more than 12 weeks are stable disease (SD) (n=11), partial response (PR) (n=3), minor response (n=2) and complete response (CR) (n=1). As of 5 th June 2023, in the AML trial, a total of 40 patients (16 (40%) FLT3-ITD, 21 (52.5%) FLT3-WT, 2 (5.0%) FLT3-TKD, and 1 (2.5%) unknown mutations) with a median of 3 prior treatments (range, 1 - 10) have been treated with LUX G1 formulation at dose levels from 450 mg - 900 mg BID (n=34) or with 50 mg BID of G3 formulation (n=6). Four (10%) experienced drug related SAE and 7 (17.5%) had a drug related grade ≥3 TEAEs. The most common related TEAEs were lymphocyte count decrease, platelet count decrease, and anemia (n=2; 5% patients each). One (2.5%) patient at 450 mg dose, reported complete remission without minimum residual disease (CRmrd) and remained on study for 56 weeks. In the RBA sub-study, G3 (50 mg) produced comparable exposures to G1 (450-900 mg range) (Figure B) and was, therefore, selected as the starting dose for use in the R/R AML study. Six patients were treated with a continuous dosing of 50 mg BID G3; with plasma levels of 274 ng/mL and 195 ng/mL LUX observed by the end of C1D15 and C1D22 respectively. No drug related Grade ≥3 TEAEs or DLTs were observed in 50 mg BID G3 LUX treated patients; with no new safety signals observed for the G3 formulation. Based on these findings and expected exposures for higher dose levels, the cohort safety review committee has approved escalation of G3 dosing to 200 mg BID at which dosing is ongoing. CONCLUSIONS: LUX has a favorable safety profile in patients at all tested dose levels, for multiple cycles, for both studies. Antitumor activity was observed in a heavily pretreated relapsed AML patient and in multiple B-NHL subtypes and CLL/SLL patients including several with prior ibrutinib exposure. Continuous dosing of patients with R/R AML and Higher-Risk MDS with the G3 formulation is ongoing; with updated clinical data (200 mg dose level) to be presented at the meeting.

Background. The inclusion of gene mutations and chromosomal abnormalities in the 2022 WHO and ICC Classifications of MDS has enhanced diagnostic precision and is expected to improve clinical decision-making process. Although these two systems share similarities, clinically relevant discrepancies still exist and potentially cause inconsistency in their adoption in a clinical setting. In this study on behalf of the International Consortium for MDS (icMDS), we adopted a data-driven approach to provide a harmonization roadmap between the 2022 WHO and ICC classification for MDS. A modified Delphi Process consensus approach is currently ongoing among icMDS experts to finalize a harmonized MDS classification scheme. Methods. We analyzed retrospective international cohorts of patients with a diagnosis of MDS (n=7017) and AML (n=1002) according to WHO 2016 criteria. Hierarchical Dirichlet Processes were applied to define clusters capturing broad dependencies among all gene mutations and cytogenetic abnormalities. To investigate the features of importance and their impact on the clustering process, we employed the SHapley Additive exPlanations approach (SHAP). This allowed to define harmonized labels for each clinical entity. The clinical relevance of the unsupervised clustering was assessed through the analysis of phenotypic features and outcomes among each group. ( Blood 2022;140: 9828-9830) Results. Patients' characteristics are summarized in Table 1. We identified 9 clusters, defined by specific genomic features. The cluster of highest hierarchical importance was characterized by biallelic inactivation of TP53 (biTP53). According to SHAP analysis, bi TP53 was defined as 2 or more TP53 mutations, or 1 mutation with copy number loss or cnLOH. Most patients assigned to bi TP53 cluster had TP53 VAF>10% (77.9%) and complex karyotype (70.1%). Assignment to bi TP53 cluster was irrespective of blast count. Patients with monoallelic TP53 mutation segregated into other clusters. Hierarchically, the second cluster included patients with del(5q). SHAP analysis highlighted 5q deletion alone, or with one other chromosomal abnormality other than -7, and absence of bi TP53, as the most relevant features. Most of these patients had blast counts <5% (88.1%). The third distinct cluster included patients with SF3B1 mutations (in the absence of concurrent del(7q), abn3q26.2, complex karyotype or RUNX1 mutation). Most patients with MDS and SF3B1 mutation had <5% blasts (94.2%). Common co-mutated variants in the SF3B1 cluster included mutant DNMT3A (25.2%) and TET2 (38.3%). Morphologically defined MDS cases (i.e., not meeting criteria for bi TP53, del(5q) or SF3B1) were preferentially assigned to the following additional clusters: SF3B1 and concurrent higher-risk mutations (e.g., RUNX1 and ASXL1); SRSF2 and concomitant TET2 mutations; U2AF1 mutations with del(20q), del(7q) or -7; SRSF2 with TET2 mutations and co-mutational patterns including RUNX1 and ASXL1; and AML-like genomic signatures. Our analyses suggest that morphologically defined MDS is characterized by a large heterogeneity in terms of mutation profiles, not entirely captured by the presence of unilineage versus multilineage dysplasia, percentage of bone marrow blasts, and presence of hypocellularity and fibrosis. To better investigate the continuum between high risk MDS (i.e., patients with ≥10% blasts) and AML, an exploratory comparison was made using a cohort of AML (defined according to WHO 2016) patients analyzed using the same statistical methods. Only a partial overlap in genetic signatures was observed between MDS with ≥10% blasts and AML. However, similarities were observed between the AML-like MDS clusters (characterized by mutant NPM1, bZIP CEBPA, and Core Binding Factor abnormalities) and AML clusters defined by the same genetic signature, thus supporting the classification of these entities as AML, irrespective of blast count. Conclusion. Our study demonstrated the utility of a data-driven approach based on advanced statistical methods to generate a harmonized classification for MDS. Table 2 shows a provisional, hierarchical classification algorithm. Further refinement of entity labels and classification criteria is the subject of the ongoing modified Delphi Process consensus approach among icMDS experts.

Abstract Myelodysplastic neoplasms (MDS) are a collection of hematopoietic disorders with widely variable prognoses and treatment options. Accurate pathologic diagnoses present challenges because of interobserver variability in interpreting morphology and quantifying dysplasia. We compared local clinical site diagnoses with central, adjudicated review from 918 participants enrolled in the ongoing National Heart, Lung, and Blood Institute National MDS Natural History Study, a prospective observational cohort study of participants with suspected MDS or MDS/myeloproliferative neoplasms (MPNs). Locally, 264 (29%) were diagnosed as having MDS, 15 (2%) MDS/MPN overlap, 62 (7%) idiopathic cytopenia of undetermined significance (ICUS), 0 (0%) acute myeloid leukemia (AML) with <30% blasts, and 577 (63%) as other. Approximately one-third of cases were reclassified after central review, with 266 (29%) diagnosed as MDS, 45 (5%) MDS/MPN overlap, 49 (5%) ICUS, 15 (2%) AML with <30%, and 543 (59%) as other. Site miscoding errors accounted for more than half (53%) of the local misdiagnoses, leaving a true misdiagnosis rate of 15% overall, 21% for MDS. Therapies were reported in 37% of patients, including 43% of patients with MDS, 49% of patients with MDS/MPN, and 86% of patients with AML with <30% blasts. Treatment rates were lower (25%) in cases with true discordance in diagnosis compared with those for whom local and central diagnoses agreed (40%), and receipt of inappropriate therapy occurred in 7% of misdiagnosed cases. Discordant diagnoses were frequent, which has implications for the accuracy of study-related and national registries and can lead to inappropriate therapy. This trial was registered at www.clinicaltrials.gov as #NCT05074550.

Abstract Myeloid neoplasms and acute leukemias derive from the clonal expansion of hematopoietic cells driven by somatic gene mutations. Although assessment of morphology plays a crucial role in the diagnostic evaluation of patients with these malignancies, genomic characterization has become increasingly important for accurate diagnosis, risk assessment, and therapeutic decision making. Conventional cytogenetics, a comprehensive and unbiased method for assessing chromosomal abnormalities, has been the mainstay of genomic testing over the past several decades and remains relevant today. However, more recent advances in sequencing technology have increased our ability to detect somatic mutations through the use of targeted gene panels, whole-exome sequencing, whole-genome sequencing, and whole-transcriptome sequencing or RNA sequencing. In patients with myeloid neoplasms, whole-genome sequencing represents a potential replacement for both conventional cytogenetic and sequencing approaches, providing rapid and accurate comprehensive genomic profiling. DNA sequencing methods are used not only for detecting somatically acquired gene mutations but also for identifying germline gene mutations associated with inherited predisposition to hematologic neoplasms. The 2022 International Consensus Classification of myeloid neoplasms and acute leukemias makes extensive use of genomic data. The aim of this report is to help physicians and laboratorians implement genomic testing for diagnosis, risk stratification, and clinical decision making and illustrates the potential of genomic profiling for enabling personalized medicine in patients with hematologic neoplasms.

Abstract Despite much of the past 2 years being engulfed by the devastating consequences of the SAR‐CoV‐2 pandemic, significant progress, even breathtaking, occurred in the field of chronic myeloid malignancies. Some of this was show‐cased at the 15th Post‐American Society of Hematology (ASH) and the 25th John Goldman workshops on myeloproliferative neoplasms (MPN) held on 9th‐10th December 2020 and 7th‐10th October 2021, respectively. The inaugural Post‐ASH MPN workshop was set out in 2006 by John Goldman (deceased) and Tariq Mughal to answer emerging translational hematology and therapeutics of patients with these malignancies. Rather than present a resume of the discussions, this perspective focuses on some of the pivotal translational hematology and therapeutic insights in these diseases.