He, Rong

ABSTRACT Background IDH mutations are found in 15%–20% of acute myeloid leukemia (AML). Recent evidence suggests that IDH mutation subtypes may respond differently to intensive chemotherapy. We evaluated blast clearance patterns, remission outcomes, and overall survival (OS) in AML patients with IDH2 R140, IDH2 R172, and IDH1 R132 mutations to assess differences in treatment response. Methods We retrospectively reviewed AML patients diagnosed at Mayo Clinic, Rochester (2016–2023) with NGS data and treated with intensive chemotherapy (7+3 or CPX‐351). Bone marrow blasts were assessed at diagnosis, mid‐induction, and end‐of‐cycle; blast clearance was defined as < 5%. Composite remission (CRc) included CR/CRi per ELN 2022. IDH2 responders were classified as early (after Cycle 1) or late (≥ 2 cycles). Blast reduction was calculated as log 10 (diagnosis blasts/end‐induction blasts) and normalized per day. OS was measured from diagnosis. Results Among 381 patients, 31 had IDH2 mutations (23 R140, 8 R172) and eight had IDH1 R132. Baseline blasts were similar. Mid‐cycle blasts were lower in R140 versus R172 (4% vs. 10%), with higher clearance (68% vs. 38%). End‐induction blasts were lower in R140 versus R172 (2% vs. 4%) with higher clearance (100% vs. 75%). IDH1 and IDH2 showed similar clearance patterns. Log 10 analyses showed deeper and faster blast reduction in R140 versus R172, with comparable kinetics between IDH1 and IDH2 . OS did not differ across subtypes. Early CRc in IDH2 ‐mutated patients was associated with numerically longer OS. Conclusion IDH2 R140 demonstrated faster blast clearance than R172, while remission and survival were similar across IDH subtypes. Trial Registration : The authors have confirmed clinical trial registration is not needed for this submission.

Abstract Background Momelotinib, a small-molecule Janus kinase 1 and 2 (JAK1/2) inhibitor (JAKi), is FDA-approved (September 15, 2023) for use in anemic patients with myelofibrosis (MF). The drug appears to have an edge over other FDA-approved JAKis in regard to its unique erythropoietic effect that has been attributed to its inhibitory activity on activin A receptor type-1 (ACVR1). In clinical trials, anemia response to momelotinib in JAKi-naïve MF patients has been reported in more than a third of patients with or without transfusion-dependent anemia (TDA). The current study examines the drug's efficacy and toxicity in JAKi-naïve patients treated outside of clinical trials and after the drug was commercially approved. Methods The current study was conducted under an institutional review board approved minimum risk protocol. Diagnostic criteria were according to the International Consensus Classification (Arber et al. Blood 2022; 140:1200). Study inclusion criteria included a hemoglobin level of &lt;10 g/dL and absence of previous treatment with JAKi. Responses were adjudicated by the Revised International Working Group-European LeukemiaNet criteria (IWG-ELN; Blood 2024; 144:1813). Conventional statistical methods were used (JMP Pro 18.0.0 software SAS Institute, Cary, NC, USA). Results A Mayo Clinic enterprise-wide search identified 60 patients (median age 73 years; 55% males) with primary or secondary MF who received momelotinib outside of clinical trials as their first JAKi for treatment of anemia and associated symptoms. Driver mutation distribution included JAK2 42%, CALR 30%, MPL 18%, and triple-negative 10%. Table 1 outlines clinical and laboratory findings at the time of momelotinib treatment initiation; Dynamic International Prognostic Scoring System (DIPSS)-plus risk distribution included high (72%) and intermediate 1/2 (28%) risk. Twenty-seven (45%) patients were transfusion-requiring, 24 (40%) displayed peripheral blood (PB) blast ≥2%, 10 (17%) platelet count &lt;100 x 109/L, and 14 (25%) marked palpable splenomegaly (≥20cm). Unfavorable karyotype was seen in 9 (16%) of 58 patients. NGS-derived mutations were assessed in 57 cases and included ASXL1 (35%), TET2 (19%), SF3B1 (16%), SRSF2 (14%) and 7% (N=4) each for EZH2, IDH2, SH2B3, and ZRSR2. Baseline plasma cytokine levels were assessed in 17 patients with elevated TNF-a in 88%, IL-2 soluble 65%, IL-6 29% and IL-18 53%. Anemia response and predictors Fourteen (23%) patients met revised IWG-ELN criteria for anemia response (TDA 15% and non-TDA 30%; p=0.15). The anemia response was within 3 months in 10 (71%) patients. Median (range) durations of momelotinib exposure and anemia response were 8 (1-23) and 5 (1-13) months, respectively. The drug was discontinued in 29 (48%) patients (39% due to side effects; Table 2). In age-adjusted univariate analysis, predictors of anemia response included circulating blasts &lt;2% (33% [12/36] vs. 8% [2/24]; p=0.02), presence of SH2B3 mutation (100% [4/4] vs. 19% [10/53]; p&lt;0.01), and elevated IL-2 soluble (36% [4/11] vs. 0% [0/6]; p=0.02). The correlation with SH2B3 mutation remained significant (p&lt;0.01) after accounting for circulating blasts. Treatment emergent neuropathy and nephropathy Sensory peripheral neuropathy (PN) was reported by 12 (20%) patients with a median onset of 2 months (range 1-7); CTCAE v5.0 grades 1 (N=8), 2 (N=3), and 3 (N=1); reversibility was documented only for grade 1 severity and did not appear to be consistently affected by drug discontinuation or dose reduction (Table 3). Seventeen (29%) patients experienced a &gt;20% treatment-emergent decrease in estimated glomerular filtration rate from baseline, including 14 (23%) whose serum creatinine level crossed from the normal to abnormal range with pre- and post-treatment median (range) values of 1.05 (0.60-1.26) and 1.53 (1.1-3.31), respectively, with the majority reverting back to the normal range upon drug discontinuation. Conclusion In routine practice, momelotinib therapy might alleviate anemia in about a quarter of JAKi-naive patients with MF but is associated with non-trivial rates of treatment-emergent peripheral neuropathy and nephropathy. The latter appeared to be reversible on treatment discontinuation. Our novel observation regarding association of anemia response with SH2B3 mutation requires validation in a larger group of informative cases.

Abstract Background A previous multicenter study of patients with TP53-mutated myeloproliferative neoplasms showed a significantly shorter survival in chronic phase myelofibrosis (MF-CP) that included primary (PMF) and secondary MF and was mostly based on research-based mutation screening and was not systematically controlled for patients without TP53 mutations (AJH 2025;100:552). The objective of the current study was to examine the prognostic impact of TP53 mutations (VAF ≥2%) that were discovered during clinical NGS testing among consecutive patients with PMF-CP. Impact on overall (OS) and leukemia-free (LFS) survival was analyzed in the context of other genetic risk factors and calculated from the time of mutation detection. Methods The current retrospective study includes consecutive patients with PMF-CP who underwent clinical NGS testing at the Mayo Clinic between 2015 and 2025. Diagnoses of PMF-CP and leukemic transformation (LT) were retrospectively fitted to be in accordance with the International Consensus Classification criteria (Blood 2022;140:1200). Mutation and cytogenetic analyses were performed according to institutional protocols for clinical use and reported in conformity with international guidelines. OS and LFS analyses were censored for treatment with allogeneic stem cell transplantation (ASCT) and calculated from the date of NGS. Conventional statistical methods were utilized (JMP Pro 17.1.0, SAS Institute, Cary, NC, USA). Results A total of 633 patients with PMF-CP underwent clinical NGS testing prior to LT and prior to ASCT (median age 65 years; males 59%). Median interval from initial diagnosis/referral to NGS testing was 2 months; 357 (56%), 392 (62%), and 429 (68%) patients had NGS performed within 3, 6 and 12 months of diagnosis, respectively. Risk distribution according to the dynamic International Prognostic Scoring System (DIPSS; Blood 2010;115:1703) were low (19%), intermediate-1 (44%), intermediate-2 (31%), or high (6%). TP53 mutations (TP53MUT) with variant allele frequency (VAF) of ≥2% were detected in 28 (4.4%) patients with a median VAF of 25.3% (range 2.4-85; ICC-defined multihit 43%). Patients with TP53MUT were more likely to harbor IDH2MUT (14% vs. 3%; p&lt;0.01), EZH2MUT (14% vs. 4%; p=0.03), and unfavorable karyotype (36% vs. 19%; p=0.047) and less likely to harbor CALR type 1/like (4% vs. 18%; p=0.02) and SF3B1MUT (0% vs. 6%; p=0.07). The association with unfavorable karyotype was mainly driven by multihit configuration. No significant associations with clinical features were apparent. At a median follow-up of 40 months for surviving patients, 157 (25%) deaths, 48 (8%) LTs and 135 (21%) ASCTs were documented. A near-two-fold lower, albeit not statistically significant OS was observed in the presence of TP53MUT (median 123 vs. 228 months; HR 1.9, 95% CI 0.94-3.7; p=0.074); the difference reached significance for multihit TP53MUT (median 81 months; HR 3.6, 1.7-7.7; p&lt;0.01) but not for non-multihit TP53MUT (median not reached; HR 0.7, 0.2-2.8; p=0.6), both compared to TP53WT (median 228 months). The significant impact of multihit TP53MUT on OS was confirmed in multivariable analysis (MVA) that included other high molecular risk (HMR) mutations and unfavorable karyotype: multihit TP53MUT (HR 2.5, 1.1-5.5; p=0.02), SRSF2MUT (2.4, 1.5-3.8; p&lt;0.01), ASXL1MUT (1.8, 1.2-2.6; p&lt;0.01), U2AF1MUT-Q157 (4.8, 2.6-8.6; p&lt;0.01), and absence of CALR type 1/like (4.0, 2.0-7.8; p&lt;0.01); additional prognostic contribution was not evident for unfavorable karyotype (p=0.17), EZH2MUT (p=0.3), IDH1MUT (p=0.6), IDH2MUT (p=0.7), or any other HMR mutation. Multihit TP53MUT was also associated with inferior LFS (10-year risk 62% vs. 32% for non-multihit TP53MUT vs. 15% for TP53WT; p=0.03) but significance was lost during MVA that included SRSF2MUT, which was the only HMR mutation showing a significant effect on LFS (HR 5.0, 2.5-9.8; p&lt;0.01). Post-ASCT survival among 135 transplanted patients was significantly shorter for patients with multihit TP53MUT (N=4; median 5 months) vs. those with non-multihit TP53MUT (N=7; median not reached) vs. patients with TP53WT (N=124; median not reached) [p=0.02]. Conclusion The current study implicates multihit TP53MUT as an HMR mutation-independent prognostic factor for OS in PMF-CP. By contrast, prognosis in PMF-CP patients with non-multihit TP53MUT was more likely to be influenced by other HMR mutations, as was the case for those with TP53WT.

Abstract Background In our first exploration of mutations in essential thrombocythemia (ET; N=183), we described somatic variants other than JAK2/CALR/MPL in 53% (N=96) of patients with the most frequent being TET2 (16%), ASXL1 (11%), DNMT3A (6%), and SF3B1 (5%) [Blood Adv 2016;1:21]. In a subsequent report (N=270; BJH 2020;189:291), we highlighted the prognostic relevance of SF3B1, SRSF2, and EZH2 mutations for overall survival (OS), SRSF2, EZH2, and TP53 for leukemia-free survival (LFS), and SF3B1 and U2AF1 for myelofibrosis-free survival (MFFS). We have now expanded our NGS-informative patient cohort to 500 and examined the distribution and frequencies of specific mutations at different stages of the disease and corresponding prognostic correlates. Methods Molecularly-annotated ET patients diagnosed at the Mayo Clinic between January 1980 and May 2025 were considered. Diagnoses of chronic phase ET (ET-CP), post-ET MF, and post-ET acute myeloid leukemia (AML) were retrospectively fitted to be in accordance with the International Consensus Classification criteria (Blood 2022;140:1200). Mutation and cytogenetic analyses were performed according to institutional protocols for clinical use that included multi-gene next-generation sequencing (NGS); in a subset of patients, historically archived samples were accessed for analysis in a research setting. Patients were monitored until death or time of last follow-up, determined through electronic medical records or direct communication with patients or healthcare providers. Conventional statistical methods were utilized (JMP Pro 17.1.0, SAS Institute, Cary, NC, USA). Results A total of 500 ET patients (median 57 years; Females 61%) were informative for NGS-derived mutations that were obtained in the chronic (N=401; 80.2%; group A), post-ET MF (N=88; 17.6%; group B), or post-ET AML (N=11; 2.2%; group C) phase of the disease; group C included 9 (1.8%) patients who transformed directly to AML without transitioning through the MF phase. The most frequent mutations with at least 1% (N=5) mutational frequency were (approximately) TET2 (10%), ASXL1 (10%), DNMT3A (7%), SF3B1 (4%), TP53 (5%), SRSF2 (3%), EZH2 (2%), U2AF1 (2%), CBL (1%), IDH1 (1%), IDH2 (1%), RUNX1 (1%), ZRSR2 (1%), and PPM1D (1%). Comparison of distribution of mutations and their frequencies based on timing of NGS (AML phase vs. MF phase vs. ET-CP) revealed significant differences for TP53MUT (72.7% vs. 11.4% vs. 1%; p&lt;0.01), ASXL1MUT (18.2% vs. 25% vs. 7.2%; p&lt;0.01), and EZH2MUT (18.2% vs. 6.8% vs. 0.3%; p&lt;0.01), respectively; borderline significance was also apparent for RUNX1MUT (9.1% vs. 0% vs. 1.3%; p=0.10) and ZRSR2MUT (9.1% vs. 2.3% vs. 0.5%; p=0.08). Notably, among 9 patients in whom NGS was performed at the time of direct transition from ET to AML, without an intermediary MF phase, 8 (88.9%) displayed TP53MUT and only one (11.1%) EZH2MUT and none (0%) ASXL1MUT. At a median follow-up of 66 months, 93 (18.6%) deaths, 26 (5.2%) leukemic transformations (LT), and 108 (21.6%) MF transformations were reported. In group A patients, age-adjusted multivariable analysis (MVA) of mutations identified ASXL1MUT (N=29; HR 3.8, 1.9-7.7; p&lt;0.01) and SF3B1MUT (N=12; HR 3.9, 1.4-11.0; p=0.01) to be associated with inferior OS, ASXL1MUT (HR 4.9, 1.01-24.2; p=0.048) and SRSF2MUT (N=11; HR 11.9, 1.3-104.8; p=0.03) with inferior LFS, and ASXL1MUT (HR 9.0, 2.8-29.5; p&lt;0.01) and SF3B1MUT (HR 15.5, 3.1-77.5; p&lt;0.01) with inferior MFFS, all calculated from time of NGS. A similar analysis in group B patients identified ASXL1MUT (N=22; HR 3.7, 1.2-11.7; p=0.03) to be associated with inferior OS and TP53MUT (N=10; HR 13.4, 1.7-108.6; p=0.02) with inferior LFS. Age-adjusted MVA combining groups A and B (N=489) confirmed the association between inferior OS and ASXL1MUT (N=51; p&lt;0.01) and SF3B1MUT (N=18; p&lt;0.01) while inferior LFS was associated with TP53MUT (N=14; p&lt;0.01) and ASXL1MUT (p=0.03). Conclusions The majority (⁓73%) of patients with post-ET AML harbor TP53MUT, at the time of LT. By contrast, TP53MUT are infrequent in ET-CP (⁓1%) and did not appear to predict LT, as was the case with post-ET MF. ASXL1MUT was shown to be an independent risk factor for OS, MFFS, and LFS in ET-CP and for OS in post-ET MF. SF3B1MUT was associated with inferior OS and MFFS in ET-CP and SRSF2 with inferior LFS in ET-CP. Identifying ET patients with adverse mutations allows for closer surveillance and potentially more tailored therapeutic interventions.

Abstract Background Despite CD19-directed chimeric antigen receptor T (CAR-T) therapy achieving remarkable remission rates in relapsed/refractory B-cell acute lymphoblastic leukemia (R/R B-ALL), long-term survival remains constrained by T-cell exhaustion and immunosuppressive microenvironments. Dasatinib, a tyrosine kinase inhibitor (TKI), has been shown to alleviate T cell exhaustion and enhance CAR-T cell persistence, demonstrating therapeutic synergy in newly diagnosed ALL. However, it may also suppress CAR-T cytotoxicity and is ineffective against BCR-ABLT315I mutations. Third-generation TKIs, including ponatinib and olverembatinib, effectively overcome T315I-mediated resistance, yet their impact on CAR-T cell function and immune modulation remains insufficiently defined. Methods and Results: We first established in vitro co-culture models of CD19 CAR-T cells with the B-ALL cell line NALM6 to evaluate the effects of dasatinib, ponatinib and olverembatinib on resting and tumor antigen-activated CAR-T cells. At clinically relevant concentrations, none of the TKIs affected resting CAR-T viability. In contrast, upon activation, all three TKIs significantly inhibited CAR-T activation, cytotoxicity, and cytokine secretion (IL-2, TNF-α, IFN-γ), while reducing activation-induced CAR-T cell apoptosis. TKIs treatment also downregulated exhaustion markers (eg. PD-1, TIM3, LAG3) and promoted differentiation toward naïve (TN) and central memory (TCM) subsets, while reducing terminal effector T cells. After the drug elution, CAR-T cells regained their cytolytic function in response to tumor targets. Notably, ponatinib-treated CAR-T cells exhibited higher levels of IFN-γ, TNF-α and IL-2 post-washout compared to other groups. Importantly, the TN/TCM phenotype and low exhaustion marker expression were preserved after washout in all TKI-treated groups. Transcriptomic profiling of CAR-T cells in vitro revealed that all three TKIs downregulated key exhaustion-associated genes, including PDCD1, HAVCR2, CTLA4 and NR4A1, along with upregulation of stemness- and memory-associated genes (eg. CCR7, TCF7, LEF1, IL7R). Gene set enrichment analysis showed inhibition of T-cell activation, apoptosis, glycolysis, and TGF-β signaling by all TKIs. Remarkably, ponatinib uniquely activated the IFN-γ pathway, suggesting superior immunostimulatory effects. Mechanistically, all three TKIs suppressed the phosphorylation of AKT, p38 MAPK, and NF-κB p65, indicating shared inhibition of downstream TCR signaling. Based on these findings, we evaluated ponatinib in a clinical setting. A prospective study (No. ChiCTR2000036350) enrolled three R/R B-ALL patients with the BCR-ABLT315I mutation. All the patients received CD19 CAR-T cell therapy followed by ponatinib maintenance, initiated two months post-infusion. All three patients remained progression-free during ponatinib maintenance. Notably, the DNA copies of CAR-T cells remained detectable at months 5 and 9 after ponatinib treatment in two patients, respectively. To further explore the in vivo effects of ponatinib on T cells and other immune cells,peripheral blood mononuclear cells were collected from these patients before and one month after ponatinib initiation for single-cell RNA sequencing. Ponatinib exposure led to an increased proportion of CD8+T cells and a decreased abundance of myeloid cells subsets. Within T cells, effector cells expanded while Tregs and exhausted T cells decreased. Differential gene analysis showed suppression of activation, adhesion, apoptosis, and PD-1/PD-L1 signaling, aligning with in vitro results. Functional scoring revealed enhanced cytotoxicity, IFN-γ responses, and reduced glycolysis, exhaustion, TGF-β, and Treg signatures. Furthermore, analysis of NK cell subsets showed enhanced cytolytic scores and enrichment of proliferation and immune activation pathways, suggesting that ponatinib preserves innate immune responses in vivo. Conclusions: This study provides preclinical and preliminary clinical evidence that third-generation TKIs, particularly ponatinib, can effectively alleviate CAR-T cell exhaustion, promote memory phenotypes, and remodel the immune microenvironment. Compared to dasatinib and olverembatinib, ponatinib uniquely enhances effector cytokine production and activates the IFN-γ pathway. These findings support ponatinib as a promising combinatorial agent with CAR-T therapy, offering a rational strategy for improving outcomes in patients with T315I-mutated R/R B-ALL.

Abstract Introduction: VEXAS (vacuoles, E1 enzyme, X-linked, autoinflammatory, somatic) is an adult-onset autoinflammatory disorder defined by somatic UBA1 mutations in hematopoietic stem cells (HSCs). Given the higher median age at onset and prevalent inflammation, approximately 60% of patients have concurrent clonal hematopoiesis (CH) involving epigenetic regulators, DNMT3A and TET2. We have previously demonstrated (Gutierrez-Rodrigues, Blood 2023) that DNMT3A and TET2 mutations in VEXAS are independently associated with increased mortality, without an increased risk of myelodysplastic syndrome (MDS) or acute myeloid leukemia (AML). To define the role of CH in VEXAS, we investigated the impact of CH on mortality and related epigenetic dysregulation in primary VEXAS patient samples and validated these findings using an adenine base-editing (ABE) strategy to model cooccurring UBA1 and DNMT3A mutations in CD34+ HSCs. Methods: After IRB approval, 114 VEXAS patients from the Mayo Clinic and the NIH were retrospectively assessed, including 104 screened for CH by error-corrected DNA sequencing (ECS). DNA methylation changes were identified using the Illumina Infinium MethylationEPIC BeadChip and genome-wide using Biomodal 6-base sequencing on peripheral blood samples (PB). Cellular indexing of transcriptomes and epitopes (CITE)-seq was performed using the 10x Chromium 3' GEX platform; 21,114 pooled cells were subjected to UMAP dimensionality reduction, followed by Azimuth based cell identification. HSCs from different donors were base edited for UBA1 M41T mutation with and without cooccurring DNMT3A splice-site mutations. Levels of cytokines in cell culture supernatants were measured using Olink technology, transcriptomic changes were assessed using bulk RNA-seq. Statistical analyses were carried out using R. Results: Patients' median age was 68 (62-74) years; 95% were white and 99% were males. 39% had a pathogenic CH variant, with DNMT3A (18%; median VAF: 42%; range 6-46%) and TET2 (11.5%; median VAF: 11%; range: 2-37%) being most common (2% had both). While the presence of any CH mutation did not impact survival (7.7 vs 11.5yrs, p =0.69), DNMT3Amt CH had an age-independent negative impact on mortality (9.2 vs 5.6yrs, p=0.02), without an increased risk of MDS/AML (p=0.31). Changes in DNA methylation were profiled using the methylation array in 19 VEXAS patients without CH (Median Age: 68 years) and in 9 with DNMT3Amt CH (Median Age: 74 years), respectively. VEXAS samples with DNMT3Amt CH displayed a hypomethylation phenotype compared to VEXAS samples with no CH, with 4,096 unique hypomethylated CpGs, occurring mainly at gene enhancers (Enh) and transcriptional states (Tx, TxWk). This loss of DNA methylation was enriched in inflammatory pathways with extensive hypomethylation observed in the promoters and gene bodies of IL-1 family genes. CITE-seq performed on 7 VEXAS samples (4 DNMT3Amt CH vs 3 no CH) demonstrated an upregulation of gene expression predominantly in T-cell subsets. This increased expression was enriched in inflammatory genes, largely centered around IL-1 and IL-18 family signaling. Pathway analysis revealed an enrichment in respiratory electron transport and oxidative phosphorylation (oxphos), with the VEXAS samples with DNMT3Amt CH demonstrating significantly increased oxphos gene signatures. Base editing of CD34+ cells was done using an adenine base-editing (ABE) strategy to model dual UBA1 and DNMT3A splice-site mutations. We observed that the HSCs base edited for the UBA1 M41T recapitulated the cellular hallmarks of VEXAS demonstrating reduced ubiquitination, unfolded protein response (UPR) activation, and increased inflammation. The addition of cooccurring DNMT3A mutations resulted in decreased DNMT3A expression, further increasing inflammatory markers, confirming altered inflammatory and metabolic pathways. Conclusion Our study validates the age-independent, negative prognostic impact of DNMT3Amt CH on survival in VEXAS syndrome. DNMT3A mutations mediate epigenetic and transcriptional priming associated with upregulation of inflammatory and mitochondrial function pathways. These findings have been validated in a base edited cell model with UBA1 and DNMT3A co-mutations.

Abstract Introduction: The DEAD-box helicase 41 (DDX41) gene, located on chromosome 5q35, is a tumor suppressor gene involved in RNA processing. Germline mutations in this gene can predispose patients to myeloid malignancies. Studies have suggested a more favorable prognosis in those with germline mutations in DDX41, with progression of disease being a frequently encountered cause of death. In this retrospective study, we explored the causes of death in a cohort of patients with pathogenic DDX41 mutations. Methods: This was a retrospective study of patients diagnosed with myeloid neoplasms between 2009-2024 and found to have DDX41 mutation (DDX41m) via next generation sequencing (NGS) at our institution. Myeloid NGS was obtained at or after the diagnosis of myeloid disease. Germline testing (when available) was performed through buccal/skin samples. Carriers of DDX41m without a myeloid neoplasm diagnosis and patients with only DDX41m VUS were excluded. Baseline characteristics at the time of myeloid neoplasm diagnosis included age at diagnosis, DDX41m variant allele frequency (VAF), blood counts (hemoglobin, white blood cell count, platelets), cytogenetics, bone marrow blast percentage, number of co-mutations, and treatment received. Unadjusted comparisons were made using continuous or categorical variables. Median overall survival (OS) was calculated from the time of diagnosis with myeloid neoplasm to the time of death, using BlueSky Statistics V.10.3.4. Results: Of the 112 patients identified to have pathogenic DDX41m, 29 (26%) patients were deceased at the time of data analysis. In this cohort of 29 patients (median age at diagnosis 72 years, 17 (59%) males), disease groups at initial diagnosis included 17 (59%) patients with MDS, 9 (31%) AML, and 3 (10%) MPN. Fourteen of the 17 (82%) of the patients with MDS were classified as MDS-EB1 or MDS-EB2. Seven of the 17 (41%) patients with MDS progressed to AML at the time of death, with 57% of the patients having more than 30% bone marrow blasts at time of progression. Blood counts at diagnosis in the cohort included a median hemoglobin of 9.8 g/dL, platelets of 83 x 109/L, and white blood cell count of 2.1 x 109/L. Twenty-one (72%) of patients had normal cytogenetics. Nine (31%) patients had both a pathogenic mutation and a variant of uncertain significance (VUS) in DDX41, with the remaining 20 patients harboring only a pathogenic DDX41 mutation. Eight (27%) patients underwent germline testing, with 7 confirmed to harbor a germline DDX41m. In the deceased cohort, 9 (31%) patients underwent HSCT. Three of the patients with AML and 1 patient with MDS were observed and did not undergo treatment. Median overall survival of the deceased cohort was 29 months. The median time to AML progression in the group with MDS was 14 months. Causes of death included infection in 11 (38%) patients, 9 (31%) with disease progression/relapse, 3 (10%) with acute gastrointestinal graft versus host disease (GVHD), and 1 (3%) from cerebral bleed. The cause of death was unknown in the remaining 5 (17.2%) patients. Infections included pneumonia, bacteremia, neutropenic enterocolitis, fungal, and unknown etiology. Of the 4 patients who were observed, 2 died from unknown cause and 2 died from disease progression. Of the 16 patients with AML at time of death, 9 (56%) died from disease progression or relapse, 3 (19%) from infection, 2 (13%) from GVHD, and 2 (13%) from unknown causes. Of the 10 deaths in the MDS group, 7 (70%) were from infection, 1 (10%) from GVHD, 1 (10%) from cerebral bleed, and 1 (10%) from an unknown cause. Three cases of infection in the MDS group occurred during remission. Infection was a more common cause of death in the MDS group compared to the AML group, where disease progression prevailed as a cause of death (70% vs 19%, p=0.01). Eight (80%) of the patients with MDS who died from infection were neutropenic prior to death, and 4 (50%) of those patients were on neutropenic antimicrobial prophylaxis. Conclusions: In this cohort of 29 deceased patients with a DDX41-mutated myeloid neoplasm, we characterized causes of death. Disease progression/relapse was a significantly more common cause of death in those with AML, compared to infection in patients with MDS. Our work underscores the need for additional studies looking into non-leukemic causes of death in patients with DDX41m myeloid diseases and potential strategies to mitigate infection-related mortality in this population.

Abstract Background Blast transformation (BT) occurs in approximately 15-30% of patients with chronic myelomonocytic leukemia (CMML) and remains a leading cause of death. Allogeneic stem cell transplantation (ASCT) is currently the only treatment modality with the potential to cure the disease or prolong survival. Optimal timing of ASCT is critical for maximizing benefit while minimizing risks. To that end, contemporary risk models have focused on the prognostic relevance of individual, as opposed to concurrent mutations. In the current study, we looked into the possibility of prognostic prominence from concurrent mutations in predicting BT in CMML. Methods CMML diagnostic criteria were according to the International Consensus Classification (Arber et al. Blood 2022; 140:1200). A machine-learning hierarchical clustering algorithm was developed and tailored for patient stratification using survival outcomes and co-expression of genomic alterations. To reduce complexity and improve interpretability, we generalized each cluster using existing rule induction algorithms, including the in Trees framework and JRip. The final output was a set of mutation-based cluster definitions, each representing a distinct patient subgroup with similar survival trajectories. Competing risk analysis and cumulative incidence functions were used in downstream evaluation to validate the clinical distinctiveness of the clusters. For all survival analysis, patients were censored at the time of ASCT. Time-to-BT was calculated from the date of diagnosis to the date of BT or ASCT or last contact. BT-free-survival was calculated from the date of diagnosis to the date of BT, ASCT, death, or last contact. Results The core study cohort included 605 patients from the Mayo Clinic, USA, and the external validation cohort 501 patients from Humanitas Cancer Center, Milan, Italy. Using the patient cohort from the Mayo Clinic, machine-learning algorithms identified five molecular clusters with 3-year blast transformation (BT) rates ranging from 0% to 100% (AUC at 3 years 0.78): the order of molecular signature assignment (probability of BT/death from another cause) was i) PHF6MUT/ASXL1WT (0%/17% at 3 years; N=32), ii) NPM1MUT OR BCORMUT/ASXL1MUT OR SETBP1MUT/NRASMUT (48%/30% at 1 year; N=24), iii) RUNX1MUT/ASXL1MUT OR SRSF2MUT/NRASMUT OR EZH2MUT/ASXL1MUT OR SETBP1MUT OR BCORMUT (31%/55% at 3 years; N=132), iv) ASXL1MUT/TET2MUT OR DNMT3AMUT OR JAK2MUT (24%/28% at 3 years; N=123), and v) all other permutations (10%/40% at 3 years; N=294) [Figure 1]. Additional analysis confirmed significant differences in survival between RUNX1MUT/ASXL1MUT vs. RUNX1MUT/ASXL1WT (p&lt;0.01) OR RUNX1WT/ASXL1WT (p&lt;0.01) OR RUNX1WT/ASXL1MUT (p=0.038) [Figure 2]. Similar patterns of differences in survival were also documented for NRAS/SETBP1, ASXL1/EZH2, and NRAS/SRSF2 mutation combinations (Figure 2). A subsequent Cox regression analysis confirmed independent prognostic contributions from “PHF6MUT/ASXL1WT” (HR 5.43e-10; p&lt;0.01), NPM1MUT (HR 26.7; p&lt;0.01), “SETBP1MUT/NRASMUT” (HR 12.7; p&lt;0.01), BCORMUT(HR 5.8; p&lt;0.01), “RUNX1MUT/ASXL1MUT” (HR 2.3, p&lt;0.01), JAK2MUT (HR 2.1; p&lt;0.01), and “ASXL1MUT/TET2MUT” (HR 1.7; p=0.02). The prognostic relevance of “SETBP1MUT/NRASMUT”, “RUNX1MUT/ASXL1MUT”, NPM1MUT, and BCORMUT was validated in the external cohort from Italy (N=501). In the Mayo Clinic cohort, presence of any of the latter mutations was associated with 1-, 3-, and 5-year BT (death from other cause) rates of 27% (21%), 44% (49%), and 44% (51%), respectively (Figure 3). The corresponding values in the absence of high risk mutations were 7% (15%), 15% (37%), and 18% (52%) [Gray's p value &lt;0.01 for both BT and death from another cause; Figure 3]. Similarly, the 1-, 3-, and 5-year BT (death from another cause) rates in the Italian cohort were 21% (19%), 37% (47%), and 42% (54%) in the presence and 8% (14%), 20% (35%), and 24% (45%) in the absence of high-risk mutations (Gray's p value &lt;0.01 for BT and 0.18 for death from another cause; Figure 4). Conclusions In the current study, machine-learning algorithms enabled the discovery of concurrent mutations in CMML that were shown to be prognostically more significant than their individual constituents. Such prognostic interaction might have contributed to some of the discrepancies noted in current literature regarding the prognostic relevance of certain mutations in CMML and should be accounted for in the development of future risk models.