Alsugair, Ali

ABSTRACT The recently published BLAST clinical risk model for chronic myelomonocytic leukemia (CMML) and its molecular version (BLAST‐Mol) differentiate low, intermediate, and high‐risk groups. The objective of the current retrospective study was to examine the survival impact of allogeneic stem cell transplant (ASCT) in a consecutive series of Mayo Clinic patients ( n = 775; 68% males, median age 71 years) with CMML, overall and adjusted for baseline BLAST/BLAST‐Mol risk categories. At a median follow‐up of 77 months, 151 (20%) patients underwent ASCT. Overall survival (OS) was longer in the ASCT compared to the non‐ASCT cohorts (median 77 vs. 28 months; p < 0.01). The significant difference in OS between the ASCT and non‐ASCT cohorts was retained after adjusting for BLAST clinical risk groups: high‐risk (median 50 vs. 14 months; p < 0.01), intermediate‐risk (81 vs. 28 months; p < 0.01), and low‐risk (111 vs. 65 months; p = 0.04), respectively. The same was mostly the case when OS comparison was adjusted for BLAST‐Mol with respective p values of < 0.01, < 0.01, and 0.08, respectively. Time‐dependent cox models confirmed the favorable survival impact of ASCT in the BLAST/BLAST‐Mol high‐ and intermediate‐risk groups. The current study highlights the benefit of ASCT for BLAST/BLAST‐Mol high‐ and intermediate‐risk groups in CMML and its potential to overcome the adverse impact of some high risk cytogenetic or molecular abnormalities. These observations support the early use of ASCT in CMML, ideally before BT and regardless of genetic characteristics.

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 The comparative value of liposomal cytarabine/daunorubicin (CPX-351) versus venetoclax plus a hypomethylating agent (Ven-HMA) in the frontline treatment of older adults with primary ( de novo ) or secondary acute myeloid leukemia (AML) remains uncertain. In the current study, we retrospectively examined outcomes of 600 patients with newly diagnosed AML treated with CPX-351 (N = 112) or Ven-HMA (N = 488). AML subtypes included de novo (46%), post-myelodysplastic syndrome (MDS) (19%), post-myeloproliferative neoplasm (MPN) (12%), post-MDS/MPN (6%), therapy-related (17%) and AML with myelodysplasia-related genetic abnormalities (AML-MR; 46%). Patients receiving CPX-351 were younger (median 65 vs. 73 years; p < 0.01), predominantly female (50% vs. 38%; p = 0.02), more likely to have secondary AML (68% vs. 51%; p < 0.01), and less likely to harbor NPM1 MUT (5% vs. 12%; p = 0.02). Rates of complete response with or without count recovery (CR/CRi) were comparable between CPX-351 and Ven-HMA (55% vs. 60%; p = 0.30), including in AML-MR (60% vs. 63%; p = 0.70). Ven-HMA use was associated with fewer infectious complications (62% vs. 83%; p < 0.01) and yielded higher CR/CRi rates in males (60% vs. 45%; p = 0.04), de novo AML (68% vs. 50%; p = 0.03), and in the presence of STAG2 MUT (86% vs. 44%; p = 0.02), or CEBPA MUT (88% vs. 50%; p = 0.03). Overall survival censored for transplant, was similar (median 10 vs. 13 months; p = 0.90), with Ven-HMA being superior in post-MDS AML (median 12 vs. 7 months; p = 0.02) and CPX-351 in the presence of SF3B1 MUT (not reached vs. 14 months; p < 0.01). Our findings suggest that Ven-HMA is as effective and less toxic than CPX-351 in newly diagnosed AML, including AML-MR, despite selection of younger, fitter patients for CPX-351.

Abstract Venetoclax (Ven) in combination with hypomethylating agents (HMA) is widely used as frontline treatment in older or unfit patients with acute myeloid leukemia (AML). Liposomal cytarabine and daunorubicin (CPX-351) is FDA-approved for the treatment of secondary AML, including therapy-related (t-AML) and AML with myelodysplasia-related changes (AML-MR). The current study aimed to provide a comprehensive comparison between the two treatment strategies to better inform clinical decisions. Methods The current retrospective analysis was performed under an institutional review board approved minimal risk protocol at Mayo Clinic (MN, AZ, FL). AML-MR gene mutations or cytogenetic abnormalities were categorized according to the International Consensus Classification (Arber et al. Blood 2022;140:1200). Treatment response was assessed according to the 2022 European LeukemiaNet (ELN) criteria (Dohner et al. Blood 2022;140:1345). Overall survival (OS) analysis was censored for allogeneic stem cell transplant (ASCT). Statistical analyses were performed using JMP Pro (Version 18.0.0). Results A total of 600 patients with newly diagnosed AML (ND-AML) treated with CPX-351 (N-112, 19%), or Ven-HMA (N=488, 81%) were included. AML subtypes included de novo (N=277, 46%), post-myelodysplastic syndrome (post-MDS, N=114,19%), post-myeloproliferative neoplasm (post-MPN, N=70, 12%), post-MDS/MPN (N=36, 6%), t-AML (N=103, 17%) and AML-MR (N=274, 46%). Compared with those treated with Ven-HMA, patients receiving CPX-351 were younger (median age 65 vs 73 years; p&lt;0.01), more likely to be female (50% vs 38%; p=0.02), more frequently diagnosed withsecondaryAML (68% vs 51%; p&lt;0.01), and less likely to have NPM1MUT (5% vs 12%; p=0.02) whereas ELN 2022 cytogenetic risk distribution was similar between the two (adverse risk; 43% vs 40%; p=0.5). Comparison of treatment response and survival Complete response rates with (CR) or without (CRi) count recovery were similar between CPX-351 and Ven-HMA overall (55% vs 60%) as well as specifically in patients with AML-MR (60% vs 63%), adverse karyotype (44% vs 44%), NPM1MUT (100% vs 89%), TP53MUT(32% vs 45%), IDH1MUT (60% vs 76%), IDH2MUT (63% vs 77%), SF3B1MUT(71% vs 45%), and CBLMUT (33% vs 69%) [p&gt;0.05 in all instances]. Compared to those with CPX-351, CR/CRi rates with Ven-HMA were superior in males (60% vs. 45%; p=0.04) and in patients with de novo AML (68% vs. 50%; p=0.03), STAG2MUT (86% vs. 44%; p=0.02), or CEBPAMUT (88% vs. 50%; p=0.03); infectious complications were significantly more frequent with CPX-351 (83% vs 62%, p&lt;0.01). At a median follow-up of 12 months (range; 1-88), 416 (69%) deaths, 179 relapses (44% in CPX-351 and 52% in Ven-HMA responders) and 149 ASCTs (53% in CPX-351 and 18% in Ven-HMA) were documented. OS rates were similar between CPX-351 and Ven-HMA, in general (median 10 vs 13 months), as well as in patients with adverse karyotype, TP53MUT, IDH1MUT, and IDH2MUT (p&gt;0.05 in all instances). By contrast, OS was superior in Ven-HMA-treated patients with post-MDS AML (median 12 vs. 7 months; age-adjusted p=0.02) and in CPX-351-treated patients harboring SF3B1MUT(median not reached vs 14 months; age-adjusted p&lt;0.01). In addition, a borderline-significant OS advantage for CPX-351 was apparent in patients with PTPN11MUT (13.5 vs 8 months; p=0.08). Comparison in ICC defined AML-myelodysplasia-related CR/CRi and OS rates were comparable between patients treated with CPX-351 (N=57) or Ven-HMA (N=217), with response rates of 60% vs 63% (p=0.68) and median OS of 10 vs 14 months (p=0.61), respectively. However, OS was superior with Ven-HMA in patients with post-MDS AML (15 vs 8 months; age-adjusted p=0.02) and with CPX-351 in those with SF3B1MUT (NR vs 14 months; age-adjusted p=0.02). Conclusions: The current study suggests that Ven-HMA was as effective and possibly less toxic than CPX-351 for the treatment of ND-AML, including AML-MR, despite the bias for younger and fitter patients treated with the latter regimen. Observed differences involving patients with SF3B1MUT or post-MDS AML require validation in prospective studies and provide parameters for developing treatment-specific predictive models that will be presented at the meeting.

Abstract Background: The recently published BLAST clinical and BLAST molecular (BLAST-Mol) risk models for chronic myelomonocytic leukemia (CMML) incorporate clinical and molecular variables, respectively, for prediction of overall survival (OS), while BLAST-BT (blast transformation) risk model was predictive of BT free survival (BTFS) [Blood 2025;doi:]. In the current study, the Mayo Clinic (USA) CMML cohort used in the aformentioned study was expanded from 457 to 600 patients and merged with an external cohort of 501 patients from the Humanitas Research Hospital (HRH; Italy) in order to validate the BLAST, BLAST-Mol and BLAST-BT risk models. Methods: CMML diagnosis and sub-categorization were according to the International Consensus Classification, which included CMML-1 (BM/PB blasts &lt;10%/&lt;5%) vs. CMML-2 (BM/PB blasts ≥10%/≥5%) and CMML-MP (leukocytes ≥13 x 10⁹/L) vs. CMML-MD (leukocytes &lt;13 x 10⁹/L) [Blood 2022;140:1200]. The BLAST score is based on clinical risk factors including PB blasts ≥2%, leukocytes ≥13 x 109/L, and severe or moderate anemia resulting in BLAST low, intermediate, and high risk groups. BLAST-Mol also accounts for mutations and karyotype and identifies PHF6 and TET2 as “favorable” and DNMT3A, U2AF1, BCOR, SETBP1, ASXL1, NRAS, PTPN11, RUNX1, TP53, as “unfavorable” mutations with adverse karyotype also considered unfavorable. BLAST-BT variables include absence of PHF6MUT, BM blasts ≥10%, presence of DNMT3AMUT, PB blasts ≥2%, leukocyte count ≥13 x 109 /L, and ASXL1MUT. OS analyses were censored for allogeneic stem cell transplant (ASCT). Conventional statistical methods were employed, using JMP Pro 18.0.0 software SAS Institute, Cary, NC, USA. Results: A total of 1,101 patients (median age 73 years; 67% males) with newly-diagnosed CMML were considered: Mayo cohort 600 and HRH cohort 501. Compared to the HRH cohort, the Mayo cohort was more likely to include CMML-MP (44% vs. 28%; p&lt;0.01), CMML-1 (87% vs. 81%; p&lt;0.01), ASXL1MUT (48% vs. 35%; p&lt;0.01), SRSF2MUT (43% vs. 33%; p&lt;0.01), NRASMUT (15% vs 9%; p&lt;0.01), PHF6MUT (7% vs. 4%; p&lt;0.01), and less likely to harbor TET2MUT (50% vs. 58%; p&lt;0.01), and SF3B1MUT (4% vs. 10%; p&lt;0.01) [Table 1]. At a median follow-up of 55 months (range 0-202), 686 (62%) deaths, 218 (20%) BTs, and 142 (13%) ASCTs were documented. CPSS-mol risk categories at diagnosis included low (N=190; median OS 67 months), intermediate-1(N=271; median 38 months), intermediate-2 (N=407; median 26 months), and high (N=231; median 16 months; p&lt;0.01) [AUC at 5 years 0.75]. BLAST clinical risk distribution was low (N=356; median OS 65 months), intermediate (N=393; median 30 months), and high (N= 352; median 16 months; p&lt;0.01) [Figure 1; AUC at 5 years 0.79]. The corresponding AUCs calculated for the Mayo and HRH cohorts, separately, were 0.81 and 0.76, respectively. BLAST-Mol risk assignments included low (N=357; median OS 66 months), intermediate (N=512; median 27 months) and high (N=232; median 15 months; p&lt;0.01) [Figure 2; AUC at 5 years 0.79]. The corresponding AUCs for the Mayo and HRH cohorts were 0.81 and 0.77, respectively. The 3-year cumulative incidence of BT (accounting for death from another cause) stratified by BLAST-BT risk model included 8% for very low risk (N=54), 11% for low risk (N=332), 20% for intermediate-risk (N=281), 27% for high risk (N=250), and 34% for very high risk (N=176) [p&lt;0.01; Figure 3]. Multivariable analysis of the combined Mayo-Humanitas cohort (N=1,101) identified age &gt;65 years (HR 1.7, 95% CI 1.3-2.1), CMML-2 subtype (HR 2.0; 95% CI 1.6-2.5), and a number of other mutations or co-mutations with BLAST-Mol-independent and CPSS-mol-independent prognostic contribution (to be elaborated further at the time of meeting presentation). Conclusions: The current study validates the predictive performance of the BLAST, BLAST-Mol and BLAST-BT risk models in a large two-center international cohort of patients with CMML. The possibility of further enhancement of the BLAST-Mol model is suggested by the demonstration of independent prognostic relevance from additional mutations and co-mutations.

Abstract Introduction Blast transformation (BT) in CMML occurs in 15-30% of patients (pts) with a median overall survival (OS) &lt;6 months (mo). While clonal evolution can be observed, biological mechanisms of BT remain unknown for many pts. Using paired samples from chronic phase (CP) and at BT, this study defines the cytogenetic and molecular landscape of BT-CMML. Methods BT-CMML pts from Mayo Clinic (n=153, 31%), MD Anderson (n=195, 40%), and 7 centers of the Groupe Francophone des Myélodysplasies (n=145, 29%) were included after IRB approval. ICC 2022 criteria defined CMML and AML. Pt data were collected at initial diagnosis or referral at CP and again at BT. Clonal dominance was inferred from a natural log-fold difference of mutation variant allele fractions (VAF). OS was censored at allogeneic stem cell transplant (alloSCT). Single-cell multiomic analyses used the Tapestri platform (Mission Bio). Statistics used R. Results Among 1,883 cases of CMML with a median follow up of 96 mo, 493 (26%) underwent BT. The median age at CP and BT was 69 and 71 years, respectively. BT-CMML pts were predominantly male (69%) and had proliferative CMML (53%) or CMML-1 (69%) in CP; 39% and 33% were considered high-risk by CPSS-Mol and BLAST-Mol criteria, respectively. The median time to BT was 16 mo (interquartile range 7-35 mo) and was not different in males vs females (p=0.60). Compared to their CP parameters (p&lt;0.001 each), pts at BT had lower median hemoglobin (10.8 vs 9.2 g/dL) and platelets (100 vs 44 x109/L) but higher leukocytes (13.9 vs 16.3 x109/L), peripheral blasts (0% vs 14%), and bone marrow blasts (6% vs 32%). Blasts exhibited mostly monocytic (57%) or immature myeloid (40%) differentiation. Abnormal karyotypes (AK) were more prevalent at BT (25% vs 62%, p&lt;0.001). Among 318 pts with paired karyotype data, 221 (69%) had a normal karyotype (NK) in CP, of which 123 (56%) remained normal at BT and 98 (44%) acquired new abnormalities. Conversely, 97 (31%) pts had an AK in CP, of which 67 (69%) acquired abnormalities or increased clonal metaphases (6%), 23 (24%) remained stable, and 7 (7%) reverted to a NK at BT. Overall, 46% acquired and 8% lost a clonal cytogenetic abnormality, while 46% remained unchanged. Numeric (37%) and structural (30%) changes were most common. Complex (12% vs 3%) and monosomal (5% vs 2%) karyotypes were more frequent at BT than in CP. Only 6 (2%) pts acquired an AML-defining rearrangement at BT. Mutational data were available for 248 paired cases. The number of somatic mutations was higher at BT (median 3 vs 4, p&lt;0.001). Mutations in RUNX1 (27% vs 39%), NRAS (23% vs 33%), KRAS (11% vs 17%), FLT3 (6% vs 15%), NPM1 (0% vs 11%), IDH2 (5% vs 11%), and CEBPA (3% vs 10%) were more frequent at BT (all p&lt;0.05). At BT, the average VAF of the dominant clone increased in 32%, decreased in 35%, and remained unchanged (delta ≤5%) in 33%. The most frequent dominant clones both in CP and at BT had mutations in TET2 (8% vs 4%) or co-dominant mutations involving SRSF2-TET2 (7% vs 3%). Mutational clonal evolution was observed in 72%, with mutations gained in 45% and lost from the dominant clone in 19%. The most gained mutations at BT were in NRAS (15%) and RUNX1 (13%). Single cell proteogenomic analyses in 4 selected CP and BT pts shed light on the impact of NRAS and RUNX1 mutations on clonal hierarchies and differentiation. Among 196 fully evaluable cases, a new cytogenetic and/or molecular aberration was uniquely gained in 106 (54%) cases and lost in 9 (5%), with 40 (20%) both gaining and losing a genetic alteration. Forty-one (21%) patients had no identifiable genetic change between CP and BT, suggesting driver alterations outside of that detected by routine analyses. Median OS was 31 mo from CMML diagnosis and 5.6 mo from BT. Compared to supportive care, treatment in CP did not prolong median time to BT (14 vs 17 mo, p=0.91) or OS (35 vs 29 mo, p=0.05), regardless of intensity. After BT, median OS was 1.2 mo with supportive care (n=83), 8.7 mo with a hypomethylating agent (HMA, n=39), 10 mo with HMA plus venetoclax (n=37), 7.8 mo with chemotherapy (n=91), and 31 mo in pts who underwent alloSCT (n=57). Conclusions In this large BT-CMML cohort, cytogenetic (46% gained, 8% lost) or mutational (45% gained, 19% lost) driver events were identified in 79% of pts, with 21% having no identifiable changes by conventional testing. Whole genome/transcriptome analyses are underway in this subgroup to identify novel drivers of BT.

Abstract Background: VEXAS (Vacuoles, E1 enzyme, X-linked, Autoinflammatory, Somatic) syndrome is a hemato-inflammatory syndrome due to somatic mutations in UBA1 gene. Recently, DNA methyltransferase inhibitors (specifically, 5-azacitidine) and allogeneic hematopoietic stem cell transplantation (alloHSCT) have shown success in eradication of UBA1 clones and clinical remission in some patients. This study aims to provide a comparative efficacy analysis between DNA methyltransferase inhibitors (hypomethylating agents/HMA) versus alloHSCT in VEXAS syndrome patients. Methods: This is a multi-center, retrospective cohort study. UBA1 mutations were detected either through next generation sequencing [NGS, limit of detection (LOD) 2% variant allele fraction (VAF)] or quantitative droplet digital polymerase chain reaction testing (ddPCR, LOD 0.5% VAF). Outcomes of interest included overall survival (OS), glucocorticoid (GC) discontinuation/reduction in dose (prednisone &lt; 10 mg/day), and complete molecular remission (CMR, defined as an undetectable UBA1 mutation). OS was calculated from the time of diagnosis to death or last follow up. Cumulative incidence of reduction in GC dose was calculated using competing risk analysis after accounting for death. Results: Between years 2020-2024, a total of thirty-nine male patients (median age 67, range 45-82 years) with VEXAS syndrome, necessity for therapy (GC-refractory inflammation and/or progressive marrow failure/myeloid neoplasm) and confirmed UBA1 pathogenic mutation were included. Of these, 18 (46%) received HMA therapy (5-azacitidine 72% and Decitabine 28%) with a median of 4 (range 1-36) cycles. and 21 (54%) underwent alloHSCT (MSD=4, MUD=12, MMUD=2, and haploidentical=3), all received reduced intensity conditioning (Flu/Mel =11, Flu/Bu=5, Flu/Cy/TBI=2, and TBF=3) and 91% received post-transplant cyclophosphamide-based graft-versus-host disease (GVHD) prophylaxis (only 2 patients in alloHSCT group received prior HMA without benefit). Baseline characteristics were well-balanced between HMA and alloHSCT groups; age at treatment (median 70 vs 65 years, p=0.2), and UBA1 M41V subtype (25% vs 40%, p=0.3), cytogenetic and non-UBA1 mutation abnormalities (p=0.4), prior lines of therapy (median 4 in both, p=0.5), time from diagnosis to therapy (median 7 vs 13 months, p=0.15), indication for therapy (p=0.12), Charlson CI scores (median 4 in both, p=0.4) and HCI-CI scores (median 4 in both, p=0.7). At a median follow-up of 45 (range 7-57) months, 11 (28%) deaths (alloHSCT=3 and HMA=8) were documented. Causes of death included infections (n=6), cardiac disease (n=2), poor graft function (n=2) and pulmonary GVHD (n=1). Compared to HMA therapy, alloHSCT group demonstrated higher rates of GC discontinuation (52% vs 6%, p&lt;0.01) and CMR (evaluable= 22, 100% vs 50%, p&lt;0.01). In the HMA group, 50% (n=9) discontinued therapy after a median of 4 months due to infectious complications or lack of benefit. In the alloHSCT group, 3 (14%) patients developed grade 2 acute GVHD (1-skin, 2-gut, no grade 3-4 acute GVHD) and 4 (19%) experienced moderate to severe chronic GvHD (2-lung, 2-mucocutaneous). In multivariable analysis (MVA) adjusted for age and HCT-CI, alloHSCT was identified as the strongest favorable predictor for OS (HR 0.18 95% CI 0.04-0.8) with similar results when analysis was restricted to transplant-eligible patients &lt; 75 years of age (HR 0.1, 95% CI 0.03-0.6). In a 6-month post-treatment landmark analysis (n=31 evaluable), patients who underwent alloHSCT (n=17) exhibited numerically superior GC discontiuation rate (29% vs 14%, p=0.049) and subsequent OS compared to HMA (2-years OS: 84% vs. 61%, median not reached vs 25 months, 95% CI: 0.06–1.7). In a post-treatment competing risk [GC dose reduction (death)] analysis alloHSCT was associated with superior 2-, and 3-year rates of 57% (10%), and 76% (10%), compared to HMA 22% (24%), and 31% (42%) [p&lt;0.01 (0.04)]. AlloHSCT was also associated with higher rate of CMR (evaluable= 21, alloHSCT N=16 and HMA N=5, 100% vs 60%, p=0.01). At the last follow up, none of the patients who achieved CMR had re-emergence of the UBA1 clone (despite early mixed chimerism). Conclusions: This study represents the largest comparative analysis of alloHSCT versus HMA therapy in VEXAS syndrome, and confirms superiority of alloHSCT in achieving molecular remission, GC discontinuation/dose reduction, and overall survival. Prospective clinical trial confirmation is warranted.

Abstract Introduction Chronic myelomonocytic leukemia (CMML) is a myeloid neoplasm with overlapping features of myelodysplastic syndromes (MDS) and myeloproliferative neoplasms (MPN). Blast transformation (BT) is a frequent complication of CMML with a 3-year risk of approximately 31%. MPN driver mutations (i.e., JAK2, CALR, MPL) are known to occur in CMML but their impact on overall survival (OS) or BT remains uncertain. Methods The current study was conducted under institutional review board approved minimum risk protocols that allowed retrospective collection and analysis of patient data. Diagnostic criteria were according to the International Consensus Classification (Blood 2022; 140:1200). For survival analysis, patients were censored at the time of allogeneic stem cell transplant (ASCT). All statistical analyses were conducted using JMP Pro 17.0.0 software (SAS Institute, Cary, NC, USA) and Bluesky Statistics Software (Worldwide Headquarters, Chicago, IL, USA). Results A total of 612 CMML patients were considered (median age 71 years; 68% males). MPN driver mutations (MPNMUT) were detected in 56 (9%) patients, including 43 (77%) with JAK2, 10 (18%) MPL, and 3 (5%) CALR. The median variant allele frequencies were 44% for JAK2 (range, 0.3–100%), 49% for MPL (range, 0.3–97%), and 50% for CALR (range, 20–80%). Age and sex distributions and CMML-1 vs. CMML-2 representation were similar between CMML patients with and without MPNMUT. On the other hand, CMML patients with MPNMUT were more likely to display higher hemoglobin level (p &lt;0.01), platelet count (p &lt;0.01), absolute neutrophil count (p = 0.02) and leukocytosis (≥13 ×109/L; p &lt;0.01); they were also less likely to be red blood transfusion dependent (p &lt;0.01), display platelet counts of &lt;100 ×109/L (p &lt;0.01) or abnormal karyotype (p= 0.03), present with severe anemia (p= 0.03) or harbor NRAS mutation (p = 0.02). Higher Mutational frequencies of SRSF2 (median 53% vs. 41%; p = 0.01), TP53 (median 8% vs. 2%; p = 0.02) and IDH2 (median 13% vs. 4%; p = 0.01) were noted in CMML patients with MPNMUT. During a median follow-up of 23 months (inter-quantile range 11-51 months) for all 612 CMML patients, 402 (67%) deaths, 118 (19%) BT and 108 (18%) ASCT were documented. Of these, 36 (9%) deaths, 18 (15%) BT and 13 (12%) ASCT occurred in patients with MPNMUT. Median OS for the entire group (N=612) was 32 months with 1-, 2- and 3-year OS rates of 78%, 58% and 47%, respectively. There was no significant difference in OS between CMML patients with or without MPNMUT (median 41 vs 31 months; p = 0.27). Thrombotic events were reported in 53 (9%) patients after diagnosis of CMML, including 48 venous and 5 arterial events. There was no significant difference in arterial (p = 0.10) or venous (p = 0.76) thrombosis-free survival between CMML patients with or without MPNMUT. Among all 612 patients with CMML, followed for a median of 18 months for living patients, 118 (19%) experienced BT, with 1-, 3-, and 5-year BT rates of 10.8%, 23.1%, and 31%, respectively. Cumulative incidence analysis function (CIF) was calculated in order to assess the BT-free survival while accounting for death as a competing risk; 3-year CIF was 30% for CMML patients with vs. 18% for those without MPNMUT (Gray's test; p = 0.01). This observation was confirmed in univariate analysis of time to BT (HR 1.7; p=0.03) as well as the corresponding multivariable analysis involving other mutations and clinical risk factors: MPNMUT (HR 1.8; 0.036), ASXL1MUT (HR 2.3; p&lt;0.01), DNMT3AMUT (HR 2.6; p&lt;0.01), CMML-2 vs. CMML-1 (HR 3.4; p&lt;0.01), and leukocyte count ≥13 ×109/L (HR 2.0; p&lt;0.01). SRSF2, IDH2, and TP53 mutations did not impact BT. Notably, the aforementioned risk factors for BT, including ASXL1MUT and DNMT3AMUT, were no longer significant when analysis was restricted to patients with MPNMUT. Conclusions The current study suggests a higher risk of BT in CMML patients with MPNMUT, independent of other molecular or clinical risk factors for BT. On the other hand, overall and thrombosis-free survival did not appear to be similarly influenced. The differential impact of previously recognized risk factors for BT in CMML (e.g., ASXL1MUT, DNMT3AMUT, CMML-2, CMML-MP), in the presence (lost significance) vs. absence (remained significant) of MPNMUT was intriguingly noted.

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.