Faldu, Priyansh

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.

6588 Background: TET2 is the most frequently mutated gene in chronic myelomonocytic leukemia (CMML) and has been associated with favorable outcome, with recent studies suggesting a more pronounced prognostic impact in the presence of ≥2 TET2 mutations ( Csizmar et al. leukemia 2025;39:2030; Kynning et al. Br J Haematol. 2025 Nov 25. doi: 10.1111/bjh.70264 ). We sought to determine if this particular observation extended to patients with ≥3 TET2 mutations ( TET2 MUT ) and also held true in the context of recently reiterated genetic risk factors. Methods: The current study was conducted under institutional review board approved minimum risk protocols allowing retrospective patient data collection and analysis. Diagnostic criteria were according to the International Consensus Classification (Arber et al. Blood 2022. 140:1200). All statistical analyses were conducted using JMP 18 software. Results: 536 CMML patients who underwent CLIA-approved NGS testing were stratified according to the number of TET2 MUT : 221 (41%) wild-type, 148 (28%) with one, 153 (29%) 2, and 14 (2%) ≥3 TET2 MUT . Co-mutation frequencies with significant differences between one vs. two TET2 MUT included ASXL1 (46% vs. 29%; p<0.01), KRAS (7% vs. 14%; p=0.02) and SETBP1 (5% vs. 0.6%; p=0.02). Phenotypic comparisons revealed preponderance of prognostically favorable traits associated with wild-type TET2 but no significant differences between one vs. two TET2 MUT . In age-adjusted univariate analysis, transplant-censored overall survival (TCOS), calculated from the time of mutation detection, was superior in patients with one (p<0.01; HR 0.7) or 2 (p<0.01; HR 0.4) but not ≥3 (p=0.4) TET2 MUT , vs. those with wild-type TET2 . TCOS was also superior with 2 vs. 1 (p=0.02; HR 0.7) but not with ≥3 vs. 1 (p=0.7) TET2 MUT ; the results were similar when TCOS was calculated from the time of diagnosis. Multivariable analysis confirmed the survival advantage of exactly two TET2 MUT vs. wild-type TET2 (p<0.01; HR 0.5), one TET2 MUT (p<0.01; HR 0.6), or ≥3 TET2 MUT (p<0.01; HR 0.4), after adjusting for age, sex, anemia, circulating blasts ≥2%, and leukocyte count ≥13×10⁹/L. The favorable impact of exactly two TET2 MUT persisted in CMML-MD and CMML-MP and remained independent of TET2 VAF, mutation type, karyotype, and other prognostically relevant mutations. This association was sustained in the BLAST (p<0.01; HR 0.5) and CPSS-mol (p=0.02; HR 0.7) models, but not in BLAST-mol model (p=0.12). Conclusions: Mechanistic explanation for this novel observation includes the possibility that TET2 mutational categories based on mutation count reflect distinct biological states rather than having a simple linear effect. The persistence of this signal despite adjustment for established molecular and genetic risk factors supports its consideration in the development of future CMML prognostic models.

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: 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 Background: Myeloproliferative neoplasms (MPNs) are associated with an elevated risk of thrombotic and hemorrhagic complications. Selective serotonin reuptake inhibitors (SSRIs), commonly prescribed for major depressive disorder and various anxiety disorders, exert a dual effect on platelet function, displaying both prothrombotic and pro hemorrhagic tendencies. However, their impact on vascular outcomes in patients with concomitant MPNs remains unclear. The current study examines the association between SSRI use and the risk of thrombotic and bleeding events in patients with MPNs. Methods: We conducted a retrospective, propensity matched study using the TrinetX network database. Patients &gt;18 years of age, diagnosed with any of the following MPNs: Polycythemia Vera (PV), Essential Thrombocythemia (ET), or Primary Myelofibrosis (PMF) were included. The cohorts were then compared between MPN patients prescribed SSRIs after this diagnosis to those who were never on SSRIs. Patients who were ever prescribed Serotonin Norepinephrine Reuptake Inhibitors (SNRIs) were excluded. Propensity score matching was applied to match demographics and comorbidities. The primary outcomes were all-cause mortality and risk of thrombotic events like deep vein thrombosis (DVT), pulmonary embolism (PE), stroke and myocardial infarction (MI). Secondary outcomes were risk of gastrointestinal (GI) bleeding and intracranial hemorrhage (ICH). Results: Propensity score-matching resulted in 10,920 patients in each group, with MPNs, with and without SSRI use respectively. All-cause mortality was higher in those with SSRI use, Hazard Ratio 1.094, (95% CI 1.006, 1.19). The risk of thromboembolism was higher in those with SSRI use: venous thromboembolism, OR 1.968 (1.666, 2.324), PE, OR 2.225 (1.754, 2.824), Stroke OR 3.019 (2.556, 3.566) and MI OR 2.72 (2.288, 3.233). The risk of bleeding was as follows: GI bleeding OR 2.123 (1.877, 2.401) and ICH OR 2.893 (2.268, 3.691). Conclusion: The current study suggests that SSRI use in patients with MPNs is significantly associated with increased risk of thrombosis and bleeding, particularly stroke and ICH. SSRIs predispose to thrombosis by transiently elevating serotonin levels, causing a pro inflammatory state, impaired fibrinolysis, and vascular endothelial dysfunction. However, with chronic use, SSRIs can deplete intraplatelet serotonin levels, impairing platelet aggregation causing an increased risk of bleeding, especially in conjunction with antiplatelet or cytoreductive agent use. Given the high prevalence of SSRI use, our study underscores the need for further prospective studies, heightened clinical vigilance when prescribing SSRIs in patients with MPNs and potential consideration of alternate agents, using individualized treatment strategies.

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: Paroxysmal nocturnal hemoglobinuria (PNH) is a clonal hematopoietic stem cell disorder caused by PIGA mutations, resulting in complement-mediated hemolysis. Myeloproliferative neoplasms (MPNs) are also clonal hematopoietic stem cell disorders driven by mutations in JAK2, CALR, or MPL, and include polycythemia vera (PV), essential thrombocythemia (ET), and primary myelofibrosis (PMF). Although the coexistence of PNH and and MPN is rare, both entities are associated with anemia and an increased risk of thrombosis. The main objectives of the current study were to characterize the clinical phenotype, and evaluate treatment outcomes, including response to complement inhibition in patients with treatment-requiring PNH and MPN. Methods A Mayo Clinic database search was conducted following Institutional Review Board approval to identify patients with PNH and MPN. Between January 2000 and June 2025, 11 patients had a pathologic diagnosis of MPN per the International Consensus Classification, and PNH requiring therapy. Clinical features, including hemolysis and/or thrombosis, and therapeutic interventions were recorded. Results The study cohort included 11 patients (median age 63 years; 73% male) with MPN (6 with PMF, 3 ET, 1 post-ET MF, 1 post-PV MF) in whom PNH was diagnosed concurrently (n=5), or at a median of 9 years (range: 2-15) after MPN diagnosis (n=6). In 9 of 11 patients (82%), PNH workup was initiated due to hemolytic anemia, while in 2 patients (18%), it was prompted by splanchnic vein thrombosis. Transfusion-dependent anemia was present in 6 patients (54%). PNH clone size [median (range)] was 0.58% (0–10.96%) in red blood cells, 18.82% (0–91.2%) in granulocytes, and 23.27% (0–98.8%) in monocytes. MPN driver mutations were evaluated in 8 cases and identified mutations in JAK2 (n=3), CALR (n=4), and MPL (n=1); two additional cases were negative for JAK2 mutations. Next-generation sequencing (NGS) was performed in 6 patients and identified ASXL1, ZRSR2, and SF3B1 mutations in one case each. Cytogenetic analysis (n =10) demonstrated an abnormal karyotype in 3 patients (30%), all of which were categorized as favorable risk. First-line treatment for PNH included complement inhibitors in 9 patients (82%), with eculizumab (n=8), or ravulizumab (n=1). Hemolysis was controlled in only 2 of 9 (22%) patients; one patient treated with eculizumab achieved durable anemia response for five years, while another patient achieved transfusion-independence within three months of eculizumab initiation. 3 patients underwent allogeneic stem cell transplant (ASCT); 2 achieved remission with follow up exceeding 5 years, while the third patient experienced PNH recurrence five months after transplant. The latter received donor lymphocyte infusions and eculizumab was re-initiated resulting in eradication of the PNH clone. Among patients treated with complement inhibitor and not transplanted, 4 of 6 (67%) were transfusion-dependent at last follow-up. Notably, one patient with PNH clone size of 91.19 % in granulocytes, had ongoing hemolysis despite dual complement blockade with ravulizumab and danicopan. Treatment for MPN included hydroxyurea (n=5), ruxolitinib (n=4), pacritinib (n=1), and erythropoiesis stimulating agents (n=4). Additionally, two patients each received antiplatelet therapy alone, anticoagulation alone, or a combination of antiplatelet and anticoagulation. During a median follow-up of 8.4 years (range, 0.6-19), 2 patients (18%) experienced venous thrombosis, and 1 patient (9%) had progression to myelodysplastic syndrome. 5 patients (45.5%) died, with sepsis as the cause of death in 3 cases. The incidence rate of thrombosis was 22 events per 1,000 person-years. Recurrent thrombosis was observed in a 68-year-old male with CALR-mutated MF and PNH clone size of 14.65% in granulocytes, with history of portal vein thrombosis. Despite treatment with eculizumab and low-molecular weight heparin, he developed thrombosis involving the inferior vena cava, common iliac, and hepatic veins. The second event occurred in a patient who developed deep venous thrombosis, while in remission and not on anticoagulation. Conclusion The current study represents the largest series of patients with treatment-requiring PNH and MPN. It reveals a predominance of MF patients, particularly among those harboring CALRmutations, and underlines suboptimal efficacy of complement inhibitor therapy in this patient 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.