Patnaik, Mrinal M.

Background TP53-mutant (mt) myelodysplastic syndromes (MDS) are high-risk (HR) neoplasms, with high rates of AML progression and suboptimal response to hypomethylating agents (HMA). Given the lack of effective therapies for HR-MDS, azacitidine (AZA) was combined with venetoclax (VEN) in a phase Ib MDS study demonstrating safety and early efficacy (Garcia et al. ASH abstract 2023). We retrospectively sought to explore clinical outcomes comparing VEN + HMA, to HMA alone in TP53mt HR-MDS. Methods Among 221 TP53mt MDS pts treated at the Mayo Clinic between January 2007 and April 2024, we reviewed outcomes of pts who received HMA alone (n=98) or HMA+VEN combination (n=34) as their first-line chemotherapy regimen. MDS diagnosis was based on the 5th edition of WHO classification of hematolymphoid tumors (Khoury et al. Leukemia 2022). Responses were assessed according to the International Working Group 2006, MDS response criteria (Cheson et al Blood 2006). Results Baseline characteristics and response The median age (years [yrs]) was 65 (R,37-80) and 70 (range [R], 19-87) yrs in the HMA + VEN and HMA alone groups (gps) (p= 0.42), respectively. The median bone marrow (BM) blast % (9.5 [R, 0-18] vs 5 [R, 0-16], p= 0.01) and TP53 variant allele frequency (VAF) (42 [R, 6-96] vs 37 [R, 2-94], p= 0.03) were significantly higher in HMA + VEN compared to HMA gps, respectively. However, proportion of pts with biallelic (BA)/multihitTP53mt (85% vs 79%, p= 0.61) and complex cytogenetics (CG) (85% vs 81%, p= 0.85) were not different between HMA + VEN and HMA alone gps. The distribution of pts with frequently occurring myeloid co-mutations (ASXL1, TET2, DNMT3A, RAS, BCOR and splicing factor) were not significantly (NS) different between the two gps. IPSS-M scores were assessed in 108 (83%) pts; HR/very HR-MDS as per IPSS-M were NS different between HMA + VEN and HMA gps (100% vs 91%, p= 0.12). While the overall response rate (ORR) (76% vs 49%, p= 0.01) and marrow complete remission (mCR) rates (21% vs 7%, p= 0.05) were higher with HMA+VEN compared to HMA, CR rates were similar (17% vs 12%, p= 0.47). Higher proportion of pts were bridged to allogeneic stem cell transplantation (allo-HCT) (41% vs 20%, p= 0.02), while AML progression rates (29% vs 31%, p= >0.99) were comparable between HMA + VEN and HMA gps, respectively. The non-relapse mortality (NRM) at day 60 (3% vs 3%, p=0.96) and day 90 (3% vs 4%, p=0.75) were comparable between HMA + VEN and HMA gps, respectively. RFS and OS The median follow-up from the time of initiation of HMA or HMA + VEN was 9.7 months (mo) (R, 0.3-90.6). The median RFS (8.47 vs 9.90 mo, p= 0.83) and OS (16.33 vs 14.20 mo, p= 0.66) from the time of initiation of therapy were comparable between the two gps. Similarly, among transplanted pts, there was no OS difference between HMA (21.7 mo) and HMA + VEN (18.43 mo) gps, respectively (p= 0.72). Comparable results for OS and RFS were obtained in both gps after censoring pts at the time of allo-HCT. Multivariable analysis for RFS and OS We conducted multivariable analysis (MVA) for RFS and OS using baseline variables that were significant/ trended towards significance (p<0.1), on univariate analysis (UVA) censored at the time of allo-HCT. Achieving ORR (HR; 0.30, 95% CI: 0.14-0.62, p= 0.001) retained significance for better RFS in MVA. Interestingly CR (HR; 1.74, 95% CI; 0.63-4.77, p= 0.28), BA TP53mt (HR; 1.27, 95% CI; 0.13-11.72, p= 0.83) and complex CG (HR; 1.52, 95% CI 0.16-14.03, p= 0.70) did not retain significance for RFS in MVA. In MVA for OS, achievement of ORR (HR; 0.56, 95% CI; 0.30-1.05, p=0.07) and CR (HR; 0.32, 95% CI; 0.09-1.11, p=0.071) trended towards favorable OS. BA TP53mt status (p= 0.42) and complex CG (p= 0.19) did not significantly impact OS in UVA. Conclusion We conclude that while HMA+VEN combination therapy in comparison to HMA monotherapy led to improved response rates, with higher percentage of pts being bridged to allo-HCT, this was not associated with reduced risk of AML transformation, or improved RFS/OS. We eagerly await results from the prospective randomized trial of VEN + AZA in treatment-naïve HR-MDS (VERONA).

Introduction: ASXL1-mutant Chronic Myelomonocytic Leukemia (CMML) is a high-risk myeloid neoplasm characterized by epigenetic remodeling and overexpression of leukemogenic driver genes. DLK1 (delta-like homolog 1) is a non-canonical Notch ligand, crucial for the proliferation of early hematopoietic progenitor cells and its expression is controlled by maternal imprinting. DLK1 expression is restricted to select progenitor populations, but was found to be overexpressed in several malignancies including ASXL1-mutant CMML. Here we investigate the molecular mechanisms that drive the aberrant re-expression of DLK1 and postulate potential targeted therapeutic interventions. Methods: We performed bulk RNA- and ChIP-seq (H3K4me1/3, H3K27ac/me3, H2AK119ub, H2BK20ac) on bone marrow mononuclear cells from 20 patients with CMML (11 ASXL1-mutant, 9 -wildtype). All libraries were sequenced on an Illumina NovaSeq instrument. Differential gene expression and histone modification occupancy between ASXL1-mutant and -wildtype patients were assessed. Single-cell RNA-seq was performed for a subset of patients to investigate the cell populations of interest for DLK1 expression. To assess DLK1 allelic expression, we identified a single nucleotide polymorphism (SNP) in the coding region of DLK1 (rs1802710) and used cases which were confirmed heterozygous by Sanger sequencing. DLK1 transcript levels were quantified by RT-PCR, and the relative abundance of alleles was measured using digital droplet PCR. We designed primers to amplify the region around our SNP of interest and utilized high mismatch discrimination locked nucleic acid (LNA) probes labeled with FAM (reference SNP allele) and HEX (alternate SNP allele) to quantify specific alleles. The number of RNA molecules originating from each allele was quantified by counting the number of droplets that fluoresced with the corresponding probe colors. Illumina 850K EPIC microarrays were used to evaluate DNA methylation. Drug studies were carried out in progenitor colony forming assays derived from ASXL1-mutant patients (bone marrow mononuclear cells) with the dual BRD4 and p300 / CBP inhibitor EP31670 (62 nM, 24-hour exposure), quantifying DLK1 expression by real-time RT-PCR. Results: This study included 20 patients with CMML (median age at diagnosis 74 years). All ASXL1 mutations were typical hotspot mutations (most commonly Gly646Trpfs*12) and the variant allele frequencies were compatible with heterozygosity (median 0.41). The spectrum of co-mutations was typical and included TET2 (23%), SRSF2 (16%), CBL (7%), among others. DLK1 was strongly overexpressed in ASXL1-mutant patients (log2 fold-change +4.0, FDR < 0.001). Allele-specific gene expression studies (n = 3) revealed the re-expression of the imprinted maternal DLK1 allele in ASXL1-mutant patients. Single-cell gene expression studies (n = 5) demonstrated that the DLK1 overexpression is restricted to the hematopoietic progenitor cell population. Differential methylation analysis between patients with ASXL1-mutant clonal hematopoiesis (n = 4) and matched controls (n = 8) identified two hypermethylated CpG islands in the DLK1 promoter region (cg18122767, Δß = +8.6%, p = 0.021 and cg15831296, Δß = +5.8%, p = 0.008). Histone modification analysis identified DLK1 as a p300 target gene by mapping H2BK20ac onto established ASXL1-mutant-specific enhancer regions (H3K4me1 + H3K27ac co-occupancy). The distal enhancer EH38D2760182 was predicted to bind p300 and to govern the expression of DLK1. ChIP-seq experiment in K-562 and Kasumi-1 cells showed the binding of BRD4 and p300 to EH38D2760182, respectively. Targeting BRD4 and p300 using EP31670 led to the downregulation of DLK1 expression (mean fold-change = 0.569, p < 0.001, n = 3) in progenitor colony forming assays. Conclusions: We observed the aberrant re-expression of the maternally imprinted DLK1 allele in patients with ASXL1-mutant CMML. Both DLK1 promoter hypermethylation and the genotype-specific activation of enhancers by p300 were identified as putative regulatory mechanisms. The distal enhancer EH38D2760182 was found to bind BRD4 and p300 and the pharmacologic disruption of BRD4 / p300 activity in model systems led to the downregulation of DLK1. The clinical-grade dual inhibitor of BRD and CBP / p300 EP31670 is currently being investigated in patients with ASXL1-mutant chronic myeloid neoplasms (NCT05488548).

Background: While myeloproliferative neoplasms (MPN), including essential thrombocythemia (ET), polycythemia vera (PV), and primary myelofibrosis (MF), are usually sporadic, adult-onset neoplasms, an increasing number of germline risk alleles have been described (e.g. EGLN1, ETV6, SH2B3, and ATM) in these disorders. DDX41MT Germline Predisposition Syndrome (GPS) is the most common myeloid GPS in adults and while there is extensive data on MDS/AML, little is known regarding MPN occurring in this context. We carried out this study to define the prevalence and characteristics of DDX41MT-GPS associated MPN. Methods: After IRB approval, we retrospectively assessed the Mayo Clinic cohort of 174 patients with DDX41MT-GPS, which included both pathogenic and clinically relevant germline variants of undetermined significance (VUS), based on our previous analysis (Badar et al Haematologica 2023). Standard statistical measures were applied. Results: We identified 12 (6.9%) patients with MPN (ET-5, PV-2, PMF-4, MPN-NOS-1). The median age at MPN diagnosis was 61.2 years (range, 8.-70.4); 58.3% (n=7) were male, and 83.3% (n=10) were Caucasian. A family history of hematologic malignancy was present in 16.7% (n=2, AML and T-LGL), while 50% (n=6) had a family history of visceral malignancies and 41.7% (n=5) had no family history of malignancies. Among ET patients (n=5) with DDX41MT-GPS, JAK2V617F was the MPN driver in 4 (80%) while type 1-CALR (L367fs*46) was a driver in 1 (20%). This included a 9-year-old child diagnosed with JAK2V617FMT ET. The DDX41 variant was classified as pathogenic in 40% (n=2; E113Kfs*14, D140Gfs*2) and VUS in 60% (n=3; V544L, V591I, P38L). Bone marrow (BM) aspirates in the ET patients were hypercellular in 40% (n=2), normocellular in 40% (n=2) and hypocellular in 20% (n=1), and none had increased blasts, or reticulin fibrosis (RF). In addition to JAK2V617F, somatic mutations seen included SF3B1 (K666T, VAF 16%) in 1 patient and IDH2 (R140Q, VAF 6%) and DNMT3A (R882H, VAF 7%) in 1 patient, respectively. With a median follow-up from diagnosis of 3.9yrs (range 2.9-8.9), there were no thrombotic events and no disease progressions was documented. There were 2 patients with JAK2V167FMT PV in whom the DDX41MT were clinically significant VUS (c.138+5G>T and M155I). Both patients had hypercellular BM, with no increase in blasts, no RF, normal karyotypes and no additional somatic mutations. With a median follow up of 7.5yrs (range, 2.1-12.9), 1 patient developed a deep vein thrombosis (DVT) and there were no fibrotic or leukemic transformations. There were 4 patients with PMF; 3 (75%) with JAK2V617F and 1(25%) with a type 1-CALR driver mutation (L367fs*46). DIPPS-plus scores ranged from 1 to 4 (median 2.5). The DDX41 variants were pathogenic in 50% (n=2, E256K and P78Qfs*3) and VUS in 50% (n=2, P510S and M155I). The median grade of RF at PMF diagnosis was grade 2 (range, 2-3). BM were hypercellular in 75% (n=3) and hypocellular in 25% (n=1), and 1 patient had 3% peripheral blasts (and no BM blasts). Somatic co-mutations included TET2 in 1 patient with a JAK2V617F, and CBL, EZH2 and SRSF2 in 1 patient with a CALR driver-mutation, respectively. PMF patients were treated with ruxolitinib (n=3), stem cell transplant (n=1), and pIFNα (n=1). With a median follow up of 3.9yrs (range,1.1-21.9), all patients were alive, and none had leukemia transformation. There was 1 patient with a JAK2V617F MPN-NOS with trisomy 9, where the DDX41MT-GPS was a VUS (I215L). There were no somatic co-mutations and at last follow up (3.1 years), there was no evidence for progression. Conclusions: While associations between late onset MDS/AML and DDX41MT-GPS has been well established, we systematically describe the MPN landscape seen in this context. MPN was diagnosed in 7% of our cohort, with JAK2V617F being the most common driver mutation. Most importantly, unlike in AML/MDS, where somatic DDX41 mutations are frequently associated with neoplastic transformation (30-50%; R525H being most common), none of our MPN patients had a somatic DDX41 mutation. Our work underscores the importance of germline mutation testing in patients with MPN.

Background: Clonal cytopenia of undetermined significance (CCUS), a precursor of myeloid neoplasms (MN), is characterized by one or more persistent cytopenias, and acquired mutations in myeloid malignancy-associated genes. ZRSR2, located at Xp22.2, is one of the MN-associated genes and a member of the spliceosome family of genes. Aim: Describe the clinical characteristics, pattern of progression, and genetics of ZRSR2 mutation (ZRSR2m)-harboring CCUS patients. Methods: Next-generation sequencing (NGS) was performed for 9320 patients between 2016-2023 at Mayo Clinic. After obtaining IRB approval, clinical characteristics and results of bone marrow morphology, cytogenetics, and molecular studies were abstracted. Overall Survival (OS) was calculated using Kaplan-Meier, from the date of NGS until death or last follow-up. The ZRSR2m MN control cohort included 125 patients with myelodysplastic syndrome (MDS), myeloproliferative neoplasm (MPN), and MDS/MPN overlap. BlueSky Statistics V10.3.1 was used for statistical analysis. Results: ZRSR2m was detected in 39 CCUS patients, all of whom were males. Concurrent hematological neoplasms were identified in 8 patients (21%). Five (13%) had plasma cell proliferative disorders including 3 multiple myeloma, 1 MGUS, and 1 AL amyloidosis. There were also 2 patients with chronic lymphocytic leukemia and 1 with VEXAS syndrome. Prior chemotherapy, with or without radiotherapy, was given to 4 patients (10.3%), whereas 13 patients (33%) had received previous immunotherapy. Abnormal cytogenetics were detected in 11 patients (29%), with the most common abnormality being +8 (n=5, 13%). In 23 patients (59%), an absolute monocyte count of ≥0.5 x 10^9/L was documented which could be classified as clonal cytopenia with monocytosis of unknown significance (CCMUS). ZRSR2 median gender-corrected VAF among CCUS patients was 32% (range, 1-45). Isolated ZRSR2m was found in 6 patients (15%), and 1 (3%) had multiple ZRSR2m. The median number of co-mutations was 1 (range, 0-3). Sequential NGS, available in 13 patients, showed that 1 patient developed 3 ZRSR2 mutations and 2 ZRSR2 VUS. TET2 was the most common co-mutation (n=25, 64%). Additionally, TET2 was an isolated co-mutation in 18 patients (46%). ASXL1 co-mutation was the second most common (n=8, 20.5%), while other less common co-mutations were IDH1, IDH2, SRSF2, SF3B1, TP53, GATA2, and KDM6A. Pre-ZF1 was the most commonly mutated region in ZRSR2 mutations (n=23, 59%). With a median follow-up of 32 months, 9 (23%) of the ZRSR2m CCUS patients progressed to MNs, none progressed to AML. Five (55.6%) progressed to MDS, 4 were subclassified as low blast (LB) and 1 as increased blast-1 (IB1). Four (44.4%) progressed to MDS/MPN overlap syndrome, with 3 subclassified as chronic myelomonocytic leukemia (CMML). None of the patients with isolated ZRSR2m progressed to MDS or CMML. None of the patients who received prior immunotherapy progressed to MDS. Thirty-six (92.3%) patients had high-risk CCUS (Malcovati et al, Blood 2017) while 3 had intermediate risk with no low-risk patients. None of the intermediate-risk patients progressed to MDS, while 5 patients of the high-risk (13.9%) progressed to MDS (p=1). Twelve (31%) patients died, and the median overall survival (mOS) was 56 months. Higher hemoglobin levels improved OS (HR=0.59, p=0.02), while higher adjusted ZRSR2 VAF worsened OS (HR=1.05, p=0.017). Patients with TET2 as isolated co-mutations showed better mOS than the rest of the cohort (not reached vs 41 months, p= 0.03). ZRSR2m CCUS patients showed a trend suggestive of better mOS than ZRSR2m with MNs including AML (56 vs 30 months, p=0.14), and with excluding AML (56 vs 39 months, p=0.24). On multivariate analysis, both Hgb (HR=0.61, p=0.03) and isolated TET2 co-mutation (HR=0.19, p=0.04) retained statistical significance. mOS was not affected by prior history of treatment, number of co-mutations, isolated ZRSR2, ASXL1 co-mutation, or MDS progression. Conclusion: ZRSR2m CCUS cohort was exclusively males. There was a significant number of patients with concurrent hematological malignancy or a history of prior chemo- and/or immuno-therapy (36%). Most patients had high-risk CCUS but showed a low rate of progression to MNs, especially in those with isolated ZRSR2. Additionally, patients with isolated TET2 co-mutation had better survival, indicating that TET2 confers a favorable prognosis among ZRSR2m CCUS patients.

Background Survival risk models in essential thrombocythemia (ET) include the International Prognostic Scoring System (IPSET; Blood 2012;120:1197) and the more recently described “triple-A” prognostic score that considers Age and absolute neutrophil (ANC) and lymphocyte (ALC) counts, as risk variables (AJH 2023;98:1829). Monocytosis, defined by absolute monocyte count (AMC) of ≥0.8 x 109/L, was recently reported to be associated with inferior survival in polycythemia vera (ASH 2024 abstract). The current study examined the prognostic contribution of monocytosis in ET, in the context of other clinical and genetic risk factors. Methods Study patients were recruited from Mayo Clinic (USA) databases, based on availability of information on ANC, ALC, and AMC (N=649). Diagnostic criteria were according to the International Consensus Classification (Blood 2022;140:1200). Mutations were screened by next-generation sequencing (NGS). Conventional statistical methods were employed (JMP Pro 17.0.0, SAS Institute, Cary, NC, USA) and optimal cut-points for age, ANC, ALC, and AMC were determined by Receiver Operating Characteristic (ROC) analysis. Akaike Information Criterion (AIC) and ROC plots were used to estimate predictive accuracy of risk models. Results A total of 649 patients (median age 60 years; females 65%) were informative for AMC, ANC, and ALC, with median (range) values of 0.6 x 109/L (0.2-2.5), 5.7 x 109/L (1.5-26.5), and 1.9 (0.4-5.7), respectively. At presentation, IPSET risk distribution was low in 34%, intermediate 47%, and high 19%; triple-A risk distribution was low 21%, intermediate-1 50%, intermediate-2 13%, and high 16%; driver mutation distribution was 63.8% JAK2, 24.0% CALR, 3.7% MPL, and 8.5% triple-negative; median for platelets were 728 x 109/L, hemoglobin 13.9 g/dL, and leukocytes 8.5 x 109/L ; leukocytosis (leukocytes ≥11 x 109/L) was documented in 18.8% of patients, palpable splenomegaly 7%, arterial thrombosis (AT) history 14.5%, venous thrombosis (VT) history 9.2%, and major hemorrhage 7.8%. At median follow-up of 7 years (range 0.02-31.4), 146 (22.5%) deaths, 52 (8%) fibrotic progressions, 22 (3.4%) leukemic transformations, 71 (11%) AT events, 36 (5.6%) VT events, and 64 (10%) major bleeds were recorded. In age-adjusted univariate analysis, higher AMC was significantly associated with inferior survival, with a ROC determined cutoff value of ≥0.8 x 109/L (N=154; 24%); significance was sustained (HR 2.3; p<0.01) during multivariable analysis (MVA) that also identified age >70 years (HR 16.6; p<0.01), age 50-70 years (HR 4.3; p<0.01), ANC ≥8 x 109/L (HR 1.9; p<0.01), ALC <1.7 x 109/L (HR 1.8; p<0.01), and AT history (HR 1.6; p=0.01). A similar MVA conducted on an external cohort from the University of Florence (N=514) confirmed the significant contribution from all of these risk variables, except AT (p=0.8). An HR-based 4-variable prognostic model based on Age >70 years (4 points) or 50-70 years (2 points), AMC ≥0.8 x 109/L (1 point), ANC ≥8 x 109/L (1 point), and ALC <1.7 x 109/L (1 point), henceforth referred to as the AAA+A model, was subsequently developed using the Mayo Clinic cohort and validated by the Florence cohort: Low (0-1 points; N= 180; median not reached), intermediate-1 (2-3 points; N=266; median 21.6 years), intermediate-2 (4-5 points; N=151; median 12.2 years), and high (6-7 points; N=52; median 8.7 years); HR values were 2.1 for high vs. intermediate-2, 5.4 for intermediate-2 vs. intermediate-1, and 3.8 for intermediate-1 vs. low (p<0.001in all instances). The 20-year survival predictive performance of AAA+A (AIC 131; AUC 0.88) was superior to that of AAA (AIC 143; AUC 0.85) and IPSET (AIC 149; AUC 0.84). In MVA that included AAA+A risk variables, AMC ≥0.8 x 109/L (p=0.04) and ALC <1.7 x 109/L (p=0.06) appeared to affect leukemia-free survival and ANC ≥8 x 109/L (p=0.04) myelofibrosis-free survival. In univariate analysis, AMC ≥0.8 x 109/L was associated with AT (p=0.03) but not VT (p=0.14) history and showed borderline significance for venous (p=0.09) and arterial (p=0.07) thrombosis-free survivals; however, significance was lost during MVA. Conclusions: Monocytosis is an adverse prognostic factor in ET and its inclusion as a risk variable enhances the predictive performance of the AAA risk model and is equally simple to apply worldwide. Analyses that include mutations will be presented at meeting.

Background: TP53 mutations (TP53mut) are highly prevalent in therapy-related myeloid neoplasms (t-MN) compared to de novo MN (35-40% vs 7-13%) and are associated with a poor outcome. Understanding the risk factors involved in the pathogenesis of TP53mut t-MN is critical to prevent its development. Methods: We characterized t-MN cases by examining primary cancer type vs autoimmune disease diagnosis vs solid organ transplantation, treatment modality, and latency (interval between primary cancer/disease and t-MN diagnosis) to identify patient and disease-related factors associated with TP53mut t-MN. Allelic loss of TP53mut MN was defined according to International Consensus Classification (ICC) criteria (Arber et al., Blood 2022). Results: Of 587 t-MN patients, 33% (n=194) had acute myeloid leukemia (t-AML) and 67% (n=393) had myelodysplastic syndrome (t-MDS, blasts<20%). Primary diagnosis comprised of 243 (41.6%) solid cancers and 300 (51.4%) hematological malignancies, while 7% (n=41) of t-MN cases had autoimmune disease or underwent solid organ transplant. Overall, 94 (16.1%) patients received prior radiotherapy (RT) alone and 75.6% (n=444) received chemotherapy (CT) with/without RT. 109 patients (18.7%) underwent autologous stem cell transplant (ASCT). The median latency from primary diagnosis to t-MN was 83.2 months (IQR 41.3, 153.2), and there was a trend towards shorter latency in t-AML compared to t-MDS (70.5 vs 85.8 months; P=0.07). Of the t-MN patients, 280 (47.7%) harbored TP53mut, which was associated with significantly poorer survival compared to wild-type (TP53wt) t-MN (9.7 vs 21.9 months; P <0.001). In contrast to TP53wt (59.0% vs 41.0%), the majority of TP53mut t-MN presented with t-MDS vs t-AML (75.7% vs 24.3%; P <0.001). According to ICC criteria, multi-hit MDS (n=131; 47.8%) was the most common entity, followed by AML (n=68; 24.8%), MDS/AML (n=34; 12.4%), and single-hit MDS (n=8, 2.9%). Poor prognostic karyotype changes e.g., del 5q, del 7q, complex karyotype and monosomal karyotype, were more prevalent in TP53mut compared to TP53wt t-MN. Co-mutations in other genes were enriched in TP53wt t-MN. As TP53mut t-MN is associated with a dismal outcome, we assessed the factors associated with its development. There were no significant differences in median age at primary cancer/disease diagnosis (59.0 vs 59.9 years; P=0.4) or gender (females 43.3% vs 39.3%; P=0.3) between TP53mut and TP53wt t-MN. However, TP53mut patients were older at t-MN diagnosis (69 vs 67.4 years; P=0.05). Correlations between gene mutations and prior malignancies revealed a significant association between TP53mut and hematological primary cancers (odds ratio [OR] 1.6; P=0.006), especially multiple myeloma (MM, OR 4.9; P<0.001) and lymphoproliferative disease (LPD, OR 2.0; P=0.013). Among solid cancers, head and neck malignancies were significantly associated with increased risk of developing TP53mut t-MN (OR 7.7; P=0.01). Compared to RT alone, ASCT (OR 2.2; P=0.004) and CT (OR 2.0; P=0.008) were associated with an increased risk of TP53mut t-MN. Recent studies indicate that CT/RT confer a selective advantage to preexisting TP53mut hematopoietic stem and progenitor cells, allowing clonal expansion/evolution and progression to t-MN. We hypothesized that TP53mut t-MN with high-risk disease features is a function of TP53mut clonal expansion/evolution rate and would predict latency between primary cancer and t-MN. Indeed, the latency between primary cancer and t-MN diagnosis was longer in TP53mut (87.8 months, IQR 45.5, 154.1) compared to TP53wt (74.7 months, IQR 37.5, 146.9 months) t-MN (P=0.05). Interestingly, 54% and 29% of TP53mut t-MN had a latency of ≥5 and ≥10 years, respectively. There were no correlations between latency and TP53 variant allele frequency (VAF) (r=0.38 and P=0.7) or between TP53mut t-MDS and t-AML (85.2 vs 109.3 months; P=0.9). Together, latency between primary cancer and t-MN was not associated with TP53mut t-MN phenotype, VAF or other poor-risk disease features. Conclusion: Hematological malignancies, especially MM and LPD treated with high-dose CT, were strongly associated with TP53mut t-MN development, highlighting the importance of careful and ongoing screening in this population. Also, the long latency of TP53mut t-MN provides an opportunity to devise effective surveillance strategies and preventative interventions long before TP53mut t-MN development.

Background: SETBP1 gene, located on 18q12.3, is a major oncogene in myeloid neoplasms. GATA2 gene, located on 3q21, is one of the six GATA transcription factors regulating gene expression via two conserved zinc finger domains (ZF). Previous data suggested that in patients with germline GATA2 mutation (m), acquisition of a somatic SETBP1 mutation (m) was associated with leukemic transformation among patients with excess blast MDS and CMML. Aim: To study the characteristics of patients with somatic SETBP1-GATA2 mutated myeloid neoplasms. Methods: This study is a retrospective study at Mayo Clinic. After obtaining IRB approval, we retrospectively reviewed the charts of patients who had myeloid NGS panel results between 2016-2023. All data were recorded at time of first NGS. Cohort 1 was defined as patients with SETBP1m and GATA2m, cohort 2; patients with SETBP1m and GATA2wt, and cohort 3; patients with SETBP1wt and GATA2m. Germline work-up was not performed in the majority of GATA2 cases. We stratified risk based on the European LeukemiaNet 2022 guidelines for AML, IPSS-M for MDS and MDS/MPN, and CPSS-M for CMML. Overall survival (OS) was calculated from date of NGS to date of last follow-up based on Kaplan-Meier estimates and Cox regression analysis. For statistical analysis, we used BlueSky Statistics V10.3.1. Results: General characteristics: 114 patients had SETBP1m (median VAF= 39%), and 63 patients had GATA2m (median VAF= 35%). Nine patients had co-occurring SETBP1m/GATA2m mutations (cohort 1). 4/9 patients in cohort 1 had MDS/MPN (44.4%), while only 13/105 in cohort 2 (12.4%) had MDS/MPN (P=0.02). AML was seen in 2 patients in cohort 1 (22.2%) compared to18 in cohort 2 (17.1%) (p=0.6). The median WBC count was 22.9 x 109 cells/L among cohort 1 compared to 9 x 109 cells/L among cohort 2 cases (p=0.09). BM blasts were higher in cohort 3 (7%) compared to cohort 1 (5%) and cohort 2 (3%) (p=0.09), while peripheral blasts tended to be lower in cohort 2 (1%) in comparison to cohort 1 (6%) and cohort 3 (4%) (p=0.48). Genetic characteristics: In cohort 1,7 GATA2m clustered in zinc finger 2 (ZF2) (77.8%), while the other two mutations were outside the ZF domains (22.2%). This was higher than the ZF2 mutated cases in cohort 3 (46.3%, p=0.1). Abnormal cytogenetics were seen in 66.7% of cohort 1 patients and 45% of cohort 2 (p= 0.3). Two cases with trisomy 8 were seen among patients in cohort 1 (22.2%), compared to only 4.9% in cohort 2 (p=0.09). Two incidences of isochromosome 17q [i(17q)] were seen in cohort 1 (22.2%), versus 5 cases in cohort 2 (4.8%) and 1 case in cohort 3 (1.9%) (p= 0.068). Co-mutations: The median number of co-mutationswas 3 in both cohort 1 and cohort 2 (p= 0.6). In cohort 1, ASXL1 and SRSF2 mutations were the most common (7/9, 77.8%) followed by NRAS (22.2%) and TET2 (22.2%). 77.8% of cohort 1 patients had SRSF2 co-mutation, compared to 44.8% in cohort 2 (p=0.08), and 27.8% in cohort 3 (p= 0.006). No isolated SETBP1m/GATA2m cases were found. Survival: Patients in cohort 1 had a numerically higher median OS compared to those in cohort 2 (19.4 vs 15.4 months, p= 0.3). When comparing with the cohort 3, patients in cohort 1 tended to have better outcomes (median OS= 19.4 vs 13.8 months, p=0.8). Among cohort 1, SRSF2 co-mutation was associated with worse survival outcomes compared to patients with SRSF2wt (median OS= 5.3 vs 19.4 months, p= 0.02); this association was not found in cohort 2 (12.5 vs 18.4 months, p= 0.3) and cohort 3 (13.2 vs 17.1 months, p= 0.4). Allogeneic hematopoietic cell transplantation was associated with favorable survival outcomes in all cohorts (cohort 1: 22.6 vs 7.8 months, p= 0.1; cohort 2: 20.9 vs 12.5 months, p= 0.04; cohort 3: 25.6 vs 13.1 months, p= 0.03). Conclusion: SETBP1m/GATA2m myeloid neoplasms included a significantly higher proportion of MDS/MPN overlap cases in comparison with the SETBP1m/GATA2wt group. The SETBP1m/GATA2m group had a higher proportion of ZF2 GATA2m and SRSF2 co-mutation compared to patients with SETBP1wt/GATA2m. Survival of SETBP1m/GATA2m patients was not worse compared to SETBP1wt/GATA2m or SETBP1m/GATA2wt.

Background Blast or accelerated phase myeloproliferative neoplasm (MPN-BP/AP) carries a dismal prognosis, with 3-year survival estimates of <5% (BCJ 2023;108). Patients with MPN-BP/AP were excluded from venetoclax (Ven) plus hypomethylating agent (HMA) clinical trials for acute myeloid leukemia (NEJM 2020;383:617). In the current retrospective study, we examined response patterns and long-term survival of newly-diagnosed MPN-BP/AP patients who received treatment with Ven+HMA, outside of clinical trials. Methods Newly-diagnosed patients with MPN-BP/AP treated with Ven+HMA at the Mayo Clinic, between March 2019 and May 2024, were retrospectively reviewed. Diagnostic criteria were according to the International Consensus Classification (Blood 2022;140:1200). Cytogenetic and molecular studies were performed by conventional karyotype and next-generation sequencing, respectively. All patients received at least one cycle of Ven+HMA (azacitidine 75 mg/m2 days 1-7 or decitabine 20 mg/m2 days 1-5). Response was assessed according to the 2022 European Leukemia Net criteria (Blood 2022;140:1345). Standard statistical analyses were performed using JMP Pro (Version 17.1.0). Results Patient characteristics 70 patients (median age 73 years, 59% males, 48% splenomegaly >14 cm, 4% isolated myeloid sarcoma) with newly-diagnosed MPN-BP (n=58) or AP (n=12) received Ven+HMA with (n=13) or without (n=57) concomitant JAK2 inhibitor. Driver mutation distribution was 69% JAK2, 21% CALR, 6% MPL, and 4% triple negative. Mutations involved ASXL1 (31%), TP53 (28%), TET2 (28%), RUNX1 (25%), SRSF2 (18%), IDH2 (12%), U2AF1 (11%), DNMT3A (9%), IDH1 (7%), and K/NRAS (7%). Karyotype was abnormal in 50 (76%) of 66 informative cases, of which 28 (56%) were complex (CK). Median TP53 mutation variant allele frequency (VAF) was 30% (8-96%) and all evaluable cases displayed CK (n=18). Response and Survival Complete remission (CR; 21%) or CR with incomplete count recovery (CRi; 19%) was documented in 28 (40%) patients with residual MPN in 18 (64%) patients. Median response duration was 5.5 months (1-60 months). After a median follow up of 7 months (1-62 months), 48 (69%) deaths, 13 relapses (46%), and 15 (21%) allogeneic stem cell transplants (ASCT; 12 in CR/CRi) were recorded. Median overall survival (OS) was 9 months and was superior with ASCT (median 22 vs. 8 months; p=0.01). In univariate analysis, transplant-censored survival was superior with CR/CRi (12 vs. 5 months; p<0.01) and IDH1 mutation (33 vs. 8 months; p=0.04) and inferior with CK (7 vs. 10 months; p=0.05), TP53 mutation (5 vs. 10 months; p<0.01), post polycythemia vera myelofibrosis (post-PV MF) (3 vs. 9 months; p=0.01), and splenomegaly >14 cm (5 vs. 16 months; p<0.01). Multivariable analysis confirmed the negative survival impact of not achieving CR/CRi (HR 3.8; p<0.01) and presence of TP53 mutation (HR 4.0; p<0.01); median survival (1/3-year survival rate) was 3 months (10%/0%) in TP53 mutated patients not achieving CR/CRi (n=11) vs. 27 months (65%/28%) in TP53 unmutated cases achieving CR/CRi (n=19) (p < 0.01). Median survival in patients with TP53 mutations or CK who achieved CR/CRi (n=7; 7 months) was inferior to that in treatment responders without TP53 mutations or CK (n=18; 23 months; p=0.01). CR/CRi rates in the presence vs. absence of TP53 mutations were 42% vs. 39% (p=0.80) and of CK (25% vs. 50% (p=0.04). Importantly, responses in the presence of TP53 mutations or CK were too short-lived to allow successful bridging to ASCT (median 2 vs. 9 months; p<0.01). Additional predictors of inferior treatment response included splenomegaly >14 cm (24% vs. 53%; p=0.01), and post-PV MF (0% vs. 46%; p<0.01) while SRSF2 (67% vs. 34%; p=0.04) and IDH2 mutations (75% vs. 35%; p=0.03) were associated with favorable response. In multivariable analysis, CK (p=0.04) and splenomegaly >14 cm (p=0.01) remained independent predictors of inferior response. The use of concomitant JAK2 inhibitor therapy did not impact treatment response (CR/CRi 46% vs. 39%; p=0.62) or survival (median 9 vs. 8 months; p=0.71). Conclusions TP53 mutations and CK undermine the value of Ven+HMA, with or without concomitant JAK2 inhibitor, in enabling successful bridging of newly-diagnosed MPN-BP/AP to ASCT. An alternative treatment approach is advised, in the particular scenario, while the observed 3-year survival rate of 28%, in treatment responders without TP53 mutations, is encouraging.

Introduction Oligomonocytic chronic myelomonocytic leukemia (OM-CMML) is defined by relative monocytosis ≥ 10% and an absolute monocyte count (AMC) between ≥ 0.5 and < 1.0 x109/L. The 5th ed WHO and International Consensus Classifications lowered the AMC threshold to ≥ 0.5 x10/9L for CMML diagnosis, thereby incorporating OM-CMML (Khoury, 2022; Arber, 2022). However, prior reports differ as to whether OM-CMML is a distinct CMML subtype. This multi-center study compares the clinical, molecular, and survival features of OM-CMML with myelodysplastic (MD, WBC < 13.0 x109/L) and myeloproliferative (MP, WBC ≥ 13.0 x109/L) CMML with an AMC ≥1.0. Methods After IRB approval, patients with CMML from Mayo Clinic (n = 400, 47%) and MD Anderson Cancer Center (n = 449, 53%) were identified retrospectively. Analyses considered clinical, laboratory, and next generation sequencing parameters at diagnosis or first referral (in chronic phase). Categorical variables were compared by Fisher exact or Pearson χ2 tests and continuous variables by Mann-Whitney U or ANOVA tests. Survival was assessed via the Kaplan-Meier method with outcomes censored at allogeneic stem cell transplantation (alloSCT). P < 0.05 was considered significant. Calculations used BlueSky Statistics (v10.3.1). Results A molecularly annotated cohort of 849 patients with CMML (median age 71 years, 32% female, 90% white, median follow up 31 months [mo]) was categorized as OM-CMML (n = 57, 7%), MD-CMML (n = 394, 46%), and MP-CMML (n = 391, 46%). There were no differences in age or sex across subtypes. No clinical differences were observed between OM-CMML and MD-CMML, with similar hematologic parameters, karyotype distributions, Mayo-Molecular (Patnaik, 2014) or CPSS-Molecular (Elena, 2016) risk stratifications, and rates of leukemic transformation (12% vs 12%, p = 0.98) and death (35% vs 43%, p = 0.27). Cases of OM-CMML had lower WBC counts (median 4.4 vs 24.7 x109/L, p < 0.0001), fewer circulating immature myeloid cells (23% vs 57%, p < 0.0001) and fewer marrow blasts (median 3% vs 4%, p = 0.0065) than MP-CMML. Comparatively, OM-CMML cases were overrepresented in the lower-risk groups of the CPSS-Molecular and Mayo-Molecular models (p < 0.0001). Leukemic transformation (12% vs 20%, p = 0.015) and death (35% vs 52%, p = 0.034) rates were higher in the MP-CMML cohort. Molecular profiles were similar between OM-CMML and MD-CMML, including median number of genes mutated (3 vs 3, p = 0.88). Frequencies of ASXL1 (39% vs 38%, p = 0.91), SRSF2 (48% vs 43%, p = 0.49), DNMT3A (7% vs 5%, p = 0.60), and SF3B1 (4% vs 7%, p = 0.48) mutations were also similar. TET2 mutation frequency was higher in OM-CMML (70% vs 55%, p = 0.031) and occurred in isolation more frequently (12% vs 6%, p = 0.048) compared to MD-CMML. Neither median number of TET2 mutations (1 vs 2, p = 0.87), nor TET2 variant allele fractions (41% vs 44%, p = 0.19) were different between the two groups. Compared to OM-CMML, patients with MP-CMML were more likely to have mutations in ASXL1 (39% vs 56%, p = 0.017), EZH2 (0% vs 9%, p = 0.019), JAK2 (0% vs 9%, p = 0.019), NRAS (7% vs 25%, p = 0.0024), and SETBP1 (2% vs 13%, p = 0.021). RAS family (CBL, BRAF, KRAS, NRAS, PTPN11; 25% vs 54%, p < 0.0001) and signaling pathway (CSF3R, FLT3, JAK2, SH2B3; 2% vs 14%, p = 0.0078) mutations were also more frequent whereas spliceosome mutations (SF3B1, SRSF2, U2AF1, ZRSR2; 61% vs 46%, p = 0.033) were less frequent in MP-CMML. The median (95% CI) overall survival (OS) of OM-CMML patients was 44 (38 - not reached) mo compared to 45 (34 - 60) mo in MD-CMML (p = 0.76) and 23 (20 - 29) mo in MP-CMML (p < 0.0032). Similar results were obtained when comparing the acute leukemia-free survival (LFS) of the OM-CMML (41 mo), MD-CMML (39 mo), and MP-CMML (19 mo) groups. At last follow up (medians 42 and 62 mo, respectively), 33% of evaluable OM-CMML patients had progressed to MD-CMML and 28% of MD-CMML patients had progressed to MP-CMML. No patient with OM-CMML progressed directly to MP-CMML. Conclusions These data show that OM-CMML and MD-CMML are a relatively homogenous subset of patients with similar clinicomolecular profiles and survival outcomes. Although OM-CMML patients are more likely to have TET2 mutations in comparison to other CMML subtypes, they have similar rates of disease progression as MD-CMML. This validates recent modifications to CMML classification criteria, in which OM-CMML cases are included as bona fide CMML.

Background: Age-related clonal hematopoiesis (ARCH) is a precursor state to blood cancers and is associated with epigenetic age acceleration (EpiAgeAccel) (Aging Cell, 2021). While ARCH in combination with AgeAccel has the highest risk for all cause mortality and cardiovascular disease, not much is known about context-relevant clonal hematopoiesis (CRCH) - CH occurring in the context of prior chemo/radiation, bone marrow failure and germline predisposition syndromes. CRCH has a unique mutational signature enriched in genes in DNA damage response and repair (TP53 and PPM1D). To answer this question, we assessed EpiAge in a prospective cohort of patients with both ARCH and CRCH. Methods: Patients were prospectively recruited for CH and EpiAge assessment from the Mayo Clinic CH clinic between 2022 and 2024. Demographic and clinical data including chronologic age, BMI, sex, blood counts, and medical history were recorded at the time of enrollment. CH status was determined using error corrected sequencing on peripheral blood (PB) DNA. All somatic variants with a variant allele frequency (VAF) ≥0.5% were considered as CH. For EpiAge analysis PB DNA was analyzed using the Illumina MethylationEPIC array. The resulting beta values were used to obtain epigenetic age estimates using Horvath's clock (Genome Biol., 2013), Hannum's Clock (Mol Cell., 2013), PhenoAge (Aging, 2018), DunedinPACE (eLife, 2022), and predicted telomere length (Aging, 2019). Results: 106 (62%) of 170 patients assessed were found to have CH, with the most frequent mutations being TET2 (19%), PPM1D (17%), DNMT3A (16%), ASXL1 (9%), and TP53 (6%); median VAF 9.5%. Except for a higher median chronologic age (68 vs 60 years, p<0.001) in the CH group, baseline characteristics including BMI, comorbidities, baseline blood counts, sex and tobacco use history were similar between the two groups. The CH group demonstrated significant EpiAgeAccel by all three clocks: Horvath (p=0.001), Hannum (p<0.001), and PhenoAge (p<0.001); with an increase in biological age of 4.9 years (95% CI 2-7.7) by Horvath clock, 4.8 years (95% CI 2.2-7.5) by Hannum clock, and 7 years (95% CI 2.9-10.5) by PhenoAge, after adjusting for chronologic age, sex, smoking status, and cancer history. CH was also associated with increased DunedinPACE of aging by 0.13 biological year per chronologic year (bioyear/chronoyear) (95% CI 0.06-0.2, p<0.001), and shortened telomere lengths by 0.24kb (95% CI 0.11-0.35, p<0.001) after adjusting for chronologic age and excluding patients with telomere biology disorders. CH patients were then further classified into ARCH-63 (59%) and CRCH-43 (41%). While the median chronological age (69 vs 67 years) was similar between the 2 groups, CRCH patients had lower Hgb [10.9g/dL vs. 13g/dL (p=0.0001)] , lower platelet [146x109/L vs. 192x109/L (p=0.0132)] and lower WBC [4.4x109/L vs. 5.2x109/L (p=0.0345)]. The median BMI, comorbidities, and tobacco use history were similar between the 2 groups. The 3 most common ARCH mutations were TET2 (20%), DNMT3A (19%), and ASXL1 (14%), while, PPM1D (27%), TET2 (18%), and DNMT3A (14%) were frequent in CRCH. There was no significant difference found in median EpiAge via Horvath (68 vs 67.5years p=0.2826), Hannum (65 vs 66 years p=0.9333), or PhenoAge (55 vs 56 years p=0.618) between ARCH and CRCH. However, DunedinPACE of aging was higher in CRCH (1.27 vs 1.18 bioyear/chronoyear p=0.0148) and median telomere length was shorter in CRCH (6.35 vs 6.49kb p=0.0247), in comparison to ARCH. Multivariable regression analysis was completed for both ARCH and CRCH compared to non-CH, adjusting for chronologic age, smoking status, and male sex. While both ARCH and CRCH demonstrated EpiAgeAccel via Horvath(5.8years p=0.0001, 3.4 years p=0.051), Hannum(5years p=0.001, 4.5 years p=0.007), and PhenoAge (6.7years p=0.002, 7.6 years p=0.002) clocks, CRCH more than doubled DunedinPACE (0.2 bioyear/chronoyear, p<0.001) of aging compared to ARCH (0.08 bioyear/chronoyear, p=0.026). CRCH also demonstrated double the decrease in telomere length (0.34kb, p<0.001) compared to ARCH (0.17kb, p=0.015). Conclusion: Our prospective CH cohort study validates the association between CH and EpiAgeAccel using several different methylation clocks and for the first time, highlights increased pace of aging and shorter telomere lengths in CRCH versus ARCH. Correlations with cardiovascular disease and mortality outcomes are ongoing.