Patnaik, Mrinal M.

ASXL transcriptional regulator 1 (ASXL1) is one of the three most frequently mutated genes in age-related clonal hematopoiesis (CH), alongside DNA methyltransferase 3 alpha (DNMT3A) and Tet methylcytosine dioxygenase 2 ( TET2) . CH can progress to myeloid malignancies including chronic monomyelocytic leukemia (CMML) and is also strongly associated with inflammatory cardiovascular disease and all-cause mortality in humans. DNMT3A and TET2 regulate DNA methylation and demethylation pathways, respectively, and loss-of-function mutations in these genes reduce DNA methylation in heterochromatin, allowing derepression of silenced elements in heterochromatin. In contrast, the mechanisms that connect mutant ASXL1 and CH are not yet fully understood. CH/CMML-associated ASXL1 mutations encode C-terminally truncated proteins that enhance the deubiquitinase activity of the ASXL-BAP1 “PR-DUB” deubiquitinase complex, which removes monoubiquitin from H2AK119Ub. Here, we show that ASXL1 mutant proteins interact with the euchromatic histone lysine methyltransferases 1 and 2 (EHMT1–EHMT2) complex, which generates H3K9me1 and me2, the latter a repressive modification in constitutive heterochromatin. Compared to cells from age-matched wild-type mice, we found that expanded myeloid cells from old (≥18-mo-old) Asxl1tm/+ mice, a heterozygous knock-in mouse model of CH, display genome-wide decreases of H3K9me2, H3K9me3, and H2AK119Ub as well as an associated increase in expression of transposable elements (TEs) and satellite repeats. Increased TE expression was also observed in monocytes from ASXL1 -mutant CMML patients compared to monocytes from healthy controls. Our data suggest that mutant ASXL1 proteins compromise the integrity of both constitutive and facultative heterochromatin in an age-dependent manner by reducing the levels of H3K9me2/3 and H2AK119Ub. This increase in TE expression correlated with increased expression of nearby genes, including many interferon-inducible (inflammation-associated) genes (ISGs).

ABSTRACT Patients with newly diagnosed acute myeloid leukemia (ND‐AML) derive variable survival benefit from venetoclax + hypomethylating agent (Ven‐HMA) therapy. The primary objective in the current study was to develop genetic risk models that are predictive of survival and are applicable at the time of diagnosis and after establishing treatment response. Among 400 ND‐AML patients treated with Ven‐HMA at the Mayo Clinic, 247 (62%) achieved complete remission with (CR) or without (CRi) count recovery. Multivariable analysis–derived hazard ratios (HR), including 1.8 for European LeukemiaNet (ELN) adverse karyotype, 4.7 for KMT2Ar , 1.7 for TP53 MUT , 2.6 for KRAS MUT , and 2.1 for IDH2 WT were applied to develop an HR‐weighted risk model: low, intermediate, and high; respective median survival censored for allogeneic stem cell transplant (ASCT) (3‐year survival) were “not reached” (67%), 19.1 (33%), and 7.1 months (0%). In patients achieving CR/CRi, adverse karyotype, KMT2Ar , KRAS MUT , IDH2 WT predicted inferior survival, allowing for a complementary response‐stratified risk model. The model was externally validated and was shown to be superior to the ELN 2024 risk model (AIC 179 vs. 195 and AUC 0.77 vs. 0.69). Survival was inferior with failure to achieve CR/CRi or not receiving ASCT; 3‐year survival for high‐risk with or without ASCT was 42% versus 0% ( p < 0.01); intermediate 72% versus 43% ( p = 0.06); and low‐risk 88% versus 78% ( p = 0.53). The Mayo genetic risk models offer pre‐treatment and response‐based prognostic tools for ND‐AML treated with Ven‐HMA. The current study underscores the prognostically indispensable role of achieving CR/CRi and ASCT.

Background: There is an increased risk of second primary malignancies including second hematological malignancies (SHM) in multiple myeloma (MM) patients undergoing autologous stem cell transplant (auto-SCT) followed by lenalidomide maintenance. We analyzed the characteristics and outcomes of patients who developed SHM after an auto- SCT for MM. Methods: A retrospective study of all MM patients who underwent auto- SCT at Mayo Clinic, Rochester between January 1, 1990, and 31 August 2023 and later developed SHM. Demographic, clinical and pathologic data were collected retrospectively. Overall survival (OS) was calculated from the date of auto-SCT to the date of last follow up. Statistical analyses were performed using GraphPad prism 9.0. Chi-square test was used to calculate the difference between categorical variables. Kaplan Meier method and log rank test were used to estimate OS. Results: Among 3513 patients who underwent at least 1 auto-SCT, 104 (2.9%) developed a SHM at a median follow up of 59 (range, 0.2-265) months. Patients who developed SHM, more frequently received pretransplant alkylating agents (37.5 vs 24.2 %, odds ratio [OR], 1.87; P=0.003) and topoisomerase II inhibitors (anthracyclines/etoposide) (17.3% vs 10.4%, OR [1.79]; P=0.03) compared to a control group of MM patients without SHM. Further, exposure to lenalidomide (77.8% vs 57.6%, OR[2.59]; P &lt;0.0001) and radiation therapy (32.6% vs 23.1%, [1.54]; P=0.04) were more often seen in the SHM cohort compared to control group. Among the 381 patients who underwent &gt; 1 auto- SCT, 3.1% developed SHM. Therapy related myeloid neoplasms (t-MN) accounted for 90.3% of cases [n=94; t-myelodysplastic syndrome (t-MDS=64), t-acute myeloid leukemia (t-AML=12), t-MDS transformed to AML(n=16), chronic myeloid leukemia (n=1), MDS/myeloproliferative neoplasm overlap syndrome (n=1)]. Eight patients (7.6%) developed therapy related B- cell acute lymphoblastic leukemia (t-ALL); Philadelphia (Ph) negative ALL (n=7) and Ph- like ALL (n=1). One patient each developed mixed phenotype acute leukemia and acute leukemia, not otherwise specified. Sixty patients (57.6%) were males and the median age at diagnosis of SHM was 70 (range, 43-84) years. The median time from auto-SCT to diagnosis of SHM was 58.5 (range, 7-236) months. In a multivariate analysis, receiving an alkylating agent (hazard ratio [95% confidence interval]: 2.51 [1.54 to 4.01]; P = 0.0002) and/or topoisomerase II inhibitor as induction for MM (3.12 [1.59 to 5.88]; P = 0.0006), exposure to lenalidomide (7.08 [3.92 to 13.50]; P = &lt;0.0001) and radiation therapy (1.60 [1.02 to 2.44]; P = 0.03) were independent predictors of developing SHM. At diagnosis, 57% (n=37) of t-MDS and 71% (n=20) with t-AML had high risk disease per R-IPSS and 2022 European Leukemia Net respectively. Clonal abnormality in chromosome 5 and/or 7 was present in 45% (n=42) of patients. Complex and monosomal karyotype was seen in 32% (n=30) with t-MN. The most frequently mutated genes based on next generation sequencing data included TP53 (n=33), DNMT3A (n=9), RUNX1 (n=5), TET2 (n=4) and CEBPA (n=4). In the t-MDS/AML cohort, 3 patients (3.1%) underwent second auto-SCT and 9 (9.5%) received allogenic SCT (allo-SCT) for SHM. After a median follow-up of 27.2 months, the median OS from t-MDS/AML diagnosis was 8.04 months (95%CI, 6.1-11.0 months) and there was no difference in median OS for allo-SCT recipients versus nonrecipients (9.1 vs 6.8 months, P =0.19). In the t-ALL (n=8) cohort, all of them received lenalidomide based induction and five received lenalidomide maintenance. Most of the t-ALL patients had adverse risk cytogenetics [IKZF1 deletion (n=2), complex karyotype (n=2), TP53 mutation (n=1) and P2RY8-CRLF2 fusion (n=1)]. Three patients with t-ALL underwent allo-SCT and the median OS for allo-SCT recipients versus non recipients were 8.3 vs 7.9 months respectively, P=0.50. Among patients with SHM, 92.3% (n = 96) have died with SHM (72%) being the most common cause of death. MM patients who developed SHM had an inferior OS when compared to those without SHM (median OS, 75 vs 90 months, P =0.006). Conclusion: SHM following auto-SCT tends to have aggressive disease biology with poor outcomes. Short term follow up underestimates the risk of SHM and the higher incidence noted in our study may be due to longer follow up. As the OS in MM patients continues to improve, SHM remains an important challenge in improving long term outcomes.

Background: Therapy-related myeloid neoplasms (t-MN) occur after exposure to DNA-damaging agentsincluding cytotoxic chemo and radiation therapy and are associated with dismal outcomes. TP53 and PPM1D (protein phosphatase Mn2+/Mg2+-dependent 1D) mutations (MT) disrupt the DNA damage response and repair (DDR) pathway, are often co-mutated (25-35%), and although enriched in t-MN (20%), can also be seen in age-related clonal hematopoiesis (CH) (5-10%). While progressive genomic instability with biallelic inactivation has been described as a mechanism of MN progression with TP53 MT, similar mechanisms remain to be elucidated for PPM1D MT. We conducted this study to assess the clinical phenotype and outcomes of TP53 and PPM1D co-mutated (PPM1DTP53m) versus PPM1D MT and wild type TP53 (PPM1DTP53wt) CH and MN. Methods: After approval from the Mayo Clinic IRB, the CH and MN databases were queried and 119 pts with PPM1D MT (CH= 26, clonal cytopenia of unknown significance [CCUS]= 64, myelodysplastic syndrome [MDS]=16, myeloproliferative neoplasm [MPN]=8, acute myeloid leukemia [AML]= 5) were identified. We analyzed baseline characteristics, karyotypic changes, somatic mutations, and survival outcomes between the PPM1DTP53m (n= 22) and PPM1DTP53wt (n= 97) groups (gp). Results: Baseline characteristics The median age in years (yrs) was 68.5 (range [R], 43-89) and 71 (R,30-92) in the PPM1DTP53m and PPM1DTP53wt gp (p= 0.65). 22% vs 18% (p=0.78), 58% vs 32% (p=0.03), 9% vs 32% (p=0.01), 7% vs 4.5% (p=&gt;0.99) and 3% vs 14% (p=0.07) pts met criteria for CH, CCUS, MDS, MPN and AML in the PPM1DTP53wt and PPM1DTP53m gp, respectively. Similarly, 19% vs 18% (p=&gt;0.99), 47% vs 32% (p=0.23), 7% vs 36% (p=0.001), 2% vs 0% (p=&gt;0.99) and 2% vs 14% (p=0.04) of pts met criteria for t-CH, t-CCUS, t-MDS, t-MPN and t-AML in the PPM1DTP53wt and PPM1DTP53m gp, respectively. All PPM1D variants were truncating, located in exon 6 of the gene, with median variant allele frequency (VAF) (8% [R,1-64] vs 5.5% [R,2-24], p= 0.10) and number of PPM1D MT (1 [R,1-5] vs 1 [R, 1-3], p=&gt;0.99) being similar between the two gp. While proportion of pts with t-MN were similar between the two gps (77% vs 86%, p= 0.40), cytogenetic (CG) abnormalities (67% vs 31%, p= 0.006), including monosomies (28% vs 2%, p= &lt;0.001) and complex CG (53% vs 4%, p= &lt;0.001) were more frequent in PPM1DTP53m gp compared to PPM1DTP53wt gp, respectively. The median TP53 MT VAF was 14% (R, 1-14); 50% had multi-hit TP53 MT. Somatic mutations in PPM1D MT myeloid neoplasm with and without TP53 MT Somatic co-mutations excluding TP53 were seen in 71% of pts; 73.5% in PPM1DTP53wt and 59% in PPM1DTP53m gp (p= 0.20). Apart from CBL (0% vs 9%,p=0.03), MT involving DNMT3A (20% vs 14%, p= 0.56), TET2 (15% vs. 14%, p= &gt;0.99), IDH1 (6% vs 19%, p= 0.07), splicing factors (8% vs 14%, p=0.08), ASXL1 (11% vs 4.5%, p=0.46), and JAK2 (9% vs 0%,p=0.20) were comparable between PPM1DTP53wt and PPM1DTP53m gps, respectively. The proportion of pts with ≥ 2 somatic co-mutations excluding TP53 MT were numerically higher in PPM1DTP53wt gp (43%) compared to PPM1DTP53m gp (23%) (p= 0.09). In the PPM1DTP53wt gp, other somatic driver mutations included RUNX1 (n= 7 [7%]; CH [n=1], CCUS [n=2], MDS [n=3], MPN [n=1]), NRAS (n=1 [1%]; CCUS), BCOR (n=1 [1%]; CCUS), and PTPN11 (n=1 [1%]; CCUS). Leukemic transformation and survival With a median follow up of 6.43 months (mo) (R, 0.23-36.4), median overall survival (mOS) in mo among high-risk MDS/AML (16.4 vs 15.0, p= 0.66) and CHIP/CCUS pts (35.79 vs 26.28, p= 0.93) was similar between PPM1DTP53wt and PPM1DTP53m gps, respectively. CHIP/CCUS pts harboring multiple vs single PPM1D MT had an inferior mOS (23.9 vs 36.7 mo, p= 0.05). Three (2.5%) MDS pts underwent AML transformation; 1 (1%) and 2 (10%) in PPM1DTP53wt and PPM1DTP53m gp, respectively (p= 0.07). Conclusions In our study, 18% of pts had concurrent TP53 and PPM1D MT (82% t-MN), with the PPM1DTP53wt genotype being more frequent in CCUS, while the PPM1DTP53m genotype was more frequent in MN. The PPM1DTP53m genotype had a higher frequency of CG abnormalities, including complex CG. Survival outcome was inferior and comparable in PPM1D MT MN with or without TP53 MT. While 73.5 % of the PPM1DTP53wt gp had somatic driver MT and 31% had karyotypic abnormalities, 22% had no additional MT or CG changes (all CH/CCUS), underscoring the need to understand how PPM1D MT contribute to hematopoietic dysfunction and MN.

Background: The majority of patients with chronic myelomonocytic leukemia (CMML) harbor somatic mutations with the most frequent being TET2 (56%), SRSF2 (42%), and ASXL1 (41%) (Leukemia 2020;34:1407). The prognostic relevance of mutations in CMML has been studied extensively with consistent observations suggesting favorable survival impact from TET2 and unfavorable from DNMT3A, ASXL1, NRAS, and SETBP1 mutations. Among the latter, DNMT3A mutation stands out as being the strongest predictor of inferior overall (OS) and leukemia-free (LFS) survival (AJH 2017;92:56). The current study was inspired by observations from exploratory analyses of a large Mayo Clinic CMML cohort. Methods: The current retrospective study was conducted under an institutional review board approved minimum risk protocol that allowed retrospective collection and analysis of data from patient records (Mayo Clinic, Rochester, MN; Scottsdale, AZ; and Jacksonville, FL). Mutations were screened by multi-gene next-generation sequencing (NGS). Diagnostic criteria were according to the International Consensus Classification (Blood 2022; 140:1200). Conventional statistical methods were employed for comparisons of groups and survival analysis (JMP Pro 17.0.0 software SAS Institute, Cary, NC, USA). Results: Exploratory analysis of a well-characterized cohort of 398 Mayo Clinic patients with CMML suggested an unusually long median survival of 96 months for 7 patients harboring PHF6 mutation vs. 27 months for those without the mutation. A subsequent institutional database search focusing on PHF6-mutated CMML identified 20 more cases, expanding the total number of study patients to 418, including 27 PHF6-mutated cases. PHF6 mutations clustered with (co-mutation frequency) TET2 (93%) and less likely to be co-mutated with TP53 (0%), PTPTN11 (0%) and SF3B1 (0%) mutations. PHF6-mutated patients often presented with thrombocytopenia (platelet count &lt;100 x 10(9)/L; 85% vs. 51% in PHF6 wild-type cases; p&lt;0.01). Median time from initial presentation with thrombocytopenia to CMML diagnosis was 4 years (0-14 years). In order to isolate the prognostic impact of PHF6 mutation without associated DNMT3A mutation and independent of TET2 mutation, we considered 4 mutational categories: i) DNMT3A-mutated (N=19; 2 co-expressed PHF6 and 7 TET2 mutations), ii) PHF6-mutated with wild-type DNMT3A (N=25; 23 co-expressed TET2 mutation), iii) TET2-mutated without DNMT3A or PHF6 co-expression (N=169), and iv) wild-type for DNMT3A, TET2, and PHF6 (N=205). Compared to the other groups, PHF6-mutated patients with wild-type DNMT3A were less likely to display leukocytosis (p&lt;0.01) or red cell transfusion need at presentation (p&lt;0.01). At a median follow-up of 18 months, 302 deaths, 78 leukemic transformations, and 44 allogenic stem cell transplants were documented. Univariate analysis for OS disclosed superiority in favor of PHF6-mutated patients with wild-type DNMT3A (median OS 90 months) vs. the other three groups with median OS ranging from 10 months for DNMT3A-mutated patients (HR 20.7, 95% CI 8.1-52.7; p&lt;0.01) to 40 months for TET2-mutated cases with wild-type DNMT3A (HR 3.5, 95% CI 1.7-7.6; p&lt;0.01). Results were similar for multivariable analysis of LFS, where, remarkably, none (0%) of the 25 PHF6-mutated patients with wild-type DNMT3A experienced leukemic transformation vs. 15-30% risk of leukemic transformation in the other three groups (p&lt;0.01). Multivariable analysis for both OS and LFS, which included other risk factors such as red cell transfusion need, leukocytosis (leukocyte count ≥13 x 109/L) and karyotype, confirmed the independent and favorable impact of PHF6 mutation/wild-type DNMT3A (p&lt;0.01 in both instances). Finally, all-inclusive multivariable analysis of karyotype and mutations, in DNMT3A wild-type patients, confirmed the highly favorable and independent prognostic impact of PHF6 mutation (HR 0.18, 95% CI 0.09-0.37). Conclusion: The current study proposes a 2-gene genomic signature (PHF6 mutated and DNMT3A wild-type) to identify a unique subset of CMML patients who often present with thrombocytopenia and whose clinical course is characterized by a very low risk of leukemic transformation, resulting in superior overall survival. Additional studies are warranted to validate these findings and include the information in contemporary risk models.

Introduction Chronic myelomonocytic leukemia (CMML) is associated with a 15-30% risk for blast transformation (BT) over 3-5 years. Post-BT survival remains dismal with a median overall survival (mOS) of ~6 months (mo), even with intensive therapies. Although genetic drivers are identified in &gt;40% of BT-CMML cases (Carr, 2021), mechanisms of BT remain to be elucidated. This multicenter study examines risk factors for BT in CMML and predictors of post-BT survival. Methods CMML patients at Mayo Clinic (n = 400, 47%) and MD Anderson Cancer Center (n = 449, 53%) were included with IRB approval. Analyses used clinical and molecular data at diagnosis or first referral in chronic phase (CP) and again at BT. Categorical variables were compared by Chi squared and continuous by Mann-Whitney U or Kruskal-Wallis tests. Multivariate analyses used Cox proportional hazards models with binarization via receiver operator curves. Kaplan-Meier analyses were censored at hematopoietic cell transplantation (HCT). P &lt; 0.05 was considered significant. Calculations used BlueSky (v10.3.1) or Prism (v10.2.3). Results Of 849 CMML patients (median age 71 years, 32% female, 90% white) included in the study, 133 (16%) underwent BT. In comparison to CP-CMML without BT, those with BT were more likely (p &lt; 0.05) to have had higher WBC counts (15.1 vs 11.4 x109/L), higher absolute monocyte counts (2.9 vs 2.2 x109/L), lower platelet counts (84 vs 102 x109/L), have circulating immature myeloid cells (52% vs 37%), and be classified as myeloproliferative (MP)-CMML (58% vs 44%) or CMML-2 (33% vs 17%) at diagnosis/first referral in CP. More mutations were detected in BT-CMML than in CP-CMML (mean 3.2 vs 2.8, p = 0.002). Mutations in RAS (NRAS, KRAS, BRAF, CBL, PTPN11; 51% vs 40%, p = 0.02) and signaling (CSF3R, FLT3, JAK2, SH2B3; 15% vs 7%, p = 0.004) pathway genes were more frequent in BT-CMML. Conversely, there were fewer BT-CMML patients with the favorable ASXL1WT/TET2MT genotype compared to CP-CMML (22% vs 33%, p = 0.004). Multivariate analysis identified MP-CMML (hazard ratio [HR] 1.5, p = 0.04), CMML-2 (HR 2.4, p &lt; 0.001), and the presence of ≥4 somatic gene mutations (HR 1.8, p = 0.002) as risk factors for BT whereas the ASXL1WT/TET2MTgenotype was protective (HR 0.45, p = 0.002). The ASXL1WT/TET2MT genotype was also protective in the MP-CMML (HR 0.49, p = 0.04) and RAS-mutated (HR 0.35, p = 0.005) subgroups. Amongst BT-CMML cases, the median time to BT was 10 mo from diagnosis/referral. Compared to their CP assessment, patients in an overlapping Mayo Clinic BT-CMML cohort (n = 156, median age 69 years, 35% female) were more likely to have NPM1 (24% vs 3%, p &lt; 0.001) and IDH2 (14% vs 1%, p = 0.01) mutations at BT. Amongst cases with paired molecular evaluations (n = 44), 7 (16%) acquired new mutations, including FLT3-ITD (n = 2) and NPM1 (n = 2). Conversely, 6 (14%) lost mutations, including TET2 (n = 3), SRSF2 (n = 2), CBL, NRAS, or PTPN11 (n = 1 each). There were no differences in variant allele fractions in driver genes present at CP and BT. Abnormal karyotypes were more prevalent at BT than in CP (60% vs 34%, p &lt; 0.001), and 26 (25%) patients with a normal karyotype in CP acquired structural (65%) and/or numerical (69%) changes at BT, including 6 (23%) that acquired a complex karyotype. Acute myeloid leukemia defining translocations were seen in 4 (4%) cases: 2 with t(8;21) and 1 each with inv(3) and t(10;11)(KMT2A::TET1). After considering mutation and karyotype changes, only bone marrow blasts ≥30% (HR 1.7, p = 0.04) were independently prognostic for OS after BT (mOS 4 mo). Compared to supportive care (n = 50, mOS 1.3 mo), OS was improved by hypomethylating agents (HMA, n = 14, mOS 16 mo, HR 0.3, p &lt; 0.001) or induction chemotherapy (n = 56, mOS 8 mo, HR 0.3, p &lt; 0.001), but not by HMA + venetoclax (n = 11, mOS 6 mo, HR 0.7, p = 0.4). Allogeneic HCT (n = 28) improved mOS to 46 vs 3 mo (p &lt; 0.001). Amongst 4 patients with paired whole genome sequencing before and after BT, 3 had increased copy number alterations (including 2 with loss of heterozygosity, 2 with gains, and 3 with deletions) while the 4th acquired novel likely pathogenic somatic mutations (MUC4, BAX, WNK2). Conclusions Survival in CMML after BT remains exceptionally poor. In this multicenter cohort, MP-CMML, CMML-2, and the presence of ≥4 somatic gene mutations were identified as risk factors for BT, with the ASXL1WT/TET2MT genotype being protective. Following BT, bone marrow blast burden ≥30% was an independent adverse predictor of survival.

Background: TP53-mutated (TP53mut) myeloid neoplasms (MN) have particularly poor survival. Discrepancies in defining TP53mut MN have impact on diagnostic work up, therapeutic decisions, and clinical trial enrolment. Methods: MN cases harboring TP53mut (variant allele frequency, VAF ≥2%) were classified based on bone marrow (BM) and peripheral blood (PB) blast % using the 4th revision of the WHO classification (WHO-4R). Biallelic loss was defined as (i) ≥2 mutations each with VAF ≥2%; (ii) single TP53mut VAF ≥2% plus 17p loss detected on karyotype, FISH, or SNP; or (iii) single TP53mut VAF ≥50%, whereas monoallelic loss was defined as single TP53mut VAF &lt;50% without 17p loss. Primary endpoint was overall survival (OS) from diagnosis. Conditional Inference Trees (CIT) analysis was used to determine the true effect of a predictor. Results: We identified 580 cases including WHO-4R defined acute myeloid leukemia (AML, BM/PB blasts ≥20%, n=219, 37.8%), myelodysplastic syndrome (MDS) with excess blasts-2 (EB-2, BM 10-19% or PB 5%-19%, n=92, 15.9%), MDS with excess blasts-1 (EB-1, BM 5-9% or PB 2-4%, n=75, 12.9%), and the remaining were MDS with low blasts (-LB, BM &lt;5% and PB ≤1%, n=194, 33.4%). Of the 578 cases evaluable for allelic status, 437 (75.6%) and 141 (24.4%) had biallelic and monoallelic TP53 loss, respectively. Higher frequency of biallelic loss was observed with increasing blasts. 63.2%, 73.3%, 78% and 86.3% of cases with MDS-LB, MDS-EB1, MDS-EB2, and AML had bi-allelic TP53 loss (P&lt;0.0001). In a multivariable analysis, WHO-4R categories, VAF ≥10%, and biallelic loss were independent predictors of poor survival. CIT analysis further stratified the cohort into 4 groups with distinct survival: (1) MDS-LB (n=194, 33.4%); (2) MDS-EB1/EB2 and AML with VAF &lt;10% (n=38, 6.6%); (3) MDS-EB1/EB2 with VAF ≥10% (n=149, 25.7%); and (4) AML with VAF ≥10% (n=199, 34.3%). MDS-LB cases could be further stratified based on allelic status and complex karyotype (CK): OS was poor for cases with biallelic TP53 loss and monoallelic TP53mut with CK compared to monoallelic TP53mut without CK, who had the most favorable survival (12.7 vs. 13 vs. 34.8 months, P&lt;0.0001).MDS-EB1/EB2/AML with VAF&lt;10% could also be stratified by CK: MDS-EB1/EB2/AML with VAF&lt;10% cases without CK had the favorable survival compared to their counterparts with CK and MDS-EB1/EB2 with VAF ≥10% cases (26.2 vs. 5.6 vs. 6.3 months, P=0.003).MDS-EB1/EB2 with VAF ≥10% was a homogenous subgroup: Biological characteristics including the proportion of cases with biallelic TP53 loss, CK (P&gt;0.9), monosomal karyotype (MK, P&gt;0.9), del 5q (P=0.6), del 7q (P=0.4), and del 17p (P=0.2) were comparable between MDS-EB1 and -EB2 with VAF ≥10%. Importantly, median OS of MDS-EB1 and EB2 with VAF ≥10% was comparable (9.6 vs. 7.2 months, P=0.12). OS in this group was comparable regardless of the blast %, allelic status, or presence of CK.AML with VAF ≥10% had extremely poor survival: Median OS was 3.9 months. Survival of AML was equally poor irrespective of the mono- or biallelic (3.6 vs. 3.9, P=0.89) and non-CK vs. CK (1.8 vs. 3.9 months, P=0.09). Combined, our model would acknowledge poor survival of 514 (89.1%) cases. In contrast, retrospective application of the 5th edition of the WHO classification (WHO-5) and International Consensus Classification (ICC) would classify only 211 (36.4%) and 468 (80.7%) cases as biallelic/multi-hit TP53mut MN, respectively. Finally, the Harrell's c-index of the proposed model, WHO-5, and ICC was 0.66, 0.571, and 0.617, respectively. Conclusion: We provide evidence for subsequent refinements in classifying MN harboring TP53mut. Our salient findings include: (i) acknowledgement of CK as ‘biallelic equivalent’ in MDS-LB; as well as EB1/EB2/AML with VAF 2 to &lt;10% cases; and (ii) demonstration of poor survival of MDS-EB1 and -EB2 with VAF ≥10% regardless of the allelic status. In conclusion, our proposed model acknowledged poor survival of a higher proportion of cases as TP53mut MN compared to the current models with a higher c- index.

Introduction: Somatic mutations in RAS pathway genes are present in ~30% of patients with chronic myelomonocytic leukemia (CMML) and are usually associated with myeloproliferative features. Whether mutations in distinct RAS pathway genes share similar genomic context and have similar implications remains unknown. Such an understanding might inform future studies evaluating genotype-specific therapies (RAS-codon specific and pan-RAS inhibitors) or cooperative leukemogenic mechanisms. This multicenter study examines the landscape of RAS pathway mutations (RASMT) in CMML. Methods: Newly diagnosed CMML patients evaluated at MD Anderson Cancer Center (n=449, 54%) and Mayo Clinic (n=383, n=46%) were included after IRB approval. Clonal relationships were tested using Pearson goodness-of-fit. Clones with the highest variant allele frequency (VAF), or with VAF close to 40% were defined as dominant, and those present at VAF &lt;20% in the presence of another dominant clone were defined as subclonal. RASMT genes included NRAS, KRAS, BRAF, CBL, CBLC, PTPN11 and NF1. Standard statistical measures were applied. Results: Among 832 CMML patients (median age 71 years, 68% male) 387 (47%) had myeloproliferative (MP) and 445 (53%) had myelodysplastic (MD) CMML. A total of 350 (42%) patients had RASMT with higher prevalence among MP-CMML compared to MD-CMML (55% vs 31%, p&lt;0.001). Among patients with RASMT, 262 (32%), 59 (7%), 20 (2%), 6 (&lt;1%) and 3 (&lt;1%) had 1, 2, 3, 4 or 5 distinct RASMT, respectively. Importantly, 17 patients harbored a RASmt as the only detectable somatic mutation, with KRASMT being the most frequent (n=10, 59%), including 3 (18%) patients with &gt;1 RASMT. Among RASMT patients, a trend for higher hemoglobin (12.7 vs 10.8 g/dL, p=0.054) was observed in NF1MT CMML and lower WBC (14.4 vs 27.9 x109/L, p=0.067) values in CBLMT CMML. In total, 479 somatic mutations in RAS pathway genes were identified the most frequent involving NRAS (n=169, 35%) followed by CBL (n=120, 25%), KRAS (n=102, 21%), PTPN11 (n=38, 8%), NF1 (n=34, 7%), BRAF (n=11, 2%) and CBLC (n=5, 1%). Most frequently involved codons for each RAS pathway gene were as follows: G594 (n=3) for BRAF, R420 (n=22) and C404 (n=15) for CBL, G12 (n=41; G12D: 13, G12C: 3) and A146 (n=16) for KRAS, G12 (n=116; G12D: 74, G12C: 5) for NRAS and A72 (n=8) for PTPN11. CBLMT CMML had higher ASXL1 (58% vs 44%, p=0.011), BRAF (8% vs 4%, p=0.017), IDH2 (10% vs 4%, p=0.024), KIT (5% vs 1%, p=0.038), SRSF2 (54% vs 40%, p=0.004), TET2 (59% vs 47%, p=0.019) and ZRSR2 (10% vs 4%, p=0.014) co-mutation frequency. Of note, DNMT3A mutations were mutually exclusive of CBLMT CMML (0% vs 7%, p=0.007), and multihit TET2 was more common among TET2MT/CBLMT vs TET2MT/CBLWT CMML (82% vs 67%, p =0.039). CMML with NF1 mutations had higher BCORL1 (8% vs 0%, p=0.005), PTPN11 (15% vs 3%, p=0.014) and SETBP1 (23% vs 8%, p=0.022) mutational cooccurrences. NRASMT CMML was enriched for ASXL1 (53% vs 43%, p=0.042), ETNK1 (5% vs 1%, p=0.004), GATA2 (4% vs 1%, p=0.034) and STAG2 (4% vs 1 %, p=0.023) mutations but had lower JAK2 (1% vs 6%, p=0.036) and TP53 (1% vs 5%, p=0.022) mutational frequency. PTPN11 mutations were associated with higher NF1 (29% vs 7%, p=0.014), SETBP1 (27% vs 9%, p=0.01) and WT1 (6% vs &lt;1%, p=0.014) mutational cooccurrences and lower SRSF2 (23% vs 42%, p=0.05) frequency. We evaluated RAS mutant clonal dominance in 253 (72%) RASMT patients. NRAS (63% vs 38%), KRAS (63% vs 38%) and CBL (65% vs 35%) mutations were more frequently observed as dominant clones while PTPN11 (44% vs 56%), BRAF (25% vs 75%) and NF1 (35% vs 65%) mutations were more frequently subclonal events, particularly of TET2, ASXL1 or SRSF2 mutant clones. Presence of a RAS pathway mutation was associated with shorter LFS (36 vs 53 months, HR 1.5, 95% CI 1.1-2.2, p=0.020), with presence of multiple RAS mutations shortening LFS further (53, 43, 27 months for 0, 1 and &gt;1, p=0.017). PTPN11 mutations predicted for shorter OS (18 vs 39 months, HR 1.7, 95% CI 1.0-2.8, p=0.035) and LFS (14 vs 36 months, HR 1.9, 95% CI 1.2-2.9, p=0.008). Presence of &gt;1 RAS pathway mutation was associated with shorter OS in ASXL1MT/TET2MT CMML compared to those with no RAS mutations (24 vs 53 months, HR 4.2, 95% CI 1.6-10.8, p=0.004). Conclusions: RAS mutations exhibit distinct genomic features and clonal hierarchy in CMML and cooperate with other somatic mutations to drive clinical outcomes. This study forms the foundation for assessment of novel RAS pathway inhibitors in CMML.

Background Venetoclax + hypomethylating agent (Ven-HMA) therapy results in favorable response rates (CR/CRi 66%) and overall survival (OS; median 14.7 months) in unfit patients with newly-diagnosed acute myeloid leukemia (ND-AML; N Engl J Med 2020;383). However, there is substantial heterogeneity in individual patient outcomes based on response to treatment. The objective of the current study was to develop a genetic risk model to predict survival outcome in treatment responders and non-responders, analyzed separately, and also account for allogeneic stem cell transplant (ASCT). Methods Treatment-naïve AML patients receiving Ven-HMA, outside of a clinical trial, at the Mayo Clinic, USA (MN, AZ, FL) were retrospectively recruited. Molecular studies (48-gene panel) were performed by next-generation sequencing. Response was assessed according to the 2022 European LeukemiaNet (ELN) criteria (Blood 2022;140). Standard statistical analyses were performed using JMP Pro (Version 17.0.0). Results 400 ND-AML patients (median age 73 years, 64% male, 60% de novo) received Ven-HMA. ELN cytogenetic risk included favorable 2%, intermediate 60%, or adverse 38%. Mutations involved TP53 in 26%, TET2 19%, RUNX1 19%, SRSF2 18%, ASXL1 18%, DNMT3A 15%, K/NRAS 13%, NPM1 12%, IDH2 12%, FLT3-ITD 10%, IDH1 7% and DDX41 in 4% of informative cases. 153 (38%) patients achieved CR, 94 (24%) CR with incomplete count recovery (CRi), resulting in CR/CRi in 247 (62%) patients. CR/CRi rates were higher with NPM1 (86% vs 59%), IDH2 (77% vs 60%), and DDX41 mutations (93% vs 61%) and lower with TP53 (45% vs 67%), FLT3-ITD (41% vs 64%), RUNX1 (49% vs 65%) mutations and adverse karyotype (48% vs 71%), with all retaining significance in multivariable analysis. CR/CRi rate was highest (87%) in 75 patients with one or more favorable mutations (NPM1, IDH2, DDX41) and no unfavorable mutation (TP53, FLT3-ITD, RUNX1). CR/CRi rate was lowest in 171 patients with at least one unfavorable mutation and no favorable mutation (44%; p&lt;0.01). After a median follow up of 10.5 months (0.5-66), 105 relapses (43% of patients in CR/CRi), 248 (62%) deaths and 65 (16%) ASCT were documented. Univariate analysis for transplant-censored OS disclosed superior survival in patients achieving CR/CRi (median 21 vs 3.6 months; HR 5.4, 95% CI 4.1-7.1). Among patients achieving CR/CRi, IDH2 mutation was associated with superior (median not reached vs 20.5 months) and male gender (median 17.6 vs 29.2 months), TP53 mutations (median 11.9 vs 24.3 months) and adverse karyotype (median 12.6 vs 29.4 months) with inferior survival; multivariable analysis resulted in HRs (95% CI) of 2.1 (1.3-3.4) for male gender, 2.1 (1.2-3.8) for adverse karyotype, and 2.5 (1.1-5.7) for absence of IDH2 mutations. Male gender did not show an association with karyotype, or TP53 mutations (p&gt;0.1). Accordingly, an HR-weighted genetic risk model was generated with assignment of one point each to male gender, adverse karyotype, and absence of IDH2 mutation: high risk = 3 risk factors (n=38; median 9.6 months; 3-year survival 0%); intermediate risk = 2 risk factors (n=129; median 22 months; 3-year survival 38%); and low-risk = ≤1 risk factor (n=78; median not reached; 3-year survival 69%; p&lt;0.01). In patients bridged to ASCT (n=60), post-transplant survival was inferior in the presence of ≥ 2 risk factors (n=42; median 46 months) vs. ≤1 risk factor (n=18; median not reached; p=0.1). In patients not achieving CR/CRi, risk factors for OS included male gender (median 3.4 vs 6.1 months), adverse karyotype (median 3.3 vs 4.5 months) and TP53 mutation (median 3.1 vs 4.5 months) while those with IDH2 mutations lived longer (median 8.4 vs 3.4 months). In multivariable analysis, HRs (95% CI) were 1.9 (1.3-2.9) for male gender, 2.0 (1.4-2.9) for adverse karyotype, and 2.1 (1.1-4.3) for absence of IDH2 mutations. OS was shortest for non-responders harboring 3 risk factors (n=45; median 3 months; 1-year survival 0%) and longer for those harboring two (n=80; median 6 months, 1-year OS 15%) or ≤ 1 risk factor (n=25; median 14 months; 1-year OS 56%; p&lt;0.01). Conclusion The current study describes a molecular profile for predicting response to Ven-HMA in ND-AML and also introduces a novel approach to survival prediction that considers treatment response as the starting point. In both responders and non-responders, male gender and adverse karyotype were identified as unfavorable and IDH2 mutation favorable risk factor for OS.