Kanagal-Shamanna, Rashmi

Abstract Recent updates to monocyte count thresholds recognize oligomonocytic chronic myelomonocytic leukemia (OM-CMML) as an early form of CMML. However, the clinical validity of these changes remains uncertain without incorporating biological and genomic factors. In this study, we analyzed a cohort of 911 patients (249 with OM-CMML, 359 with overt CMML, and 303 with myelodysplastic syndromes) using unsupervised clustering to evaluate the role of genomic determinants in refining CMML diagnosis. Our findings show that CMML molecular signatures (biallelic TET2 mutations or SRSF2-TET2 comutations) are linked to a distinct transcriptome, monocytic bias, classical monocytosis, and a higher risk of progression to overt CMML in OM-CMML cases. We developed a weighted genomic model and diagnostic workflow showing that combining genomic signatures with bone marrow monocyte frequencies in OM-CMML more accurately predicts progression to overt CMML. These findings support integrating genomic determinants and our clinic-ready diagnostic workflow into the CMML diagnostic framework to improve accuracy. Significance: Through comprehensive clinical and genomic profiling of a large patient cohort, alongside immunophenotypic and transcriptional cellular analyses, this study provides evidence that incorporating genomic determinants into the diagnostic criteria for OM-CMML improves diagnostic accuracy and refines the identification of early-stage CMML, thereby preventing misclassification.

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

Abstract Background: While mutations in the fms-like tyrosine kinase 3 (FLT3) gene are well-established adverse drivers in acute myeloid leukemia (AML), their role in myelodysplastic syndromes (MDS) and chronic myelomonocytic leukemia (CMML) remains insufficiently defined. Methods: We conducted a retrospective multicenter study of 115 patients with FLT3-mutated (FLT3mut) MDS (n=63) or CMML (n=52), comparing their clinical, genomic, and therapeutic characteristics at diagnosis or first referral to 677 FLT3 wild-type (FLT3wt) controls (MDS n=388; CMML n=289) using multivariate analyses and propensity score matching (PSM). Results: FLT3mut MDS and CMML exhibited a proliferative phenotype with higher leukocyte and neutrophil counts and lower platelet levels (p<0.02); in MDS, median white blood cell counts remained below 13,000/µL. In MDS, FLT3mut cases were enriched in the MDS with increased blasts subtype (57% vs 39%, p=0.01) and favorable-risk cytogenetics (64% vs 41%, p<0.01). Genomically, FLT3mut MDS showed higher frequencies of NRAS, KRAS, PTPN11, RUNX1 and CBL co-mutations (p<0.05), and a markedly lower prevalence of TP53 mutations (2% vs 36%, p<0.001). In CMML, FLT3mut cases were more often transfusion-dependent (50% vs 23%, p<0.01), classified as CMML-2 (39% vs 25%, p=0.04), and enriched in ASXL1 (68% vs 47%; p<0.01) and SETBP1 (24% vs 8%; p<0.01) mutations. Notably, they exhibited multi-hit TET2 mutations less frequently than FLT3wt CMML (27% vs 53%, p=0.01). After adjusting for age, sex, and allogeneic stem cell transplantation, FLT3 mutations were independently associated with worse outcomes. To further assess the prognostic impact of FLT3 mutations, we conducted PSM analyses using a 1:1 ratio of FLT3mut to FLT3wt patients, adjusting for key clinical and biological confounders. In MDS, matching was based on age, sex, bone marrow blast percentage, and cytogenetic risk category; in CMML, variables included age, CMML-2 subtype, peripheral blood counts, normal karyotype, and ASXL1 mutation status. After matching, FLT3mut MDS cases showed significantly shorter overall survival (OS; 19.9 vs 44.2 months, p=0.046) and leukemia-free survival (LFS; 13.8 vs 37.1 months, p=0.023) compared to FLT3wt patients. Similarly, in CMML, FLT3mut patients experienced inferior OS (30.4 vs 67.2 months, p=0.017) and LFS (17.2 vs 65.6 months, p=0.014). Competing risk models confirmed a markedly increased cumulative incidence of AML transformation in both FLT3mut MDS and CMML (p<0.001), without significant differences in the risk of non-leukemic death. Among FLT3mut cases, tyrosine kinase domain mutations (FLT3-TKD) were associated with superior survival compared to internal tandem duplications (FLT3-ITD; MDS hazard ratio [HR]: 0.28, p=0.003; CMML HR: 0.34, p=0.012). FLT3 allelic ratio (AR), assessed by conventional PCR in 63 patients (MDS n=34, CMML n=29), provided additional prognostic value. An AR ≥0.21 identified a subgroup with significantly shorter OS (MDS: 24.4 vs 38.8; CMML: 6.7 vs 30.4 months) and LFS (MDS: 9.0 vs 18.5 months; CMML: 5.8 vs 30.4 months; all p<0.05), supporting the utility of quantitative FLT3 assessment in clinical risk stratification. FLT3 inhibitors (FLT3i) were administered in combination with hypomethylating agents (HMA) to 16 (27%) FLT3mut MDS and 15 (33%) CMML patients. Compared to HMA, FLT3i treatment was associated with higher overall response rates (MDS: 69% vs 22%, p<0.01; CMML: 73% vs 35%, p=0.06). Molecular clearance, defined as post-treatment reduction in AR to ≤0.01, was observed more frequently with FLT3i than with HMA (MDS: 56% vs 10%, p=0.03; CMML: 60% vs 20%, p=0.09). FLT3 clearance was associated with prolonged survival. In MDS, median OS and LFS were 66.0 vs 14.5 (p=0.12) and 29.0 vs 9.9 months (p=0.056), respectively; in CMML, it was 37.6 vs 14.6 months for both OS (p=0.043) and LFS (p=0.032). Conclusions: This study expands the current understanding of FLT3mut MDS and CMML by characterizing their clinical, molecular, and therapeutic features in the largest multicenter cohort reported to date. These cases exhibit a proliferative phenotype, frequent co-mutations in RAS pathway genes, and an elevated risk of leukemic transformation. Quantitative assessment of FLT3 allelic burden refines prognostication beyond mutation status alone. The observed associations between FLT3 inhibitor use, molecular clearance, and improved outcomes support further evaluation of targeted strategies in selected patients.

Abstract Recent updates to the monocyte count thresholds for diagnosing chronic myelomonocytic leukemia (CMML) have recognized oligomonocytic CMML (OM-CMML) as an early stage within the CMML spectrum. However, the clinical validity of these revised criteria remains uncertain without considering biological factors and might misclassify myelodysplastic syndromes (MDS) with mild monocytosis as CMML. To characterize the genomic landscape of OM-CMML, we evaluated OM-CMML (n=249), MDS (n=304) and myelodysplastic CMML (MD-CMML, n=358) patients (pts) treated at three academic institutions. Targeted next-generation sequencing was performed on bone marrow (BM) at initial diagnosis or first referral. OM-CMML was characterized by lower frequencies of biallelic TET2 (biTET2) and RAS pathway (RASp) gene mutations (BRAF, CBL, KRAS, NF1, NRAS and PTPN11) compared to MD-CMML (p<0.001) but higher frequencies than MDS (p<0.001). BM monocyte frequencies, assessed morphologically, were higher in OM-CMML than in MDS (p<0.001) but lower than in MD-CMML (p<0.001), indicating that OM-CMML is a heterogenous group including true CMML and distinct MDS subsets. Unsupervised hierarchical clustering based on genomic alterations across all cases (n=911) identified three distinct clusters: 1) TP53 alterations (predominantly multihit TP53) and complex karyotype (TP53-complex); 2) biTET2 or TET2-SRSF2 co-mutation (biTET2/SRSF2); 3) a heterogenous group lacking these features (not otherwise specifiable [NOS]). Among OM-CMML pts, 11%, 34% and 55% belonged to these clusters, respectively. Model-based unsupervised clustering further identified 9 unique clusters that could be consolidated into 6 groups: 1) TP53-complex; 2) biTET2/SRSF2; 3) SF3B1 (without biTET2 or SRSF2); 4) SRSF2 without TET2 and frequent IDH2 mutations (SRSF2-IDH2); 5) ASXL1 and U2AF1 mutations and copy number alterations (CNA-ASXL1/U2AF1); 6) no somatic mutations (No mutation). biTET2/SRSF2 group exhibited monocytic bias with higher AMC, PB and BM monocyte % even among OM-CMML cases. This bias was not attributed to higher RAS pathway mutation frequencies, as biTET2/SRSF2 cases had similar RASp mutation frequencies but lower median variant allele frequencies for RASp mutations compared to NOS cases (9% vs. 21%, p=0.029). PB monocyte partitioning using flow cytometry (FC) in a subset of OM-CMML pts (n=50) demonstrated higher frequency of classical monocytosis (>94% CD14+/CD16- monocytes) in biTET2/SRSF2 vs other OM-CMML. To further determine if biTET2/SRSF2 genotype defines a distinct biological subgroup, we performed RNA-sequencing of BM CD34+ cells from healthy donors (n=15) and pts with OM-CMML (n=12), MD-CMML (n=14) and MDS (n=55). Unsupervised clustering based on gene expression profiles revealed that biTET2/SRSF2 clustered irrespective of their diagnostic group with greater dispersion being observed based on diagnosis. MDS and CMML with biTET2/SRSF2 had less differentially expressed genes compared to MDS and CMML with biTET2/SRSF2 relative to other MDS and CMML genotypes. Among 138 OM-CMML pts in whom progression to overt CMML was evaluable, 37 (27%) progressed to overt CMML of which 26 (70%) belonged to the biTET2/SRSF2 group. Competing risk analysis confirmed higher cumulative incidence and shorter time to CMML progression among biTET2/SRSF2 OM-CMML. Using ElasticNet regression we identified BM monocytosis and 14 genomic variables (including biTET2 and TET2-SRSF2) as predictors of overt CMML progression among OM-CMML. We developed a score-based model able to predict progression with high reliability (AUC 0.805, sensitivity 0.70, specificity 0.76). Model accuracy was confirmed by optimism-corrected bootstrap internal validation (AUC 0.668). Monocytic bias, BM classical monocytosis (>94% CD16- monocytes) and higher overt CMML progression in biTET2/SRSF2 was confirmed in a validation cohort (28, 66 and 22 pts with OM-CMML, MDS and MD-CMML, respectively). BM monocytosis of biTET2/SRSF2 was confirmed in this cohort with morphologic and FC monocyte frequency quantification having high concordance (r=0.737, p<0.001). Genomic subgroup analysis discriminated survival outcomes more reliably than diagnostic categories alone. Our findings suggest that the presence of biTET2 or TET2-SRSF2 co-mutations, combined with BM monocytosis, can more reliably identify true CMML cases within the OM-CMML spectrum. Integrating genomic determinants into the CMML diagnostic framework enhances diagnostic accuracy.

Abstract RAS pathway (RASp) mutations induce proliferative features, and promote transformation in chronic myelomonocytic leukemia (CMML). However, the unique clonal landscape and hierarchy of distinct RASp mutations remain unexplored. To characterize the landscape, architecture, and implications of unique RASp mutations in CMML, we evaluated a cohort of 814 patients with CMML. We identified 461 RASp mutations among 342 patients (42%). N/KRAS and CBL mutations were the most common, frequently involved the P-loop or RING domains, respectively, and frequently appeared as dominant events (63% and 65%, respectively). BRAF, NF1, and PTPN11 mutations spanned throughout the gene structure, and frequently appeared as subclonal events (75%, 64%, and 59%, respectively). CBL mutations frequently occurred in codominance with SRSF2 and multihit TET2, and were enriched for KIT mutations. PTPN11 mutations more frequently co-occurred with SETBP1 and DNMT3A mutations, and were infrequently codominant with TET2 or ASXL1. RASp mutations predicted for shorter overall survival (hazard ratio [HR], 1.55; 95% confidence interval [CI], 1.15-2.07; P = .0075) and leukemia-free survival (LFS; HR, 1.67; 95% CI, 1.26-2.20; P = .0011), influenced outcomes of myelodysplastic and TET2 mutant CMML, and cooperated with IDH2 and RUNX1 mutations to induce shorter LFS. These data set the bases for refined genomic classifications of CMML, and underscore the need to develop RAS-directed therapies for patients with CMML.

We sought to develop a survival model in chronic myelomonocytic leukemia (CMML) that is primarily based on clinical variables and examine additional impact from mutations and karyotype. 457 molecularly-annotated patients were considered. Multivariable analysis identified circulating Blasts ≥2% (1 point), Leukocytes ≥13 x 109/L (1 point), and severe (2 points) or moderate (1 point) Anemia as preferred risk variables in developing a clinical risk Stratification Tool for overall survival (OS), acronymized to "BLAST": low-risk (0 points; median 63 months); intermediate-risk (1 point; median 28 months; HR 2.2, 95% CI 1.6-3.0), and high-risk (2-4 points; median 13 months; 5.4, 4.1-7.3); the corresponding 3/5 year OS rates were 68%/53%, 43%/18%, and 12%/1%. BLAST model performance (AUC 0.77/0.85 at 3/5-years) was shown to be comparable to that of the molecular CMML-specific prognostic scoring system (CMML-mol; AUC 0.73/0.75) and the international prognostic scoring system-molecular (IPSS-M; AUC 0.73/0.74). Multivariable analysis of mutations and karyotype identified PHF6MUT and TET2MUT as being "favorable" and DNMT3AMUT, U2AF1MUT, BCORMUT, SETBP1MUT, ASXL1MUT, NRASMUT, PTPN11MUT, RUNX1MUT, TP53MUT, and adverse karyotype, "unfavorable". Molecular information was subsequently encoded in a combined clinical-molecular risk model (BLAST-mol; AUC 0.80/0.86 at 3/5-years) that included the aforementioned BLAST clinical risk variables and a 3-tiered molecular risk score. BLAST and BLAST-mol were subsequently validated by two separate external cohorts. Independent risk factors for blast transformation included DNMT3AMUT, ASXL1MUT, PHF6WT, leukocytes ≥13 x 109/L, and ≥2% circulating or ≥10% bone marrow blasts. The current study proposes an easy to implement, globally applicable, and molecularly adaptive risk model for CMML.

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 >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 < 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 < 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 < 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 < 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 < 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 < 0.001) or induction chemotherapy (n = 56, mOS 8 mo, HR 0.3, p < 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 < 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.

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 <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<0.001). Among patients with RASMT, 262 (32%), 59 (7%), 20 (2%), 6 (<1%) and 3 (<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 >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 <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 >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 >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.

Introduction Somatic mutations in TET2 are present in ~60% of chronic myelomonocytic leukemia (CMML) patients and are associated with improved median overall (mOS) and acute leukemia free survival (mLFS). Multiple TET2 mutations are detected in ~50% of such cases and are thought to confer additional benefit. Whether these benefits apply to the molecularly distinct myelodysplastic (MD) and myeloproliferative (MP) CMML subtypes is unknown. This study assesses the impact of the number and type of TET2 mutations across the MD and MP-CMML subtypes. Methods CMML patients seen at Mayo Clinic (n = 400, 47%) and MD Anderson Cancer Center (n = 449, 53%) were included with IRB approval. Analyses considered the clinical and molecular data at diagnosis or first referral. Truncating (frameshift or nonsense) mutations in TET2 were further annotated by location in either the proximal genome targeting domain (aa 1 - 1128) or distal catalytic domain (aa 1129 - 1936) as described (Coltro, 2020). Categorical variables were compared by Pearson Chi squared and continuous by Mann-Whitney U or Kruskal-Wallis tests. Univariate and multivariate analyses utilized Cox proportional hazards models with continuous variables binarized by receiver operator curves. Kaplan-Meier analyses were censored at hematopoietic cell transplantation (HCT). P < 0.05 was considered significant. Calculations used BlueSky (v10.3.1) or Prism (v10.2.3). Results In a cohort of 849 CMML patients (median age 71 years, 32% female, 90% white), 454 (54%) were classified as MD-CMML and 394 (46%) as MP-CMML. Cumulatively, 664 somatic TET2 mutations were identified across the MD (n = 415, 63%) and MP-CMML (n = 249, 38%) subgroups, with ≥1 TET2 mutation in 57% vs 44% (p < 0.001) and ≥2 TET2mutations in 33% vs 20% (p = 0.001) , respectively. The median (range) number of TET2 mutations in MD vs MP-CMML was 1 (0 - 4) vs 0 (0 - 3; p < 0.001). Truncating frameshift or nonsense mutations comprised 86% vs 78% of mutations in each group with hypomorphic missense mutations comprising 13% vs 20% (p = 0.03). Proximal (48% vs 43%) and distal (38% vs 35%) truncations were evenly distributed between MD and MP-CMML (p = 0.91). In both the MD and MP subgroups as well as the overall cohort (p < 0.01 each), increasing number of TET2 mutations (0 vs 1 vs ≥2) was associated with higher median hemoglobin (10.3 vs 11.4 vs 12.0 g/dL), fewer mean peripheral blasts (1.3% vs 0.5% vs 0.3%), and a higher proportion of normal karyotypes (60% vs 76% vs 79%). Likewise, co-mutations were increasingly frequent in SRSF2 (36% vs 45% vs 53%) and less frequent in IDH2 (9% vs 1% vs 1%) and SETBP1 (14% vs 4% vs 0%) throughout the cohort. TET2 mutations were mutually exclusive with ETV6, GATA2, IDH1, and WT1 mutations. Uniquely, MD-CMML cases with TET2 mutations (0 vs 1 vs ≥2) were enriched for co-mutations in ZRSR2 (5% vs 13% vs 9%) and had fewer co-mutations in both ASXL1 (47% vs 34% vs 28%) and U2AF1 (11% vs 6% vs 3%). In MP-CMML, co-mutations in CBL (11% vs 20% vs 27%) were increased while co-mutations in BCOR (6% vs 1% vs 0%) were decreased. Accordingly, the favorable ASXL1WT/TET2MT genotype was more common in MD (39% vs 22%), while the adverse ASXL1MT/TET2WT genotype was more common in MP-CMML (20% vs 33%; p < 0.001). In multivariate analyses, the presence of ≥2 TET2 mutations was favorably associated with OS and LFS in both MD and MP-CMML (hazard ratios 0.53 - 0.67, p < 0.04) independent of several clinical and genetic features including ASXL1 mutations and abnormal karyotype. Beyond the number of TET2 mutations, however, neither the mutation class (truncating vs hypomorphic) nor location (proximal vs distal) further affected OS or LFS. Likewise, although the median variant allele fraction (VAF) was lower in MD vs MP-CMML (42% vs 46%, p < 0.001), VAF did not impact survival. Accordingly, the mOS for patients with 0, 1, or ≥2 TET2 mutations was 29, 58, and 75 months in MD-CMML and 19, 26, and 39 months in MP-CMML, respectively (p < 0.001 each). The mLFS was similarly improved to 26, 52, and 67 months in MD-CMML (p < 0.001) and 16, 22, and 31 months in MP-CMML (p = 0.003). CONCLUSIONS This multicenter study demonstrates that the favorable impact of multiple TET2 mutations in CMML extends to both the MD and MP subtypes. In MD-CMML, multiple TET2 mutations segregate against adverse ASXL1 mutations while, in MP-CMML, they appear to offset the impact of adverse RAS pathway mutations. Thus, multiple TET2 mutations may identify a lower-risk subgroup of MP-CMML patients.

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.