Calvo, Xavier

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 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.