Incorporation of genomic determinants improves diagnostic accuracy of oligomonocytic chronic myelomonocytic leukemia

Recent updates to the monocyte count thresholds for diagnosing chronic myelomonocytic leukemia (CMML) have been implemented to recognize oligomonocytic CMML (OM-CMML) as an early stage within the CMML spectrum. However, the clinical validity of these changes remains uncertain without considering biological factors. In this study, we compared a large cohort of patients (N=911) with OM-CMML (n=249), CMML (n=359), and myelodysplastic syndromes (n=303) using unsupervised clustering to assess the role of genomic determinants in improving CMML diagnostic accuracy. Our findings show that CMML molecular signatures, characterized by biallelic TET2 mutations or SRSF2-TET2 co-mutations, are associated with a distinct transcriptome, monocytic bias, classical monocytosis, and progression to overt CMML in OM-CMML cases. By developing a weighted and reproducible model, we demonstrate that genomic features, combined with bone marrow monocyte frequencies, can reliably predict CMML progression in OM-CMML. These results support the integration of genomic determinants into the CMML diagnostic framework to enhance diagnostic accuracy and suggest that incorporation of our proposed clinic-ready diagnostic workflow into clinical practice might reliably identify early stage CMML with oligomonocytic features.