Researchers identify genomic clusters to refine myelodysplastic syndromes classifications
A data-driven approach can successfully harmonized the WHO and International Consensus Classification 2022 systems for myelodysplastic syndromes (MDS), addressing inconsistencies in their application, according to a panel of experts who hope harmonization will provide a more effective framework for understanding and treating MDS.
The panel of hematologists, hematopathologists, and data scientists from the International Consortium for Myelodysplastic Syndromes utilized a modified Delphi consensus process to align the two classification systems. They focused on genomic features influencing cluster assignments, meeting regularly and conducting a two-round survey for feedback.
Their research identified 9 distinct genomic clusters. The most critical cluster was marked by biallelic TP53 inactivation, while individuals with monoallelic TP53 were placed in different clusters. The second notable group included MDS with del(5q), characterized by isolated del(5q) and fewer than 5% bone marrow blasts. Additionally, MDS with mutated SF3B1 formed another cluster, distinguished by the absence of several genetic abnormalities.
The study revealed significant genomic diversity among morphologically defined MDS entities, which single-lineage versus multilineage dysplasia criteria failed to capture effectively. The researchers also examined the genetic overlap between MDS and acute myeloid leukemia, finding only partial similarities.
Ultimately, the study recognized MDS with low blasts (≤5%) and those with increased blasts (≥5%) as distinct entities. This data-driven approach aims to streamline classifications of MDS, offering a valuable reference for patient management in clinical settings.
Reference
Komrokji RS, Lanino L, Ball S, et al; International Consortium on Myelodysplastic Syndromes. Data-driven, harmonised classification system for myelodysplastic syndromes: a consensus paper from the International Consortium for Myelodysplastic Syndromes. Lancet Haematol. 2024;S2352-3026(24)00251-5. doi: 10.1016/S2352-3026(24)00251-5. Epub ahead of print. PMID: 39393368.
