Classification and prognostic stratification based on genomic features in myelodysplastic neoplasms, myeloproliferative neoplasms, and their overlapping conditions

Abstract In this study, we analyzed clinical and genomic data from 1,585 patients diagnosed with myeloid neoplasms (MNs), including myeloproliferative neoplasms (MPN, n = 715), myelodysplastic neoplasms (MDS, n = 698), MDS/MPN (n = 94), and aplastic anemia (AA, n = 94). We identified ten distinct genomic groups that redefine MN classification using unsupervised genomic clustering through the Dirichlet Process (DP), correlating specific genetic mutations with survival outcomes and disease subtypes. Notably, groups DP1 and DP5, characterized by JAK2 and CALR mutations, respectively, showed a very favorable prognosis among patients with MPN. Groups DP2, DP7, and DP9 demonstrated a very adverse prognosis across MN subtypes. Specifically, DP2 encompasses MDS patients with TP53 mutations and complex karyotypes, DP9 is distinguished by acute myeloid leukemia-related mutations, including NPM1, and DP7 includes patients with SETBP1 mutations, indicating heterogeneous MN phenotypes. DP10 and DP8, linked to SF3B1, DDX41 mutations or chromosome 1q derivatives present a favorable risk profile. Our research emphasizes the critical role of genomic insights in enhancing the classification, prognostic accuracy, and therapeutic stratification of MNs. The survival improvement observed with transplantation in the very adverse risk groups underscores the potential of genomic classifications to inform personalized treatment strategies, signifying a significant step toward the integration of genomics into MN clinical management.