Characterization of myeloproliferative neoplasms based on genetics only and prognostication of transformation to blast phase

Abstract

Abstract Myeloproliferative neoplasms (MPN) are a heterogeneous group of clonal disorders characterized by aberrant hematopoietic proliferation and an intrinsic risk of progression to blast phase. The WHO classification 2022 identifies chronic myeloid leukemia and the BCR::ABL1 negative MPNs polycythemia vera, primary myelofibrosis and essential thrombocythemia as individual entities. However, overlaps, borderline findings or transitions between MPN subtypes occur and incomplete clinical data often complicates diagnosis. Through comprehensive genetic characterization, we developed a machine learning model based on 12 genetic markers, which can stratify MPN patients with high accuracy and can be translated into a simple decision tree. Comparing samples at chronic and blast phase revealed, that one third of patients lost their MPN driver-gene mutation, while mutations in splicing and chromatin modifying genes were stable, indicating a shared founder clone of chronic and blast phase with different driver mutations and therefore different progressing capacities. This was further supported by gain of typical de novo AML gene mutations, accompanied by gain of complex karyotypes and RAS pathway gene mutations. Our data suggest to perform a broader genetic screening at diagnosis and also at clinical progress, as driver mutations may change and the MPN driver mutations present at diagnosis may disappear.