November 12, 2024
Author(s): Alexandra Gerlach, Associate Editor
Researchers from Germany developed a model that utilizes 12 genetic markers to accurately distinguish patients with varying myeloproliferative neoplasms (MPNs) including chronic myeloid leukemia (CML) and BCR::ABL1 negative MPNs polycythemia vera (PV), primary myelofibrosis (PMF), and essential thrombocythemia (ET). Using the model, clinicians can more precisely characterize their disease and determine their risk of progression to blast phase (BP).
Red blood cells and DNA strand | Image Credit: © GustavsMD – stock.adobe.com
MPNs are clonal disorders of the blood cells and bone marrow characterized by abnormal hematopoietic proliferation, which have been differentiated into 8 subclasses by the World Health Organization. However, the 4 classical types are CML, PV, PMF, and ET, characterized by mutations in the JAK2, CALR, or MPL driver genes.1,2
Diagnosis of a specific MPN is based on their unique morphology; for example, PV is distinguished by a hypercellular bone marrow and elevated hemoglobin level, compared with ET, which is characterized by megakaryocytic proliferation and increased platelet counts. However, this approach fails to acknowledge overlaps, borderline findings, or potential transitions to other MPN subtypes. Patients with PV and patients with ET can progress to post-PV or post-ET myelofibrosis (MF), underscoring the genetic intricacy of these disorders. There is also the risk of progression to BP, also called leukemic transformation, in which the presence of circulating or bone marrow blasts is ≥20%.2-4
In the study, the researchers aimed to use genetic markers to more effectively stratify CML, PV, PMF, and ET, as well as characterize patients with progression to BP. They developed a machine-learning model based on 12 genetic markers observed in routine analysis to accurately classify MPN subtypes and provide useful prognostic information in a user-friendly decision tree format for clinicians. Using data from over 500 patients, they were able to genetically characterize 355 individuals with 1 of the 4 classic MPNs.1