New Model Can Assess Blast Phase Progression Risk in Myeloproliferative Neoplasms

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

The study also assessed factors contributing to progression, finding that almost 20% of cases advance to BP, often driven by TP53 and SRSF2 mutations. An analysis of 19 paired MPN chronic phase and MPN BP samples showed increased numbers of high-risk mutations, suggesting that the emergence of new dominating clones underlines progression to BP. The researchers identified that mutations in SRSF2, TET2, RUNX1, and TP53 correlate with progression, and that patients with ET have a higher risk than traditionally understood.¹

The model enhances both the accurate diagnosis of specific MPN subtypes and the assessment of progression risk to BP. This innovative tool enables clinicians to make more informed prognostic and treatment decisions, underscoring the need for expanded genetic testing to improve MPN classification and risk assessment. As BP represents a critical progression point, early identification and targeted care will be essential in enhancing patient outcomes and managing disease progression more effectively.

REFERENCES

1. Walter W, Nadarajah N, Hutter S, et al. Characterization of myeloproliferative neoplasms based on genetics only and prognostication of transformation to blast phase. Leukemia. September 28, 2024. doi:10.1038/s41375-024-02425-1

2. Myeloproliferative neoplasms—patient version. National Cancer Institute. Accessed November 12, 2024. https://www.cancer.gov/types/myeloproliferative

3. Frequent testing for driver mutations critical in myelofibrosis. Physician’s Weekly. November 12, 2024. Accessed November 12, 2024. https://www.physiciansweekly.com/frequent-testing-for-driver-mutations-critical-in-myelofibrosis/

4. Tefferi A, Alkhateeb H, Gangat N. Blast phase myeloproliferative neoplasm: contemporary review and 2024 treatment algorithm. Blood Cancer J. July 18, 2023. doi:10.1038/s41408-023-00878-8