Mutation profiling of chronic myeloproliferative neoplasms: improving clinical-molecular prognostic models.

Abstract

Introduction: Classic myeloproliferative neoplasms (MPN), comprising polycythemia vera (PV), essential thrombocythemia (ET), and myelofibrosis (MF), both primary and secondary to PV and ET, are clonal hematopoietic disorders characterized by abnormal proliferation of largely mature cells, commonly associated with JAK2, CALR, or MPL mutations. These mutations result in the constitutive activation of the JAK-STAT pathway. Furthermore, most patients - especially with MF - have additional mutations in genes associated with myeloid neoplasms, which encode proteins involved in chromatin modification, DNA methylation, mRNA splicing, transcriptional regulation, and oncogenesis.

Area covered: This review details the molecular landscape of MPN and examines its impact on patient management. It also evaluates emerging artificial intelligence-based prognostic models, highlighting their advantages and limitations.

Expert opinion: High throughput genomic characterization of MPN has identified clinically relevant driver and non-driver mutations. Driver mutations are crucial for diagnosis, monitoring post-transplantation, and treatment response in clinical trials and increasingly in routine practice. Mutation profiles, along with cytogenetic, histopathologic, and clinical data, are used to categorize patients by risk for thrombosis, survival, and progression to secondary leukemia. The identification of a molecular enhanced scoring system for secondary myelofibrosis and clinically relevant co-mutation patterns capable to predict specific outcomes are under investigation.