9875 – Scoring Myeloproliferative Neoplasm Fitness to Predict Clinical Outcomes

  • A method to measure and score MPN fitness that predicts clinical outcomes in MPN patients

Background & Unmet Need

  • Myeloproliferative Neoplasms (MPNs) are chronic, phenotypically diverse blood cancers associated with the overproduction of red blood cells, white blood cells, or platelets
  • A significant number of MPNs have a driver mutation in the JAK2 gene, a tyrosine kinase that regulates blood cell and platelet proliferation
  • Whole blood (WB) driver mutation allele frequency (MAF) for genes like JAK2 are often used as crude measures of tumor burden, but these measurements do not reliably distinguish clinical phenotypes or predict treatment outcomes
  • Unmet Need: There is a need for biomarkers that stratify MPN patients to predict treatment response and clinical outcomes

Technology Overview

  • The Technology: A method to measure and score MPN fitness that predicts clinical outcomes in MPN patients
  • The method uses peripheral blood (PB) and bone marrow (BM) samples collected from MPN patients, which are sorted into 11 well-defined and strictly validated hematopoietic stem, progenitor and mature cell populations
  • Unsupervised, hierarchical clustering of MPN fitness revealed 4 major fitness levels (F1, F2, F3, F4), with significantly different but overlapping clinical features
  • PoC Data: The four identified MPN fitness groups were associated with significant differences in event-free survival rate (EFS) at 24 months (Figure 1B), while WB MAF quartile was not predictive of EFS (Figure 1C)
  • MPN fitness group dynamics predicted clinical outcomes (Figure 2B), while WB MAF clustering did not (Figure 2C)

Technology Applications

  • This diagnostic can be used to stratify MPN patients into distinct clusters based on relative risk
  • The diagnostic can also be used as a monitoring biomarker to assess the therapeutic efficacy of treatments for a given patient

Technology Advantages

  • Superior at predicting clinical outcomes for MPN patients compared to alternative diagnostics (e.g., WB MAF quartile clustering)
  • Provides robust MPN clinical monitoring and prediction using easily-obtained patient samples (blood and bone marrow)


  • Abu-Zeinah et al. “Hematopoietic fitness of JAK2V617F myeloproliferative neoplasms is linked to clinical outcome.” Blood Advances. 2022.

Contact Information

Name: Brian J. Kelly

Email: bjk44@cornell.edu

Phone: 646-962-7045