A Stem and Progenitor Cell-Derived Gene Expression Signature is Prognostic for Survival in Myelofibrosis Open Access

• MPN24 is a gene expression signature for myelofibrosis (MF) based on transcriptomic analysis of MF stem and progenitor cells (HSPC).

• MPN24 is prognostic for survival in MF, independent of clinical and genomic variables and complements existing models.

We hypothesized that transcriptomic features among disease-driving hematopoietic stem and progenitor cells (HSPC) could improve the current paradigm for risk stratification in myelofibrosis (MF). Therefore, we performed bulk RNA-seq on blood from 358 MF patients split into training and test cohorts (ClinicalTrials.gov Identifier: NCT02760238). Single-cell (sc) RNA-seq data from Lin-CD34+ MF HSPCs were used to guide the development of a prognostic model trained on the bulk RNA-seq data. A NanoString assay was used to validate our final model in two independent cohorts of MF patients. We identified a 24-gene weighted-sum expression score (termed MPN24) that was prognostic of overall survival (OS). In two independent cohorts of 170 and 100 MF patients, MPN24-High scoring patients had worse 5-year OS compared to MPN24-Low scoring patients (25.5% vs 86.9%, HR = 9.81, P = 4.0e-11 and 23.5% vs 75.9%, HR = 6.40, P = 1.8e-7, respectively). MPN24-High was also associated with clinical, mutation and karyotypic features known to confer adverse risk in MF. The MPN24 score retained independent prognostic significance in multivariable analysis incorporating these covariates as well as existing risk stratification models including DIPSS, DIPSS Plus, MIPSS70, and MIPSS70 Plus v2.0, adding significant prognostic value to these risk stratification models (P = 1.6e-5, 4.0e-6, 1.5e-6, 5.4e-4, respectively). The MPN24 score was particularly useful in improving risk-stratification of DIPSS-Intermediate, and MIPSS70 Intermediate and High-risk patients. MPN24 is an HSPC-derived gene expression score that is associated with overall survival independent of clinical and genomic prognostic variables and improves risk stratification in MF.