← BioTransfer GEO Dataset Finder
GEO series

A Stem and Progenitor Cell-Derived Gene Expression Signature is Prognostic for Survival in Myelofibrosis [RNA-Seq]

GSE300470 Homo sapiens Expression profiling by high throughput sequencing 358 samples 2025/12/02 GPL24676
Summary
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 99 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 baseline 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-1 and Intermediate-2 and MIPSS70 Intermediate and High-risk patients. An HSPC-derived gene expression score is associated with overall survival independent of existing clinical and genomic prognostic variables and improves risk stratification in MF.
Download
NCBI GEO page ↗ Paper (PMID 41481381) ↗ {# Names what the click gives you. "Open in finder" meant nothing to a visitor who arrived from a search engine and has never seen the tool. #} Find more human RNA-seq datasets →
Similar datasets

Search all human RNA-seq datasets in GEO →

Share this dataset

Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.