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Updated: Oct 24, 2025
Immunophenotyping and Cell Sorting of Human MKs from Human Primary Sources or Differentiated In Vitro from Hematopoietic Progenitors
Published on: August 7, 2021
Early and late stage MPN patients show distinct gene expression profiles in CD34+ cells
Julian Baumeister1,2, Tiago Maié2,3, Nicolas Chatain1,2
1Department of Hematology, Oncology, Hemostaseology, and Stem Cell Transplantation, Faculty of Medicine, RWTH Aachen University, Aachen, Germany.
Abstract:
Myeloproliferative neoplasms (MPN), comprising essential thrombocythemia (ET), polycythemia vera (PV), and primary myelofibrosis (PMF), are hematological disorders of the myeloid lineage characterized by hyperproliferation of mature blood cells. The prediction of the clinical course and progression remains difficult and new therapeutic modalities are required. We conducted a CD34+ gene expression study to identify signatures and potential biomarkers in the different MPN subtypes with the aim to improve treatment and prevent the transformation from the rather benign chronic state to a more malignant aggressive state. We report here on a systematic gene expression analysis (GEA) of CD34+ peripheral blood or bone marrow cells derived from 30 patients with MPN including all subtypes (ET (n = 6), PV (n = 11), PMF (n = 9), secondary MF (SMF; post-ET-/post-PV-MF; n = 4)) and six healthy donors. GEA revealed a variety of differentially regulated genes in the different MPN subtypes vs. controls, with a higher number in PMF/SMF (200/272 genes) than in ET/PV (132/121). PROGENγ analysis revealed significant induction of TNFα/NF-κB signaling (particularly in SMF) and reduction of estrogen signaling (PMF and SMF). Consistently, inflammatory GO terms were enriched in PMF/SMF, whereas RNA splicing-associated biological processes were downregulated in PMF. Differentially regulated genes that might be utilized as diagnostic/prognostic markers were identified, such as AREG, CYBB, DNTT, TIMD4, VCAM1, and S100 family members (S100A4/8/9/10/12). Additionally, 98 genes (including CLEC1B, CMTM5, CXCL8, DACH1, and RADX) were deregulated solely in SMF and may be used to predict progression from early to late stage MPN.
Insights
This study identifies gene expression signatures in myeloproliferative neoplasms (MPN), revealing potential biomarkers for diagnosis and prognosis. Findings highlight altered signaling pathways, aiding in predicting MPN progression and developing new therapies.
Area of Science:
- Hematology
- Molecular Biology
- Oncology
Background:
- Myeloproliferative neoplasms (MPN), including essential thrombocythemia (ET), polycythemia vera (PV), and primary myelofibrosis (PMF), are clonal hematopoietic stem cell disorders.
- Predicting MPN clinical course and progression is challenging, necessitating novel therapeutic strategies.
- Identifying specific molecular signatures can improve treatment and prevent transformation to aggressive disease states.
Purpose of the Study:
- To identify gene expression signatures and potential biomarkers in different MPN subtypes using CD34+ cells.
- To improve the diagnosis, prognosis, and treatment of MPN.
- To understand molecular mechanisms underlying MPN progression.
Main Methods:
- Systematic gene expression analysis (GEA) of CD34+ cells from 30 MPN patients (ET, PV, PMF, secondary MF) and 6 healthy donors.
- PROGENγ analysis to identify activated or repressed signaling pathways.
- Bioinformatic analysis to identify differentially regulated genes and enriched Gene Ontology (GO) terms.
Main Results:
- GEA revealed numerous differentially regulated genes across MPN subtypes compared to controls, with more in PMF/SMF than ET/PV.
- PROGENγ analysis indicated significant induction of TNFα/NF-κB signaling (especially in SMF) and reduced estrogen signaling (in PMF/SMF).
- Inflammatory GO terms were enriched in PMF/SMF, while RNA splicing processes were downregulated in PMF. Specific genes (e.g., AREG, CYBB, S100 family) were identified as potential diagnostic/prognostic markers. 98 genes deregulated solely in SMF may predict progression.
Conclusions:
- Gene expression profiling of CD34+ cells provides insights into MPN pathogenesis and identifies potential biomarkers.
- Altered TNFα/NF-κB and estrogen signaling pathways are implicated in MPN, particularly in disease progression.
- Specific gene signatures may aid in predicting MPN subtypes, clinical course, and transformation risk, guiding therapeutic strategies.
