ArticleBlood advances2021
Gene expression profile correlates with molecular and clinical features in patients with myelofibrosis.
Article in Blood advances, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 11 citations in OpenAlex.
- A stem and progenitor cell-derived gene expression signature is prognostic for survival in myelofibrosis.Blood · 2026Article
- Prognostic and Predictive Models in Myelofibrosis.Current hematologic malignancy reports · 2024Review
- Article
- Novel Molecular Insights into Leukemic Evolution of Myeloproliferative Neoplasms: A Single Cell Perspective.International journal of molecular sciences · 2022Review
- Towards a Personalized Definition of Prognosis in Philadelphia-Negative Myeloproliferative Neoplasms.Current hematologic malignancy reports · 2022Review
- Platelet transcriptome identifies progressive markers and potential therapeutic targets in chronic myeloproliferative neoplasms.Cell reports. Medicine · 2021Article
- Increased Plasma Levels of lncRNAsCancers · 2021Article
Corrections and comments
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Authors and funding
32 authors at 7 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Myelofibrosis (MF) belongs to the family of classic Philadelphia-negative myeloproliferative neoplasms (MPNs). It can be primary myelofibrosis (PMF) or secondary myelofibrosis (SMF) evolving from polycythemia vera (PV) or essential thrombocythemia (ET). Despite the differences, PMF and SMF patients are currently managed in the same way, and prediction of survival is based on the same clinical and genetic features. In the last few years, interest has grown concerning the ability of gene expression profiles (GEPs) to provide valuable prognostic information. Here, we studied the GEPs of granulocytes from 114 patients with MF, using a microarray platform to identify correlations with patient characteristics and outcomes. Cox regression analysis led to the identification of 201 survival-related transcripts characterizing patients who are at high risk for death. High-risk patients identified by this gene signature displayed an inferior overall survival and leukemia-free survival, together with clinical and molecular detrimental features included in contemporary prognostic models, such as the presence of high molecular risk mutations. The high-risk group was enriched in post-PV and post-ET MF and JAK2V617F homozygous patients, whereas pre-PMF was more frequent in the low-risk group. These results demonstrate that GEPs in MF patients correlate with their molecular and clinical features, particularly their survival, and represent the proof of concept that GEPs might provide complementary prognostic information to be applied in clinical decision making.
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