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Experimental Modeling of Myeloproliferative Neoplasms

Authors: Olga Babosova; Josef T. Prchal; Josef T. Prchal; Lucie Lanikova;

Experimental Modeling of Myeloproliferative Neoplasms

Abstract

Myeloproliferative neoplasms (MPN) are genetically very complex and heterogeneous diseases in which the acquisition of a somatic driver mutation triggers three main myeloid cytokine receptors, and phenotypically expresses as polycythemia vera (PV), essential thrombocytosis (ET), and primary myelofibrosis (PMF). The course of the diseases may be influenced by germline predispositions, modifying mutations, their order of acquisition and environmental factors such as aging and inflammation. Deciphering these contributory elements, their mutual interrelationships, and their contribution to MPN pathogenesis brings important insights into the diseases. Animal models (mainly mouse and zebrafish) have already significantly contributed to understanding the role of several acquired and germline mutations in MPN oncogenic signaling. Novel technologies such as induced pluripotent stem cells (iPSCs) and precise genome editing (using CRISPR/Cas9) contribute to the emerging understanding of MPN pathogenesis and clonal architecture, and form a convenient platform for evaluating drug efficacy. In this overview, the genetic landscape of MPN is briefly described, with an attempt to cover the main discoveries of the last 15 years. Mouse and zebrafish models of the driver mutations are discussed and followed by a review of recent progress in modeling MPN with patient-derived iPSCs and CRISPR/Cas9 gene editing.

Keywords

Myeloproliferative Disorders, Induced Pluripotent Stem Cells, Review, Janus Kinase 2, Disease Models, Animal, Mice, Phenotype, Primary Myelofibrosis, Neoplasms, Mutation, Animals, Humans, Calreticulin, Polycythemia Vera, Receptors, Thrombopoietin, Zebrafish, Signal Transduction, Thrombocythemia, Essential

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    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    11
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
11
Top 10%
Average
Top 10%
Green
gold