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Platelet Transcriptome Yields Progressive Markers in Chronic Myeloproliferative Neoplasms and Identifies Putative Targets of Therapy

Predicting disease progression remains a particularly challenging endeavor in chronic degenerative disorders and cancer, thus limiting early detection, risk stratification, and preventive interventions. Here, profiling the spectrum of chronic myeloproliferative neoplasms (MPNs), as a model, we ident...

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Bibliographic Details
Published in:Blood 2021-11, Vol.138 (Supplement 1), p.1469-1469
Main Authors: Shen, Zhu, Du, Wenfei, Perkins, Cecelia, Fechter, Lenn, Natu, Vanita, Maecker, Holden T., Rowley, Jesse W, Gotlib, Jason, Zehnder, James L, Krishnan, Anandi
Format: Article
Language:English
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Summary:Predicting disease progression remains a particularly challenging endeavor in chronic degenerative disorders and cancer, thus limiting early detection, risk stratification, and preventive interventions. Here, profiling the spectrum of chronic myeloproliferative neoplasms (MPNs), as a model, we identify the blood platelet transcriptome as a proxy strategy for highly sensitive progression biomarkers that also enables prediction of advanced disease via machine learning algorithms. Using RNA sequencing (RNA-seq), we derive disease-relevant gene expression in purified platelets from 120 peripheral blood samples constituting two time-separated cohorts of patients diagnosed with one of three MPN subtypes at sample acquisition - essential thrombocythemia, ET (n=24), polycythemia vera, PV (n=33), and primary or post ET/PV secondary myelofibrosis, MF (n=42), and healthy donors (n=21). The MPN platelet transcriptome reveals an incremental molecular reprogramming that is independent of patient driver mutation status or therapy and discriminates each clinical phenotype. Differential markers in each of ET, PV and MF also highlight candidate genes as potential mediators of the pro-thrombotic and pro-fibrotic phenotypes in MPNs. In ET and PV, a strong thromboinflammatory profile is revealed by the upregulation of several interferon inducible transmembrane genes (IFITM2, IFITM3, IFITM10, IFIT3, IFI6, IFI27L1, IFI27L2), interleukin receptor accessory kinases/proteins (IRAK1, IL15, IL1RAP, IL17RC) and several solute carrier family genes (SLC16A1, SLC25A1, SLC26A8, SLC2A9) as glucose and other metabolic transport proteins, and coagulation factor V (F5). In MF, fibrosis-specific markers were identified by an additional focused comparison of MF patients versus ET and PV, showing increased expression of several pro-fibrotic growth factors (FGFR1, FGFR3, FGFRL1), matrix metalloproteinases (MMP8, MMP14), vascular endothelial growth factor A (VEGFA), insulin growth factor binding protein (IGFBP7), and cell cycle regulators (CCND1, CCNA2, CCNB2, CCNF). Also, focusing on the JAK-inhibitor ruxolitinib/RUX-specific signatures, we not only confirm previous observations on its anti-inflammatory and immunosuppressive effects (e.g. downregulation in our RUX-treated cohort of IL1RAP, CXCR5, CPNE3, ILF3) but also identify new gene clusters responsive to RUX - e.g. inhibition of type I interferon (e.g. IFIT1, IFIT2, IFI6), chromatin regulation (HIST2H3A/C, HIST1H2BK, H2AFY, SMARCA4, SMARCC2),
ISSN:0006-4971
1528-0020
DOI:10.1182/blood-2021-153323