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• W2983856052 abstract "•Unlike liver and lung fibrosis and ET BM, BM from PMF expresses a signature of noncanonical TGF-β signaling activation.•This signature identifies TGF-β as potential target for micro-environment therapy in PMF. Megakaryocytes have been implicated in the micro-environmental abnormalities associated with fibrosis and hematopoietic failure in the bone marrow (BM) of primary myelofibrosis (PMF) patients, the Philadelphia-negative myeloproliferative neoplasm (MPN) associated with the poorest prognosis. To identify possible therapeutic targets for restoring BM functions in PMF, we compared the expression profiling of PMF BM with that of BM from essential thrombocytopenia (ET), a fibrosis-free MPN also associated with BM megakaryocyte hyperplasia. The signature of PMF BM was also compared with published signatures associated with liver and lung fibrosis. Gene set enrichment analysis (GSEA) identified distinctive differences between the expression profiles of PMF and ET. Notch, K-Ras, IL-8, and apoptosis pathways were altered the most in PMF as compared with controls. By contrast, cholesterol homeostasis, unfolded protein response, and hypoxia were the pathways found altered to the greatest degree in ET compared with control specimens. BM from PMF expressed a noncanonical transforming growth factor β (TGF-β) signature, which included activation of ID1, JUN, GADD45b, and genes with binding motifs for the JUN transcriptional complex AP1. By contrast, the expression of ID1 and GADD45b was not altered and there was a modest signal for JUN activation in ET. The similarities among PMF, liver fibrosis, and lung fibrosis were modest and included activation of integrin-α9 and tropomyosin-α1 between PMF and liver fibrosis, and of ectoderm–neural cortex protein 1 and FRAS1-related extracellular matrix protein 1 between PMF and lung fibrosis, but not TGF-β. These data identify TGF-β as a potential target for micro-environmental therapy in PMF. Megakaryocytes have been implicated in the micro-environmental abnormalities associated with fibrosis and hematopoietic failure in the bone marrow (BM) of primary myelofibrosis (PMF) patients, the Philadelphia-negative myeloproliferative neoplasm (MPN) associated with the poorest prognosis. To identify possible therapeutic targets for restoring BM functions in PMF, we compared the expression profiling of PMF BM with that of BM from essential thrombocytopenia (ET), a fibrosis-free MPN also associated with BM megakaryocyte hyperplasia. The signature of PMF BM was also compared with published signatures associated with liver and lung fibrosis. Gene set enrichment analysis (GSEA) identified distinctive differences between the expression profiles of PMF and ET. Notch, K-Ras, IL-8, and apoptosis pathways were altered the most in PMF as compared with controls. By contrast, cholesterol homeostasis, unfolded protein response, and hypoxia were the pathways found altered to the greatest degree in ET compared with control specimens. BM from PMF expressed a noncanonical transforming growth factor β (TGF-β) signature, which included activation of ID1, JUN, GADD45b, and genes with binding motifs for the JUN transcriptional complex AP1. By contrast, the expression of ID1 and GADD45b was not altered and there was a modest signal for JUN activation in ET. The similarities among PMF, liver fibrosis, and lung fibrosis were modest and included activation of integrin-α9 and tropomyosin-α1 between PMF and liver fibrosis, and of ectoderm–neural cortex protein 1 and FRAS1-related extracellular matrix protein 1 between PMF and lung fibrosis, but not TGF-β. These data identify TGF-β as a potential target for micro-environmental therapy in PMF. Mice overexpressing the transcription factor JUN, a gene activated by several inflammatory cytokines including the noncanonical MAPK-dependent transforming growth factor β (TGF-β) [1Yoshida K Kuwano K Hagimoto N et al.MAP kinase activation and apoptosis in lung tissues from patients with idiopathic pulmonary fibrosis.J Pathol. 2002; 198: 388-396Crossref PubMed Scopus (114) Google Scholar, 2Chung WH Bennett BM Racz WJ Brien JF Massey TE Induction of c-jun and TGF-beta 1 in Fischer 344 rats during amiodarone-induced pulmonary fibrosis.Am J Physiol Lung Cell Mol Physiol. 2001; 281: L1180-L1188Crossref PubMed Google Scholar, 3Gervasi M Bianchi-Smiraglia A Cummings M et al.JunB contributes to Id2 repression and the epithelial–mesenchymal transition in response to transforming growth factor-β.J Cell Biol. 2012; 196: 589Crossref PubMed Scopus (63) Google Scholar], develop bone marrow (BM), skin, and lung fibrosis and are predisposed to developing fibrosis in response to stresses to the liver and kidney [4Wernig G Chen SY Cui L et al.Unifying mechanism for different fibrotic diseases.Proc Natl Acad Sci USA. 2017; 114: 4757-4762Crossref PubMed Scopus (102) Google Scholar]. These observations suggest that in mice, shared mechanisms mediate development of fibrosis across organs. This hypothesis is of great clinical relevance as identification of factors that stimulate fibrosis across organs would greatly advance the development of antifibrotic therapies. However, whether shared mechanisms for fibrosis among organs also exist in humans has not yet been established. Bone marrow fibrosis is the hallmark of the micro-environmental abnormalities responsible for hematopoietic failure in primary myelofibrosis (PMF), the most severe of the Philadelphia-negative myeloproliferative neoplasms (MPNs) [5Arber DA Orazi A Hasserjian R et al.The 2016 revision to the World Health Organization classification of myeloid neoplasms and acute leukemia.Blood. 2016; 127: 2391-2405Crossref PubMed Scopus (5642) Google Scholar,6Barosi G Mesa RA Thiele J et al.Proposed criteria for the diagnosis of post-polycythemia vera and post-essential thrombocythemia myelofibrosis: A consensus statement from the International Working Group for Myelofibrosis Research and Treatment.Leukemia. 2008; 22: 437-438Crossref PubMed Scopus (374) Google Scholar]. It has been hypothesized that PMF fibrosis is induced by TGF-β and possibly other inflammatory cytokines, produced by increased numbers of dysplastic megakaryocytes [7Vainchenker W Constantinescu SN Plo I Recent advances in understanding myelofibrosis and essential thrombocythemia.F1000Research. 2016; 5: 700Crossref Scopus (36) Google Scholar,8Zhan H Kaushansky K Functional interdependence of hematopoietic stem cells and their niche in oncogene promotion of myeloproliferative neoplasms: The 159th biomedical version of “it takes two to tango.”.Exp Hematol. 2019; 70: 24-30Abstract Full Text Full Text PDF PubMed Scopus (4) Google Scholar]. Fibrosis, however, is not observed in the BM of patients with essential thrombocythemia (ET), a form of MPN that presents with hyperproliferation of polylobulated megakaryocytes rather than the hypolobulated megakaryocytes that characterize PMF. To identify the fibrosis signature in PMF and to assess whether this signature is similar to that of fibrosis in other organs, we compared the expression profiling of BM from PMF with that of BM from either ET or non-diseased volunteers, as negative controls. The PMF signature was also compared with published signatures of idiopathic pulmonary fibrosis and hepatic fibrosis [9Drews F Knöbel S Moser M et al.Disruption of the latent transforming growth factor-β binding protein-1 gene causes alteration in facial structure and influences TGF-β bioavailability.Biochim Biophys Acta Mol Cell Res. 2008; 1783: 34-48Crossref PubMed Scopus (37) Google Scholar, 10Zhang DY Goossens N Guo J et al.A hepatic stellate cell gene expression signature associated with outcomes in hepatitis C cirrhosis and hepatocellular carcinoma after curative resection.Gut. 2016; 65: 1754-1764Crossref PubMed Scopus (88) Google Scholar, 11Peng X Moore M Mathur A et al.Plexin C1 deficiency permits synaptotagmin 7-mediated macrophage migration and enhances mammalian lung fibrosis.FASEB J. 2016; 30: 4056-4070Crossref PubMed Scopus (36) Google Scholar]. The data presented indicate the presence of shared, but also distinctive signatures between PMF and ET, and between the fibrotic signature of PMF and those of other organs. Cryopreserved mononuclear cells from the BM of 15 PMF and three ET patients was provided as de-identified material by IRCCS Policlinico San Matteo, Pavia, Italy. Bone marrow from eight healthy individuals was purchased from AllCells Technology (Oakland, CA). mRNA in amounts sufficient for analyses was obtained from 6 PMF and all ET patients and healthy controls. The clinical data of informative patients at the time of BM harvest are summarized in Table 1. The study was approved by the institutional review board of Policlinico San Matteo, Pavia, Italy (Authorization No. 20110004143, September 26, 2011) and is compliant with the Declaration of Helsinki for Studies Involving Human Subjects. ET7 was analyzed twice, at 3 years postdiagnosis (a) and 1 year later (b).Table 1Clinical features of the MPN patients included in the studyIDSexAge at diagnosisNo. of evaluationsDisease durationIPSSFibrosis gradeMutation (allele burden)TherapyPMF1F5725 yInt-2MF3JAK2 (86%)HydroxPMF2F7222 yInt-1MF3JAK2 (Het)HydroxPMF3M8121 yInt-1MF1CALR [del]NoPMF4M38216 yInt-10/1JAK2 (Het)RuxolPMF5M6815 yInt-1MF2CALR [ins]RuxolPMF6M5414 yInt-2MF1JAK2 (76%)RuxolET7aM5124 yHigh0MPLHydroxET7bM5113 yLow0MPLHydroxET8M4714 yLow0JAK2 (Het)AspirinET9F671DiagnosisHigh0JAK2 (5%)Aspirin Open table in a new tab Total RNA was prepared with Trizol (Gibco-BRL, Grand Island, NY) and purified with the Rneasy Mini Kit (Qiagen, Germantown, MD). Hybridization to the microarray Human HT-12_v4 Bead Chip gene expression array (Illumina, San Diego, CA, USA) was performed by the Microarray Resource Facility, Icahn School of Medicine at Mount Sinai. Two sequential microarray analyses were performed. Microarray 1 included 3 PMF patients, two replicate measurements each (PMF1-3, Table 1), and 5 nondiseased controls, one measurement each. Microarray 2 included 3 PMF patients (PMF4 and a pool of PMF5 and PMF6), 3 ET patients (ET7–ET9, Table 1) and 3healthy controls. PMF4 was analyzed in duplicate, the PMF5/PMF6 pool, ET7, ET9, and the healthy controls were measured once. BM from ET7 was analyzed at 3 years (two replicates) and 4 years postdiagnosis. The entire microarray data set is available in the Gene Expression Omnibus database, http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE124281. By using the GenomeStudio software (Illumina), the two microarrays were imported into gene cluster text (GCT) files (GCT file 1 and GCT file 2). In total, 47,323 RNA microarray probes were identified with a handful of missing values (of 47,323 probes, 7 were missing from GCT file 1 and 22 from GCT file 2), which was probably due to failure during the import of the microarray data into the GCT files. By use of SAS 9.4 software (SAS, Cary, NC), the two separate files were combined into one GCT file, and the data were normalized with the Illumina Normalizer (Illumina) module in GenePattern (Broad Institute, University of California, San Diego, CA). The data were then analyzed with the sampleFilterPercentP_R2 module of GenePattern and found to be of good quality (correlation to median array >0.95for all samples). The collapsed data by gene (took median) were created with the CollapseDataset module in GenePattern, and identified 31,426 genes. Primary component analysis (PCA) with the PCA module in GenePattern verified that the controls included in GCT files 1 and 2 were similar (Figure 1A). The data reflected the strong separation and clustering of samples, demonstrating the quality of the data. The first principal component contains the difference between controls and patients with MF, about 10% of the variance in the data (Figure 1A). Finally, we collapsed the data set by subject (took average) and excluded genes with coefficients of variation (= SD/mean) <0.1, to create the final data set for analysis. Collectively, we analyzed 8,528 genes (after excluding 22,898 noise genes). Gene set enrichment analysis was performed with the GSEA module in GenePattern, utilizing the human gene sets h.all.v6.1.symbols.gmx, comparing PMF with control, ET with control, and PMF with ET.Figure 1Comparison of the expression profiles of BM from PMF patients, ET patients, and healthy controls. (A) Principal component analysis (PCA). To assess the relationship between samples, we performed PCA on the normalized data obtained in duplicate on the same sample in the two data sets. The strong separation and clustering of samples indicate the high reproducibility of data from the same sample. The first PCA reveals differences between controls and patients with MF, about 10% of the variance in the data. (B) Comparison of the 100 genes (50 most upregulated and 50 most downregulated) differentially expressed by BM from PMF patients with respect to healthy controls, those from ET patients with respect to healthy controls, and those from PMF patients with respect to ET, as indicated.View Large Image Figure ViewerDownload Hi-res image Download (PPT) The false discovery rate (FDR) were used for multiple comparisons of gene expressions. Genes were considered up- and downregulated when fold changes were >1.4 and <0.7, respectively. In multiple comparison of genes, the level of significance was set at p < 0.05 (significant) and p < 0.1 (trend). The expression profiles of the PMF and ET patients were heterogeneous, whereas those of controls were tightly clustered (Figure 1A). As the duplicate measurements of the same patient were also tightly clustered (Figure 1A), the variability among patients likely reflects differences in driver mutations and/or fibrosis levels (International Prognostic Score System int-1–2 and fibrosis grade 1–3) (Table 1). The expression profile of ET7 clustered with that of PMF3 at the 3-year time point and with that of PMF4 at the 4-year time point (Figure 1A). The fact that the top 50 genes differentially expressed in ET7 at the two time points remain the same and do not include any gene differentially expressed between patients and controls (Figure 1B; Supplementary Figure S1, online only, available at www.exphem.org) suggests that differences observed in ET7 at the 3- and 4-year time points underlie variability unrelated to MPN. Despite the heterogeneity in expression profiles among patients, common abnormalities were observed between patients and healthy controls (Figure 1B and data not shown). In PMF, there were 426–516 transcripts up- and downregulated in the patients, as compared with controls. As expected because of the great frequency of megakaryocytes in PMF, expression of the megakaryocyte-specific transcription factor GATA1 was significantly upregulated in PMF (1.5-fold higher than in healthy controls, p = 0.04). The transcription factor JUN (3.0-fold higher than normal controls, p = 0.01) and its related genes JUNB (1.2-fold, p = 0.767) and FOSB (2.8-fold, p = 0.06) were also among the most enriched genes relative to controls (Figure 1B). Because the transcription factor complex JUN/FOS binds to consensus sequences defined as AP-1 [12Prusty BK Das BC Constitutive activation of transcription factor AP-1 in cervical cancer and suppression of human papillomavirus (HPV) transcription and AP-1 activity in HeLa cells by curcumin.Int J Cancer. 2005; 113: 951-960Crossref PubMed Scopus (189) Google Scholar, 13Rösl F Das BC Lengert M Geletneky K Zur Hausen H Antioxidant-induced changes of the AP-1 transcription complex are paralleled by a selective suppression of human papillomavirus transcription.J Virol. 1997; 71: 362-370PubMed Google Scholar, 14Antinore MJ Birrer MJ Patel D Nader L McCance DJ The human papillomavirus type 16 E7 gene product interacts with and trans-activates the AP1 family of transcription factors.EMBO J. 1996; 15: 1950-1960Crossref PubMed Scopus (190) Google Scholar], we confirmed that the high levels of JUN/FOS expressed by BM from PMF have physiological consequences by determining that the expression of several genes with putative AP-1 binding sites was also significantly altered in the profiling of the BM from the three PMF patients analyzed using microarray 1 (Table 2).Table 2Molecular pathways differentially induced between MF patients and controls (GSEA)Gene set databaseGene sets induced in MFNESpFDRGenes with AP1-related binding motif in their promoter*In the regions spanning up to 4 kb around transcription start site in the TRANSFAC database, Version 7.4 (http://gene-regulation.com/pub/databases.html).AP1_011.710.0000.000AP1_Q61.680.0000.003AP1_Q6_011.570.0000.007AP1_C1.560.0020.005AP1_Q41.540.0000.005AP1_Q4_011.440.0000.010AP1_Q2_011.430.0020.009AP1FJ_Q21.320.0090.025AP1_Q21.230.0330.060NES=normalized enrichment score; FDR=false discovery rate. Gene sets with an FDR <0.25 or top 20 are shown. Gene sets with an FDR >0.05 are in boldface. In the regions spanning up to 4 kb around transcription start site in the TRANSFAC database, Version 7.4 (http://gene-regulation.com/pub/databases.html). Open table in a new tab NES=normalized enrichment score; FDR=false discovery rate. Gene sets with an FDR <0.25 or top 20 are shown. Gene sets with an FDR >0.05 are in boldface. We found that the strong JUN signature of PMF BM determined in the current study confirms the high levels of expression of this transcription factor previously described by us by analyzing BM from three additional PMF patients with TGF-β-specific microarrays [15Ciaffoni F Cassella E Varricchio L Massa M Barosi G Migliaccio AR Activation of non-canonical TGF-beta1 signaling indicates an autoimmune mechanism for bone marrow fibrosis in primary myelofibrosis.Blood Cells Mol Dis. 2015; 54: 234-241Crossref PubMed Scopus (25) Google Scholar]. It is also consistent with the high JUN and FOS content detected by immunohistochemistry in stromal cells from BM biopsies of 57 PMF patients [4Wernig G Chen SY Cui L et al.Unifying mechanism for different fibrotic diseases.Proc Natl Acad Sci USA. 2017; 114: 4757-4762Crossref PubMed Scopus (102) Google Scholar]. In ET, there were 332–833 transcripts up- and downregulated, with respect to healthy controls (FDR, p < 0.10). Of those, 81 and 77 were consistently up- and down-regulated in all patients (Figure 1B). In the case of ET, the gene upregulated the most was PTGS2 (prostaglandin-endoperoxide synthase 2, also known as COX), an enzyme involved in the prostaglandin biosynthetic pathway expressed at high levels in BM and a potent mediator of inflammation [16Ricciotti E Fitzgerald GA Prostaglandins and inflammation.Arterioscler Thromb Vasc Biol. 2011; 31: 986-1000Crossref PubMed Scopus (2283) Google Scholar]. In ET, JUN and FOS were expressed at levels lower than those in PMF and there was only a trend toward activation (JUN, 3.0-fold increase, p = 0.097; FOSB, 4.3-fold increase, p = 0.097) relative to controls. In our study, mRNA was prepared from BM mononucleated cells thawed after cryopreservation. BM mononuclear cells are a heterogeneous population enriched for hematopoietic (mainly stem/progenitor cells, megakaryocytes, and monocytes) and stromal (mesenchymal stem cells, fibroblasts, and endothelial cells) cells and deprived of erythroid cells and granulocytes by the thawing procedure. Based on histological data, we infer that BM mononuclear cells from PMF and ET contain ∼3-fold more megakaryocytes than normal samples, while PMF is slightly enriched for CD34+ cells (2%–3%) than both ET and normal controls (∼ 2% in both cases). The overall content of monocytes and stromal cells is instead comparable among samples. To assess the contribution of stem/progenitor cells to the expression signature of BM mononuclear cells, we compared the expression profile of PMF BM with that of PMF CD34+ cells published by Guglielmelli et al. [17Guglielmelli P Zini R Bogani C et al.Molecular profiling of CD34+ cells in idiopathic myelofibrosis identifies a set of disease-associated genes and reveals the clinical significance of Wilms’ tumor gene 1 (WT1).Stem Cells. 2007; 25: 165-173Crossref PubMed Scopus (104) Google Scholar] (Supplementary Table S1, online only, available at www.exphem.org). Three of the 12 genes found differentially expressed in CD34+ cells were excluded as noise before statistical evaluation. Three genes (CD9, DLK1, and NFE-2) upregulated in Guglielmelli et al. [17Guglielmelli P Zini R Bogani C et al.Molecular profiling of CD34+ cells in idiopathic myelofibrosis identifies a set of disease-associated genes and reveals the clinical significance of Wilms’ tumor gene 1 (WT1).Stem Cells. 2007; 25: 165-173Crossref PubMed Scopus (104) Google Scholar] were also found upregulated above threshold (>1.7-fold change) with respect to controls in our study. Therefore, despite their low numbers, we believe that CD34+ cells have contributed to the readouts of our arrays. It has been suggested that the stromal and hematopoietic cells of BM respond to TGF-β by activating its noncanonical MAPK-dependent and canonical SMAD-dependent signaling pathway, respectively (see Graphical Abstract, online only, available at www.exphem.org). Because JUN is an important target of the noncanonical pathway, the strong JUN signature detected in PMF suggests that in these patients, TGF-β signaling is mostly active in stromal cells. To confirm that the canonical TGF-β signaling is not active in PMF and to exclude that the observed JUN overexpression is mediated by some other inflammatory cytokine [18Kaminska B Molecular characterization of inflammation-Induced JNK/c-Jun signaling pathway in connection with tumorigenesis.Methods Mol Biol. 2009; 512: 249-264Crossref PubMed Scopus (13) Google Scholar], the TGF-β gene expression profiling of PMF and ET with respect to controls was compared using GSEA (Figure 2). The differences observed in the TGF-β data set between samples were in general modest and not consistent. In agreement with the notion that it is not the expression of TGF-β per se but rather its bioavailability in the microenvironment that is increased in PMF [19Zingariello M Ruggeri A Martelli F et al.A novel interaction between megakaryocytes and activated fibrocytes increases TGF-β bioavailability in the Gata1(low) mouse model of myelofibrosis.Am J Blood Res. 2015; 5: 34-61PubMed Google Scholar], TGF-β was not detected in the PMF or ET signature. However, when compared with controls, PMF bone marrow had more TGF-β-related genes (5 genes, 3 upregulated and 2 downregulated) expressed at altered levels than ET (3 genes, all upregulated). In PMF, there was a significant abnormal expression of HIPK2 (downregulated) and of ID1 and JUN (upregulated) and a trend toward greater expression of FOSB and GADD45b. In addition, comparison of the TGF-β signature of PMF patients with fibrosis grade 3 (PMF1 and PMF2) with that of patients with fibrosis grade 0–2 (PMF3–PMF6) (Supplementary Table S2, online only, available at www.exphem.org) indicates that the upregulation of the expression of the non-canonical TGF-β target genes FOSb, GADD45b and ID1/2 increases with disease progression. Interestingly, BM from PMF grade 3 patients also expresses greater levels of HIPK2, homeodomain-interacting protein kinase 2, a gene encoding a serine/threonine protein kinase that interacts with homeodomain transcription factors [20Wang Y Hofmann TG Runkel L et al.Isolation and characterization of cDNAs for the protein kinase HIPK2.Biochim Biophys Acta Gene Struct Expr. 2001; 1518: 168-172Crossref PubMed Scopus (21) Google Scholar,21Ki SS Yoon YG Ahn JH Young HK Kim Y Cheol YC Differential interactions of the homeodomain-interacting protein kinase 2 (HIPK2) by phosphorylation-dependent sumoylation.FEBS Lett. 2005; 579: 3001-3008Crossref PubMed Scopus (32) Google Scholar] and is activated, by overexpression or loss of heterozygosity, in animal models of kidney fibrosis [22Jin Y Ratnam K Chuang PY et al.A systems approach identifies HIPK2 as a key regulator of kidney fibrosis.Nat Med. 2012; 18: 580-588Crossref PubMed Scopus (114) Google Scholar, 23Saul VV Schmitz ML Posttranslational modifications regulate HIPK2, a driver of proliferative diseases.J Mol Med. 2013; 91: 1051-1058Crossref PubMed Scopus (32) Google Scholar, 24Ricci A Cherubini E Ulivieri A et al.Homeodomain-interacting protein kinase2 in human idiopathic pulmonary fibrosis.J Cell Physiol. 2013; 228: 235-241Crossref PubMed Scopus (22) Google Scholar] and in patients with idiopathic pulmonary fibrosis [25Saul VV. de la Vega L Milanovic M et al.HIPK2 kinase activity depends on cis-autophosphorylation of its activation loop.J Mol Cell Biol. 2013; 5: 27-38Crossref PubMed Scopus (49) Google Scholar]. By contrast, in ET there was a modest TGF-β signature that included a trend toward FOSB, JUN, and IL6 upregulation with respect to controls. Activation of the noncanonical p38/ERK-dependent TGF-β signature JUN, ID1, and GADD45 [26Ghosh AK Quaggin SE Vaughan DE Molecular basis of organ fibrosis: Potential therapeutic approaches.Exp Biol Med (Maywood). 2013; 238: 461-481Crossref PubMed Scopus (112) Google Scholar,27Massagué J Blain SW Lo RS TGFβ signaling in growth control, cancer, and heritable disorders.Cell. 2000; 103: 295-309Abstract Full Text Full Text PDF PubMed Scopus (2068) Google Scholar] was already reported both in PMF patients and in the Gata1low animal model of the disease [28Zingariello M Martelli F Ciaffoni F et al.Characterization of the TGF-b1 signaling abnormalities in the Gata1low mouse model of myelofibrosis.Blood. 2013; 121: 3345-3363Crossref PubMed Scopus (73) Google Scholar]. In addition, expression of these genes was normalized in the mouse model by treatment with a TGF-β receptor 1 kinase inhibitor [28Zingariello M Martelli F Ciaffoni F et al.Characterization of the TGF-b1 signaling abnormalities in the Gata1low mouse model of myelofibrosis.Blood. 2013; 121: 3345-3363Crossref PubMed Scopus (73) Google Scholar], which also rescued their myelofibrosis phenotype. We believe that overexpression of these genes observed in PMF BM is an indication that the stromal cells are being activated by TGF-β to produce fibrosis (see Graphical Abstract, online only, available at www.exphem.org). By contrast, the target genes expected to be activated by the canonical TGF-β signaling were either expressed at normal levels or downregulated in BM of PMF patients. These genes included CDKN1b and HIPK2. CDKN1b, cyclin-dependent kinase inhibitor 1b, encodes p27Kip1, which induces normal hematopoietic stem/progenitor cells into quiescence in response to TGF-β [29Polyak K Lee MH Erdjument-Bromage H et al.Cloning of p27Kip1, a cyclin-dependent kinase inhibitor and a potential mediator of extracellular antimitogenic signals.Cell. 1994; 78: 59-66Abstract Full Text PDF PubMed Scopus (2051) Google Scholar,30Scandura JM Boccuni P Massague J Nimer SD Transforming growth factor-induced cell cycle arrest of human hematopoietic cells requires p57KIP2 up-regulation.Proc Natl Acad Sci USA. 2004; 101: 15231-15236Crossref PubMed Scopus (196) Google Scholar] and was also found to be downregulated in BM from PMF patients by Ciaffoni et al. [15Ciaffoni F Cassella E Varricchio L Massa M Barosi G Migliaccio AR Activation of non-canonical TGF-beta1 signaling indicates an autoimmune mechanism for bone marrow fibrosis in primary myelofibrosis.Blood Cells Mol Dis. 2015; 54: 234-241Crossref PubMed Scopus (25) Google Scholar] (see Graphical Abstract, online only, available at www.exphem.org). We believe that downregulation of CDKN1b in BM of PMF reflects the paucity or insensitivity [31Ceglia I Dueck AC Masiello F et al.Preclinical rationale for TGF-β inhibition as a therapeutic target for the treatment of myelofibrosis.Exp Hematol. 2016; 44 (1138–1155.e4)Abstract Full Text Full Text PDF PubMed Scopus (33) Google Scholar] of hematopoietic cells that respond to TGF-β in PMF BM. Support for the hypothesis that the expression signatures we have identified reflect the disease status of the patient comes from the observation that IL-8 was upregulated in the BM signature of PMF but not in that of ET. The overexpression of IL-8 in PMF BM is in agreement with recent observations indicating that the plasma of PMF patients, but not that from ET, contains greater levels of IL-8 than normal, which correlates with disease prognosis [32Tefferi A Vaidya R Caramazza D Finke C Lasho T Pardanani A Circulating interleukin (IL)-8, IL-2R, IL-12, and IL-15 levels are independently prognostic in primary myelofibrosis: A comprehensive cytokine profiling study.J Clin Oncol. 2011; 29: 1356-1363Crossref PubMed Scopus (415) Google Scholar]. The differences in expression profiling between PMF and ET were further characterized by pathway analyses with GSEA (Table 3). The expression pathways altered in PMF and ET were quite distinct. Notch signaling was the most enriched pathway in PMF (NES = 1.62, p = 0.046), followed by K-RAS (NES = 1.51, p = 0.036) and apoptosis (NES = 1.47, p = 0.121) as compared with healthy controls. In contrast, cholesterol homeostasis was the most enriched pathway in ET (NES = 1.62, p = 0.00), followed by unfolded protein response (NES = 1.18, p = 0.203). Notch and K-RAS were enriched in PMF even when the data were compared with those for ET. The individual genes abnormally expressed in each pathway are summarized in Table 4.Table 3GSEA enrichment terms from Gene Ontology using GSEA for PMF versus control, ET versus control, and PMF versus ETName of enrichment termSizeESNESNOM p-valFDR p-valFWER p-valPMF versus controlNOTCH_SIGNALING170.571.620.0460.7950.292KRAS_SIGNALING_DN380.4" @default.
• W2983856052 created "2019-11-22" @default.
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• W2983856052 title "Shared and Tissue-Specific Expression Signatures between Bone Marrow from Primary Myelofibrosis and Essential Thrombocythemia" @default.
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• W2983856052 doi "https://doi.org/10.1016/j.exphem.2019.10.001" @default.
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