Regulatory Mrna/Microrna Networks in CD34+ Cells From Primary Myelofibrosis.

Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 2854-2854
Author(s):  
Ruggiero Norfo ◽  
Roberta Zini ◽  
Valentina Pennucci ◽  
Elisa Bianchi ◽  
Simona Salati ◽  
...  

Abstract Abstract 2854 Molecular mechanisms underlying Philadephia-negative myeloproliferative neoplasm (MPN) pathogenesis were partially unraveled in 2005–2006 with the identification of somatic gain-of-function of JAK2 and MPL, after which many other mutated genes were found. Recently, several new molecular pathogenetic mechanisms were identified. Among them, aberrant microRNA (miRNA) expression especially seems to add to the molecular complexity of MPNs, as specific miRNA signatures capable of discriminating MPN cells from those of normal donors were previously reported (P. Guglielmelli et al., Exp Hematol, 2007). In order to have a comprehensive picture of miRNA deregulation and its relationship with differential gene expression in primary myelofibrosis (PMF) cells, we obtained coding gene- (GEP) and miRNA expression profiles (miEP) in the same CD34+ sample from 31 healthy donors and 42 PMF patients by means of Affymetrix technology (HG-U219 and miRNA 2.0 arrays). 726 genes were found as differentially expressed (DEG) (fold change contrast ≥2, false discovery rate ≤0.05) (FIG. 1) and further analysis pointed out that several DEG are related to processes involved in PMF progression as megakaryocyte (MK) differentiation, fibrosis and migration. Of interest, we found the upregulation of some putative cancer markers, such as WT1 (K. Inoue et al., Blood, 1994) and ANGPT1 (C.L. Cheng, Br J Cancer, 2011) whose expression has already been associated with poor prognosis in hematological neoplasms and in other malignancies. Figure 1 Figure 1. Among the deregulated transcription factors, we detected several genes involved in CD34+ commitment, and potentially in their transformation, such as NFE-2 (C. LAbbaye et al., J Clin Invest, 1995) and KLF3 (A.P. Funnell, Mol Cell Biol, 2012). As regards miEP, we achieved a list of 74 human miRNAs modulated in PMF (DEM) (fold change contrast ≥1.5, false discovery rate ≤0.05), some of which associated with hematological malignancies or known as oncomirs are upregulated, i.e. hsa-miR-155-5p (S. Jiang, Cancer Res, 2010), miRNAs belonging to the miR-17–92 cluster (L. Venturini et al., Blood, 2007), whereas other aberrantly expressed miRNAs have never been described in any hematological context. Next, we performed an in silico integrative analysis (IA) with Ingenuity Pathway analysis software, which combines the computational predicted targets with the gene expression data, in order to construct regulatory networks of the functional human miRNA-target interactions. IA between DEG and DEM disclosed a high number of predicted targets with anti-correlated expression to the trend of their targeting miRNAs. This approach allowed the identification of different networks potentially involved in PMF onset and progression, such as MK differentiation and chromatin remodeling, highlighting the potential contribution of miRNAs to PMF pathogenesis. In particular, the integrative analysis has identified an interaction network involving the oncomirs miR-155-5p and miR-29a-3p (R. M. O'Connel et al, J Exp Med, 2008, Y.C. Han et al, j Exp Med, 2010) and their targets (FIG. 2). Figure 2 Figure 2. In this network the upregulation of miR-155-5p and mir-29a-3p could explain the negative regulation of two tumor suppressor genes, HBP1 and TP53INP1, and of SPTB1, CDC42 and KLF3, whose downregulation is involved in malignant hematopoiesis (L.Yang et al, Blood 2007). This network also shows the upregulation of some miRNAs whose function is unknown in the hematopoietic context as miR-335-5p, with the negative regulation of its predicted targets, NR4A3 and PRDM2, which are described as implicated in myeloproliferation (AM Ramirez-Herrick et al, Blood 2001). The present findings lay the groundwork for functional in vitro validation of selected networks in normal and PMF CD34+ cells by means of DEG/DEM overexpression and silencing experiments; furthermore, expression data will be helpful in order to find a clinical correlation between mRNA/miRNA expression levels and diagnostic/prognostic relevance. In conclusion, GEP and miEP pointed out genes and miRNAs candidate for elucidating some of the pathogenetic features of PMF CD34+ cells, whereas IA uncovered potential regulatory networks in which aberrantly expressed miRNAs and genes interact contributing to the malignant phenotype. Disclosures: Vannucchi: Novartis: Membership on an entity's Board of Directors or advisory committees.

Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 1600-1600
Author(s):  
Roberta Zini ◽  
Ruggiero Norfo ◽  
Valentina Pennucci ◽  
Elisa Bianchi ◽  
Simona Salati ◽  
...  

Abstract Ph-negative myeloproliferative neoplasms (MPNs) are characterized by many somatic mutations which have already been shown useful in the prognostic assessment of MPN patients [A.M. Vannucchi et al., Leukemia, 2013]. Moreover, aberrant microRNA (miRNA) expression seems to add to the molecular complexity of MPNs, as specific miRNA signatures capable of discriminating MPN cells from those of normal donors were previously reported [P. Guglielmelli et al., Exp Hematol, 2007]. In order to have a comprehensive picture of miRNA deregulation and its relationship with differential gene expression in primary myelofibrosis (PMF) cells, we obtained gene- (GEP) and miRNA expression profiles (miEP) of CD34+ cells from 31 healthy donors and 42 PMF patients using Affymetrix technology (HG-U219 and miRNA 2.0 arrays). Among 726 differentially expressed genes (DEG) we found that several putative cancer markers (WT1, ANGPT1) and several genes related to PMF progression, i.e. involved in megakaryocyte (MK) differentiation (NFE2, CD9), and fibrosis development (DLK1, LEPR1), were significantly more expressed in PMF samples than in the normal counterpart. Similarly, as regards the miEP, among 74 human differentially expressed miRNAs (DEM) in PMF compared to controls we found the upregulation of several miRNAs associated with hematological malignancies or known as oncomiRs (i.e. hsa-miR-155-5p [S. Jiang et al., Cancer Res, 2010], miRNAs belonging to the miR-17-92 cluster [L. Venturini et al., Blood, 2007]), and other aberrantly expressed miRNAs never described in hematopoiesis (i.e. hsa-miR-335-5p). Then, in order to construct regulatory networks of the functional human miRNA-target interactions, we performed an integrative analysis (IA) with Ingenuity Pathway analysis software, which combines the miRNA expression profile with computational predicted targets and with the gene expression data. IA between DEG and DEM disclosed a high number of predicted targets with anti-correlated expression to the trend of their targeting miRNAs. Of note, IA identified an interaction network (see Figure) in which the upregulated oncomirs miR-155-5p [R.M. O'Connel et al., J Exp Med, 2008], miR29a-3p [Y.C. Han et al., J Exp Med, 2010] and miR-19b-3p [K.J. Mavrakis et al., Nat Cell Biol, 2010] could explain the downregulation of targets whose lower expression was already described as involved in myeloproliferative phenotypes, such as NR4A3, CDC42, HMGB3. Additionally, IA disclosed the chromatin remodeler JARID2, which is frequently deleted in leukemic transformation of chronic myeloid malignancies, as a shared target of several upregulated miRNAs in PMF samples (i.e. miR-155-5p, miR-152-3p). Noteworthy, these miRNA-mRNA interactions were functionally confirmed by 3' UTR luciferase reporter assays. Next, in order to characterize the role of JARID2 in PMF pathogenesis, we performed RNAi-mediated gene silencing experiments on CD34+ cells of healthy donor. Interestingly, inhibition of JARID2 expression produces in silenced cells a significant increase of CD41 expression when compared with control (28.6±3.1% vs 15.3±1.8% at day 8, 52.6±7.6% vs 35.4±4.9% at day 12 of serum free liquid culture) and a remarkable increase in CFU-MK colonies (59.6±6.5% vs 39.8±5.9%). The values are reported as mean ± 2S.E.M from five independent experiments. Moreover, morphological analysis after May-Grunwald-Giemsa staining showed that JARID2 silencing induces in normal CD34+ cells a considerable enrichment in MK precursors at different stages of maturation. This study allowed the identification of different networks possibly involved in PMF onset, highlighting the potential contribution of miRNAs to PMF pathogenesis. Furthermore, for the first time, we demonstrated that the JARID2 downregulation in CD34+ cells might contribute to the abnormal megakaryopoiesis typical of PMF. Disclosures: Rambaldi: Novartis: Honoraria; Sanofi: Honoraria; Italfarmaco: Honoraria.


Blood ◽  
2014 ◽  
Vol 124 (13) ◽  
pp. e21-e32 ◽  
Author(s):  
Ruggiero Norfo ◽  
Roberta Zini ◽  
Valentina Pennucci ◽  
Elisa Bianchi ◽  
Simona Salati ◽  
...  

Key Points Differential gene and miRNA expression analysis in PMF granulocytes identifies new biomarkers and putative therapeutic targets. Activation of the miR-155/JARID2 axis in PMF CD34+ cells results in overproduction of MK precursors.


2015 ◽  
Vol 138 (7) ◽  
pp. 1657-1669 ◽  
Author(s):  
Simona Salati ◽  
Roberta Zini ◽  
Simona Nuzzo ◽  
Paola Guglielmelli ◽  
Valentina Pennucci ◽  
...  

Blood ◽  
2010 ◽  
Vol 116 (21) ◽  
pp. 1926-1926
Author(s):  
Samir B. Amin ◽  
Zhenyu Yan ◽  
Parantu Shah ◽  
Jesús F. San Miguel ◽  
Stephane Minvielle ◽  
...  

Abstract Abstract 1926 Gene regulatory networks with regulatory circuits at different domains are the fundamental mechanism in phenotypic expression of the underlying genome. Regulation by transcription factors (TF) and microRNA (miRNA) are important such domains beside other epigenetic and post-translational gene regulation. With many genomic data sets in recent years, improved understanding of such regulatory network motifs would be of substantial value to find causal genomic alternations in the cancer. A particular example of one such TF-miRNA-gene feed-forward loop (FFL) is, TF (e.g. MYC) regulates the transcription of one or a set of genes/TFs (e.g. E2F1), and the TF (MYC) also regulates the transcription of one or a set of miRNAs (e.g. mir-17-5p and mir-20a), which in turn regulate the same gene or set of genes (E2F1). We hypothesize that an integrative analysis of network motifs and gene expression data can discover experimentally testable TF-miRNA regulation relationships. We have developed computational algorithms based on network motifs and expression data for identifying TF-miRNA pairs important in biological processes and disease states. We construct candidate regulatory networks and rank them using network structure and expression data. We based our prediction on a score-based algorithm, and analyzed publicly available paired gene expression-miRNA profile data from 60 multiple myeloma (MM) patients and 5 samples from healthy donors. We have identified 65 FFLs containing TF-miRNA-gene networks with loss of negative feedback regulation in MM, which supports the uncontrolled growth, anti-apoptosis or other oncogenic effects in MM. Two of the prominent examples involve known proto-oncogenes, c-Myc and FOXA2. We also observed FFL involving c-Myc - mir-629 and target gene PRDM16. Here, concurrently up-regulated c-Myc (TF) and down-regulated mir-629 favors overexpression of target gene, PRDM16, with reported role in myelodysplastic syndrome and acute myeloid leukemia. Similarly, we observe FFL involving HOXA2 – mir-15a and mir-214 and target genes RUNX1T1, HOXC13, NKD1 and PRDM16. Using independent gene expression and miRNA public datasets, we have validated the loss of the negative regulation of these FFLs in MM. We are in the process of functionally validating these identified loops and the associated changes. We will present the predicted FFLs and their biological and functional significance in MM. Such integrative analysis of network motifs and gene expression data can discover experimentally testable TF-miRNA-gene regulatory network and will be instrumental in understanding the biology of the disease, developing clinically relevant integrated models, and translating basic research into targeted therapy. Disclosures: Anderson: Millennium Pharmaceuticals: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau. Munshi:Millennium Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees; Onyx: Membership on an entity's Board of Directors or advisory committees.


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