Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA128875 | ENA |
REPOSITORIES: ENA
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Project description:The activation of PD-1 (Programmed Death receptor-1) on T cells can cause T cell exhaustion and immune tolerance. Some tumors up-regulate the expression of the ligand of PD-1, namely PD-L1 (Programmed Death Receptor-Ligand 1), thus preventing anti-tumor immune response and promoting immune-escape. Previous studies have shown that JAK2 (Janus Kinase 2) signaling can promote PD-L1 expression in Hodgkin Lymphoma. In Myeloproliferative Neoplasms (MPN), JAK2 is frequently characterized by the the presence of the point-mutation V617F, which leads to its constitutive activation and to uncontrolled cell proliferation and survival. Accordingly, tumor cell lines expressing JAK2 V617F express higher levels of PD-L1 as compared to tumor cell lines negative for such mutations. In this experiment, we transfected BaF3 cells with a vector (plasmid for Murine Stem Cell Virus) containing the gene for JAK2 with the point-mutation V617F. As control, we used BaF3 cells transfected with the same vector, but without the gene for JAK2 V617F (empty vector). Both the cell lines (with/without JAK2 V617F) were co-cultured with primary murine T cells. When co-cultured with BaF3 cells expressing JAK2 V617F, T cells upregulated genes connected to senescence pathways, showed increased apoptosis, less cytokine production, and displayed other forms of dysfunction which can be associated with the activation of PD-1.
2018-12-01 | E-MTAB-5028 | biostudies-arrayexpress
Project description:Cell lines of mediastinal lymphomas, one each of primary mediastinal (thymic) large B cell lymphoma (PMBL), classic Hodgkin lymphoma (CHL), B-cell lymphoma, unclassifiable, with features intermediate between diffuse large B-cell lymphoma and CHL, and T-cell lymphoma were treated with rituximab (RmAb), brentuximab vedotin (BV), ibrutinib (IBR), prednisone (PRED) or untreated (UT) for 48 hours. Flow cytometry for PD-L1 protein was performed, and differential expression (DE) analysis of mRNA and miRNA performed by RNAseq. B-cell lines exhibited 2- fold increase in PD-L1 protein (p<.05) with RmAb compared to UT. Others showed no effect of RmAb, however, the T-cell line showed 2-fold increase on treatment with BV (P<.05). DE performed by limma showed no genomic level changes. ANOVA analysis of PMBL treated with RmAb, however, showed physiologic level DE involving >3000 genes involving multiple pathways associated with cell death and survival, protein degradation, mRNA translation, mRNA degradation, immunologic functions, and PD-1/PD-L1 immunotherapy. In the B cell lines, DE of CD274 (PD-L1) was decreased or not significant. MiRNA DE showed upregulation of 7 miRNAs, including miR-155-5p.
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Project description:Amplification of a ~2.5 megabase region on chromosome 9p24 is frequent in both primary mediastinal B-cell lymphoma (PMBL) and Hodgkin's lymphoma (HL). To identify the oncogenic genes in this interval, we created a RNA interference library targeting amplicon genes. A genetic screen using this library identified three genes that are essential for the proliferation and survival of PMBL and HL lines with this amplicon, which encode the kinase JAK2, the histone demethylase JMJD2C and a gene of unknown function, RANBP6. Inhibition of JAK2 and JMJD2C cooperated in killing these lymphomas and in remodeling their chromatin by globally increasing trimethylation of lysine 9 on histone H3 (H3K9me3) and heterochromatin formation. JAK2 and JMJD2C inhibition silenced MYC and its target genes, which coincided with an increase in H3K9me3 and the heterochromatin protein HP1alpha at the MYC locus. We conclude that amplification of JAK2 and JMJD2C cooperatively reprograms the PMBL and HL epigenome, sustaining their survival and proliferation. Signal from untreated shRNA cells or DMSO control cells (Cy3) was compared to 4 dox-treated JAK2 shRNA cells, 4 dox-treated JMJD2C shRNA cells, or 8 JAK2 inhibitor-treated cells (Cy5).
2011-01-04 | E-GEOD-20988 | biostudies-arrayexpress
Project description:Amplification of a ~2.5 megabase region on chromosome 9p24 is frequent in both primary mediastinal B-cell lymphoma (PMBL) and Hodgkin's lymphoma (HL). To identify the oncogenic genes in this interval, we created a RNA interference library targeting amplicon genes. A genetic screen using this library identified three genes that are essential for the proliferation and survival of PMBL and HL lines with this amplicon, which encode the kinase JAK2, the histone demethylase JMJD2C and a gene of unknown function, RANBP6. Inhibition of JAK2 and JMJD2C cooperated in killing these lymphomas and in remodeling their chromatin by globally increasing trimethylation of lysine 9 on histone H3 (H3K9me3) and heterochromatin formation. JAK2 and JMJD2C inhibition silenced MYC and its target genes, which coincided with an increase in H3K9me3 and the heterochromatin protein HP1alpha at the MYC locus. We conclude that amplification of JAK2 and JMJD2C cooperatively reprograms the PMBL and HL epigenome, sustaining their survival and proliferation.
2011-01-04 | GSE20988 | GEO
Project description:Primary Mediastinal large B-cell lymphoma (PMBL) is a rare form of non-Hodgkin lymphoma (NHL) representing 2% of mature B-cell NHL in patients less than 18 years of age.We compared the gene expression profiling between fully humanized anti-CD20 targeted monoclonal antibody recognizing a unique CD20 type II epitope, obinutuzumab and IgG or PBS treated Karpas Primary Mediastinal B-cell lymphoma (PMBL) cell line. -
2016-12-01 | GSE75605 | GEO
Project description:The pathogenesis of nodular lymphocyte-predominant Hodgkin lymphoma (NLPHL) and its relationship to other lymphomas are largely unknown. This is partly due to the technical challenge of analyzing its rare neoplastic L&H cells, which are dispersed in an abundant non-neoplastic cellular microenvironment. We performed a genome-wide expression study of microdissected lymphocytic and histiocytic (L&H) lymphoma cells in comparison to normal and other malignant B cells, which indicates a relationship of L&H cells to and/or origin from germinal center B cells at transition to memory B cells. L&H cells show a surprisingly high similarity to the tumor cells of T cell-rich B cell lymphoma and classical Hodgkin lymphoma, a partial loss of their B cell phenotype and deregulation of many apoptosis-regulators and putative oncogenes. Importantly, L&H cells are characterized by constitutive NF-κB activity and aberrant ERK signaling. Thus, these findings shed new light on the nature of L&H cells, revealed several novel pathogenetic mechanisms in NLPHL, and may help in differential diagnosis and lead to novel therapeutic strategies. Experiment Overall Design: Analysis of differential gene expression in primary human lymphoma cells of nodular lymphocyte-predominant Hodgkin lymphoma (NLPHL) in comparison with primary lymphoma cells of classical Hodgkin lymphoma cells and other B-non-Hodgkin lymphoma (B-NHL) samples and subsets of non-neoplastic B lymphocytes isolated from blood or tonsils. 67 gene expression profiles were analysed.
2008-10-26 | E-GEOD-12453 | biostudies-arrayexpress
Project description:The genetics of classical Hodgkin lymphoma (cHL) is poorly understood. The finding of a JAK2-involving t(4;9)(q21;p24) in one case of cHL prompted us to characterize this translocation on a molecular level and to determine the prevalence of JAK2 rearrangements in cHL. We showed that the t(4;9)(q21;p24) leads to a novel SEC31A-JAK2 fusion. Screening of 131 cHL cases identified one additional case with SEC31A-JAK2 and two additional cases with rearrangements involving JAK2. We demonstrated that SEC31A-JAK2 is oncogenic in vitro and acts as a constitutively activated tyrosine kinase that is sensitive to JAK inhibitors. In vivo, SEC31A-JAK2 was found to induce a T-lymphoblastic lymphoma or myeloid hyperplasia in a murine bone marrow transplant model. Altogether, we identified SEC31A-JAK2 as a first aberration characteristic for cHL and provide evidence that JAK2 rearrangements occur in a minority of cHL cases. Given the proven oncogenic potential of this novel fusion, our studies provide new insights into the pathogenesis of cHL and indicate that in at least some cases, constitutive activation of the JAK-STAT pathway is caused by JAK2 rearrangements. The finding that SEC31A-JAK2 responds to JAK inhibitors indicates that patients with cHL and JAK2 rearrangements may benefit from targeted therapies. Genomic profiling of primary and secondary transplanted mice expressing SEC31A-JAK2 with myeloid hyperplasia and T-lymphoblastic lymphoma Individual sample against a normal control
2010-07-08 | E-GEOD-22404 | biostudies-arrayexpress
Project description:This is the model of IL13 induced signalling in L1236 cells described in the article:
Dynamic Mathematical Modeling of IL13-Induced Signaling in Hodgkin and Primary Mediastinal B-Cell Lymphoma Allows Prediction of Therapeutic Targets.
Raia V, Schilling M, Böhm M, Hahn B, Kowarsch A, Raue A, Sticht C, Bohl S, Saile M, Möller P, Gretz N, Timmer J, Theis F, Lehmann WD, Lichter P and Klingmüller U. Cancer Res. 2011 Feb 1;71(3):693-704. PubmedID: 21127196
; DOI: 10.1158/0008-5472.CAN-10-2987
Abstract:
Primary mediastinal B-cell lymphoma (PMBL) and classical Hodgkin lymphoma (cHL) share a frequent constitutive activation of JAK (Janus kinase)/STAT signaling pathway. Because of complex, nonlinear relations within the pathway, key dynamic properties remained to be identified to predict possible strategies for intervention. We report the development of dynamic pathway models based on quantitative data collected on signaling components of JAK/STAT pathway in two lymphoma-derived cell lines, MedB-1 and L1236, representative of PMBL and cHL, respectively. We show that the amounts of STAT5 and STAT6 are higher whereas those of SHP1 are lower in the two lymphoma cell lines than in normal B cells. Distinctively, L1236 cells harbor more JAK2 and less SHP1 molecules per cell than MedB-1 or control cells. In both lymphoma cell lines, we observe interleukin-13 (IL13)-induced activation of IL4 receptor α, JAK2, and STAT5, but not of STAT6. Genome-wide, 11 early and 16 sustained genes are upregulated by IL13 in both lymphoma cell lines. Specifically, the known STAT-inducible negative regulators CISH and SOCS3 are upregulated within 2 hours in MedB-1 but not in L1236 cells. On the basis of this detailed quantitative information, we established two mathematical models, MedB-1 and L1236 model, able to describe the respective experimental data. Most of the model parameters are identifiable and therefore the models are predictive. Sensitivity analysis of the model identifies six possible therapeutic targets able to reduce gene expression levels in L1236 cells and three in MedB-1. We experimentally confirm reduction in target gene expression in response to inhibition of STAT5 phosphorylation, thereby validating one of the predicted targets.
All concentrations in the model, apart from IL13, are in molecules/cell. IL13 is given in ng/ml. As the cell volume is not explicitely given in the article, it is just approximately derived from the MW of IL13 (15.8 kDa) and the conversion factor 3.776 molecules IL13/cell = 1 ng/ml to be around 100 fl.
SBML model exported from PottersWheel on 2010-08-10 12:14:57.
Inline follows the original matlab code:
% PottersWheel model definition file
function m = Raia2010_IL13_L1236()
m = pwGetEmptyModel();
%% Meta information
m.ID = 'Raia2010_IL13_L1236';
m.name = 'Raia2010_IL13_L1236';
m.description = '';
m.authors = {'Raia et al'};
m.dates = {'2010'};
m.type = 'PW-2-0-47';
%% X: Dynamic variables
% m = pwAddX(m, ID, startValue, type, minValue, maxValue, unit, compartment, name, description, typeOfStartValue)
m = pwAddX(m, 'Rec' , 1.8, 'fix' , 1e-006, 10000, 'molecules/cell (x 1000)', 'cell', [] , [] , [] , [] , 'protein.generic');
m = pwAddX(m, 'Rec_i' , 118.598421286338, 'global', 0.001, 10000, 'molecules/cell (x 1000)', 'cell', [] , [] , [] , [] , 'protein.generic');
m = pwAddX(m, 'IL13_Rec' , 0, 'fix' , 1e-006, 10000, 'molecules/cell (x 1000)', 'cell', [] , [] , [] , [] , 'protein.generic');
m = pwAddX(m, 'p_IL13_Rec' , 0, 'fix' , 1e-006, 10000, 'molecules/cell (x 1000)', 'cell', [] , [] , [] , [] , 'protein.generic');
m = pwAddX(m, 'p_IL13_Rec_i', 0, 'fix' , 1e-006, 10000, 'molecules/cell (x 1000)', 'cell', [] , [] , [] , [] , 'protein.generic');
m = pwAddX(m, 'JAK2' , 24, 'fix' , 1e-006, 10000, 'molecules/cell (x 1000)', 'cell', [] , [] , [] , [] , 'protein.generic');
m = pwAddX(m, 'pJAK2' , 0, 'fix' , 1e-006, 10000, 'molecules/cell (x 1000)', 'cell', [] , [] , [] , [] , 'protein.generic');
m = pwAddX(m, 'SHP1' , 9.4, 'fix' , 1e-006, 10000, 'molecules/cell (x 1000)', 'cell', [] , [] , [] , [] , 'protein.generic');
m = pwAddX(m, 'STAT5' , 209, 'fix' , 1e-006, 10000, 'molecules/cell (x 1000)', 'cell', [] , [] , [] , [] , 'protein.generic');
m = pwAddX(m, 'pSTAT5' , 0, 'fix' , 1e-006, 10000, 'molecules/cell (x 1000)', 'cell', [] , [] , [] , [] , 'protein.generic');
m = pwAddX(m, 'CD274mRNA' , 0, 'fix' , 1e-006, 10000, 'molecules/cell (x 1000)', 'cell', [] , [] , [] , [] , 'protein.generic');
%% R: Reactions
% m = pwAddR(m, reactants, products, modifiers, type, options, rateSignature, parameters, description, ID, name, fast, compartments, parameterTrunks, designerPropsR, stoichiometry, reversible)
m = pwAddR(m, {'Rec' }, {'IL13_Rec' }, {'IL13stimulation'}, 'C' , [] , 'k1 * m1 * r1 * 3.776', {'Kon_IL13Rec' });
m = pwAddR(m, {'Rec' }, {'Rec_i' }, { }, 'MA', [] , [] , {'Rec_intern' });
m = pwAddR(m, {'Rec_i' }, {'Rec' }, { }, 'MA', [] , [] , {'Rec_recycle' });
m = pwAddR(m, {'IL13_Rec' }, {'p_IL13_Rec' }, {'pJAK2' }, 'E' , [] , [] , {'Rec_phosphorylation' });
m = pwAddR(m, {'JAK2' }, {'pJAK2' }, {'IL13_Rec' }, 'E' , [] , [] , {'JAK2_phosphorylation' });
m = pwAddR(m, {'JAK2' }, {'pJAK2' }, {'p_IL13_Rec' }, 'E' , [] , [] , {'JAK2_phosphorylation' });
m = pwAddR(m, {'p_IL13_Rec' }, {'p_IL13_Rec_i'}, { }, 'MA', [] , [] , {'pRec_intern' });
m = pwAddR(m, {'p_IL13_Rec_i'}, { }, { }, 'MA', [] , [] , {'pRec_degradation' });
m = pwAddR(m, {'pJAK2' }, {'JAK2' }, {'SHP1' }, 'E' , [] , [] , {'pJAK2_dephosphorylation' });
m = pwAddR(m, {'STAT5' }, {'pSTAT5' }, {'pJAK2' }, 'E' , [] , [] , {'STAT5_phosphorylation' });
m = pwAddR(m, {'pSTAT5' }, {'STAT5' }, {'SHP1' }, 'E' , [] , [] , {'pSTAT5_dephosphorylation'});
m = pwAddR(m, { }, {'CD274mRNA' }, {'pSTAT5' }, 'C' , [] , 'm1*k1' , {'CD274mRNA_production' });
%% C: Compartments
% m = pwAddC(m, ID, size, outside, spatialDimensions, name, unit, constant)
m = pwAddC(m, 'cell', 1);
%% K: Dynamical parameters
% m = pwAddK(m, ID, value, type, minValue, maxValue, unit, name, description)
m = pwAddK(m, 'Kon_IL13Rec' , 0.00174086832237195, 'global', 1e-009, 1000);
m = pwAddK(m, 'Rec_phosphorylation' , 9.07540737285078 , 'global', 1e-009, 1000);
m = pwAddK(m, 'pRec_intern' , 0.324132341358502 , 'global', 1e-009, 1000);
m = pwAddK(m, 'pRec_degradation' , 0.417538218767296 , 'global', 1e-009, 1000);
m = pwAddK(m, 'Rec_intern' , 0.259685756311325 , 'global', 1e-009, 1000);
m = pwAddK(m, 'Rec_recycle' , 0.00392430355501153, 'global', 1e-009, 1000);
m = pwAddK(m, 'JAK2_phosphorylation' , 0.300019047540849 , 'global', 1e-009, 1000);
m = pwAddK(m, 'pJAK2_dephosphorylation' , 0.0981610557569751 , 'global', 1e-009, 1000);
m = pwAddK(m, 'STAT5_phosphorylation' , 0.00426766529531612, 'global', 1e-009, 1000);
m = pwAddK(m, 'pSTAT5_dephosphorylation', 0.0116388587580445 , 'global', 1e-009, 1000);
m = pwAddK(m, 'CD274mRNA_production' , 0.0115927572109515 , 'global', 1e-009, 1000);
%% U: Driving input
% m = pwAddU(m, ID, uType, uTimes, uValues, compartment, name, description, u2Values, alternativeIDs, designerProps)
m = pwAddU(m, 'IL13stimulation', 'steps', [-100 0] , [0 1] , [], [], [], [], {}, [], 'protein.generic');
%% Default sampling time points
m.t = 0:1:120;
%% Y: Observables
% m = pwAddY(m, rhs, ID, scalingParameter, errorModel, noiseType, unit, name, description, alternativeIDs, designerProps)
m = pwAddY(m, 'Rec + IL13_Rec + p_IL13_Rec' , 'RecSurf_obs' , 'scale_RecSurf' , '0.1 * y + 0.1 * max(y)');
m = pwAddY(m, 'IL13_Rec + p_IL13_Rec + p_IL13_Rec_i', 'IL13-cell_obs', 'scale_IL13-cell', '0.15 * y + 0.05 * max(y)');
m = pwAddY(m, 'p_IL13_Rec + p_IL13_Rec_i' , 'pIL4Ra_obs' , 'scale_pIL4Ra' , '0.10 * y + 0.15 * max(y)');
m = pwAddY(m, 'pJAK2' , 'pJAK2_obs' , 'scale_pJAK2' , '0.1 * y + 0.1 * max(y)');
m = pwAddY(m, 'CD274mRNA' , 'CD274mRNA_obs', 'scale_CD274mRNA', '0.1 * y + 0.1 * max(y)');
m = pwAddY(m, 'pSTAT5' , 'pSTAT5_obs' , 'scale_pSTAT5' , '0.1 * y + 0.1 * max(y)');
%% S: Scaling parameters
% m = pwAddS(m, ID, value, type, minValue, maxValue, unit, name, description)
m = pwAddS(m, 'scale_pJAK2' , 0.469836894150194, 'global', 0.001, 10000);
m = pwAddS(m, 'scale_pIL4Ra' , 1.80002942264669, 'global', 0.001, 10000);
m = pwAddS(m, 'scale_RecSurf' , 1, 'fix', 0.0001, 10000);
m = pwAddS(m, 'scale_IL13-cell', 174.726805005048, 'global', 0.001, 10000);
m = pwAddS(m, 'scale_CD274mRNA', 0.110568221201943, 'global', 0.001, 10000);
m = pwAddS(m, 'scale_pSTAT5' , 1, 'fix', 0.001, 10000);
%% Designer properties (do not modify)
m.designerPropsM = [1 1 1 0 0 0 400 250 600 400 1 1 1 0 0 0 0];
2011-02-14 | BIOMD0000000314 | BioModels
Project description:The pathogenesis of classical Hodgkin lymphoma (cHL), the most common lymphoma in the young, is still enigmatic, largely because its Hodgkin and Reed-Sternberg (HRS) tumor cells are rare in the involved lymph node and therefore difficult to analyze. Here, by overcoming this technical challenge and performing for the first time a genome-wide transcriptional analysis of microdissected HRS cells in comparison to other B-cell lymphomas, cHL lines and normal B-cell subsets, we show that they differ extensively from the usually studied cHL cell lines, that the lost B-cell identity of cHLs is not linked to the acquisition of a plasma cell-like gene expression program, and that Epstein-Barr virus infection of HRS cells has a minor transcriptional influence on the established cHL clone. Moreover, although cHL appears a distinct lymphoma entity overall, HRS cells of its histological subtypes diverged in their similarity to other related lymphomas. Unexpectedly, we identified two molecular subgroups of cHL associated to differential strengths of the transcription factor activity of the NOTCH1, MYC and IRF4 proto-oncogenes. Finally, HRS cells display deregulated expression of several genes potentially highly relevant to lymphoma pathogenesis, including silencing of the apoptosis-inducer BIK and of INPP5D, an inhibitor of the PI3K-driven oncogenic pathway. The present study complements the GSE12453 and GSE14879 records by adding the following 10 samples: 5 primary tumor samples and 5 cell line samples. The 5 primary tumor samples represent 1000-2000 neoplastic cells microdissected from frozen biopsies of 5 cases of primary mediastinal B-cell lymphoma (PMBL). The 5 cell line samples represent 500-1000 living neoplastic cells isolated by fluorescence-activated cell sorting from growing cultures of the classical Hodgkin lymphoma (cHL) cell lines L1236, L428, KMH2 and HDLM2 and the lymphocyte-predominant Hodgkin lymphoma (lpHL) cell line DEV.
2012-09-17 | E-GEOD-40160 | biostudies-arrayexpress