Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

MiRNA expression profiling in a murine model of KrasG12D induced CMML-like MPD

ABSTRACT: Mx1-Cre/KrasG12D mice were injected with pIpC to induce a myeloproliferative disease resembling human chronic myelomonocytic leukemia (CMML-like MPD). When the disease was fully developed, CD11b-/Ly6G-/c-Kit+ hematopoietic stem and progenitor cells (HSPCs) were isolated and subjected to miR-microarray expression profiling. pIpC-injected CD11b-/Ly6G-/c-Kit+ HSPCs of age matched wildytpe control mice were used as controls.

ORGANISM(S): synthetic construct Mus musculus

PROVIDER: GSE145083 | GEO | 2021/01/19

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

miRNA expression profiling in a murine model of KrasG12D induced CMML-like MPD

Project description:miRNA expression profiling in a murine model of KrasG12D induced CMML-like MPD

| PRJNA605975 | ENA

scRNAseq data from 4 ASM-AHN, 3 CMML patients and 3 healthy donors

Project description:Aggressive systemic mastocytosis with associated hematologic neoplasm (ASM-AHN) represents a complex myeloid neoplasm, in which KIT D816V is the phenotype-defining but not the only driver mutation. Avapritinib is a potent and specific KIT D816V inhibitor recently approved for ASM treatment. To understand the effects of inhibiting KIT D816V on MC and Non-MC compartments, we combined single cell RNA sequencing (scRNAseq) with deep whole genome sequencing (WGS) to map clonal dynamics in successive blood samples from 4 ASM-AHN patients treated with avapritinib (T1 as pretreatment sample, T2 and T3 as posttreatment samples). Since CMML is the most common AHN associated with ASM, we included samples from three treatment-naïve KIT wild type CMML patients for comparison. We also included 3 age-matched healthy donor as controls.

2024-11-22 | GSE249445 | GEO

Gene expression profile at single-cell level of hematopoietic stem and progenitor cells (HSPCs) from individuals with chronic myelomonocytic leukemia (CMML)

Project description:Myeloblast expansion is a hallmark of disease progression in leukemias and comprises of CD34+ hematopoeitic stem and progeneitor cells. We used single-cell RNA sequencing (scRNAseq) to analyze the transcriptional states of HSPCs in CMML.

2022-11-04 | GSE211033 | GEO

Bulk RNA-Seq for MDSCs

Project description:Myeloid-derived suppressor cells (MDSCs) as a population of myeloid cells enriched in cancer patients with immunosuppressive function. Further studies have determined that MDSCs are comprised of two groups: polymorphonuclear-MDSCs (G-MDSCs) and monocytic-MDSCs (M-MDSCs). We used a microbeads kit (Miltenyi) to isolate G-MDSCs and M-MDSCs with markers Ly6c2-Ly6g+CD11b+ and Ly6c2+Ly6g-CD11b+, respectively. And then using bulk RNA-seq to anlysis the enrichment gene expression in G-or M-MDSC which from wild type, APCmin mutant adenoma and immune deffiency mice.

2022-08-21 | GSE136258 | GEO

The Transcriptome Of Cmml Monocytes Is Highly Inflammatory And Reflects Leukemia-Specific And Age-Related Alterations

Project description:Chronic myelomonocytic leukemia (CMML) is an aggressive myeloid neoplasm of older individuals characterized by persistent monocytosis. Somatic mutations in CMML are heterogeneous and only partially explain the variability in clinical outcomes. Recent data suggest that cardiovascular morbidity is increased in CMML and contributes to reduced survival. Clonal hematopoiesis of indeterminate potential (CHIP), the presence of mutated blood cells in hematologically normal individuals, is a precursor of age-related myeloid neoplasms and associated with increased cardiovascular risk. To isolate CMML-specific alterations from those related to aging, we performed RNA sequencing and DNA methylation profiling on purified monocytes from CMML patients and from age-matched (old) and young healthy controls. We found that the transcriptional signature of CMML monocytes is highly pro-inflammatory, with upregulation of multiple inflammatory pathways, including tumor necrosis factor, IL-6 and IL-17 signaling, while age per se does not significantly contribute to this pattern. We observed no consistent correlations between aberrant gene expression and CpG island methylation, suggesting that pro-inflammatory signaling in CMML monocytes is governed by multiple and complex regulatory mechanisms. We propose that pro-inflammatory monocytes may contribute to cardiovascular morbidity in CMML patients, and promote progression by selection of mutated cell clones. Our data raise questions whether asymptomatic CMML patients may benefit from monocyte-depleting or anti-inflammatory therapies.

2019-10-24 | GSE135902 | GEO

Quantitative Temporal in vivo Proteomics (QTiPs) deciphers the transition of inflammatory CD11b+,Ly6G-,Ly6Chigh myeloid cells into M2-like macrophages

Project description:Phenotypic transition of myeloid cells into distinct lineages in vivo is important in pathogen response. To monitor immune cell phenotype transitions in vivo, we developed a quantitative temporal in vivo proteomics (QTiPs) platform, performing multiplexed (10-plex) tandem-mass-tag (TMT)-based mass spectrometry on sorted cells collected from their in situ microenvironment during infection. We temporally characterized a poorly understood, virus-driven CD11b+,Ly6G-,Ly6Chigh-low myeloid cell population throughout an acute phase of infection in both the site of infection and bone marrow. QTiPs, in combination with phenotypic, functional and metabolic analyses, elucidated a pivotal role for inflammatory CD11b+,Ly6G-,Ly6Chigh-low cells in anti-viral immune response and viral clearance. Most importantly, the highly time-resolved QTiPs dataset showed the transition of CD11b+,Ly6G-,Ly6Chigh-low cells into M2-like macrophages which displayed increased antigen presentation capacities and bioenergetic demands late in infection. Our QTiPs approach precisely captures myeloid cell-macrophage transition in this population, and it is a novel platform for measuring temporospatial proteome transitions in vivo.

2017-08-09 | PXD005064 | Pride

Single cell RNA sequencing of chronic myelomonocytic leukemia stem cell

Project description:Chronic myelomonocyticleukemia (CMML) is a clinically heterogeneous stem cell malignancy with overlapping features of myelodysplasiaand myeloproliferation. CMML is further subclassified according to percentage of leukemic blasts present in blood or bone marrow, reflecting its intrinsic tendency to progression towards acute myeloid leukemia. Over 90% of CMML patients carry founding mutations in epigenetic and/or splicing genes, which typically involve the primitive stem cell compartment. Thus, transcriptional dysregulation at the stem cell level is likely fundamental to disease onset and progression. However, the critical early hematopoietic stem and progenitor cell (HSPC) subpopulation has not been studied in CMML. We performed single cell RNA sequencing on>6,800 Lin-CD34+CD38-primitive HSPCs from seven CMML patients and three healthy controls. We found substantial inter-and intra-patient heterogeneity, with CMML stem cells displaying distinct transcriptional programs, differentiation potential and cellular signaling pathway priming. Pseudotime analyses revealed that CMML-1/CMML-2 HSPCs have distinct cellular trajectories, indicating that transformation events initiate early within the hematopoietic hierarchy and suggesting against a simple linear clonal evolution dynamic in acute leukemic transformation. We further identified several transcription factors uniquely active in distinct sample subsets. Together our findings provide novel insights into the CMML stem cell compartment, revealing an unexpected degree of transcriptional and subclonal heterogeneity and highlighting early mediators of disease initiation and transformation, of potential translational importance

2020-08-03 | E-MTAB-8884 | biostudies-arrayexpress

Gene expression profile at the single cell level of CD45+ CD11b+ cells isolated from the brain and bone marrow of mice either untreated or conditioned and transplanted with mouse hematopoietic stem and progenitor cells (HSPCs) expanded in culture.

Project description:We used single-cell RNA sequencing (scRNA-seq) to analyze the diversity of HSPC-derived CD45+CD11b+ microglia-like cells (MGLCs) engrafted in the brain of recipient mice that were conditioned using Busulfan and PLX3397 and transplanted intravenous with Lineage negative KIT+ SCA1+ mouse HSPCs. The HSPCs were isolated from adult C57BL/6-Tg(CAG-EGFP)131Osb/LeySopJ homozygous mice. We compared the gene expression of MGLCs to that of developmentally-derived CD45+ CD11b+ microglia/myeloid cells isolated from the brain of recipient mice (host microglia) and untreated mice (naive microglia). We also compared the gene expression of MGLCs to that of transplant-derived CD45+ CD11b+ cells engrafted in the bone marrow (abbreviated as BM-CD11b+)

2024-05-13 | GSE261246 | GEO

Ly6C monocyte subsets transcriptome analysis from wild type and hyperhomocysteinemic mice

Project description:Murine monocytes (MC) are classified into Ly6Chigh and Ly6Clow MC. Ly6Chigh MC is the pro-inflammatory subset and the counterpart of human CD14++CD16+ intermediate MC which contributes to systemic and tissue inflammation in various metabolic disorders, including hyperhomocysteinemia (HHcy). This study aims to explore molecule signaling mediating MC subset differentiation in HHcy and control mice.Mouse white blood cell were prepared from peripheral blood and stained with antibody against CD11b, Ly6G and Ly6C and subjected for flow cytometry cell sorting. CD11b+Ly6G- cells were selected as MC. MC subsets (CD11b+Ly6G-Ly6Chigh, and CD11b+Ly6G-Ly6Clow) were sorted based on Ly6C levels. The quantification of MC was used flow cytometry analysis for Ly6Chigh and Ly6Clow MC in CT and Cbs-/-. Then, 100 ng mRNA were obtained from 100,000 sorted cells of CT and Cbs-/- (HHcy) mice. Around 30 million reads were achived and 16,487 normalized genes per sample by mRNA-Seq analysis.

2021-02-02 | GSE165879 | GEO

Specific molecular signatures underlie response to Decitabine in CMML

Project description:Myelodysplastic syndromes and chronic myelomonocytic leukemia (CMML) are characterized by mutations in epigenetic modifiers and aberrant DNA methylation. DNA methyltransferase inhibitors (DMTis) are used to treat these disorders, but response is highly variable with few means to predict which patients will benefit. To develop a molecular means of predicting response at diagnosis, we examined baseline differences in mutations, DNA methylation, and gene expression in 40 CMML patients responsive and resistant to Decitabine (DAC). While somatic mutations did not differentiate responders and non-responders, we were able to identify for the first time 167 differentially methylated regions (DMRs) at baseline between responders and non-responders using next-generation sequencing. These DMRs were primarily localized to non-promoter regions and overlapped with distal regulatory enhancers. Using the methylation profiles, we developed an epigenetic classifier that accurately predicted DAC response at the time of diagnosis. Transcriptional analysis revealed that gene expression differences also exist at diagnosis between responders and non-responders. Genes up-regulated in responders were enriched in the cell cycle, potentially contributing to effective DAC incorporation. Two chemokines overexpressed in non-responders – CXCL4 and CXCL7 – were able to block the effect of DAC on normal CD34+ and primary CMML cells in vitro, suggesting their up-regulation contributes to primary DAC resistance.

2017-08-29 | GSE63787 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data