Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Next-generation sequencing analysis to compare expression pattern of relapse and baseline "CMP pattern" MDS samples

ABSTRACT: Transcriptional changes occurring in the expanding LT-HSC population of "CMP pattern" MDS patients with blast expansion post-HMA failure were compared with the transcriptional profile of untreated (baseline) "CMP pattern" MDS patients.

ORGANISM(S): Homo sapiens

PROVIDER: GSE136815 | GEO | 2022/01/03

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Similar Datasets

Next-generation sequencing analysis to compare expression pattern of relapse and baseline "GMP pattern" MDS samples

Project description:Transcriptional changes occurring in the expanding LMPP population of "GMP pattern" MDS patients with blast expansion post-HMA failure were compared with the transcriptional profile of untreated (baseline) "GMP pattern" MDS patients.

2022-01-03 | GSE136812 | GEO

Next-generation sequencing analysis to compare expression pattern of relapse and baseline "CMP pattern" MDS samples

Project description:Next-generation sequencing analysis to compare expression pattern of relapse and baseline "CMP pattern" MDS samples

| PRJNA563724 | ENA

Next-generation sequencing analysis to compare expression pattern of relapse and baseline "GMP pattern" MDS samples

Project description:Next-generation sequencing analysis to compare expression pattern of relapse and baseline "GMP pattern" MDS samples

| PRJNA563710 | ENA

Next Generation Sequencing analysis to compare expression patterns of myeloid progenitors in healthy donors and MDS patients

Project description:Transcriptional changes occurring in the CMPs and GMPs of untreated "CMP pattern" and "GMP pattern" MDS patients were compared with the transcriptional profile of CMPs and GMPs from healthy donors

2022-01-02 | GSE178840 | GEO

Next-generation sequencing analysis to compare expression pattern of relapse and baseline MDS samples

Project description:Next-generation sequencing analysis to compare expression pattern of relapse and baseline MDS samples

| PRJNA563722 | ENA

Next-generation sequencing analysis to compare expression pattern of relapse and baseline MDS samples

Project description:This SuperSeries is composed of the SubSeries listed below.

2022-01-02 | GSE136816 | GEO

A methylation signature at diagnosis in patients with high-risk Myelodysplastic Syndromes and secondary Acute Myeloid Leukemia predicts azacitidine response but not relapse

Project description:Epigenetic therapy, using hypomethylating agents (HMA), is known to be effective in the treatment of high-risk myelodysplastic syndromes (MDS) and acute myeloid leukemia (AML) patients who are not suitable for intensive chemotherapy or allogeneic stem cell transplantation. However, response rates to HMA are low and there is an unmet need in finding prognostic and predictive biomarkers of treatment response. We performed global methylation analysis of 75 patients with high risk MDS and secondary AML (sAML) who were included in CETLAM MDS-09 protocol, in which patients received HMA or intensive treatment according to age, comorbidities and cytogenetics. At diagnosis, no global methylation pattern allowed us to differentiate patients according to the cytological subtype, cytogenetics or treatment response. But we found a methylation signature defined by 200 probes, which allowed us to distinguish between responding and non-responding patients to azacitidine (AZA) treatment. Studying follow-up samples, we have confirmed that AZA decreases global DNA methylation, but in our cohort the degree of methylation decrease did not correlate with the type of response. The methylation signature detected at diagnosis was not useful in treated samples to determine a methylation pattern predictive of progression or relapse. In conclusion, altered DNA methylation patterns at diagnosis, in a subset of determined CpGs, may serve as biomarker for predicting AZA response.

2021-01-27 | GSE152710 | GEO

Expression data from G0 versus G4/G5 CMP/GMP

Project description:Telomere dysfunctional CMP/GMP have deregulated pathways that are associated with DNA damage signaling We compared differentially expressed genes in the G4/G5 CMP relative to the G0 control to identify pathways that may affect CMP differentiation.

2015-04-09 | GSE62278 | GEO

Single-cell transcriptomes of CD8+ T cells from patients with HR-MDS and AML

Project description:Treatment with hypomethylating agents (HMA), and specifically azacitidine (AZA), is the standard of care for patients with higher-risk myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML) that are not eligible to receive intensive chemotherapy. Despite research efforts, it is not possible to predict response to treatment with HMA. In this study, we aimed to identify immune cell signatures in the bone marrow (BM) associated with treatment outcomes. By employing mass cytometry, we performed an in-depth immunophenotypic analysis in BM samples deriving from patients with myeloid neoplasms prior to treatment initiation. We identified an increased pre-treatment frequency of a CD8+ T cell subset, characterized as CD57+CXCR3+CCR7-CD45RA+, in patients with MDS and AML who did not respond to treatment with AZA, compared to responders. Furthermore, a baseline frequency of more than 29% of CD57+CXCR3+CD8+ T cells was correlated with poor overall survival. We further engaged scRNA-seq to assess the transcriptional profile of BM CD8+ T cells from treatment-naïve patients with MDS and AML, to identify molecular signatures in CD8+ T subpopulations associated with favorable outcomes. Response to treatment was positively associated with enrichment of IFN-mediated pathways coupled with enhanced cytotoxic signature, whereas enrichment of the TGF-β signaling pathway was observed in cell clusters from non-responders. Together, this study identified a specific CD57+CXCR3+ CD8+ T cell population with predictive value in patients with MDS and AML treated with AZA, and characterized molecular signatures in CD8+ T cells linked to cytokine signaling that were associated with treatment outcomes.

2024-01-12 | GSE250077 | GEO

Highly-sensitive DNA hydroxymethylation analysis to aid clinic evaluation of myelodysplastic syndromes (MDS)

Project description:Aberrant DNA hydroxymethylation (5hmC) has been reported in patients with myelodysplastic syndromes (MDS). The dysregulation of 5hmC is not only observed in patients with TET2 mutations, but also those bearing other genetic defects, suggesting that 5hmC might act as a valuable epigenetic mark to reflect the status of MDS. To further evaluate the function of 5hmC during MDS pathogenesis, we reported herein an improved highthroughput 5hmC analysis method based on CMS-IP using low input DNA (10 ng) purified from bone marrow aspirates of MDS patients. Our analysis revealed relatively higher heterogeneity of 5hmC signals in MDS patients compared with those of healthy donors, CMML and AML patients. Our systematic bioinformatic analysis further unveiled that 5hmC signatures could be used to separate patients with good and poor clinical outcomes. At the molecular level, we observed dynamic changes of 5hmC within several key transcription factor binding motifs that are essential for hemopoiesis and myeloid lineage specification, which might result in impaired transcriptional outputs during leukemogenesis. Interestingly, we also observed massive changes in 5hmC and transcriptomes in patient showing response to hypomethylating agents (HMA) treatment, suggesting the prognostic value of 5hmC in evaluating epigenetic therapy. Overall, our high-sensitive 5hmC analysis method provides a useful means to greatly facilitate the clinic evaluation for MDS.

2022-07-01 | GSE148357 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

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