Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Genomic and transcriptomic landscape of T-cell lymphoblastic lymphoma compared to T-cell acute lymphoblastic leukemia: similar subtypes and different fusions

ABSTRACT: Due to the lower incidence of T-LBL and difficulties in obtaining diagnostic T-LBL material, extensive research on T-LBL has been hampered whereas genetic aberrations in T-ALL are thoroughly characterized.Ã‚Â Given the similarities and differences between T-LBL and T-ALL, the question has been raised whether T-LBL and T-ALL represent two different diseases or different manifestations of the same disease. This study aims to identify the genomic and transcriptomic landscape of T-LBL and compare the findings to what is found T-ALL. Comparison of the molecular aberrations between T-LBL and T-ALL can provide insights into the overlap and differences in malignant development between the two entities, which could lead to improved risk stratification in T-LBL in order to eventually adapt T-LBL treatment protocols based on molecular-genetic prognostic factors.

PROVIDER: EGAS00001007767 | EGA |

REPOSITORIES: EGA

ACCESS DATA

Json Xml

Similar Datasets

PMCDS000ABQ - samples

Project description:Due to the lower incidence of T-LBL and difficulties in obtaining diagnostic T-LBL material, extensive research on T-LBL has been hampered whereas genetic aberrations in T-ALL are thoroughly characterized.Ã‚Â Given the similarities and differences between T-LBL and T-ALL, the question has been raised whether T-LBL and T-ALL represent two different diseases or different manifestations of the same disease. This study aims to identify the genomic and transcriptomic landscape of T-LBL and compare the findings to what is found T-ALL. Comparison of the molecular aberrations between T-LBL and T-ALL can provide insights into the overlap and differences in malignant development between the two entities, which could lead to improved risk stratification in T-LBL in order to eventually adapt T-LBL treatment protocols based on molecular-genetic prognostic factors.

| EGAD00001015357 | EGA

Molecular genetics of pre-B acute lymphoblastic leukemia sister cell lines during disease progression - WES

Project description:Retaining the mutational pattern of tumors, immortalized cell lines represent excellent tools for the molecular study of genetic aberrations. Tumors can consist of subclones which develop under selective forces driven by mutational alterations. This explains why after therapy, relapsed clones can be genetically distinct from clones at diagnosis. We analyzed the mutational patterns of pairs of cell lines raised at early and late phases of development from patients with a hematopoietic tumor named pre-B acute lymphoblastic leukemia (ALL). All cell lines tested showed mutations that typically occur in this tumor. We also observed clonal differences in sister cell lines, genetic aberrations developing during disease progression. Especially noteworthy was the presence of two mutations which are hitherto undescribed in cell lines.

2021-12-02 | E-MTAB-11039 | biostudies-arrayexpress

Molecular genetics of pre-B acute lymphoblastic leukemia sister cell lines during disease progression - RNA-seq

2021-12-02 | E-MTAB-11038 | biostudies-arrayexpress

Different developmental trajectories of ovaries in Siberian hamsters raised in long and short day lengths

Project description:A genome-wide association study was performed on ovaries from Siberian hamsters raised in either long or short photoperiod. Few differences between long and short photoperiod were noted at 3 wk of age, when ovarian histology was identical, whereas many differences in gene expression were noted at 8 wk of age, when ovarian histologies were markedly different.

2013-09-14 | GSE50869 | GEO

Single-cell Landscape Analysis Reveals HSA21 Induced Regulatory Network in Mammalian Down Syndrome

Project description:Down syndrome (DS), characterized by various malfunctions, is the most common genetic chromosomal disorder. As DS population size keeps growing and most of them live beyond their puberty, their early‐onset health problems come into view. However, the molecular alterations have not been thoroughly surveyed before. Here we provide the first description of DS in single-cell resolution, including human and mouse, covering seven different organs. With 71934 mouse cells and 93207 human cells employed, we systematically revealed DS cells, across different cell types and different organs suffering from serious cellular stresses. We observed senescence stresses including ribosomal protein gene accumulation, mitochondrial dysfunction, apoptosis, and sterile inflammation in fetus DS cells. We further raised an HSA21 gene-induced regulatory network driving genome-wide expression alteration. Hence, this study provides valuable information to understand the pathological processes under DS condition.

2023-12-01 | GSE155409 | GEO

Affymetrix SNP array data for acute lymphoblastic leukemia and lymphoblastic lymphoma samples

Project description:Childhood T-cell malignancies include T-cell acute lymphoblastic leukemia (T-ALL) and T-cell lymphoblastic lymphoma (T-LBL). T-ALL and T-LBL share common morphologic and immunophenotypic features and are treated with similar therapeutic approaches. Nonetheless, they show distinct clinical presentations suggesting that they may represent two different biological entities. In order to investigate the common and unique genetic aberrations of T-LBL and T-ALL, copy number alteration (CNA) analysis was performed on a subset of the samples analyzed by GEP

2012-06-30 | GSE30319 | GEO

Identification of differential duodenal gene expression levels correlated with differences in energy utilization in chickens

Project description:The amount of energy that can be extracted from a diet varies between individuals. Apparent Metabolizable Energy (AME) is a measure of energy utilization efficiency and represents the difference between the energy consumed and the energy lost via the excreta. There are significant differences in the energy utilization capability of individual birds that have a similar genetic background and are raised under identical conditions. We analyzed duodenal gene expression and microbiota differences between birds with different efficiencies in food to energy conversion using microarrays and sequencing of 16s rRNA genes. Differences were found in duodenal gene expression between high and low AME birds, they were however mostly related to genes of unknown function.

2013-06-01 | GSE47213 | GEO

Rotating wall vessel (RWV) grown A549s compared to monolayer grown A549s

Project description:A549 epithelial cells grown under two different conditions were compared. A549s grown in rotating wall vessel cultures disp[lay a more in-vivo like phenotype. The data here describe the transcriptional differences between the two culture methods

2012-10-01 | GSE36931 | GEO

GTF2I Mutations are Common in Thymic Epithelial Tumors

Project description:Within a project aim to define the genomic aberration of thymic epithelial tumors, we performed array CGH in 65 thymic epithelial tumors. Tumor samples were collected during surgery or by image-guided biopsies and immediately frozen. Section from frozen material were cut and stained with Haematoxylin and Eosin. A pathologist reviewed the slides and selected only cases with >80% of cancer cells. Copy number aberrations of a series of 65 thymic epithelial tumors were evaluated using array CGH. Differences in copy number aberrations between different histotypes were evaluated. Significant regions of CN aberrations were defined using GISTIC algorithms.

2014-06-21 | E-GEOD-55852 | biostudies-arrayexpress

Transcriptional profiling of 53 tissue samples from germ-free and conventionally raised mice

Project description:Whole-transcriptome survey of gene expression differences between germ-free (GF) and conventionally raised (CONV-R) mice. To assess the role of toll-like receptor signalling, both wild-type and Myd88 -/- mice were used.

2014-01-31 | GSE31115 | 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