Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

0

Gene expression in pediatric cALL


ABSTRACT: Common ALL (cALL) is the most frequent entity of childhood ALL and carries an early pre-B cell phenotype. Expression patterns of 25 pediatric cALL samples were analyzed by use of high-density DNA microarrays HG-U133A. Leukemic patients’ bone marrow samples were compared to sorted B cells from cord blood of healthy donors expressing CD19 and CD10 surface antigens. Differential gene expression profiling of pediatric cALL versus non-malignant tissues enabled the identification of aberrantly expressed genes in malignant cells, facilitating discrimination of leukemic from normal cells and possibly revealing specific disease mechanisms. Principal component analysis clearly distinguished leukemia samples from normal controls. Significance analysis of microarrays revealed 487 genes significantly up-regulated, and 572 down-regulated genes in leukemic cells. A comparison to previous publications investigating genetically defined subsets of cALL revealed 465 genes previously not associated with cALL. Interestingly, terminal deoxynucleotidyl-transferase (DNTT) as well as in the context of cALL unknown genes, were found to be the strongest predictive genes for the malignant phenotype signifying the diagnostic value of our approach. RNA was extracted from bone marrow or peripheral blood samples form pediatric cALL patients, leukemia cell lines, and purified fetal B cells and hybridized with Affymetrix HG_U133A microarrays.

ORGANISM(S): Homo sapiens

SUBMITTER: Martin Staege 

PROVIDER: E-GEOD-34670 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

altmetric image

Publications


Acute lymphoblastic leukemia (ALL) is the most common childhood cancer. To identify novel candidates for targeted therapy, we performed a comprehensive transcriptome analysis identifying MondoA (MLXIP) - a transcription factor regulating glycolysis - to be overexpressed in ALL compared to normal tissues. Using microarray-profiling, gene-set enrichment analysis, RNA interference and functional assays we show that MondoA overexpression increases glucose catabolism and maintains a more immature phe  ...[more]

Similar Datasets

2012-06-30 | GSE34670 | GEO
| PRJNA150327 | ENA
2016-04-30 | GSE76277 | GEO
2013-07-08 | E-GEOD-47813 | biostudies-arrayexpress
2012-03-31 | E-GEOD-35504 | biostudies-arrayexpress
2018-02-08 | E-MTAB-6382 | biostudies-arrayexpress
2024-10-30 | GSE246783 | GEO
2020-07-13 | GSE101425 | GEO
2011-07-31 | E-GEOD-26268 | biostudies-arrayexpress
2020-07-13 | GSE101454 | GEO