Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Affymetrix U133A array data for 111 pediatric acute myeloid leukemia (AML) samples at diagnosis

ABSTRACT: Genome-wide profiling of Copy Number Alterations (CNA) and Loss of Heterozygosity (LOH), gene expression and resequencing of pediatric AML This study characterizes CNA and LOH, gene expression and gene sequence mutations in a representative cross-section through subtypes of pediatric AML. Keywords: Affymetrix arrays were performed according to the maufacturers directions on DNA extracted from cryopreserved diagnostic bone marrow or peripheral blood samples. Samples with less than 80% blasts were flow sorted prior to DNA extraction 111 pediatric AML samples were studied using the Affymetrix U133A array.

ORGANISM(S): Homo sapiens

SUBMITTER: Guangchun Song

PROVIDER: E-GEOD-14471 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Publications

Genomic analysis reveals few genetic alterations in pediatric acute myeloid leukemia.

Radtke Ina I Mullighan Charles G CG Ishii Masami M Su Xiaoping X Cheng Jinjun J Ma Jing J Ganti Ramapriya R Cai Zhongling Z Goorha Salil S Pounds Stanley B SB Cao Xueyuan X Obert Caroline C Armstrong Jianling J Zhang Jinghui J Song Guangchun G Ribeiro Raul C RC Rubnitz Jeffrey E JE Raimondi Susana C SC Shurtleff Sheila A SA Downing James R JR

Proceedings of the National Academy of Sciences of the United States of America 20090727 31

Pediatric de novo acute myeloid leukemia (AML) is an aggressive malignancy with current therapy resulting in cure rates of only 60%. To better understand the cause of the marked heterogeneity in therapeutic response and to identify new prognostic markers and therapeutic targets a comprehensive list of the genetic mutations that underlie the pathogenesis of AML is needed. To approach this goal, we examined diagnostic leukemic samples from a cohort of 111 children with de novo AML using single-nuc ...[more]

PMID: 19651601

Similar Datasets

Project description:Contemporary treatment of pediatric acute myeloid leukemia (AML) requires the assignment of patients to specific risk groups. To explore whether expression profiling of leukemic blasts could accurately distinguish between the known risk groups of AML, we analyzed 130 pediatric and 20 adult AML diagnostic bone marrow or peripheral blood samples using the Affymetrix U133A microarray. Class discriminating genes were identified for each of the major prognostic subtypes of pediatric AML, including t(15;17)[PML-RARalpha], t(8;21)[AML1-ETO], inv(16) [CBFbeta-MYH11], MLL chimeric fusion genes, and cases classified as FAB-M7. When subsets of these genes were used in supervised learning algorithms, an overall classification accuracy of more than 93% was achieved. Moreover, we were able to use the expression signatures generated from the pediatric samples to accurately classify adult de novo AMLs with the same genetic lesions. The class discriminating genes also provided novel insights into the molecular pathobiology of these leukemias. Finally, using a combined pediatric data set of 130 AMLs and 137 acute lymphoblastic leukemias, we identified an expression signature for cases with MLL chimeric fusion genes irrespective of lineage. Surprisingly, AMLs containing partial tandem duplications of MLL failed to cluster with MLL chimeric fusion gene cases, suggesting a significant difference in their underlying mechanism of transformation. All the gene expression arrays are available through http://www.stjuderesearch.org/site/data/AML1/ in the original study (PMID:15226186). To study the RAS gene expression in the human AML patients, a total of 104 AML cases with known KRAS and NRAS status (including 72 gene expression arrays in the original study and 32 additional arrays acquired later on), as well as 4 CD34+ normal bone marrow cases deposited in GEO GSE33315, were including in this depository. Gene expression profiling was performed on 104 single diagnosis tumor samples and 4 CD34+ normal bone marrow samples

Dataset Information

Affymetrix U133A array data for 111 pediatric acute myeloid leukemia (AML) samples at diagnosis

Publications

Genomic analysis reveals few genetic alterations in pediatric acute myeloid leukemia.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure