Homo sapiens
Ontology highlight
ABSTRACT:
OTHER RELATED OMICS DATASETS IN: GSE15347
PROVIDER: PRJNA123171 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Affymetrix SNP array data for pediatric acute myeloid leukemia (AML) samples at diagnosis: Xba SNP array
| PRJNA123007 | ENA
Project description:Affymetrix SNP array data for pediatric acute myeloid leukemia (AML) samples at diagnosis: Sty2 SNP array
| PRJNA123005 | ENA
Project description:Affymetrix SNP array data for pediatric acute myeloid leukemia (AML) samples at diagnosis: Hind SNP array
| PRJNA122987 | ENA
Project description:Affymetrix SNP array data for pediatric acute myeloid leukemia (AML) samples at diagnosis: Nsp SNP Array
| PRJNA123003 | ENA
Project description: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.
2010-01-03 | E-GEOD-14471 | biostudies-arrayexpress
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
2013-07-02 | E-GEOD-43176 | biostudies-arrayexpress
Project description:Pediatric acute myeloid leukemia (AML) is a heterogeneous disease characterized by non-random genetic aberrations related to outcome. Detecting these aberrations however still lead to failures or false negative results. Therefore, we focused on the potential of gene expression profiles (GEP) to classify pediatric AML. Gene expression microarray data of 237 children with AML were generated and cases were split into a discovery cohort (n=157) and an independent validation cohort (n=80). Next, a double-loop cross validation approach was used to generate a subtype-predictive GEP in the discovery cohort which was then tested for its true predictive value in the independent validation cohort. 237 bone marrow and peripheral blood samples were collected at diagnosis and frozen. They were later thawed and hybridized to Affymetrix U133 Plus 2.0 arrays.
2010-10-21 | E-GEOD-17855 | biostudies-arrayexpress
Project description:In high income countries 90% of the patients achieve complete remission after induction chemotherapy. However, 30-40% of these patients suffer from relapse. These patients face a dismal prognosis, as the majority (>60%) of relapsed patients die within 5 years. As a result, outcome for pediatric acute myeloid leukemia (AML) patients remains poor and has stabilized over the past 15 years. To prevent or better treat relapse of AML is the best option to improve outcome. Despite patient specific differences, most patients do respond to initial therapy. This suggests that at relapse, mechanisms are active that cause the altered response to chemotherapy. Detailed understanding of mechanisms that cause relapse remain largely elusive. To gain insight in the molecular pathways that characterize relapsed AML, we performed genome wide gene expression profiling on paired initial diagnosis and relapsed AML samples of 23 pediatric AML patients. We used pathway analysis to find which molecular pathways are involved in altered gene expression between diagnosis and relapse samples of individual AML patients. 23 paired diagnosis and relapse bone marrow or peripheral blood samples were collected and cryo-preserved. They were later thawed and processed for hybridization to Affymetrix U133 Plus 2.0 arrays.
2015-05-07 | E-GEOD-52891 | biostudies-arrayexpress
Project description:Cure rates for patients with acute myeloid leukemia (AML) remain low despite ever-increasing dose intensity of cytotoxic therapy. In an effort to identify novel approaches to AML therapy, we recently reported a new method of chemical screening based on the modulation of a gene expression signature of interest. We applied this approach to the discovery of AML-differentiation-promoting compounds. Among the compounds inducing neutrophilic differentiation was DAPH1 (4,5-dianilinophthalimide), previously reported to inhibit epidermal growth factor receptor (EGFR) kinase activity. Here we report that the Food and Drug Administration (FDA)-approved EGFR inhibitor gefitinib similarly promotes the differentiation of AML cell lines and primary patient-derived AML blasts in vitro. Gefitinib induced differentiation based on morphologic assessment, nitro-blue tetrazolium reduction, cell-surface markers, genome-wide patterns of gene expression, and inhibition of proliferation at clinically achievable doses. Importantly, EGFR expression was not detected in AML cells, indicating that gefitinib functions through a previously unrecognized EGFR-independent mechanism. These studies indicate that clinical trials testing the efficacy of gefitinib in patients with AML are warranted. golub-00392 Assay Type: Gene Expression Provider: Affymetrix Array Designs: HG-U133A, HG-U133A_2 Organism: Homo sapiens (ncbitax) Material Types: cell, total_RNA, synthetic_RNA, organism_part, whole_organism*Cell Types: Disease States: Acute Myeloid Leukemia, Normal, Acute Myeloid Leukemia
2015-05-16 | E-GEOD-68954 | biostudies-arrayexpress