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Homo sapiens
77 Downloadable Samples
Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2), Affymetrix Human Genome U133A Array (hgu133a)
Description
The clinical and cytogenetic features associated with T-cell acute lymphoblastic leukemia (T-ALL) are not predictive of early treatment failure. Based on the hypothesis that microarrays might identify patients who fail therapy, we used the Affymetrix U133 Plus 2.0 chip and prediction analysis of microarrays (PAM) to profile 50 newly diagnosed patients who were treated in the Children's Oncology Group (COG) T-ALL Study 9404. We identified a 116-member genomic classifier that could accurately distinguish all 6 induction failure (IF) cases from 44 patients who achieved remission; network analyses suggest a prominent role for genes mediating cellular quiescence. Seven genes were similarly upregulated in both the genomic classifier for IF patients and T-ALL cell lines having acquired resistance to neoplastic agents, identifying potential target genes for further study in drug resistance. We tested whether our classifier could predict IF within 42 patient samples obtained from COG 8704 and, using PAM to define a smaller classifier for the U133A chip, correctly identified the single IF case and patients with persistently circulating blasts. Genetic profiling may identify T-ALL patients who are likely to fail induction and for whom alternate treatment strategies might be beneficial.
Publication Title
Identification of genomic classifiers that distinguish induction failure in T-lineage acute lymphoblastic leukemia: a report from the Children's Oncology Group.
Sample Metadata Fields
No sample metadata fields
View Samples- Homo sapiens
- 35 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2), Affymetrix Human Genome U133A Array (hgu133a)
Description
The clinical and cytogenetic features associated with T-cell acute lymphoblastic leukemia (T-ALL) are not predictive of early treatment failure. Based on the hypothesis that microarrays might identify patients who fail therapy, we used the Affymetrix U133 Plus 2.0 chip and prediction analysis of microarrays (PAM) to profile 50 newly diagnosed patients who were treated in the Children's Oncology Group (COG) T-ALL Study 9404. We identified a 116-member genomic classifier that could accurately distinguish all 6 induction failure (IF) cases from 44 patients who achieved remission; network analyses suggest a prominent role for genes mediating cellular quiescence. Seven genes were similarly upregulated in both the genomic classifier for IF patients and T-ALL cell lines having acquired resistance to neoplastic agents, identifying potential target genes for further study in drug resistance. We tested whether our classifier could predict IF within 42 patient samples obtained from COG 8704 and, using PAM to define a smaller classifier for the U133A chip, correctly identified the single IF case and patients with persistently circulating blasts. Genetic profiling may identify T-ALL patients who are likely to fail induction and for whom alternate treatment strategies might be beneficial.
Publication Title
Identification of genomic classifiers that distinguish induction failure in T-lineage acute lymphoblastic leukemia: a report from the Children's Oncology Group.
Sample Metadata Fields
No sample metadata fields
View Samples- Homo sapiens
- 42 Downloadable Samples
Affymetrix Human Genome U133A Array (hgu133a)
Description
The clinical and cytogenetic features associated with T-cell acute lymphoblastic leukemia (T-ALL) are not predictive of early treatment failure. Based on the hypothesis that microarrays might identify patients who fail therapy, we used the Affymetrix U133 Plus 2.0 chip and prediction analysis of microarrays (PAM) to profile 50 newly diagnosed patients who were treated in the Children's Oncology Group (COG) T-ALL Study 9404. We identified a 116-member genomic classifier that could accurately distinguish all 6 induction failure (IF) cases from 44 patients who achieved remission; network analyses suggest a prominent role for genes mediating cellular quiescence. Seven genes were similarly upregulated in both the genomic classifier for IF patients and T-ALL cell lines having acquired resistance to neoplastic agents, identifying potential target genes for further study in drug resistance. We tested whether our classifier could predict IF within 42 patient samples obtained from COG 8704 and, using PAM to define a smaller classifier for the U133A chip, correctly identified the single IF case and patients with persistently circulating blasts. Genetic profiling may identify T-ALL patients who are likely to fail induction and for whom alternate treatment strategies might be beneficial.
Publication Title
Identification of genomic classifiers that distinguish induction failure in T-lineage acute lymphoblastic leukemia: a report from the Children's Oncology Group.
Sample Metadata Fields
No sample metadata fields
View Samples- Homo sapiens
- 17 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
Previous studies have reported that human pluripotent stem cells (hPSCs) generate dorsal forebrain, cortical-like neurons under default differentiation in the absence of patterning morphogens. Novel bioinformatic analyses of whole transcriptome data allow us to examine these cells' regional specification more comprehensively. Furthermore, these tools allow us to ask how well hPSNs mimic their endogenous counterparts during various stages of in vivo human brain development.
Publication Title
Default Patterning Produces Pan-cortical Glutamatergic and CGE/LGE-like GABAergic Neurons from Human Pluripotent Stem Cells.
Sample Metadata Fields
Sex, Specimen part, Time
View Samples
GSE77741- Homo sapiens
- 100 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
MLL rearrangements impact outcome in HOXA-deregulated T-lineage acute lymphoblastic leukemia: a Children's Oncology Group Study.
Sample Metadata Fields
Specimen part, Disease
View Samples- Homo sapiens
- 100 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
The clinical and cytogenetic features associated with T-cell acute lymphoblastic leukemia (T-ALL) are not predictive of early treatment failure or relapse. We used the Affymetrix U133 Plus 2.0 chip to profile 100 newly diagnosed patients who were treated in the Children's Oncology Group (COG) T-ALL AALL0434. We performed unsupervised hierarchical clustering of 25 HOXA probe sets within the cohort of 100 T-ALL cases. We identified a cluster of 20 cases (20%) characterized by increased expression of HOXA3, 5, 7, 9, and 10. In samples with HOXA9/10 deregulation, the presence of specific molecular lesions were confirmed through a systematic review of cytogenetic databases, FISH and PCR testing, and by RNA sequence analysis. Because MLL and AF10 genes rearrangements (MLL-R, AF10-R) are hallmarks of HOXA-deregulated leukemias, we sought to identify specific genes that are enriched with these genomic abnormalities.
Publication Title
MLL rearrangements impact outcome in HOXA-deregulated T-lineage acute lymphoblastic leukemia: a Children's Oncology Group Study.
Sample Metadata Fields
Specimen part, Disease
View Samples- Homo sapiens
- 34 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
Primary xenografts were made from a variety of different high-risk childhood BCP-ALL leukemia samples.
Publication Title
Evaluation of the in vitro and in vivo efficacy of the JAK inhibitor AZD1480 against JAK-mutated acute lymphoblastic leukemia.
Sample Metadata Fields
Specimen part
View Samples- Mus musculus
- 20 Downloadable Samples
- Affymetrix Murine Genome U74A Version 2 Array (mgu74av2)
Description
Pregnant C57Bl6N mice were treated with 0 (corn oil), 1.5, 3.0, or 6.0 ug/kg TCDD on gd14.5. Fetal hearts were collected on gd17.5. Hearts from each litter were pooled onto one chip. 4 replicates of each condition were run on affymetrix MG_U74Av2 chips, using standard affymetrix protocols and controls.
Publication Title
No associated publication
Sample Metadata Fields
No sample metadata fields
View Samples- Homo sapiens
- 12 Downloadable Samples
- Affymetrix Human Transcriptome Array 2.0 (hta20)
Description
Despite widespread knowledge that bone marrow-resident breast cancer cells (BMRCs) affect tumor progression, signaling mechanisms of BMRCs implicated in maintaining long-term dormancy have not been characterized. To overcome these hurdles, we developed a novel experimental model of tumor dormancy employing circulating tumor cells (CTCs) derived from metastatic breast cancer patients (de novo CTCs), transplanted them in immunocompromised mice, and re-isolated these cells from xenografted mice bone marrow (ex vivo BMRCs) and blood (ex vivo CTCs) to perform downstream transcriptomic analyses.
Publication Title
Molecular Interplay between Dormant Bone Marrow-Resident Cells (BMRCs) and CTCs in Breast Cancer.
Sample Metadata Fields
Sex, Specimen part, Disease stage
View Samples- Saccharomyces cerevisiae
- 8 Downloadable Samples
- Affymetrix Yeast Genome 2.0 Array (yeast2)
Description
A population of Saccharomyces cerevisiae was cultured for approximately 450 generations in the presence of high glucose to select for genetic variants. This experiment allows for a controlled model of adaptive evolution under natural selection. Using the parental strain BY4741 as the starting population, an evolved culture was obtained after continuous aerobic growth in a glucose-high medium for approximately 450 generations. After the evolution period three single colony isolates were selected for analysis. Next-generation Ion Torrent sequencing was used to evaluate genetic changes. Greater than 100 deletion/insertion changes were found with approximately half of these effecting genes. Additionally, over 180 single-nucleotide polymorphisms (SNPs) were identified with more than one quarter of these resulting in a non-synonymous mutation. Affymetrix DNA microarrays and RNseq analysis were used to determine differences in gene expression in the evolved strains compared to the parental strain. It was established that approximately 900 genes demonstrated significantly altered expression in the evolved strains relative to the parental strain. Many of these genes showed similar alterations in their expression in all three evolved strains. Interestingly, genes with altered expression in the three evolved strains included genes with a role in the TCA cycle. Overall these results are consistent with the physiological observations of decreased ethanol production and suggest that the underlying metabolism switched from fermentation to respiration during aerobic growth.
Publication Title
No associated publication
Sample Metadata Fields
No sample metadata fields
View Samples