Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA114441 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Microarray analyses of induction failure in T-ALL (COG study 9404)
| PRJNA114443 | ENA
Project 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. This SuperSeries is composed of the following subset Series:; GSE14613: Microarray analyses of induction failure in T-ALL (COG study 8704); GSE14615: Microarray analyses of induction failure in T-ALL (COG study 9404) Experiment Overall Design: Refer to individual Series Experiment Overall Design: This was a case-controlled, retrospectively designed study. We performed expression profiles on 92 patients with T-ALL treated on Children's Oncology Group studies 8704 (42 patients) and 9404 (50 patients). Experiment Overall Design: Expression profiles were obtained from patients with newly diagnosed T-ALL. NR = no response (induction failure); F= failure (relapse); C= Complete Continous Remission.
2009-02-07 | E-GEOD-14618 | biostudies-arrayexpress
Project description:Microarray analyses of induction failure in T-ALL
| PRJNA112317 | ENA
Project 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. Experiment Overall Design: The was a case-controlled, retrospectively designed study. We performed expression profiles on 92 patients with T-ALL treated on Children's Oncology Group studies 8704 (42 patients) and 9404 (50 patients). Experiment Overall Design: Expression profiles were obtained from patients with newly diagnosed T-ALL. NR = no response (induction failure); F= failure (relapse); C= Complete Continous Remission. Experiment Overall Design: Note: Failure (relapse) samples F8,12 and F19 were removed for reasons of failure other than relapse.
2009-02-09 | E-GEOD-14613 | biostudies-arrayexpress
Project 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. Experiment Overall Design: This was a case-controlled, retrospectively designed study. We performed expression profiles on 92 patients with T-ALL treated on Children's Oncology Group studies 8704 (42 patients) and 9404 (50 patients). Experiment Overall Design: Expression profiles were obtained from patients with newly diagnosed T-ALL. NR = no response (induction failure); F= failure (relapse); C= Complete Continous Remission. Experiment Overall Design: NOTE: non-sequential numbers were removed for reasons other than relapse, or poor hybridization during chip preparation.
2009-02-09 | E-GEOD-14615 | biostudies-arrayexpress
Project description: Not available
| S-EPMC2531291 | biostudies-literature
Project description:RNA extracted at 240min. Samples are rRNA depleted. Expression measurement of Homo sapiens genes.
2019-07-31 | GSE114179 | GEO
Project description:To study pathways associated with ferroptosis sensitivity
2022-06-01 | GSE173905 | GEO
Project description:RNA-sequencing (RNA-Seq) protocols and bioinformatic pipelines are designed to streamline downstream analyses on sequences believed to be the most important. Here, we have challenged this dogma by preserving ribosomal RNA (rRNA) in our samples and by lowering the minimal RNA size window of our small RNA-Seq analyses to 8 nt
2022-09-01 | GSE179678 | GEO