Dataset Information


Microarray analyses of induction failure in T-ALL

ABSTRACT: 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 SubSeries listed below. Overall design: Refer to individual Series 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). Expression profiles were obtained from patients with newly diagnosed T-ALL. NR = no response (induction failure); F= failure (relapse); C= Complete Continous Remission.


INSTRUMENT(S): [HG-U133A] Affymetrix Human Genome U133A Array

SUBMITTER: Stuart S. Winter  

PROVIDER: GSE14618 | GEO | 2009-01-29



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