Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Identification of genomic classifiers that distinguish induction failure in T-lineage acute lymphoblastic leukemia: a report from the Children's Oncology Group

11 May 2007

Abstract excerpt

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...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Acute Lymphoblastic Leukemia research
Share to Cancer Genomics and Diagnostics
Share to Genomic variations and chromosomal abnormalities

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Source

Identifiers

PMID: 17495134
DOI: 10.1182/blood-2006-12-059790

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 8 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Identification of genomic classifiers that distinguish induction failure in T-lineage acute lymphoblastic leukemia: a report from the Children's Oncology GroupPMID 17495134Read ↗

Gene expression classifiers for relapse-free survival and minimal residual disease improve risk classification and outcome prediction in pediatric B-precursor acute lymphoblastic leukemiaSemantic proximity Read ↗

Prediction of immunophenotype, treatment response, and relapse in childhood acute lymphoblastic leukemia using DNA microarraysSemantic proximity Read ↗

Gene expression profile of adult T-cell acute lymphocytic leukemia identifies distinct subsets of patients with different response to therapy and survivalSemantic proximity Read ↗

Microarray-based classification of a consecutive series of 121 childhood acute leukemias: prediction of leukemic and genetic subtype as well as of minimal residual disease statusSemantic proximity Read ↗

Pediatric acute lymphoblastic leukemia (ALL) gene expression signatures classify an independent cohort of adult ALL patientsSemantic proximity Read ↗

Gene expression–based classification and regulatory networks of pediatric acute lymphoblastic leukemiaSemantic proximity Read ↗

DNA methylation-based subtype prediction for pediatric acute lymphoblastic leukemiaSemantic proximity Read ↗

Classification of pediatric acute lymphoblastic leukemia by gene expression profilingSemantic proximity Read ↗

DNA methylation for subtype classification and prediction of treatment outcome in patients with childhood acute lymphoblastic leukemiaSemantic proximity Read ↗

Pediatric Acute Lymphoblastic LeukemiaSemantic proximity Read ↗

Distinct gene expression profiles determine molecular treatment response in childhood acute lymphoblastic leukemiaSemantic proximity Read ↗

Genomic Classification in Acute Myeloid LeukemiaSemantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.