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GSE67684
Homo sapiens
418 Downloadable Samples
Affymetrix Human Genome U133A Array (hgu133a)
Description
ALL is the most common form of childhood cancer with >80% cured with contemporary treatment protocols. Accurate risk stratification in childhood ALL is essential to avoid under- and over-treatment. Currently, we use presenting clinical, biological features, and minimal residual disease (MRD) quantitation to risk stratify patients. Although whole genome gene expression profiling (GEP) can accurately classify patients with ALL into various WHO 2008 defined subgroups, its value in predicting relapse remained to be defined. We hypothesized that global time-series GEPs of bone marrow (BM) samples at diagnosis and specific points during initial remission-induction therapy can measure the success of cytoreduction and be used for relapse prediction.
Publication Title
Effective Response Metric: a novel tool to predict relapse in childhood acute lymphoblastic leukaemia using time-series gene expression profiling.
Sample Metadata Fields
Specimen part, Disease, Subject, Time
View Samples- Homo sapiens
- 213 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
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.
Publication Title
Evaluation of gene expression signatures predictive of cytogenetic and molecular subtypes of pediatric acute myeloid leukemia.
Sample Metadata Fields
Specimen part, Subject
View Samples