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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- Mus musculus
- 23 Downloadable Samples
- Affymetrix Mouse Genome 430 2.0 Array (mouse4302)
Description
A transcriptomic meta-analysis of over 400 microarrays was undertaken to compare LPC lines against datasets of; muscle and embryonic stem cell lines, embryonic and developed liver (DL), and HCC. Uploaded here, is the array data from seven of the ten LPC lines used. These seven were prepared in our laboratory. The remaining LPC arrays and arrays from other tissues/cells were obtained from the GEO.
Publication Title
A Transcriptomic Signature of Mouse Liver Progenitor Cells.
Sample Metadata Fields
Sex, Specimen part
View Samples- Homo sapiens
- 48 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
Background In childhood acute lymphoblastic leukemia (ALL), central nervous system (CNS) involvement is rare at diagnosis (1-4%), but more frequent at relapse (~30%). Minimal residual disease diagnostics predict most bone marrow (BM) relapses, but likely cannot predict isolated CNS relapses. Consequently, CNS relapses may become relatively more important. Because of the significant late sequelae of CNS treatment, early identification of patients at risk of CNS relapse is crucial. Methods Gene expression profiles of ALL cells from cerebrospinal fluid (CSF) and ALL cells from BM were compared and differences were confirmed by real-time quantitative PCR. For a selected set of overexpressed genes, protein expression levels of ALL cells in CSF at relapse and of ALL cells in diagnostic BM samples were evaluated by 8-color flow cytometry. Results CSF-derived ALL cells showed a clearly different gene expression profile than BM-derived ALL cells, with differentially-expressed genes (including SCD and OPN) involved in survival and apoptosis pathways and linked to the JAK-STAT pathway. Flowcytometric analysis showed that a subpopulation of ALL cells (>1%) with a CNS signature (SCD positivity and increased OPN expression) was already present in BM at diagnosis in ALL patients who later developed a CNS relapse, but was <1% or absent in virtually all other patients. Conclusions The presence of a subpopulation of ALL cells with a CNS signature at diagnosis may predict isolated CNS relapse. Such information can be used to design new diagnostic and treatment strategies that aim at prevention of CNS relapse with reduced toxicity.
Publication Title
New cellular markers at diagnosis are associated with isolated central nervous system relapse in paediatric B-cell precursor acute lymphoblastic leukaemia.
Sample Metadata Fields
Sex, Age, Time
View Samples- Homo sapiens
- 3 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
We used microarrays to detail the global programme of gene expression to identify TNF-induced genes that are negatively regulated by EHMT1
Publication Title
EHMT1 protein binds to nuclear factor-κB p50 and represses gene expression.
Sample Metadata Fields
Cell line
View Samples- Homo sapiens
- 1492 Downloadable Samples
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
An international standardization programme towards the application of gene expression profiling in routine leukaemia diagnostics: the Microarray Innovations in LEukemia study prephase.
Sample Metadata Fields
No sample metadata fields
View Samples- Homo sapiens
- 357 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
An International Multi-Center Study to Define the Clinical Utility of MicroarrayBased Gene Expression Profiling in the Diagnosis and Sub-classification of Leukemia (MILE Study)
Publication Title
An international standardization programme towards the application of gene expression profiling in routine leukaemia diagnostics: the Microarray Innovations in LEukemia study prephase.
Sample Metadata Fields
Disease
View Samples- Homo sapiens
- 351 Downloadable Samples
Affymetrix Human Genome U133A Array (hgu133a), Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
Oncogenic pathway combinations predict clinical prognosis in gastric cancer.
Sample Metadata Fields
Specimen part, Cell line
View Samples- Homo sapiens
- 213 Downloadable Samples
- Affymetrix Human Genome U133A Array (hgu133a)
Description
Background and Aims: Gastric adenocarcinoma (gastric cancer, GC) is a major cause of global cancer mortality. Identifying molecular programs contributing to GC patient survival may improve our understanding of GC pathogenesis, highlight new prognostic factors, and reveal novel therapeutic targets. We aimed to produce a comprehensive inventory of gene expression programs expressed in primary GCs, and to identify those expression programs significantly associated with patient survival.
Publication Title
Comprehensive genomic meta-analysis identifies intra-tumoural stroma as a predictor of survival in patients with gastric cancer.
Sample Metadata Fields
Specimen part
View Samples- Homo sapiens
- 204 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
An international standardization program towards the application of gene expression profiling in routine leukaemia diagnostics: The MILE study pre-phase.
Publication Title
An international standardization programme towards the application of gene expression profiling in routine leukaemia diagnostics: the Microarray Innovations in LEukemia study prephase.
Sample Metadata Fields
No sample metadata fields
View Samples- Homo sapiens
- 200 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2), Affymetrix Human Genome U133A Array (hgu133a)
Description
Genome-wide mRNA expression profiles of 200 primary gastric tumors from the Singapore patient cohort. Gastric cancer (GC) is the second leading cause of global cancer mortality, with individual gastric tumors displaying significant heterogeneity in their deregulation of various oncogenic pathways. We aim to identify major oncogenic pathways in GC that robustly impact patient survival and treatment response. We used an in silico strategy based on gene expression signatures and connectivity analytics to map patterns of oncogenic pathway activation in 25 unique GC cell lines, and in 301 primary gastric cancers from three independent patient cohorts. Of 11 oncogenic pathways previously implicated in GC, we identified three predominant pathways (proliferation/stem cell, NF-kB, and Wnt/b-catenin) deregulated in the majority (>70%) of gastric tumors. Using a variety of proliferative, Wnt, and NF-kB-related assays, we experimentally validated the pathway predictions in multiple GC cell lines showing similar pathway activation patterns in vitro. Patients stratified at the level of individual pathways did not exhibit consistent differences in clinical outcome. However, patients grouped by oncogenic pathway combinations demonstrated robust and significant survival differences (e.g., high proliferation/high NF-kB vs. low proliferation/low NF-kB), suggesting that tumor behavior in GC is likely influenced by the combined effects of multiple oncogenic pathways. Our results demonstrate that GCs can be successfully taxonomized by oncogenic pathway activity into biologically and clinically relevant subgroups.
Publication Title
Oncogenic pathway combinations predict clinical prognosis in gastric cancer.
Sample Metadata Fields
Specimen part
View Samples