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GSE22470
Homo sapiens
271 Downloadable Samples
Affymetrix Human Genome U133A Array (hgu133a)
Description
Background: Germinal center B-cell (GCB) lymphomas are common in children and adults. The prognosis strongly depends on age. Subgroups of GCB-lymphomas are characterized by chromosomal translocations affecting immunoglobulin (IG) loci leading to oncogene deregulation.
Publication Title
Translocations activating IRF4 identify a subtype of germinal center-derived B-cell lymphoma affecting predominantly children and young adults.
Sample Metadata Fields
Sex, Age
View Samples- Homo sapiens
- 127 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2), Affymetrix Human Gene 1.0 ST Array (hugene10st)
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
Identification of a new gene regulatory circuit involving B cell receptor activated signaling using a combined analysis of experimental, clinical and global gene expression data.
Sample Metadata Fields
Specimen part, Cell line, Treatment, Time
View Samples- Homo sapiens
- 133 Downloadable Samples
- Affymetrix Human Genome U133A Array (hgu133a)
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
Molecular classification of mature aggressive B-cell lymphoma using digital multiplexed gene expression on formalin-fixed paraffin-embedded biopsy specimens.
Sample Metadata Fields
Sex, Age, Specimen part, Disease
View Samples- Homo sapiens
- 74 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
Understanding the structure and interplay of cellular signalling pathways is one of the great challenges in molecular biology. Boolean Networks can infer signalling networks from observations of protein activation. In situations where it is difficult to assess protein activation directly, Nested Effect Models are an alternative. They derive the network structure indirectly from downstream effects of pathway perturbations. To date, Nested Effect Models cannot resolve signalling details like the formation of signalling complexes or the activation of proteins by multiple alternative input signals. Here we introduce Boolean Nested Effect Models (B-NEM). B-NEMs combine the use of downstream effects with the higher resolution of signalling pathway structures in Boolean Networks. We show that B-NEMs accurately reconstruct signal flows in simulated data. Using B-NEM we then resolve BCR signalling via PI3K and TAK1 kinases in BL2 lymphoma cell lines.
Publication Title
Analyzing synergistic and non-synergistic interactions in signalling pathways using Boolean Nested Effect Models.
Sample Metadata Fields
Specimen part, Cell line, Treatment
View Samples- Homo sapiens
- 84 Downloadable Samples
- Affymetrix Human Genome U133A Array (hgu133a)
Description
Since follicular lymphoma (FL) grade 3A often coexist with a FL1/2 component a linear progression model of FL1, FL2 and FL3A has been developed. FL3B, on the other hand, is supposed to be more closely related to diffuse large B-cell lymphoma (DLBCL) and both FL3B and DLBCL are often simultaneously present in one tumor (DLBCL/FL3B).
Publication Title
Gene expression profiling reveals a close relationship between follicular lymphoma grade 3A and 3B, but distinct profiles of follicular lymphoma grade 1 and 2.
Sample Metadata Fields
Sex, Age, Specimen part
View Samples- Homo sapiens
- 60 Downloadable Samples
- Affymetrix Human Gene 1.1 ST Array (hugene11st)
Description
High-grade gliomas are amongst the most deadly human tumors. Treatment results are overall disappointing. Nevertheless, in several trials around 20% of patients respond to therapy. Diagnostic strategies to identify those patients that will ultimately profit from a specific targeted therapy are urgently needed. Gene expression profiling of untreated tumors is a well established approach for identifying biomarkers or diagnostic signatures. However, reliable signatures predicting treatment response in gliomas do not exist. Here we suggest a novel strategy for developing diagnostic signatures. We postulate that predictive gene expression patterns emerge only after tumor cells have been treated with the agent in vitro. Moreover, we postulate that enriching specimens for tumor initiating cells sharpens predictive expression patterns. Here, we report on the prediction of treatment response of cancer cells in vitro. As a proof of principle we analyzed gene expression in 18 short-term serum-free cultures of high-grade gliomas enhanced for brain tumor initiating cells (BTIC) before and after in vitro treatment with the tyrosine kinase inhibitor Sunitinib. Profiles from treated but not from untreated glioma cells allowed to predict therapy-induced impairment of proliferation of glioma cells in vitro. Prediction can be achieved with as little as 6 genes allowing for a straightforward translation into the clinic once the predictive power of the signature is shown also in vivo. Our strategy of using expression profiles from in vitro treated BTIC-enriched cultures opens new ways for trial design for patients with malignant gliomas.
Publication Title
Response-predictive gene expression profiling of glioma progenitor cells in vitro.
Sample Metadata Fields
Specimen part, Treatment
View Samples- Homo sapiens
- 43 Downloadable Samples
- Affymetrix Human Genome U133A Array (hgu133a)
Description
The most frequent mature aggressive B-cell lymphomas are diffuse large B-cell lymphoma (DLBCL) and Burkitt lymphoma (BL). Patients suffering from molecularly defined BL (mBL) but treated with a regimen developed for DLBCL show an unfavorable outcome compared to mBL treated with chemotherapy regimens for BL. Distinguishing BL from DLBCL by conventional histopathology is challenging in lymphomas that have features common to both diseases (aggressive B-cell lymphoma unclassifiable with features of DLBCL and BL [intermediates]). Moreover, DLBCL are a heterogeneous group of lymphomas comprising distinct molecular subtypes: the activated B-cell (ABC)-like, the germinal center B-cell-like (GCB) and the unclassifyable subtype as defined by gene expression profiling (GEP). Attempts to replace GEP with techniques applicable to formalin-fixed paraffin-embedded (FFPE) tissue led to algorithms for immunohistochemical stainings (IHS). Disappointingly, the algorithms yielded conflicting results with respect to their prognostic potential, raising concerns about their validity. Furthermore, IHS algorithms did not provide a fully resolved classification: They did not identify mBL; nor did they separate ABC from unclassified DLBCL.
Publication Title
Molecular classification of mature aggressive B-cell lymphoma using digital multiplexed gene expression on formalin-fixed paraffin-embedded biopsy specimens.
Sample Metadata Fields
Sex, Age, Specimen part
View Samples- Homo sapiens
- 36 Downloadable Samples
- Affymetrix Human Genome U133A Array (hgu133a)
Description
The spectrum of entities, the therapeutic strategy and the outcome of mature aggressive B-cell lymphomas (maB-NHL) differs between children and adolescents on the one hand and adult patients on the other. Whereas adult maB-NHL have been studied in detail, data on molecular profiling of pediatric maB-NHL are hitherto lacking. Our aim was to characterize pediatric maB-NHL on the molecular level and to evaluate whether a molecular diagnosis of pediatric maB-NHL reveals clinically relevant groups.
Publication Title
Molecular profiling of pediatric mature B-cell lymphoma treated in population-based prospective clinical trials.
Sample Metadata Fields
Age
View Samples- Homo sapiens
- 34 Downloadable Samples
- Affymetrix Human Gene 1.0 ST Array (hugene10st)
Description
All living cells rely on the communication with other cells to ensure their function and survival. Molecular signals are sent among cells of the same cell type and from cells of one cell type to another. In cancer, not only the cancer cells themselves are responsible for the malignancy, but also stromal (non-cancerous) cells and the molecular signals they send to cancer cells are important factors that determine the severity and outcome of the disease. Therefore, the identification of stromal signals and their influence on cancer cells is important when looking for novel treatment strategies.
Publication Title
Causal Modeling of Cancer-Stromal Communication Identifies PAPPA as a Novel Stroma-Secreted Factor Activating NFκB Signaling in Hepatocellular Carcinoma.
Sample Metadata Fields
Specimen part
View Samples- Homo sapiens
- 33 Downloadable Samples
Affymetrix Human Gene 1.0 ST Array (hugene10st)
Description
To discover new essential regulatory pathways in B lymphoma cells a combined analysis of experimental and clinical high throughput data was performed. Among others, a specific cluster of coherently expressed genes named BCR.1 was identified in primary lymphoma samples. These coherently expressed genes are suppressed by -IgM treatment of lymphoma cells in vitro. This B cell receptor activation leads to a G2 phase prolongation, delayed entry into the M phase, an overall diminished capacity of the cells to enter into mitosis and defects in metaphases. Cytogenetic changes are detected under long term -IgM treatment. Furthermore, an inverse correlation of BCR.1 genes with c-Myc coregulated genes in distinct groups of lymphoma patients is observed. In addition to the impact of c-Myc in the regulation of cell cycle regulators, BCR.1 genes are regulated by a combined action of IKK2, MAPK14 and JNK. Finally, the BCR.1 index discriminates activated B cell like and germinal centre B cell like diffuse large B cell lymphoma. Therefore, a new regulatory circuit is described affecting cell cycle and chromosome instability in B cells.
Publication Title
Identification of a new gene regulatory circuit involving B cell receptor activated signaling using a combined analysis of experimental, clinical and global gene expression data.
Sample Metadata Fields
Specimen part, Time
View Samples