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accession-icon GSE47772
Expression data from subpopulations of Apc1638N/+ intestinal adeno tumors versus Apc1638N/+ / KRAS v12G intestinal adenocarcinomas tumors
  • organism-icon Mus musculus
  • sample-icon 24 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Constitutive activation of the Wnt pathway leads to adenoma formation, an obligatory step towards intestinal cancer. In view of the established role of Wnt in regulating stemness, we attempted the isolation of cancer stem cells (CSCs) from Apc- and Apc/KRAS-mutant intestinal tumours. Whereas CSCs are present in malignant Apc/KRASmutant carcinomas, they appear to be very rare (<10-6) in the benign Apcmutant adenomas. In contrast, the Lin-CD24hiCD29+ subpopulation of adenocarcinoma cells appear to be enriched in CSCs with increased levels of active -catenin. Expression profiling analysis of the CSC-enriched subpopulation confirmed their enhanced Wnt activity and revealed additional differential expression of other signalling pathways, growth factor binding proteins, and extracellular matrix components. As expected, genes characteristic of the Paneth cell lineage (e.g. defensins) are co-expressed together with stem cell genes (e.g. Lgr5) within the CSC-enriched subpopulation. This is of interest as it may indicate a cancer stem cell niche role for tumor-derived Paneth-like cells, similar to their role in supporting Lgr5+ stem cells in the normal intestinal crypt. Overall, our results indicate that oncogenic KRAS activation in Apc-driven tumours results in the expansion of the CSCs compartment by increasing b-catenin intracellular stabilization.

Publication Title

Cancer stemness in Apc- vs. Apc/KRAS-driven intestinal tumorigenesis.

Sample Metadata Fields

Specimen part

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accession-icon GSE60926
Prediction of isolated central nervous system relapses in pediatric acute lymphoblastic leukemia
  • organism-icon Homo sapiens
  • sample-icon 48 Downloadable Samples
  • Technology Badge Icon 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

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accession-icon GSE9782
Gene expression profiling and correlation with outcome in clinical trials of the proteasome inhibitor bortezomib
  • organism-icon Homo sapiens
  • sample-icon 264 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

The aims of this study were to assess the feasibility of prospective pharmacogenomics research in multicenter international clinical trials of bortezomib in multiple myeloma and to develop predictive classifiers of response and survival with bortezomib. Patients with relapsed myeloma enrolled in phase 2 and phase 3 clinical trials of bortezomib and consented to genomic analyses of pretreatment tumor samples. Bone marrow aspirates were subject to a negative-selection procedure to enrich for tumor cells, and these samples were used for gene expression profiling using DNA microarrays. Data quality and correlations with trial outcomes were assessed by multiple groups. Gene expression in this dataset was consistent with data published from a single-center study of newly diagnosed multiple myeloma. Response and survival classifiers were developed and shown to be significantly associated with outcome via testing on independent data. The survival classifier improved on the risk stratification provided by the International Staging System. Predictive models and biologic correlates of response show some specificity for bortezomib rather than dexamethasone. Informative gene expression data and genomic classifiers that predict clinical outcome can be derived from prospective clinical trials of new anticancer agents.

Publication Title

Gene expression profiling and correlation with outcome in clinical trials of the proteasome inhibitor bortezomib.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE55145
Gene expression profile alone is inadequate in predicting complete response in multiple myeloma
  • organism-icon Homo sapiens
  • sample-icon 67 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [transcript (gene) version (huex10st)

Description

We have analyzed gene expression microarray datasets from four different clinical trials to assess accuracy of gene expression based signature in predicting treatment complete response in patients with multiple myeloma. Two of four datasets were made available via The Intergroupe Francophone du Mylome (IFM) group, and remaining two datasets were downloaded from NCBI GEO portal with accession IDs: GSE19784 (HOVON65/GMMG-HD4 trial) and GSE9782 (APEX/SUMMIT trial). Analysis UUID: datasets_archive--2afcd42a-7e12-11e3-9145-5fcc1e060548--15-Jan-2014-12-23-44-CST.

Publication Title

Gene expression profile alone is inadequate in predicting complete response in multiple myeloma.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE19784
Gene expression profiling of multiple myeloma patients included in the HOVON65/GMMG-HD4 trial
  • organism-icon Homo sapiens
  • sample-icon 315 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

In order to identify relevant, molecularly defined subgroups in Multiple Myeloma (MM), gene expression profiling (GEP) was performed on purified CD138+ plasma cells of 320 newly diagnosed myeloma patients included in the Dutch-Belgian/German HOVON-65/ GMMG-HD4 trial using Affymetrix GeneChip U133 plus 2.0 arrays. Hierarchical clustering identified 10 distinct subgroups. Using this dataset as training data, a prognostic signature was built. The dataset consists of 282 CEL files previously used in the hierarchical clustering study of Broyl et al (Blood, 116(14):2543-53, 2010) outlined above. To this set 8 CEL-files/gene expression profiles were added. Using this set of 290 CEL-files, a prognostic signature of 92 genes (EMC-92-genesignature) was generated by supervised principal components analysis combined with simulated annealing (Kuiper et al.).

Publication Title

Gene expression profiling for molecular classification of multiple myeloma in newly diagnosed patients.

Sample Metadata Fields

Specimen part

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accession-icon SRP017511
Marker gene discovery for Staphylococcus epidermidis infection in zebrafish embryos (RNA-Seq)
  • organism-icon Danio rerio
  • sample-icon 8 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2000

Description

We use the zebrafish embryo model to study the innate immune response against Staphylococcus epidermidis. Therefore, we injected S. epidermidis into the yolk at 2 hpf and took samples at 5 days post injection. Overall design: This deep sequence study was designed to determine the gene expression profile by Staphylococcus epidermidis infection. RNA was isolated from embryos at 5 days post injection. Wildtypes zebrafish embryos were micro-injected into the yolk (2hpf) with 20 CFU of S. epidermdis O-47 mCherry bacteria suspended in PVP (Polyvinylpyrrolidone), or Non-injected as a control. After injections embryos were transferred into fresh egg water and incubated at 28°C. At 5 days post injection 100-200 embryos per group were snap-frozen in liquid nitrogen, and total RNA was isolated using TRIZOL reagent.

Publication Title

Analysis of RNAseq datasets from a comparative infectious disease zebrafish model using GeneTiles bioinformatics.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP042084
Gene expression profiling of zebrafish embryos at 5 days post fertilization
  • organism-icon Danio rerio
  • sample-icon 8 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2000

Description

We use the zebrafish embryo model to study the innate immune response against Mycobacterium marinum. Therefore, we injected M. marinum into the yolk at the 64 cell stage and took samples at 5 days post injection. Overall design: This deep sequence study was designed to determine the gene expression profile by Mycobacterium marinum infection. RNA was isolated from embryos at 5 days post injection. Wildtypes zebrafish embryos were micro-injected into the yolk (64 cell stage) with 40 CFU of Mycobacterium marinum E11 mCherry bacteria suspended in PVP (Polyvinylpyrrolidone), or Non-injected as a control. After injections embryos were transferred into fresh egg water and incubated at 28°C. At 5 days post injection 50 embryos per group were snap-frozen in liquid nitrogen, and total RNA was isolated using TRIZOL reagent.

Publication Title

Analysis of RNAseq datasets from a comparative infectious disease zebrafish model using GeneTiles bioinformatics.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP018699
Gene expression profiling of zebrafish embryos at 5 days post fertilization [Illumina RNA-Seq]
  • organism-icon Danio rerio
  • sample-icon 3 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2000

Description

We compared Agilent custom made expression microarrays with Illumina deep sequencing for RNA analysis of zebrafish embryos 5 days post fertilization, showing as expected a high degree of correlation of expression of a common set of 15,927 genes for untreated fish. The transcriptomes were also compared for fish injected in the yolk with Mycobacterium marinum Overall design: This RNA deep sequencing study was designed to determine the gene expression profile of zebrafish embryos 5 days post fertilization. We also have compared expression with embryos that were injected with Mycobacterium marinum in the yolk at 2 hours post fertilization. After injections embryos were transferred into fresh egg water and incubated at 28°C. 150 embryos of mock-injected embryos or 200 embryos injected with 12 CFU bacteria were snap-frozen in liquid nitrogen, and total RNA was isolated using TRIZOL reagent.

Publication Title

Analysis of RNAseq datasets from a comparative infectious disease zebrafish model using GeneTiles bioinformatics.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP151425
RNA-Seq of newly diagnosed patients in the PADIMAC study leads to a bortezomib/lenalidomide decision signature
  • organism-icon Homo sapiens
  • sample-icon 42 Downloadable Samples
  • Technology Badge IconNextSeq 500

Description

Improving outcomes in multiple myeloma will not only involve development of new therapies, but better use of existing treatments. We performed RNA sequencing (RNA-Seq) on samples from newly diagnosed patients enrolled into the phase II PADIMAC study. Using an empirical Bayes approach and synthetic annealing, we developed and trained a seven-gene signature to predict treatment outcome. We tested the signature on independent cohorts treated with bortezomib- and lenalidomide-based therapies. The signature was capable of distinguishing which patients would respond better to which regimen. In the CoMMpass dataset, patients who were treated correctly according to the signature had a better progression-free and overall survival than those who were not. Indeed, the outcome for these correctly treated patients was non-inferior to those treated with combined bortezomib, lenalidomide, and dexamethasone (VRD). PADIMAC: Bortezomib, Adriamycin and Dexamethasone (PAD) therapy for previously untreated patients with multiple myeloma: Impact of minimal residual disease (MRD) in patients with deferred ASCT (autologous stem cell transplant) Overall design: RNA-Seq data from 44 patients enrolled into the PADIMAC study who provided RNA with an RNA Integrity score of 6 or greater. Thirteen out of forty-four patients had at least a very good partial remission sustained for at least a year without progression and were labelled as "bortezomib-good".

Publication Title

RNA-seq of newly diagnosed patients in the PADIMAC study leads to a bortezomib/lenalidomide decision signature.

Sample Metadata Fields

Age, Specimen part, Subject

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accession-icon GSE99636
Gene expression profiles of multiple myeloma plasma cell fractions from bone marrow
  • organism-icon Homo sapiens
  • sample-icon 21 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2), Affymetrix Human Exon 1.0 ST Array [CDF: huex10st_Hs_ENSG_20.0 (huex10st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

A multiple myeloma classification system that associates normal B-cell subset phenotypes with prognosis.

Sample Metadata Fields

Specimen part, Disease

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refine.bio is a repository of uniformly processed and normalized, ready-to-use transcriptome data from publicly available sources. refine.bio is a project of the Childhood Cancer Data Lab (CCDL)

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Cite refine.bio

Casey S. Greene, Dongbo Hu, Richard W. W. Jones, Stephanie Liu, David S. Mejia, Rob Patro, Stephen R. Piccolo, Ariel Rodriguez Romero, Hirak Sarkar, Candace L. Savonen, Jaclyn N. Taroni, William E. Vauclain, Deepashree Venkatesh Prasad, Kurt G. Wheeler. refine.bio: a resource of uniformly processed publicly available gene expression datasets.
URL: https://www.refine.bio

Note that the contributor list is in alphabetical order as we prepare a manuscript for submission.

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