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accession-icon GSE51697
The effect of imatinib therapy on tumor associated macrophages (TAMs) in human gastrointestinal stromal tumor (GIST)
  • organism-icon Homo sapiens
  • sample-icon 20 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A 2.0 Array (hgu133a2)

Description

The gene expression profile of TAMs microbead isolated from freshly obtained human GISTs were compared in tumors that were untreated, responding to imatinib (sensitive), or resistant to imatinib (resistant)

Publication Title

KIT oncogene inhibition drives intratumoral macrophage M2 polarization.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE51698
The effect of imatinib therapy on tumor associated macrophages (TAMs) in murine gastrointestinal stromal tumor (GIST)
  • organism-icon Mus musculus
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430A 2.0 Array (mouse430a2)

Description

The gene expression profile of TAMs sorted from vehicle control tumors in GIST mice (Sommer et al, PNAS 2003) was compared to TAMs sorted from mice after 2 weeks of imatinib therapy

Publication Title

KIT oncogene inhibition drives intratumoral macrophage M2 polarization.

Sample Metadata Fields

Specimen part

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accession-icon SRP160999
Cardiomyocyte mRNA Content
  • organism-icon Homo sapiens
  • sample-icon 1 Downloadable Sample
  • Technology Badge IconIllumina HiSeq 3000

Description

Determine mRNA expression levels in cultured cardiomyocytes derived from human iPS cells Overall design: 1 sample

Publication Title

Muscle-specific stress fibers give rise to sarcomeres in cardiomyocytes.

Sample Metadata Fields

Specimen part, Subject

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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

View Samples
accession-icon GSE13231
The effect of inherited polymorphism on prognostic gene expression signatures
  • organism-icon Mus musculus
  • sample-icon 42 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Expression 430A Array (moe430a), Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

The origins of breast cancer prognostic gene expression profiles.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE13230
Met1 or DB7 tumor gene expression
  • organism-icon Mus musculus
  • sample-icon 7 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Expression 430A Array (moe430a)

Description

Metastasis predictive gene signatures can result from either somatic mutation, inherited polyrmorphism or both. This experiment is designed to look at the gene expression differences due to differences in somatic mutations in the initiating oncogene, PyMT. Met1 is from a fully metastatic FVB mammary tumor cell line, DB7 contains a mutation that permits tumor formation, but suppresses metastatic ability.

Publication Title

The origins of breast cancer prognostic gene expression profiles.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE13227
(AKR/J x FVB/NJ)F1 versus (DBA/2J x FVB)F1 Thymus expression data
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302), Affymetrix Mouse Expression 430A Array (moe430a)

Description

F1 hybrids from (AKR/J x FVB/NJ) and (DBA/2J x FVB/NJ) outcrosses display a 20-fold difference in mammary tumor metastatic capacity, due to differences in inherited polymorphisms. Expression studies were performed to determine whether polymorphism-driven gene expression signatures predictive of outcome could be generated from normal tissues

Publication Title

The origins of breast cancer prognostic gene expression profiles.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE13221
(AKR/J x PyMT)F1 versus (DBA/2J x PyMT)F1 tumor expression data
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Expression 430A Array (moe430a)

Description

F1 hybrids from (AKR/J x FVB/NJ) and (DBA/2J x FVB/NJ) outcrosses display a 20-fold difference in mammary tumor metastatic capacity, due to differences in inherited polymorphisms. Expression studies were performed to determine whether polymorphism-driven gene expression signatures predictive of outcome could be generated from mouse tumor tissues

Publication Title

The origins of breast cancer prognostic gene expression profiles.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE13224
(AKR/J x FVB/NJ)F1 versus (DBA/2J x FVB)F1 lung expression data
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302), Affymetrix Mouse Expression 430A Array (moe430a)

Description

F1 hybrids from (AKR/J x FVB/NJ) and (DBA/2J x FVB/NJ) outcrosses display a 20-fold difference in mammary tumor metastatic capacity, due to differences in inherited polymorphisms. Expression studies were performed to determine whether polymorphism-driven gene expression signatures predictive of outcome could be generated from normal tissues

Publication Title

The origins of breast cancer prognostic gene expression profiles.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE41870
CD4+ and CD8+ T cells responding to LCMV-Armstrong or LCMV-Clone 13
  • organism-icon Mus musculus
  • sample-icon 79 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Network analysis reveals centrally connected genes and pathways involved in CD8+ T cell exhaustion versus memory.

Sample Metadata Fields

Specimen part

View Samples
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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)

fund-icon Fund the CCDL

Developed by the Childhood Cancer Data Lab

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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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