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accession-icon GSE89401
Clonal variation in drug and radiation response among glioma-initiating cells is linked to proneural-mesenchymal transition
  • organism-icon Homo sapiens
  • sample-icon 146 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Transcriptome Array 2.0 (hta20), Illumina HumanMethylation450 BeadChip (HumanMethylation450_15017482)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Clonal Variation in Drug and Radiation Response among Glioma-Initiating Cells Is Linked to Proneural-Mesenchymal Transition.

Sample Metadata Fields

Specimen part, Cell line

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accession-icon GSE89399
Clonal variation in drug and radiation response among glioma-initiating cells is linked to proneural-mesenchymal transition (HTA 2.0)
  • organism-icon Homo sapiens
  • sample-icon 146 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Transcriptome Array 2.0 (hta20)

Description

Intra-tumor heterogeneity is a hallmark of glioblastoma multiforme, and thought to negatively affect treatment efficacy. Here we establish libraries of glioma-initiating cell (GIC) clones from patient samples and find extensive molecular and phenotypic variability between clones, including a wide range of responses to radiation and drugs. This widespread variability was observed as a continuum of multitherapy resistance phenotypes linked to a proneural-to-mesenchymal shift in the transcriptome.

Publication Title

Clonal Variation in Drug and Radiation Response among Glioma-Initiating Cells Is Linked to Proneural-Mesenchymal Transition.

Sample Metadata Fields

Specimen part, Cell line

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accession-icon GSE76896
Affymetrix profiling of IMIDIA biobank samples from organ donors and partially pancreatectomized patients
  • organism-icon Homo sapiens
  • sample-icon 200 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Systems biology of the IMIDIA biobank from organ donors and pancreatectomised patients defines a novel transcriptomic signature of islets from individuals with type 2 diabetes.

Sample Metadata Fields

Age

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accession-icon GSE76894
Affymetrix profiling of IMIDIA biobank samples from organ donors and partially pancreatectomized patients [organ donor cohort]
  • organism-icon Homo sapiens
  • sample-icon 99 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Pancreatic islet beta cell failure causes type 2 diabetes (T2D). The IMIDIA consortium has used a strategy entailing a stringent comparative transcriptomics analysis of islets isolated enzymatically or by laser microdissection from two large cohorts of non-diabetic (ND) and T2D organ donors (OD) or partially pancreatectomized patients (PPP). This work led to the identification of a signature of genes that were differentially expressed between T2D and ND regardless of the sample type (OD or PPP). This signature includes 19 genes, of which 9 have never been previously reported to be differentially expressed in T2D islets. The PPP cohort also includes samples from individuals with impaired glucose tolerance (IGT) or recent onset diabetes associated with a pancreatic exocrine disorder (T3cD). Notably, none of the 19 signature genes of T2D islets were significantly dysregulated in islets of subjects with IGT or T3cD, suggesting that their changed expression reflects beta cell deterioration rather than a deficit preceding it.

Publication Title

Systems biology of the IMIDIA biobank from organ donors and pancreatectomised patients defines a novel transcriptomic signature of islets from individuals with type 2 diabetes.

Sample Metadata Fields

Age

View Samples
accession-icon GSE76895
Affymetrix profiling of IMIDIA biobank samples from organ donors and partially pancreatectomized patients [partially pancreatectomized patient cohort]
  • organism-icon Homo sapiens
  • sample-icon 101 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Pancreatic islet beta cell failure causes type 2 diabetes (T2D). The IMIDIA consortium has used a strategy entailing a stringent comparative transcriptomics analysis of islets isolated enzymatically or by laser microdissection from two large cohorts of non-diabetic (ND) and T2D organ donors (OD) or partially pancreatectomized patients (PPP). This work led to the identification of a signature of genes that were differentially expressed between T2D and ND regardless of the sample type (OD or PPP). This signature includes 19 genes, of which 9 have never been previously reported to be differentially expressed in T2D islets. The PPP cohort also includes samples from individuals with impaired glucose tolerance (IGT) or recent onset diabetes associated with a pancreatic exocrine disorder (T3cD). Notably, none of the 19 signature genes of T2D islets were significantly dysregulated in islets of subjects with IGT or T3cD, suggesting that their changed expression reflects beta cell deterioration rather than a deficit preceding it.

Publication Title

Systems biology of the IMIDIA biobank from organ donors and pancreatectomised patients defines a novel transcriptomic signature of islets from individuals with type 2 diabetes.

Sample Metadata Fields

Age

View Samples
accession-icon SRP125882
Transcriptomic analysis to map mechanisms of viral replication control in HIV-1 positive Elite Controllers
  • organism-icon Homo sapiens
  • sample-icon 33 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

In order to understand the underlying mechanisms, which ensure that disease progression is prevented in EC, a comprehensive analysis of clinical phenotypes coupled to genetics and biomolecular mechanisms is required. The rapidly increasing accessibility of genetic and biomolecular expression data from new high-throughput technologies is the foundation to shift the traditional phenotype-first approach to explorative genetic or molecular data-first approaches. In this study, we aimed to explore a comprehensive analysis of host transcriptomics and proteomics data coupled to clinical phenotypes in a well-defined Swedish EC cohort with up to 20 years of clinical follow-up data.

Publication Title

Transcriptomics and Targeted Proteomics Analysis to Gain Insights Into the Immune-control Mechanisms of HIV-1 Infected Elite Controllers.

Sample Metadata Fields

Sex, Age, Specimen part, Disease, Treatment, Race

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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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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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