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accession-icon GSE98588
Genetically-defined Diffuse Large B-cell Lymphoma Subsets Arise by Distinct Pathogenetic Mechanisms and Predicts Outcome
  • organism-icon Homo sapiens
  • sample-icon 137 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

We obtained gene experssion profiles of 52 newly diagnosed diffuse large B-cell lymphoma (DLBCL).

Publication Title

Molecular subtypes of diffuse large B cell lymphoma are associated with distinct pathogenic mechanisms and outcomes.

Sample Metadata Fields

Specimen part

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accession-icon GSE22470
Translocations Activating IRF4 Identify a Subtype of Germinal-Center-Derived B-cell Lymphoma Affecting Predominantly Children and Young Adults
  • organism-icon Homo sapiens
  • sample-icon 271 Downloadable Samples
  • Technology Badge Icon 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

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accession-icon SRP067091
Neuron-specific changes in gene expression caused by NPC1 deficiency
  • organism-icon Mus musculus
  • sample-icon 8 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Background: Niemann-Pick type C is a rare autosomal recessive lysosomal storage disorder presenting aggravating neurologic symptoms due degeneration of specific types of CNS neurons. At present, it is not well understood how neurons react to NPC1 deficiency and why some neuronal cell types are more vulnerable than others. Purpose: We took aimed to uncover how a specific type of CNS neuron that can be highly purified reacts to NPC1 deficiency based on changes in gene expression. Methods: Retinal ganglion cells were purified from individual one-week old Balb/c mice homozygous for a mutant NPC1 allele (NPC1m1N) and wildtype littermates (n = 4 mice each genotype) using immunopanning. Total RNA was isolated from acutely isolated neurons and subjected to RNAseq using 4 biological replicates for each genotype. Results: Our analysis revealed a strong downregulation of transcripts known to be decreased in mutant mice including Npc1 and Calb1 thus validating our approach. We observed a strong upregulation of genes for cellular cholesterol accretion and the downregulation of those for cholesterol release. Other changes including downregulation genes involved in the immune response and synaptic components. Conclusions: The observed changes suggest that neurons already at one week of age sense a cholesterol deficit because lipids accumulate in the endosomal-lysosomal system and cannot be redistributed intracellularly. Overall design: Gene expression analysis by RNAseq in retinal ganglion cells acutely purified from eight-days-old NPC1-deficient mice and wildtype littermates

Publication Title

Reversal of Pathologic Lipid Accumulation in NPC1-Deficient Neurons by Drug-Promoted Release of LAMP1-Coated Lamellar Inclusions.

Sample Metadata Fields

Subject

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accession-icon GSE6272
House keeping gene analysis - carcinoids and normal mucosa
  • organism-icon Homo sapiens
  • sample-icon 36 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

Accurate and reproducible quantitation of target genes depends on correct normalization. Historically, genes with variable tissue transcription e.g. GAPDH, have been used as normalization factors which is problematic, particularly in clinical samples which often are derived from different tissue sources. Using a large-scale gene database (GeneChip (Affymetrix U133A) dataset of 36 gastrointestinal tumors and normal tissues), we identified 8 candidate reference genes that were highly expressed with low variability and established expression levels by real-time RT-PCR in an independent set of GI tissue samples (n=42).

Publication Title

GeneChip, geNorm, and gastrointestinal tumors: novel reference genes for real-time PCR.

Sample Metadata Fields

No sample metadata fields

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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

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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

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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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