refine.bio
  • Search
      • Normalized Compendia
      • RNA-seq Sample Compendia
  • Docs
  • About
  • My Dataset
github link
Showing
of 11 results
Sort by

Filters

Technology

Platform

accession-icon GSE4885
Role of coactivator SRC-1/NcoA-1 for IL-6 target gene induction in HepG2 cells
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

This experiment series addresses the role of coactivator SRC-1/NcoA-1 for the induction of interleukin-6 (IL-6) target genes in HepG2 cells. For that purpose, HepG2 human hepatocellular carcinoma cells were manipulated to stably express an shRNA that knocks down SRC-1 expression yielding the HepG2-Src1 cells. Either unmanipulated HepG2 or HepG2-Src1 cells were then treated for various periods with IL-6.

Publication Title

Co-activator SRC-1 is dispensable for transcriptional control by STAT3.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE26440
Expression data for derivation of septic shock subgroups
  • organism-icon Homo sapiens
  • sample-icon 130 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Background: Septic shock is a heterogeneous syndrome within which probably exist several biological subclasses. Discovery and identification of septic shock subclasses could provide the foundation for the design of more specifically targeted therapies. Herein we tested the hypothesis that pediatric septic shock subclasses can be discovered through genome-wide expression profiling. Methods: Genome-wide expression profiling was conducted using whole blood-derived RNA from 98 children with septic shock, followed by a series of bioinformatic approaches targeted at subclass discovery and characterization. Results: Three putative subclasses (subclasses A, B, and C) were initially identified based on an empiric, discovery-oriented expression filter and unsupervised hierarchical clustering. Statistical comparison of the 3 putative subclasses (ANOVA, Bonferonni correction, p < 0.05) identified 6,934 differentially regulated genes. K means clustering of these 6,934 genes generated 10 coordinately regulated gene clusters corresponding to multiple signaling and metabolic pathways, all of which were differentially regulated across the 3 subclasses. Leave one out cross validation procedures indentified 100 genes having the strongest predictive values for subclass identification. Forty-four of these 100 genes corresponded to signaling pathways relevant to the adaptive immune system and glucocorticoid receptor signaling, the majority of which were repressed in subclass A patients. Subclass A patients were also characterized by repression of genes corresponding to zinc-related biology. Phenotypic analyses revealed that subclass A patients were younger, had a higher illness severity, and a higher mortality rate than patients in subclasses B and C. Conclusions: Genome-wide expression profiling can identify pediatric septic shock subclasses having clinically relevant phenotypes.

Publication Title

Identification of pediatric septic shock subclasses based on genome-wide expression profiling.

Sample Metadata Fields

Age, Specimen part, Disease, Disease stage

View Samples
accession-icon GSE26378
Expression data from validation cohort of children with septic shock
  • organism-icon Homo sapiens
  • sample-icon 103 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Background: Septic shock heterogeneity has important implications for the conduct of clinical trials and individual patient management. We previously addressed this heterogeneity by indentifying 3 putative subclasses of children with septic shock based on a 100-gene expression signature corresponding to adaptive immunity and glucocorticoid receptor signaling. Herein we attempted to prospectively validate the existence of these gene expression-based subclasses in a validation cohort. Methods: Gene expression mosaics were generated from the 100 class-defining genes for 82 individual patients in the validation cohort. Patients were classified into 1 of 3 subclasses (A, B, or C) based on color and pattern similarity relative to reference mosaics generated from the original derivation cohort. Separate classifications were conducted by 21 individual clinicians and a computer-based algorithm. After subclassification the clinical database was mined for clinical phenotyping. Results: In the final consensus subclassification generated by clinicians, subclass A patients had a higher illness severity, as measured by illness severity scores and maximal organ failure, relative to subclasses B and C. The k coefficient across all possible inter-evaluator comparisons was 0.633. Similar observations were made based on the computer-generated subclassification. Patients in subclass A were also characterized by repression of a large number of genes having functional annotations related to zinc biology. Conclusions: We have validated the existence of subclasses of children with septic shock based on a biologically relevant, 100-gene expression signature. The subclasses can be indentified by clinicians without formal bioinformatics training, at a clinically relevant time point, and have clinically relevant phenotypic differences.

Publication Title

The influence of developmental age on the early transcriptomic response of children with septic shock.

Sample Metadata Fields

Age, Specimen part, Disease, Disease stage

View Samples
accession-icon GSE8121
Pediatric septic shock
  • organism-icon Homo sapiens
  • sample-icon 66 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

In an ongoing translational research program involving microarray-based expression profiles in pediatric septic shock, we have now conducted longitudinal studies focused on the temporal expression profiles of canonical signaling pathways and gene networks. Genome-level expression profiles were generated from whole blood-derived RNA samples of children with septic shock (n = 30 individual patients) corresponding to days 1 and 3 of admission to the pediatric intensive care unit. Based on sequential statistical and expression filters, day 1 and day 3 of septic shock were characterized by differential regulation of 2,142 and 2,504 gene probes, respectively, relative to normal control patients. Venn analysis demonstrated 239 unique genes in the day 1 data set, 598 unique genes in the day 3 data set, and 1,906 genes common to both data sets. Analyses targeted toward derivation of biological function from these data sets demonstrated time-dependent, differential regulation of genes involved in multiple canonical signaling pathways and gene networks primarily related to immunity and inflammation. Notably, multiple and distinct gene networks involving T cell- and MHC antigen-related biological processes were persistently downregulated from day 1 to day 3. Further analyses demonstrated large scale and persistent downregulation of genes corresponding to functional annotations related to zinc homeostasis. These data represent the largest reported cohort of patients with septic shock, which has undergone longitudinal genome-level expression profiling. The data further advance our genome-level understanding of pediatric septic shock and support novel hypotheses that can be readily tested at both the experimental and translational levels.

Publication Title

Genome-level longitudinal expression of signaling pathways and gene networks in pediatric septic shock.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE13904
Expression profiling across the pediatric systemic inflammatory response syndrome, sepsis, and septic shock spectrum
  • organism-icon Homo sapiens
  • sample-icon 191 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Normal children, children with SIRS, children with sepsis, and children with septic shock.

Publication Title

Genomic expression profiling across the pediatric systemic inflammatory response syndrome, sepsis, and septic shock spectrum.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE9692
Validation of Genome-wide Expression patterns in Pediatric Septic Shock
  • organism-icon Homo sapiens
  • sample-icon 16 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Rationale: We previously generated genome-wide expression data in children with septic shock, based on whole blood-derive RNA, having the potential to lead the field into novel areas of investigation.

Publication Title

Validating the genomic signature of pediatric septic shock.

Sample Metadata Fields

Sex

View Samples
accession-icon GSE4607
Systemic inflammatory response syndrome and septic shock
  • organism-icon Homo sapiens
  • sample-icon 55 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Goal of the experiment: To identify correlated genes, pathways and groups of patients with systemic inflammatory response syndrome and septic shock that is indicative of biologically important processes active in these patients.

Publication Title

Genome-level expression profiles in pediatric septic shock indicate a role for altered zinc homeostasis in poor outcome.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE44368
The human placental sexome differs between trophoblast epithelium and villous vessel endothelium
  • organism-icon Homo sapiens
  • sample-icon 29 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

As susceptibility to many adult disorders originates in utero, we here hypothesized that fetal sex influences gene expression in placental cells and produces functional differences in human placentas. We found that fetal sex differentially affects gene expression in a cell-phenotype dependent manner among all four placental cell-phenotypes studied: cytotrophoblasts, syncytiotrophoblasts, arterial endothelial cells and venous endothelial cells. The markedly enriched pathways in males were identified to be signaling pathways for graft-versus-host disease as well as the immune and inflammatory systems, both supporting the hypothesis that there is reduced maternal-fetal compatibility for male fetuses.

Publication Title

The human placental sexome differs between trophoblast epithelium and villous vessel endothelium.

Sample Metadata Fields

Sex, Specimen part

View Samples
accession-icon GSE59126
Different Preference of Degradome in Invasion versus Angiogenesis
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

We hypothesized altered expression of Proteases in calls capable of physiological invasion vs angiogenesis. We analyzed trophoblasts isolated from first trimester placenta that are invasive, and placental endothelial cells, that gave a high angiogenic potential. We found different expression levels of most proteases.

Publication Title

Different Preference of Degradome in Invasion versus Angiogenesis.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE69086
Pigment epithelium derived factor (PEDF): a novel trophoblast derived factor limiting feto-placental angiogenesis in late pregnancy
  • organism-icon Homo sapiens
  • sample-icon 3 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

We hypothesized that the trophoblast secretes anti-angiogenic factors, which increase in late pregnancy to limit angiogenesis. Therefore, we determined the paracrine effect of primary human trophoblasts from early versus late pregnancy on the angiogenic potential of isolated feto-placental endothelial cells.

Publication Title

Pigment epithelium-derived factor (PEDF): a novel trophoblast-derived factor limiting feto-placental angiogenesis in late pregnancy.

Sample Metadata Fields

Specimen part

View Samples

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

Powered by Alex's Lemonade Stand Foundation

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.

BSD 3-Clause LicensePrivacyTerms of UseContact