refine.bio
  • Search
      • Normalized Compendia
      • RNA-seq Sample Compendia
  • Docs
  • About
  • My Dataset
github link
Showing
of 107 results
Sort by

Filters

Technology

Platform

accession-icon GSE26928
Human peripheral blood CD4+ T cell subsets
  • organism-icon Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Cells were isolated from healthy human donors (n=2). Unstimulated cells. Cells were stained with CD4, CD45RA, CCR7 and CXCR7. Using flow cytometry, 4 CD4+ T cell populations were sorted: (1) Nave (CD45RA+CCR7+CXCR5-), (2) Central memory (CD45RA-CCR7+CXCR5-), (3) Effector memory (CD45RA-CCR7-CXCR5-) and (4) CXCR5+ cells (CD45RA-CCR7-CXCR5+)

Publication Title

CXCR5 expressing human central memory CD4 T cells and their relevance for humoral immune responses.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE19330
Expression data from Epiderm cultured skin derived from four different donors
  • organism-icon Homo sapiens
  • sample-icon 17 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

This study provides a comparison of genes expressed in reconstructed cultured epidermis derived from four different donors.

Publication Title

Xenobiotic metabolism gene expression in the EpiDermin vitro 3D human epidermis model compared to human skin.

Sample Metadata Fields

Sex, Specimen part

View Samples
accession-icon GSE6566
Strength of T cell stimulation
  • organism-icon Homo sapiens
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The strength of T cell stimulation determines IL-7 responsiveness, recall potential and lineage commitment of primed human CD4+IL-7Rhi T cells

Publication Title

The strength of T cell stimulation determines IL-7 responsiveness, secondary expansion, and lineage commitment of primed human CD4+IL-7Rhi T cells.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE73066
Transcriptional profiles of pilocytic astrocytoma
  • organism-icon Homo sapiens
  • sample-icon 35 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Pilocytic astrocytoma is the most common type of brain tumor in pediatric population, generally connected with favorable prognosis, although recurrences or dissemination sometimes are also observed. For tumors originating in supra- or infratentorial location different molecular background was suggested but plausible correlations between transcriptional profile and radiological features and/or clinical course are still undefined. The purpose of this study was to identify gene expression profiles related to the most frequent locations of this tumor, subtypes based on various radiological features and clinical pattern of the disease. According to the radiological features presented on MRI, all cases were divided into four subtypes: solid or mainly solid, cystic with an enhancing cyst wall, cystic with a non-enhancing cyst wall and solid with central necrosis. Bioinformatic analyses showed that gene expression profile of pilocytic astrocytoma highly depends on the tumor location. Most prominent differences were noted for IRX2, PAX3, CXCL14, LHX2, SIX6, CNTN1 and SIX1 genes expression which could distinguish pilocytic astrocytomas of different location even within supratentorial region. Analysis of the genes potentially associated between radiological features showed much weaker transcriptome differences. Single genes showed association with the tendency to progression. Here we showed that pilocytic astrocytomas of three different locations could be precisely differentiated on the basis of gene expression level but their transcriptional profiles did not strongly reflect the radiological appearance of the tumor or the course of the disease.

Publication Title

Transcriptional profiles of pilocytic astrocytoma are related to their three different locations, but not to radiological tumor features.

Sample Metadata Fields

Sex, Age, Specimen part, Disease

View Samples
accession-icon GSE16176
Expression profiles of amniotic fluid from human fetuses with Down syndrome and euploid controls
  • organism-icon Homo sapiens
  • sample-icon 13 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

In order to characterize the differences between second trimester Down syndrome (DS) and euploid fetuses, we compared gene expression in uncultured amniotic fluid supernatant samples. We identified individually differentially expressed genes via paired t-tests in the matched samples, and a set of differentially expressed genes on chromosome 21 using Gene Set Enrichment Analysis. Functional pathway analysis of the resulting genes highlighted the importance of oxidative stress, ion transport, and G-protein signaling in the DS fetuses.

Publication Title

Functional genomic analysis of amniotic fluid cell-free mRNA suggests that oxidative stress is significant in Down syndrome fetuses.

Sample Metadata Fields

Sex, Specimen part

View Samples
accession-icon GSE50567
BRCA1-related gene signature in breast cancer: the role of ER status and molecular type
  • organism-icon Homo sapiens
  • sample-icon 41 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

We have analyzed, using DNA microarrays, putative differences in gene-expression level between hereditary BRCA1 mutation-linked and sporadic breast cancer. Our results show that a previously reported marked difference between BRCA1-mutation linked and sporadic breast cancer was probably due to uneven stratification of samples with different ER status and basal-like versus luminal-like subtype. We observed that apparent difference between BRCA1-linked and other types of breast cancer found in univariate analysis was diminished when data were corrected for ER status and molecular subtype in multivariate analyses. In fact, the difference in gene expression pattern of BRCA1-mutated and sporadic cancer is very discrete. These conclusions were supported by the results of Q-PCR validation. We also found that BRCA1 gene inactivation due to promoter hypermethylation had similar effect on general gene expression profile as mutation-induced protein truncation. This suggests that in the molecular studies of hereditary breast cancer, BRCA1 gene methylation should be recognized and considered together with gene mutation.

Publication Title

BRCA1-related gene signature in breast cancer: the role of ER status and molecular type.

Sample Metadata Fields

Age

View Samples
accession-icon GSE13909
Molecular signature of cell cycle exit induced in human T lymphoblasts by IL-2 withdrawal
  • organism-icon Homo sapiens
  • sample-icon 17 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Molecular mechanisms of cell cycle exit are poorly understood. A group of genes required for cell cycle exit and maintenance of cell quiescence in human fibroblasts following serum deprivation has been recently identified. Studies on lymphocytes following growth factor deprivation-induced cell cycle exit have predominantly focused on the initiation of apoptosis. A set of genes involved in lymphocyte quiescence have also been identified among genes highly expressed in resting lymphocytes and down-regulated after cell activation. In our study, proliferating IL-2-dependent human T cells were forced to exit cell cycle by growth factor withdrawal, and their gene expression profiles were examined.

Publication Title

Molecular signature of cell cycle exit induced in human T lymphoblasts by IL-2 withdrawal.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE53669
Fetal transcripts in maternal blood
  • organism-icon Homo sapiens
  • sample-icon 43 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

The discovery of fetal mRNA transcripts in maternal circulation holds great promise for noninvasive prenatal diagnosis. To identify potential fetal biomarkers, we studied whole blood and plasma transcripts common to term pregnant women and their newborns but reduced or absent in the postpartum mothers.

Publication Title

Gene expression analysis in pregnant women and their infants identifies unique fetal biomarkers that circulate in maternal blood.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE63885
Gene expression profiling in ovarian cancer
  • organism-icon Homo sapiens
  • sample-icon 99 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The introduction of microarray techniques to cancer research brought great expectations for finding biomarkers that would improve patients treatment; however, the results of such studies are poorly reproducible and critical analyses of these methods are rare. In this study, we examined global gene expression in 97 ovarian cancer samples. Also, validation of results by quantitative RT-PCR was performed on 30 additional ovarian cancer samples. We carried out a number of systematic analyses in relation to several defined clinicopathological features. The main goal of our study was to delineate the molecular background of ovarian cancer chemoresistance and find biomarkers suitable for prediction of patients prognosis. We found that histological tumor type was the major source of variability in genes expression, except for serous and undifferentiated tumors that showed nearly identical profiles. Analysis of clinical endpoints [tumor response to chemotherapy, overall survival, disease-free survival (DFS)] brought results that were not confirmed by validation either on the same group or on the independent group of patients. CLASP1 was the only gene that was found to be important for DFS in the independent group, whereas in the preceding experiments it showed associations with other clinical endpoints and with BRCA1 gene mutation; thus, it may be worthy of further testing. Our results confirm that histological tumor type may be a strong confounding factor and we conclude that gene expression studies of ovarian carcinomas should be performed on histologically homogeneous groups. Among the reasons of poor reproducibility of statistical results may be the fact that despite relatively large patients group, in some analyses one has to compare small and unequal classes of samples. In addition, arbitrarily performed division of samples into classes compared may not always reflect their true biological diversity. And finally, we think that clinical endpoints of the tumor probably depend on subtle changes in many and, possibly, alternative molecular pathways, and such changes may be difficult to demonstrate.

Publication Title

Gene expression analysis in ovarian cancer - faults and hints from DNA microarray study.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE35459
Transcriptome profiles of mouse and human monocyte and dendritic cell subsets
  • organism-icon Mus musculus, Homo sapiens
  • sample-icon 36 Downloadable Samples
  • Technology Badge IconIllumina MouseWG-6 v2.0 expression beadchip, Illumina HumanHT-12 V4.0 expression beadchip

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Human tissues contain CD141hi cross-presenting dendritic cells with functional homology to mouse CD103+ nonlymphoid dendritic cells.

Sample Metadata Fields

Sex, Specimen part, Disease, Disease stage

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