refine.bio
  • Search
      • Normalized Compendia
      • RNA-seq Sample Compendia
  • Docs
  • About
  • My Dataset
    0
github link
Build and Download Custom Datasets
refine.bio helps you build ready-to-use datasets with normalized transcriptome data from all of the world’s genetic databases.
Showing
of 16 results
Sort by

Filters

Technology

Platform

accession-icon GSE53124
Migration and invasion of 5 glioblastoma cell lines
  • organism-icon Homo sapiens
  • sample-icon 5 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U219 Array (hgu219)

Description

Glioblastoma cells are characterized by a highly invasive behavior whose mechanisms are not yet understood. Using the wound healing and Boyden chamber assays we compared in the present study the migration and invasion abilities of 5 glioblastoma cell lines (DK-MG, GaMG, U87-MG, U373-MG, SNB19) differing in p53 and PTEN status. We also analyzed by Western blotting the expression of PTEN, p53, mTOR and several other marker proteins involved in cell adhesion, migration and invasion. Among 5 cell lines, GaMG cells exhibited the fastest rate of wound closure, whereas U87-MG cells showed the most rapid chemotactic migration in the Boyden chamber assay. In DK-MG and GaMG cells, F-actin mainly occurred in the numerous stress fibers spanning the cytoplasm, whereas U87-MG, U373-MG and SNB19 cells preferentially expressed F-actin in filopodia and lamellipodia. Moreover, the two glioblastoma lines mutated in both p53 and PTEN genes (U373-MG and SNB19) were found to exhibit the fastest invasion rates through the Matrigel matrix.

Publication Title

Actin cytoskeleton organization, cell surface modification and invasion rate of 5 glioblastoma cell lines differing in PTEN and p53 status.

Sample Metadata Fields

Specimen part, Cell line

View Samples
accession-icon SRP074349
Next Generation Sequencing (RNAseq) of non-small cell lung cancer
  • organism-icon Homo sapiens
  • sample-icon 171 Downloadable Samples
  • Technology Badge Icon

Description

Cancer testis antigens (CTAs) are of clinical interest as biomarkers and present valuable targets for immunotherapy. To comprehensively characterize the CTA landscape of non-small cell lung cancer (NSCLC), we compared RNAseq data of 199 NSCLC tissues to the normal transcriptome of 142 samples from 32 different normal organs. Of 232 CTAs currently annotated in the CTdatabase, 96 were confirmed in NSCLC. To obtain an unbiased CTA profile of NSCLC, we applied stringent criteria on our RNAseq data set and defined 90 genes as CTAs, of which 55 genes were not annotated in the CTdatabase. Cluster  analysis revealed that CTA expression is histology-dependent and concurrent expression is common. Immunohistochemistry confirmed tissue specific protein expression of selected genes. Furthermore, methylation was identified as a regulatory mechanism of CTA expression based on independent data from the Cancer Genome Atlas. The proposed prognostic impact of CTAs in lung cancer, was not confirmed, neither in our RNAseq-cohort nor in an independent meta-analysis of 1117 NSCLC cases. Overall design: Fresh frozen tumor tissue from 199 patients diagnosed with NSCLC and surgically treated 2006-2010 at the Uppsala University Hospital, Uppsala, Sweden and 19 paired normal lung tissues. Clinical data were retrieved from the regional lung cancer registry. Several of the new CTAs are poorly characterized Sample characteristics values represent; pTNM: decided by Hans Brunnström, pathologist in Lund Spring 2013 Stage according to pTNM: 1=1a 2=1b 3=2a 4=2b 5=3a 6=3b 7=IV Histology diagnosis spring 2013 HB: 1=squamous cell cancer 2=AC unspecified 3=Large cell/ NOS Surgery date: the date when sample arrived at Patologen UAS Age: age when surgery was performed Vital date: day of death or latest contact Dead: 0=no 1= yes Smoking history : 1=current 2=ex >1year 3=never WHO performance status: Performance status 0-4 Please note that the L608T_2122, L771T_1 data columns (in the processed data files) are associated with L608T and L771T samples, respectively.

Publication Title

Multispectral imaging for quantitative and compartment-specific immune infiltrates reveals distinct immune profiles that classify lung cancer patients.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE47478
Transcriptional responses of wild-type and Gcn2-/- Th17 cells to halofuginone and rapamycin
  • organism-icon Mus musculus
  • sample-icon 36 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

This study was designed to evaluate similarities and differences between transcriptional responses of developing Th17 cells to the prolyl-tRNA synthetase inhibitor, halofuginone, and the mTOR inhibitor, rapamycin. Further comparisons between wild-type and Gcn2-/- Th17 cells allow for investigation into which gene modules regulated by halofuginone or rapamycin treatment require Gcn2.

Publication Title

Halofuginone-induced amino acid starvation regulates Stat3-dependent Th17 effector function and reduces established autoimmune inflammation.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE34053
CD133+ colon cancer cells are more interactive with the tumor microenvironment than CD133- cells
  • organism-icon Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

CD133-positive colorectal cancer cells exhibit enhanced tumorigenicity over CD133-negative cells. The CD133+ cells are more interactive with and responsive to their stromal microenvironment because they also express the cognate receptors, such as CXCR4, for ligands produced by their neighboring carcinoma-associated fibroblasts, such as SDF-1 (stromal-derived growth factor).

Publication Title

CD133+ colon cancer cells are more interactive with the tumor microenvironment than CD133- cells.

Sample Metadata Fields

Specimen part, Disease, Disease stage

View Samples
accession-icon SRP095533
Transcriptomic, Proteomic, and Metabolomic Landscape of Positional Memory in the Caudal Fin of Zebrafish
  • organism-icon Danio rerio
  • sample-icon 30 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2000

Description

Regeneration requires cells to regulate proliferation and patterning according to their spatial position. Positional memory is a property that enables regenerating cells to recall spatial information from the uninjured tissue. Positional memory is hypothesized to rely on gradients of molecules, few of which have been identified. Here, we quantified the global abundance of transcripts, proteins and metabolites along the proximodistal axis of caudal fins of uninjured and regenerating adult zebrafish. Using this approach, we uncovered complex overlapping expression patterns for hundreds of molecules involved in diverse cellular functions, including developmental and bioelectric signaling as well as amino acid and lipid metabolism. Moreover, 32 genes differentially expressed at the RNA level had concomitant differential expression of the encoded proteins. Thus, the identification of proximodistal differences in levels of RNAs, proteins, and metabolites will facilitate future functional studies of positional memory during appendage regeneration. Overall design: RNA-seq was performed on 5 biological replicates for each of 3 positions along the proximodistal axis of the caudal fin; proximal, middle and distal (15 total samples). Each biological replicate was a pool of fin regions cut from 2 male and 2 female zebrafish.

Publication Title

Transcriptomic, proteomic, and metabolomic landscape of positional memory in the caudal fin of zebrafish.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE21595
Comparisons between fully and partially reprogrammed iPS cells induced by pMX-Klf4, pMX-Oct4 and pMX-Sox2 retroviruses
  • organism-icon Mus musculus
  • sample-icon 18 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

Induced pluripotent stem (iPS) cell reprogramming is a gradual epigenetic process that reactivates the pluripotent transcriptional network by erasing and establishing heterochromatin marks. Here, we characterize the physical structure of heterochromatin domains in full and partial mouse iPS cells by correlative Electron Spectroscopic Imaging (ESI). In somatic and partial iPS cells, constitutive heterochromatin marked by H3K9me3 is highly compartmentalized into chromocenter structures of densely packed 10 nm chromatin fibers. In contrast, chromocenter boundaries are poorly defined in pluripotent ES and full iPS cells, and are characterized by unusually dispersed 10 nm heterochromatin fibers in high Nanog-expressing cells, including pluripotent cells of the mouse blastocyst prior to differentiation. This heterochromatin reorganization accompanies retroviral silencing during conversion of partial iPS cells by Mek/Gsk3 2i inhibitor treatment. Thus, constitutive heterochromatin reorganization serves as a novel biomarker with retroviral silencing for identifying iPS cells in the very late stages of reprogramming.

Publication Title

Constitutive heterochromatin reorganization during somatic cell reprogramming.

Sample Metadata Fields

Specimen part, Cell line

View Samples
accession-icon GSE49703
Transcriptional profiles of CCR7lo effector memory human T cell subsets
  • organism-icon Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

The aim of this study was to identify differentially-expressed genes in CCR4hi/CXCR3- and CCR4lo CXCR3+ CCR6+ human Th17 cell subsets

Publication Title

Pro-inflammatory human Th17 cells selectively express P-glycoprotein and are refractory to glucocorticoids.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE49702
Expression profiling of MDR1+ and MDR1- human memory T cells from the blood and clinically-inflamed gut tissue
  • organism-icon Homo sapiens
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

The aim of this study was to characterize the transcriptional signature of MDR1+ human memory T cells isolated from clinically inflamed gut tissue, and compare it to local MDR1- memory T cells

Publication Title

Pro-inflammatory human Th17 cells selectively express P-glycoprotein and are refractory to glucocorticoids.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE89809
Multi-tissue transcriptomics delineates the diversity of airway T cells functions in asthma
  • organism-icon Homo sapiens
  • sample-icon 145 Downloadable Samples
  • Technology Badge Icon Affymetrix HT HG-U133+ PM Array Plate (hthgu133pluspm)

Description

Asthma arises from the complex interplay of inflammatory pathways in diverse cell types and tissues including epithelial and T cells.

Publication Title

Multitissue Transcriptomics Delineates the Diversity of Airway T Cell Functions in Asthma.

Sample Metadata Fields

Sex, Subject

View Samples
accession-icon GSE114669
OnPLS-based multi-block data integration: a multivariate approach to interrogating biological interactions in asthma
  • organism-icon Homo sapiens
  • sample-icon 22 Downloadable Samples
  • Technology Badge Icon Affymetrix HT HG-U133+ PM Array Plate (hthgu133pluspm)

Description

Integration of multi-omics data remains a key challenge in fulfilling the potential of comprehensive systems biology.

Publication Title

OnPLS-Based Multi-Block Data Integration: A Multivariate Approach to Interrogating Biological Interactions in Asthma.

Sample Metadata Fields

Sex, Age, 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