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accession-icon E-TABM-450
Transcription profiling by array of human lung cancer cells after treatment with various inhibitors of LIMK1 and LIMK2
  • organism-icon Homo sapiens
  • sample-icon 45 Downloadable Samples
  • Technology Badge Icon Affymetrix HT Human Genome U133A Array (hthgu133a), Affymetrix Human Genome U133A 2.0 Array (hgu133a2)

Description

To investigate an unknown mechanism of cytotoxicity, A549 human lung-cancer cells were treated with compounds from a series of inhibitors developed against the human LIM kinases LIMK1 and LIMK2. Compounds 1 and 2 inhibit LIM kinase activity in vitro and affect cell proliferation and survival in vivo. Compounds 3 and 4 inhibit LIM kinases but do not affect cell survival or proliferation. Compounds 5 and 6 affect proliferation and survival but do not inhibit LIM kinases. Nocodazole was included as a comparator because the compounds were known to affect microtubule stability. A treatment of 7 hours was used to examine events prior to apoptosis, while the dose levels captured both cytotoxicity and inhibition of LIMKs (Compounds 1 and 2), LIMK inhibition alone ( Compounds 3 and 4) or cytotoxicity alone (Compounds 5, 6, and Nocodazole).

Publication Title

Identification of a nonkinase target mediating cytotoxicity of novel kinase inhibitors.

Sample Metadata Fields

Cell line, Subject, Compound

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accession-icon GSE40422
Gene expression profiling of enforced HOXA1 expression in melanoma cell line (SkMel30)
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

We recently reported an oncogenomics-guided screening approach designed to identify genetic drivers of early stage melanoma metastasis, and in this study we functionally validate the top-scoring candidate, homeobox transcription factor A1 (HOXA1), by demonstrating HOXA1s robust effects on melanoma cell invasion, metastasis and tumorigenicity. Transcriptome and pathway profiling analyses of cells expressing HOXA1 reveal up-regulation of factors involved in diverse cytokine pathways that include the TGF signaling axis, which we further demonstrate to be required for HOXA1-mediated cell invasion. Transcriptome profiling also informed HOXA1s ability to potently down-regulate expression of microphthalmia-associated transcription factor (MITF) and other genes required for melanocyte differentiation, suggesting a mechanism by which HOXA1 expression de-differentiates cells into a pro-invasive precursor cell state concomitant with TGF activation. Our analysis of publicly available datasets indicate that the HOXA1-induced gene signature successfully categorizes melanoma specimens based on their metastatic potential and, importantly, is capable of stratifying melanoma patient risk for metastasis based on expression in primary tumors.

Publication Title

HOXA1 drives melanoma tumor growth and metastasis and elicits an invasion gene expression signature that prognosticates clinical outcome.

Sample Metadata Fields

Cell line

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accession-icon GSE37136
Gene expression profiling of enforced HOXA1 expression in melanoma cell line
  • organism-icon Homo sapiens
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

We recently reported an oncogenomics-guided screening approach designed to identify genetic drivers of early stage melanoma metastasis, and in this study we functionally validate the top-scoring candidate, homeobox transcription factor A1 (HOXA1), by demonstrating HOXA1s robust effects on melanoma cell invasion, metastasis and tumorigenicity. Transcriptome and pathway profiling analyses of cells expressing HOXA1 reveal up-regulation of factors involved in diverse cytokine pathways that include the TGF signaling axis, which we further demonstrate to be required for HOXA1-mediated cell invasion. Transcriptome profiling also informed HOXA1s ability to potently down-regulate expression of microphthalmia-associated transcription factor (MITF) and other genes required for melanocyte differentiation, suggesting a mechanism by which HOXA1 expression de-differentiates cells into a pro-invasive precursor cell state concomitant with TGF activation. Our analysis of publicly available datasets indicate that the HOXA1-induced gene signature successfully categorizes melanoma specimens based on their metastatic potential and, importantly, is capable of stratifying melanoma patient risk for metastasis based on expression in primary tumors.

Publication Title

HOXA1 drives melanoma tumor growth and metastasis and elicits an invasion gene expression signature that prognosticates clinical outcome.

Sample Metadata Fields

Cell line

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accession-icon GSE61562
Murine Norovirus Effect on Cells
  • organism-icon Mus musculus
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Changes in gene expression on MNV infection of RAW264.7 cells

Publication Title

Murine norovirus replication induces G0/G1 cell cycle arrest in asynchronously growing cells.

Sample Metadata Fields

Cell line

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accession-icon GSE35428
Transcriptional profiling of clinically relevant SERMs and SERM/estradiol complexes in a cellular model of breast cancer
  • organism-icon Homo sapiens
  • sample-icon 106 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

In this study, we have utilized microarray analysis to directly compare a subset of structurally distinct, clinically relevant SERMs in the presence and absence of estradiol, using a high replicate number (10) to ensure detection of modestly regulated genes.

Publication Title

Research resource: Transcriptional profiling in a cellular model of breast cancer reveals functional and mechanistic differences between clinically relevant SERM and between SERM/estrogen complexes.

Sample Metadata Fields

Cell line

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accession-icon GSE47346
Identification of differentially expressed genes due to LBH589 treatment in aromatase inhibitor-resistant tumors
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

In order to validate the utility of a novel pathway algorithm (BD-Func), we test if an LBH589 signature based data from 3 cell lines (GSE36509) in an independent experiment in vivo.

Publication Title

BD-Func: a streamlined algorithm for predicting activation and inhibition of pathways.

Sample Metadata Fields

Specimen part, Treatment

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accession-icon GSE38053
Host Response Signature to Staphylococcus aureus alpha-Hemolysin
  • organism-icon Mus musculus
  • sample-icon 18 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Staphylococcus aureus pneumonia causes significant morbidity and mortality. Alpha-hemolysin (Hla), a pore-forming cytotoxin of S. aureus, has been identified through animal models of pneumonia as a critical virulence factor that induces lung injury. In spite of considerable molecular knowledge of how this cytotoxin injures the host, the precise host response to Hla in the context of infection remains poorly understood. We employed whole-genome expression profiling of infected lung to define the host response to wild-type S. aureus compared with an Hla-deficient isogenic mutant in experimental pneumonia. These data provide a complete expression profile at four and at twenty-four hours post-infection, revealing a unique response to the toxin-expressing strain. Gene ontogeny analysis revealed significant differences in the extracellular matrix and cardiomyopathy pathways, both of which govern cellular interactions in the tissue microenvironment. Evaluation of individual transcript responses to Hla-secreting bacteria was notable for upregulation of host cytokine and chemokine genes, including the p19 subunit of interleukin-23. Consistent with this observation, the cellular immune response to infection was characterized by a prominent TH17 response to wild-type staphylococci. These findings define specific host mRNA responses to Hla-producing S. aureus, coupling the pulmonary TH17 response to the presence of this cytotoxin. Expression profiling to define the host response to a single virulence factor proved to be a valuable tool in identifying pathways for further investigation in S. aureus pneumonia. This approach may be broadly applicable to the study of bacterial toxins, defining host pathways that can be targeted to mitigate toxin-induced disease.

Publication Title

Host response signature to Staphylococcus aureus alpha-hemolysin implicates pulmonary Th17 response.

Sample Metadata Fields

Sex, Specimen part

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accession-icon GSE42310
COHCAP: City of Hope CpG Island Analysis Pipeline
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

COHCAP (City of Hope CpG Island Analysis Pipeline) is an algorithm to analyze single-nucleotide resolution DNA methylation data. It provides QC metrics, differential methylation for CpG Sites, differential methylation for CpG Islands, integration with gene expression data, and visualization of methylation values. COHCAP is currently the only DNA methylation package that can handle integration with gene expression data, and the results of this study show that COHCAP can identify regions of differential methylation with ~50% concordance with gene expression. COHCAP is scalable for analysis of both cell line data and heterogeneous patient data, and it can identify known cancer biomarkers as well as intriguing new roles of epigenetic regulation in cancer (such as methylation of estrogen receptor in breast cancer patients). This study also uses cell line data to show that COHCAP is capable of analyzing Illumina methylation array and targeted bisulfite sequencing data, with either 1-group or 2-group study designs. The accuracy of COHCAP is accessed using qPCR, EpiTect, and comparison of COHCAP regions of differential methylation with MIRA peaks. This software is freely available at https://sourceforge.net/projects/cohcap/.

Publication Title

COHCAP: an integrative genomic pipeline for single-nucleotide resolution DNA methylation analysis.

Sample Metadata Fields

Disease, Cell line

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accession-icon GSE42307
COHCAP HCT116 Mutant Comparison [expression]
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Genome-wide expression and methylation differences are compared for a normal HCT116 cell line and a derived mutant with altered DNA methylation patterns.

Publication Title

COHCAP: an integrative genomic pipeline for single-nucleotide resolution DNA methylation analysis.

Sample Metadata Fields

Cell line

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accession-icon GSE40904
Gene expression analysis for Il13Ra2-positive and IL13Ra2-negative glioma cell lines
  • organism-icon Homo sapiens
  • sample-icon 26 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Affymetrix expression profiling was used to evaluate the association between IL13R2 expression, and mesenchymal, proneural, classical and neural signature genes expression for glioma subclasses defined by Verhaak et al (Cancer Cell; 2010).

Publication Title

Glioma IL13Rα2 is associated with mesenchymal signature gene expression and poor patient prognosis.

Sample Metadata Fields

Cell line, Treatment

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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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