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accession-icon GSE13898
Robust prognostic biomarkers for EAC identified by systems-level characterization of tumor transcriptome
  • organism-icon Homo sapiens
  • sample-icon 118 Downloadable Samples
  • Technology Badge IconIllumina human-6 v2.0 expression beadchip

Description

Despite continual efforts to rationalize a prognostic stratification of patients with esophageal adenocarcinoma (EAC) before treatment, current staging system only shows limited success owing to the lack of molecular and genetic markers that reflect prognostic features of the tumor. To develop molecular predictors of prognosis, we used systems-level characterization of tumor transcriptome. Using DNA microarray, genome-wide gene expression profiling was performed on 75 biopsy samples from patients with untreated EAC. Various statistical and informatical methods were applied to gene expression data to identify potential biomarkers associated with prognosis. Potential marker genes were validated in an independent cohort using quantitiative RT-PCR to measure gene expression. Distinct subgroups of EAC were uncovered by systems-level characterization of tumor transcriptome. We also identified a six-gene expression signature that could be used to predict overall survival (OS) of EAC patients. In particular, expression of SPARC and SPP1 was a strong independent predictor of OS, and a combined gene expression signature with these two genes was associated with prognosis (P < 0.024), even when all relevant pathological variables were considered together in multivariate Cox hazard regression analysis. Our findings suggest that molecular features reflected in gene expression signatures may dictate the prognosis of EAC patients, and these gene expression signatures can be used to predict the likelihood of prognosis at the time of diagnosis and before treatment.

Publication Title

Prognostic biomarkers for esophageal adenocarcinoma identified by analysis of tumor transcriptome.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP075478
Targeting Taxane-Platin Resistant Lung Cancers with JumonjiC Lysine Demethylase Inhibitors (RNA-Seq)
  • organism-icon Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Characterization of gene expression changes upon development of taxane-platin drug resistance in NSCLC cells and further, upon treatment of these resistant cells with the Jumonji KDM inhibitor, GSK-J4. Overall design: Comparison of gene expression changes between H1299 Parental cells (chemo-sensitive) and H1299 T18 cells (taxane-platin resistant), and comparison of H1299 T18: GSK-J4 treated vs. H1299 T18: DMSO control.

Publication Title

Taxane-Platin-Resistant Lung Cancers Co-develop Hypersensitivity to JumonjiC Demethylase Inhibitors.

Sample Metadata Fields

Sex, Age, Treatment, Race, Subject

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accession-icon GSE57660
Novel strategies to enforce an epithelial phenotype in mesenchymal cells
  • organism-icon Homo sapiens
  • sample-icon 3 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

E-cadherin downregulation in cancer cells is associated with epithelial-to-mesenchymal transition (EMT) and metastatic prowess, but the underlying mechanisms are incompletely characterized. In this study, we probed E-cadherin expression at the plasma membrane as a functional assay to identify genes involved in E-cadherin downregulation. The assay was based on the E-cadherin-dependent invasion properties of the intracellular pathogen Listeria monocytogenes. On the basis of a functional readout, automated microscopy and computer-assisted image analysis were used to screen siRNAs targeting 7,000 human genes. The validity of the screen was supported by its definion of several known regulators of E-cadherin expression, including ZEB1, HDAC1 and MMP14. We identified three new regulators (FLASH, CASP7 and PCGF1), the silencing of which was sufficient to restore high levels of E-cadherin transcription. Additionally, we identified two new regulators (FBXL5 and CAV2), the silencing of which

Publication Title

Novel strategies to enforce an epithelial phenotype in mesenchymal cells.

Sample Metadata Fields

Age, Specimen part, Cell line, Treatment

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accession-icon GSE16058
Distinctions between the stasis and telomere attrition senescence barriers in cultured human mammary epithelial cells
  • organism-icon Homo sapiens
  • sample-icon 48 Downloadable Samples
  • Technology Badge Icon Affymetrix HT Human Genome U133A Array (hthgu133a)

Description

Molecular distinctions between the stasis and telomere attrition senescence barriers in cultured human mammary epithelial cells

Publication Title

Molecular distinctions between stasis and telomere attrition senescence barriers shown by long-term culture of normal human mammary epithelial cells.

Sample Metadata Fields

Specimen part, Subject

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accession-icon SRP185826
Next Generation Sequencing of langerhans islets of miR-17-92/106b KO vs control
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

NGS was used in order to discover novel downstream targets of the miR-17-92/106b clusters. Overall design: Comperasion of gene expression from miR-17-92/106b KO and control

Publication Title

miR-17-92 and miR-106b-25 clusters regulate beta cell mitotic checkpoint and insulin secretion in mice.

Sample Metadata Fields

Specimen part, Cell line, Subject

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accession-icon GSE39966
Expression data from replicating and quiescent liver cells isolated from mice young liver
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

We have developed a new transgenic mouse strain, expressing a CyclinB1-GFP fusion reporter, which marks replicating cells in the S/G2/M phases of the cell cycle to isolate live replicating and quiescent cells from the liver.

Publication Title

A transgenic mouse marking live replicating cells reveals in vivo transcriptional program of proliferation.

Sample Metadata Fields

Age, Specimen part

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accession-icon GSE35570
Gene signature of the post-Chernobyl papillary thyroid cancer
  • organism-icon Homo sapiens
  • sample-icon 116 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Thyroid gland is among the most sensitive organs to ionizing radiation. Whether low-dose radiation-induced papillary thyroid cancer (PTC) differs from sporadic PTC is yet unknown.

Publication Title

Gene signature of the post-Chernobyl papillary thyroid cancer.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE37138
Exon array analysis of the response to bevacizumab/erlotinib in advanced non-small cell lung cancer
  • organism-icon Homo sapiens
  • sample-icon 116 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [probe set (exon) version (huex10st)

Description

In the current study, we used exon arrays and clinical samples from a previous trial (SAKK 19/05) to investigate the expression variations at the exon-level of 3 genes potentially playing a key role in modulating treatment response (EGFR, KRAS, VEGFA).

Publication Title

EGFR exon-level biomarkers of the response to bevacizumab/erlotinib in non-small cell lung cancer.

Sample Metadata Fields

Sex, Specimen part, Disease, Disease stage, Treatment

View Samples
accession-icon SRP198959
Small extracellular vesicles are key regulators of non-cell autonomous intercellular communication in senescence via the interferon protein, IFITM3
  • organism-icon Homo sapiens
  • sample-icon 45 Downloadable Samples
  • Technology Badge IconNextSeq 500

Description

Senescence is a cellular phenotype present in health and disease, characterized by a stable cell cycle arrest and an inflammatory response, denominated senescence-associated secretory phenotype (SASP). The SASP is important in influencing the behaviour of neighbouring cells and altering the microenvironment; yet, this role has been mainly attributed to soluble factors. Here, we show that both the soluble factors in addition to small extracellular vesicles (sEV) are capable of transmitting paracrine senescence to nearby cells. Analysis of individual cells internalizing sEV, using a Cre-reporter system, show a positive correlation between sEV uptake and senescence activation. Interestingly, we find an increase in the number of multivesicular bodies during senescence in vivo. sEV protein characterization by mass spectrometry (MS) followed by a functional siRNA screen identify the Interferon Induced Transmembrane Protein 3 (IFITM3) as partially responsible for transmitting senescence to normal cells. Altogether, we found that sEV contribute to paracrine senescence. Overall design: SASP related mRNA transcripts in HFFF2 treated with sEV from iRAS cells in comparison with HFFF2 treated with sEV from iC cells

Publication Title

Small Extracellular Vesicles Are Key Regulators of Non-cell Autonomous Intercellular Communication in Senescence via the Interferon Protein IFITM3.

Sample Metadata Fields

Disease, Subject

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accession-icon SRP068596
RNA profiling of p16ink4a-expressing pancreatic beta-cells
  • organism-icon Mus musculus
  • sample-icon 5 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Transcriptome of beta-cells isolated from mice expressing p16ink4a and GFP transgenes and of control ß-cells isolated from mice expressing only the GFP transgene Overall design: RNAseq of murine beta-cells sorted based on GFP expression from three Ins-rtTA/tet-GFP/tet-p16ink4a mice and two control Ins-rtTA/tet-GFP mice following 10 days tet-mediated induction.

Publication Title

p16(Ink4a)-induced senescence of pancreatic beta cells enhances insulin secretion.

Sample Metadata Fields

Specimen part, Subject

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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)

fund-icon Fund the CCDL

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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