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accession-icon GSE28582
Gene Copy Number Aberrations are Associated with Survival in Histological Subgroups of Non-Small Cell Lung Cancer
  • organism-icon Homo sapiens
  • sample-icon 100 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Gene copy number aberrations are associated with survival in histologic subgroups of non-small cell lung cancer.

Sample Metadata Fields

Specimen part

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accession-icon GSE28571
Gene Copy Number Aberrations are Associated with Survival in Histological Subgroups of Non-Small Cell Lung Cancer (expression data)
  • organism-icon Homo sapiens
  • sample-icon 100 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Hypothesis: Non-small cell lung cancer (NSCLC) is characterized by a multitude of genetic aberrations with unknown clinical impact. In this study, we aimed to identify gene copy number changes that correlate with clinical outcome in NSCLC. To maximize the chance to identify clinically relevant events, we applied a strategy involving two prognostically extreme patient groups.

Publication Title

Gene copy number aberrations are associated with survival in histologic subgroups of non-small cell lung cancer.

Sample Metadata Fields

Specimen part

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accession-icon GSE37745
Biomarker discovery in non-small cell lung cancer: integrating gene expression profiling, meta-analysis and tissue microarray validation
  • organism-icon Homo sapiens
  • sample-icon 195 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Background: Global gene expression profiling has been widely used in lung cancer research to identify clinically relevant molecular subtypes as well as to predict prognosis and therapy response. So far, the value of these multi-gene signatures in clinical practice is unclear and the biological importance of individual genes is difficult to assess as the published signatures virtually do not overlap.

Publication Title

Biomarker discovery in non-small cell lung cancer: integrating gene expression profiling, meta-analysis, and tissue microarray validation.

Sample Metadata Fields

Sex, Age

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accession-icon GSE33363
CD99 is a novel prognostic stromal marker in non-small cell lung cancer
  • organism-icon Homo sapiens
  • sample-icon 10 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The delicate interaction between cancer cells and the surrounding stroma plays an essential role in all stages of tumourigenesis. Despite the significance of this interplay, alterations in protein composition underlying tumour-stroma interactions are largely unknown. The aim of this study was to identify stromal proteins with clinical relevance in non-small cell lung cancer.

Publication Title

CD99 is a novel prognostic stromal marker in non-small cell lung cancer.

Sample Metadata Fields

Specimen part, Subject

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accession-icon GSE58749
Human proliferating and differentiating keratinocytes treated with retinoic acid or 3,4-didehydroretinoic acid
  • organism-icon Homo sapiens
  • sample-icon 36 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 2.1 ST Array (hugene21st)

Description

Targets of Retinoic Acid (RA) and 3,4-didehydroretinoic acid (ddRA) were identified in primary human epidermal keratinocytes grown in the presence of atRA or ddRA for 4 and 24 hours.

Publication Title

The effect of two endogenous retinoids on the mRNA expression profile in human primary keratinocytes, focusing on genes causing autosomal recessive congenital ichthyosis.

Sample Metadata Fields

Treatment

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accession-icon SRP075457
Comparison of Kras;Rank+/+ and Kras;Rankfl/fl mouse primary pneumocytes treated with Rankl ex vivo
  • organism-icon Mus musculus
  • sample-icon 4 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

The transcriptional profile of Kras;Rank +/+ and Kras;Rank fl/fl mouse primary pneumocytes were determined by mRNA sequencing and uncovered differences in their molecular signatures including genes involved in cell-cell junction, mitosis, mitochondrial homeostasis, TCA cycle and respiratory electron transport Overall design: Transcriptome comparison of primary pneumocytes purified from Kras;Rank+/+ and Kras;Rankfl/fl mice treated with Rankl ex vivo

Publication Title

RANK rewires energy homeostasis in lung cancer cells and drives primary lung cancer.

Sample Metadata Fields

Specimen part, Cell line, Subject

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accession-icon SRP126511
Global transcriptional changes in U87MG glioblastoma cells upon shRNA-mediated TRIM52 knockdown
  • organism-icon Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

shRNA-mediated ablation of the RING-finger protein TRIM52 from multiple glioblastoma cell lines reduces proliferation and tumorigenesis. To identify gene signatures underlying this phenomenon, transcritional profile of TRIM52 knockdown cells was compared to control cells. Upon TRIM52 ablation, we find 278 differentially regulated genes. Gene ontology analysis reveals that many of the upregulated genes are associated with glycolysis and biosynthetic processes. Overall design: U87MG glioblastoma cells were stably transduced with doxycycline-inducible shRNA constructs targeting TRIM52 (two different shRNAs) or controls (two different non-targeting shRNAs). Knockdown was induced for five days using 2µg/ml doxycycline. shRNA expressing cells were sorted based on shRNA-coupled GFP expression via flow cytometry. mRNA sequening was performed in duplicate per shRNA cell line.

Publication Title

Human tripartite motif protein 52 is required for cell context-dependent proliferation.

Sample Metadata Fields

Specimen part, Subject

View Samples
accession-icon GSE50118
Effect of AMPK activation by AICAR on MA-10 Leydig cell transcriptome
  • organism-icon Mus musculus
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

Steroid hormones regulate essential physiological processes and inadequate levels are associated with various pathological conditions. In testosterone-producing Leydig cells, steroidogenesis is strongly stimulated by LH via its receptor leading to increased cAMP production and expression of the steroidogenic acute regulatory (STAR) protein, which is essential for the initiation of steroidogenesis. Leydig cell steroidogenesis then passively decreases following the rapid degradation of cAMP into AMP by phosphodiesterases. In this study, we show that AMP-activated protein kinase (AMPK) is activated following cAMP breakdown in MA-10 and MLTC-1 Leydig cells. Activated AMPK then actively inhibits cAMP-induced steroidogenesis by repressing the expression of key regulators of steroidogenesis including Star and Nr4a1. Similar results were obtained in Y-1 adrenal cells and in the constitutive steroidogenic cell line R2C. Our data identify AMPK as an active repressor of steroid hormone biosynthesis in steroidogenic cells that is essential to preserve cellular energy and prevent excess steroid production.

Publication Title

A cell-autonomous molecular cascade initiated by AMP-activated protein kinase represses steroidogenesis.

Sample Metadata Fields

Specimen part, Treatment

View Samples
accession-icon SRP183682
Single-cell RNA-sequencing of CD14+ monocyte differentiation with M-CSF stimulus
  • organism-icon Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge IconNextSeq 550

Description

We obtained single-cell RNA-sequencing (scRNA-seq) profiles of CD14+ monocytes isolated from human peripheral blood at 0, 3 and 6 days after M-CSF stimulation (to differentiate the cells into macrophages) across multiple donors. Integration of single-cell RNA sequencing (scRNA-seq) data from multiple experiments, laboratories, and technologies can uncover biological insights, but current methods for scRNA-seq data integration are limited by a requirement for datasets to derive from functionally similar cells. We use a novel algorithm, Scanorama, to identify and merge the shared cell types among all pairs of datasets and to accurately integrate heterogeneous scRNA-seq datasets. Scanorama is sensitive to subtle temporal changes within the same cell lineage, successfully integrating functionally similar cells across time series data of CD14+ monocytes at different stages of differentiation into macrophages. Scanorama is not only able to differentiate between completely disparate cell types but is also sensitive to subtler transcriptional changes within a cell type due to processes like stimulation. Overall design: scRNA-seq of human CD14+ monocytes at 0, 3, and 6 days after M-CSF stimulation in multiple donors

Publication Title

Efficient integration of heterogeneous single-cell transcriptomes using Scanorama.

Sample Metadata Fields

Specimen part, Treatment, Subject

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accession-icon GSE8440
Expression data from Congenital disorders of Glycosylation type-1 patients (CDG-I)
  • organism-icon Homo sapiens
  • sample-icon 35 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

Disruption of N-linked glycosylation has a broad impact on proper glycosylation of nascent glycoproteins in the endoplasmic reticulum, which affect multiple signalling pathways( by changing the stability of membrane proteins or the signalling ability of membrane receptors) and may be responsible of the fibrotic stage associated to CDG type-I.

Publication Title

Fibrotic response in fibroblasts from congenital disorders of glycosylation.

Sample Metadata Fields

No sample metadata fields

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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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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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