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accession-icon SRP173383
Combined MEKi (GDC-0973) and WNT (G007-LK) treatment in APC and KRAS mutant HCT-15 cell line
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

We report RNAseq data from HCT-15 cells were treated wih control(DMSO), GDC-0973, G007-LK and combined GDC-0973 and G007-LK treatmetn for 24 hours. Overall design: Three biological replicates of cultured HCT-15 cells treated with DMSO (0.02%), G007-LK (1µM), GDC-0973 (1µM) or G007-LK and GDC-0973 for 24 hours before Rna extraction

Publication Title

MEK Inhibition Induces Canonical WNT Signaling through YAP in <i>KRAS</i> Mutated HCT-15 Cells, and a Cancer Preventive FOXO3/FOXM1 Ratio in Combination with TNKS Inhibition.

Sample Metadata Fields

Specimen part, Treatment, Subject

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accession-icon GSE19314
Sarcoidosis-specific markers from whole blood gene expression
  • organism-icon Homo sapiens
  • sample-icon 63 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

We hypothesized that microarray analyses of whole blood gene expression would identify patterns of gene expression useful in the diagnosis for sacroidosis and identify inflammatory mediators relevant to the underlying pathophysiology.

Publication Title

Sarcoidosis blood transcriptome reflects lung inflammation and overlaps with tuberculosis.

Sample Metadata Fields

Sex, Disease, Race

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accession-icon GSE58386
Slug-dependent upregulation of L1CAM is responsible for the increased invasion potential of pancreatic cancer cells following long-term 5-FU-treatment
  • organism-icon Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V4.0 expression beadchip

Description

In pancreatic cancer the survival rate is low, as the available treatment options usually only extend survival and seldom produce a cure. Drug resistance and disease reoccurrence is the typical reason for death after cancer diagnosis. 5-Fluorouracil (5-FU) is the main chemostatic used in first line therapy. However the majority of the tumors become resistant to treatment. To investigate acquired 5-FU resistance in pancreatic adenocarcinoma, we established chemoresistant monoclonal cell lines from the Panc03.27 cell line by long-term exposure to 5-FU. In addition to increased expression of markers associated with multidrug resistance, the 5-FU resistant clones showed alterations typical of the process of epithelial-to-mesenchymal transition (EMT), including upregulation of mesenchymal markers and increased invasiveness. Microarray analysis revealed the L1CAM pathway as one of the most upregulated pathways in the chemoresistant clones, which was confirmed on RNA and protein levels. Expression of the adhesion molecule L1CAM is associated with a chemoresistant and migratory phenotype of pancreatic cancer. Using esiRNA targeting L1CAM, or by blocking the extracellular part of L1CAM with monoclonal antibodies, we discovered that the increased invasiveness observed in the chemoresistant cells depends on L1CAM. Using esiRNA targeting -catenin and/or Slug, we discovered that L1CAM expression depends on Slug rather than -catenin in the 5-FU resistant cells. We demonstrate a functional link between Slug and the expression level of L1CAM in pancreatic cancer cells having undergone EMT following long-term exposure to 5-FU. Our findings provide further insight into the molecular mechanisms leading to a chemoresistant and migratory phenotype in pancreatic cancer cells and indicate the importance of Slug-induced L1CAM in refractory pancreatic cancer.

Publication Title

Slug-dependent upregulation of L1CAM is responsible for the increased invasion potential of pancreatic cancer cells following long-term 5-FU treatment.

Sample Metadata Fields

Cell line

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accession-icon GSE62092
Gene Expression of Kidney from HSRA-S (congenital solitary kidney) and HSRA-C (two-kidney) using Rat Gene 1.1 ST Array [RaGene-1_1-st]
  • organism-icon Rattus norvegicus
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Gene 1.1 ST Array (ragene11st)

Description

We recently developed a new model of renal agenesis [i.e., the heterogeneous stock derived model of unilateral renal agenesis, (HSRA)]. The HSRA model consistently exhibits unilateral renal agenesis ranging from 50-75% in each generation and is characterized by low nephron number, early kidney hypertrophy, and an inherent susceptibility to develop significant kidney injury and decline in renal function with age.

Publication Title

Nephron Deficiency and Predisposition to Renal Injury in a Novel One-Kidney Genetic Model.

Sample Metadata Fields

Age, Specimen part

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accession-icon GSE57118
Heterogeneous stock rats that differ in glucose tolerance
  • organism-icon Rattus norvegicus
  • sample-icon 58 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Genome 230 2.0 Array (rat2302)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Identification of a novel gene for diabetic traits in rats, mice, and humans.

Sample Metadata Fields

Sex, Age, Specimen part

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accession-icon GSE54935
Gene expression profiles in heterogeneous stock rats that differ in glucose tolerance
  • organism-icon Rattus norvegicus
  • sample-icon 58 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Genome 230 2.0 Array (rat2302)

Description

Using heterogeneous stock (HS) rats, we have identified a region on rat chromosome 1 that maps multiple diabetic traits. We sought to use global expression analysis to determine if genes within this region are differentially expressed between HS rats with normal glucose tolerance and those with glucose intolerance

Publication Title

Identification of a novel gene for diabetic traits in rats, mice, and humans.

Sample Metadata Fields

Sex, Age, Specimen part

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accession-icon GSE4737
HCaRG vs NEO
  • organism-icon Homo sapiens
  • sample-icon 2 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Summary:

Publication Title

HCaRG increases renal cell migration by a TGF-alpha autocrine loop mechanism.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE2555
HCaRG-9 vs NEO-1
  • organism-icon Homo sapiens
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2), Affymetrix Human Genome U133A Array (hgu133a)

Description

HEK293 cells were transfected with control plasmid (pcDNAI/Neo;Invitrogen) or with the plasmid encoding HCaRG. Stable transfectants were synchronized and grown in the presence of 10% FBS for 48 h. Total RNAs were purified with the mini RNeasy kit (Qiagen).

Publication Title

HCaRG increases renal cell migration by a TGF-alpha autocrine loop mechanism.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE4611
Breast Cancer Gene Expression Data from Frankfurt Series
  • organism-icon Homo sapiens
  • sample-icon 218 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

Pooling of microarray datasets seems to be a reasonable approach to increase sample size when a heterogeneous disease like breast cancer is concerned. Different methods for the adaption of datasets have been used in the literature. We have analyzed influences of these strategies using a pool of 3,030 Affymetrix U133A microarrays from breast cancer samples. We present data on the resulting concordance with biochemical assays of well known parameters and highlight critical pitfalls. We further propose a method for the inference of cutoff values directly from the data without prior knowledge of the true result. The cutoffs derived by this method displayed high specificity and sensitivity. Markers with a bimodal distribution like ER, PgR, and HER2 discriminate different biological subtypes of disease with distinct clinical courses. In contrast, markers displaying a continuous distribution like proliferation markers as Ki67 rather describe the composition of the mixture of cells in the tumor.

Publication Title

Data-driven derivation of cutoffs from a pool of 3,030 Affymetrix arrays to stratify distinct clinical types of breast cancer.

Sample Metadata Fields

Sex, Specimen part

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accession-icon GSE29583
Circadian Clock Activity in Mouse and Human CD4+ T Cells
  • organism-icon Homo sapiens
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Though it is well established that immunological functions of CD4+ T cells are time of day-dependent, the underlying molecular mechanisms remain largely obscure. To address the question whether T cells themselves harbor a functional clock driving circadian rhythms of immune function, we analyzed clock gene expression and immune responses of CD4+ T cells purified from blood of healthy subjects at different time points throughout the day. Circadian clock function as well as immune function was further analyzed in cultivated T cells and circadian clock reporter systems. We found robust rhythms of clock gene expression as well as, after stimulation, of IFN-g production and CD40L expression in both freshly isolated and in cultured CD4+ T cells. Moreover, circadian luciferase reporter activities in CD4+ T cells and in thymic sections from PER2::LUCIFERASE reporter mice suggest that endogenous T cell clock rhythms are self-sustained under constant culture conditions. Microarray analysis of stimulated CD4+ T cell cultures revealed a rhythmic regulation of the NF-kB pathway as a candidate mechanism regulating circadian immune responses. Collectively, these data demonstrate for the first time that CD4+ T cell responses are regulated by an intrinsic cellular circadian oscillator capable of driving rhythmic adaptive immune responses in vitro and in vivo.

Publication Title

Circadian clocks in mouse and human CD4+ T cells.

Sample Metadata Fields

Specimen part, Time

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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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