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accession-icon SRP176633
Whole-transcriptome profiling of LCMV.GP66-77 specific CD4 T cells isolated from bone marrow (BM) and spleen, 60 days after last immunization [RNA-seq]
  • organism-icon Mus musculus
  • sample-icon 48 Downloadable Samples
  • Technology Badge IconNextSeq 500

Description

To udnderstand the tissue-resident features of antigen-specific memory T cells of the bone marrow and spleen, we performed RNA-Seq and compared expression levels of genes of resting LCMV.GP66-77 specific CD4 T cells isolated from bone marrow (BM) and spleen of LCMV.GP61-80 primed C57BL/6 mice. Overall design: C57BL/6 mice were primed at day 0 with LCMV.GP61-80-NP-MSA + poly(I:C) and immunized again at day 14 with LCMV.GP61-80 + poly(I:C). Sixty days after the last immunization mice were sacrificed and LCMV.GP66–77-specific CD69+ and CD69- memory CD4 T cells were isolated from BM and spleen.

Publication Title

CD69<sup>+</sup> memory T lymphocytes of the bone marrow and spleen express the signature transcripts of tissue-resident memory T lymphocytes.

Sample Metadata Fields

Sex, Age, Specimen part, Cell line, Subject

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accession-icon SRP198678
Single-Cell transcriptomes of murine Bone Marrow Stromal Cells Reveal Niche-Associated Heterogeneity
  • organism-icon Mus musculus
  • sample-icon 1 Downloadable Sample
  • Technology Badge IconNextSeq 500

Description

Bone marrow (BM) stromal cells are important in the development and maintenance of cells of the immune system. Using single cell RNA sequencing, we here explore the functional and phenotypic heterogeneity of individual transcriptomes of 1,167 murine BM mesenchymal stromal cells. These cells exhibit a tremendous heterogeneity of gene expression, which precludes the identification of defined subpopulations. However, according to the expression of 108 genes involved in the communication of stromal cells with hematopoietic cells, we have identified 14 non-overlapping subpopulations, with distinct cytokine or chemokine gene expression signatures. With respect to the maintenance of subsets of immune memory cells by stromal cells, we identify distinct subpopulations expressing IL7, IL15 and Tnfsf13b. Together, this study provides a comprehensive dissection of the BM stromal heterogeneity at the single cell transcriptome level and provides a basis to understand their lifestyle and their role as organizers of niches for the long-term maintenance of immune cells. Overall design: For single cell library preparation, ex vivo FACS sorted VCAM-1+CD45-Ter119-CD31- BM cells were applied to the 10X Genomics platform using the Single Cell 3' Reagent Kit V2 (10x Genomics) following the manufacturer's instructions. Upon adapter ligation and index PCR, the quality of the obtained cDNA library was assessed by Qubit quantification, Bioanalyzer fragment analysis (HS DNA Kit, Agilent) and KAPA library quantification qPCR (Roche). The sequencing was performed on a NextSeq500 device (Illumina) using a High Output v2 Kit (150 cycles) with the recommended sequencing conditions (read1: 26nt, read2: 98nt, index1: 8 nt, index2: n.a.).

Publication Title

Single-cell transcriptomes of murine bone marrow stromal cells reveal niche-associated heterogeneity.

Sample Metadata Fields

Specimen part, Subject

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accession-icon GSE62691
Gene expression of resting memory, resting naive and in vitro activated memory CD8+CD127+ T cells from spleen and bone marrow (BM)
  • organism-icon Mus musculus
  • sample-icon 15 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

To understand differences between resting and activated memory CD8+ T cells, we compared the global gene expression of ex vivo isolated naive and spleen and BM memory cells to in vitro activated spleen and BM memory cells.

Publication Title

Memory CD8(+) T cells colocalize with IL-7(+) stromal cells in bone marrow and rest in terms of proliferation and transcription.

Sample Metadata Fields

Sex, Specimen part

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accession-icon GSE53403
Expression data from mouse adipose tissue macrophage
  • organism-icon Mus musculus
  • sample-icon 16 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

In mammals, expansion of adipose tissue mass induces accumulation of adipose tissue macrophages (ATMs). We isolated CD11c- (FB) and CD11c+ (FBC) perigonadal ATMs from SVCs of lean (C57BL/6J Lep +/+) and obese leptin-deficient (C57BL/6J Lep ob/ob) mice.

Publication Title

Obesity activates a program of lysosomal-dependent lipid metabolism in adipose tissue macrophages independently of classic activation.

Sample Metadata Fields

Specimen part

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accession-icon GSE38614
Hierarchical regulation in a KRAS pathway-dependent transcriptional network revealed by a reverse-engineering approach
  • organism-icon Rattus norvegicus
  • sample-icon 18 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Gene 1.0 ST Array (ragene10st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Reverse engineering a hierarchical regulatory network downstream of oncogenic KRAS.

Sample Metadata Fields

Cell line, Treatment

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accession-icon GSE38584
Hierarchical regulation in a KRAS pathway-dependent transcriptional network revealed by a reverse-engineering approach (7TF and control)
  • organism-icon Rattus norvegicus
  • sample-icon 16 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Gene 1.0 ST Array (ragene10st)

Description

RAS mutations are highly relevant for progression and therapy response of human tumours, but the genetic network that ultimately executes the oncogenic effects is poorly understood. Here we used a reverse-engineering approach in an ovarian cancer model to reconstruct KRAS oncogene-dependent cytoplasmic and transcriptional networks from perturbation experiments based on gene silencing and pathway inhibitor treatments. We measured mRNA and protein levels in manipulated cells by microarray, RT-PCR and Western Blot analysis, respectively. The reconstructed model revealed complex interactions among the transcriptional and cytoplasmic components, some of which were confirmed by double pertubation experiments. Interestingly, the transcription factors decomposed into two hierarchically arranged groups. To validate the model predictions we analysed growth parameters and transcriptional deregulation in the KRAS-transformed epithelial cells. As predicted by the model, we found two functional groups among the selected transcription factors. The experiments thus confirmed the predicted hierarchical transcription factor regulation and showed that the hierarchy manifests itself in downstream gene expression patterns and phenotype.

Publication Title

Reverse engineering a hierarchical regulatory network downstream of oncogenic KRAS.

Sample Metadata Fields

Cell line, Treatment

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accession-icon GSE71482
Expression data from Caenorhabditis elegans fed with a Lactoferrin-based product
  • organism-icon Caenorhabditis elegans
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix C. elegans Genome Array (celegans)

Description

Lactoferrin is a highly multifunctional protein. Indeed, it is involved in many physiological functions, including regulation of iron absorption and immune responses.

Publication Title

A nutritional supplement containing lactoferrin stimulates the immune system, extends lifespan, and reduces amyloid &lt;i&gt;β&lt;/i&gt; peptide toxicity in &lt;i&gt;Caenorhabditis elegans&lt;/i&gt;.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE38585
Hierarchical regulation in a KRAS pathway-dependent transcriptional network revealed by a reverse-engineering approach (RAS-ROSE and ROSE with siRNA)
  • organism-icon Rattus norvegicus
  • sample-icon 2 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Gene 1.0 ST Array (ragene10st)

Description

RAS mutations are highly relevant for progression and therapy response of human tumours, but the genetic network that ultimately executes the oncogenic effects is poorly understood. Here we used a reverse-engineering approach in an ovarian cancer model to reconstruct KRAS oncogene-dependent cytoplasmic and transcriptional networks from perturbation experiments based on gene silencing and pathway inhibitor treatments. We measured mRNA and protein levels in manipulated cells by microarray, RT-PCR and Western Blot analysis, respectively. The reconstructed model revealed complex interactions among the transcriptional and cytoplasmic components, some of which were confirmed by double pertubation experiments. Interestingly, the transcription factors decomposed into two hierarchically arranged groups. To validate the model predictions we analysed growth parameters and transcriptional deregulation in the KRAS-transformed epithelial cells. As predicted by the model, we found two functional groups among the selected transcription factors. The experiments thus confirmed the predicted hierarchical transcription factor regulation and showed that the hierarchy manifests itself in downstream gene expression patterns and phenotype.

Publication Title

Reverse engineering a hierarchical regulatory network downstream of oncogenic KRAS.

Sample Metadata Fields

Cell line, Treatment

View Samples
accession-icon GSE14359
Expression data from conventional osteosarcoma compared to primary non-neoplastic osteoblast cells
  • organism-icon Homo sapiens
  • sample-icon 20 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

In osteosarcoma patients, the development of metastases, often to the lungs, is the most frequent cause of death. To improve this situation, a deeper understanding of the molecular mechanisms governing osteosarcoma development and dissemination and the identification of novel drug targets for an improved treatment are needed. Towards this aim, we characterized osteosarcoma tissue samples compared to primary osteoblast cells using Affymetrix HG U133A microarrays.

Publication Title

De novo expression of EphA2 in osteosarcoma modulates activation of the mitogenic signalling pathway.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP097691
Oncogenic PIK3CA(H1047R) and CTNNB1(stab) in intestinal organoids
  • organism-icon Mus musculus
  • sample-icon 8 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Goals of the study was to compare transcripional and phenotypic response of mouse intestinal organoid cultures to the PIK3CA(H1047R) and CTNNB1(stab) oncogenes. Overall design: Two biological replicates of organoids with transgenic tdTomato-Luciferase, tdTomato-PIK3CAH1047R, tdTomato-CTNNB1stab or td-Tomato-PIK3CAH1047R-CTNNB1stab were analysed by RNA-Seq By comparing 7-10 x 10E7 50bp paired end reads per library we identify transcriptional alterations in the intestinal epithelium following expression of each or both oncogenes,

Publication Title

Oncogenic β-catenin and PIK3CA instruct network states and cancer phenotypes in intestinal organoids.

Sample Metadata Fields

Specimen part, Cell line, 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)

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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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