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accession-icon SRP166967
Single cell sequencing of mouse syngeneic tumor models
  • organism-icon Mus musculus
  • sample-icon 48 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Tumor ecosystems are composed of multiple cell types that communicate by ligand-receptor interactions. Targeting ligand-receptor interactions, for instance with immune check-point inhibitors, can provide significant benefit for patients. However, our knowledge of which interactions occur in a tumor and how these interactions affect outcome is still limited. We present an approach to characterize communication by ligand-receptor interactions across all cell types in a microenvironment using single-cell RNA sequencing. We apply this approach to identify and compare ligand-receptor interactions present in six syngeneic mouse tumor models. To identify interactions potentially associated with outcome, we regress interactions against phenotypic measurements of tumor growth rate. In addition, we quantify ligand-receptor interactions between T-cell subsets and their relation to immune infiltration using a publicly available human melanoma data-set. Overall, this approach provides a tool for studying cell-cell interactions, their variability across tumors, and their relationship to outcome. Overall design: We used three different types of immuno-competent inbred mouse strains: BALB/c, and A/J z. All animals enrolled in our study were 6-8 weeks old female mice that were housed in vivarium under specific pathogen free conditions in cages of up to 5 animals and receiving special rodent diet (Teklad). We implanted two mice for each syngeneic model resulting in a total of 12 samples. Each mouse tumor was harvested when the tumor size reached 100 – 200 mm3. Each sample was minced and digested with reagents from Mouse Tumor Dissociation Kit (Miltenyi) according to the manufacturer's instructions. Cells were resuspended at 2x105 cells/mL in PBS-0.04% BSA. Each sample was processed individually and run in technical duplicates. For each sample (except CT26 and MC-38) one replicate was enriched for CD45 positive cells. Live CD45 positive cells were sorted with BD Aria after staining with FITC-CD45 (Biolegend) and 7-AAD. Single cell suspensions of all samples were resuspended in PBS-0.04% BSA at 5x105 cells/mL and barcoded with a 10x Chromium Controller (10x Genomics). In total, this procedure resulted in 24 samples.

Publication Title

Analysis of Single-Cell RNA-Seq Identifies Cell-Cell Communication Associated with Tumor Characteristics.

Sample Metadata Fields

Cell line, Subject

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accession-icon GSE36902
Linking Proteomic and Transcriptional Data through the Interactome and Epigenome Reveals a Map of Oncogene-induced Signaling
  • organism-icon Homo sapiens
  • sample-icon 8 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

Linking proteomic and transcriptional data through the interactome and epigenome reveals a map of oncogene-induced signaling.

Sample Metadata Fields

Specimen part, Cell line

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accession-icon GSE36901
Expression data from U87MG cells expressing EGFRvIII
  • organism-icon Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

EGFRvIII is the most common deletion mutant of EGFR in human cancer and its levels are highly correlated with poor prognosis in GBM. The deletion of exons 2-7 removes most of the extracellular ligand binding domain, so it is unable to bind EGF or other EGFR-binding ligands. Nevertheless, the mutant receptor is constitutively phosphorylated, and is capable of activating downstream signaling pathways at a low level.

Publication Title

Linking proteomic and transcriptional data through the interactome and epigenome reveals a map of oncogene-induced signaling.

Sample Metadata Fields

Specimen part, Cell line

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accession-icon SRP066728
Sorted cells_PS2APP brains_7/13mo
  • organism-icon Mus musculus
  • sample-icon 61 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Mice of indicated ages and genotypes were perfused and their brains dissected and dissociated. Cells were fixed, immunolabeled and FACS sorted. RNA was extracted from neuron, astrocyte, and microglial cell populations. Typical RIN=4-5 for neurons, 6-8 for astrocytes, and 5-7 for microglia. Typical RNA yields ~100ng for neurons, ~20ng for microglia, and ~10ng for astrocytes. cDNA was generated from up to 25 ng of total RNA using Nugen’s RNA-Seq method for low-input RNA samples, Ovation RNA-Seq System V2 (NuGEN). (Per manufacturers instructions, total RNA was neither depleted of rRNA nor polyA-selected.) 1 µg of sheared cDNA was taken into further processing, starting at end repair step, using Illumina’s TruSeq RNA Sample Preparation Kit v2 (Illumina). The "SAMPLE_ID" sample characteristic is a sample identifier internal to Genentech. The ID of this project in Genentech''s ExpressionPlot database is PRJ0006149 Overall design: Astrocytes, microglia and neurons were sorted from 7- or 13-month old PS2APP or non-transgenic mice, 4 = n = 7 per group.

Publication Title

Untangling the brain's neuroinflammatory and neurodegenerative transcriptional responses.

Sample Metadata Fields

Age, Specimen part, Subject

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accession-icon SRP066489
LPS and brain inflammation
  • organism-icon Mus musculus
  • sample-icon 27 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Normal mice were injected i.p. with LPS or saline. 24h later, perfused brains were dissociated. Cells were fixed, immunolabeled and FACS sorted. RNA was extracted from neuron, astrocyte, and microglial cell populations. Typical RIN=4-5 for neurons, 6-8 for astrocytes, and 5-7 for microglia. Typical RNA yields ~100ng for neurons, ~20ng for microglia, and ~10ng for astrocytes. cDNA was generated from up to 25 ng of total RNA using Nugen''s RNA-Seq method for low-input RNA samples, Ovation RNA-Seq System V2 (NuGEN). (Per manufacturers instructions, total RNA was neither depleted of rRNA nor polyA-selected.) 1 µg of sheared cDNA was taken into further processing, starting at end repair step, using Illumina''s TruSeq RNA Sample Preparation Kit v2 (Illumina). The "SAMID" sample characteristic is a sample identifier internal to Genentech. The ID of this project in Genentech''s ExpressionPlot database is PRJ0005404 Overall design: Astrocytes, microglia and neurons were sorted from LPS or saline treated mice. n=4 or 5 per group.

Publication Title

Untangling the brain's neuroinflammatory and neurodegenerative transcriptional responses.

Sample Metadata Fields

Specimen part, Treatment, Subject

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accession-icon SRP066622
PS2APP whole tissue RNAseq
  • organism-icon Mus musculus
  • sample-icon 24 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

RNA was purified from intact cerebrocortical tissue of female PS2APP or non-transgenic mice, perfused at 7 or 13 months of age. The "SAMPLE_ID" sample characteristic is a sample identifier internal to Genentech. The ID of this project in Genentech''s ExpressionPlot database is PRJ0007648 Overall design: RNA from whole cortex of female PS2APP or non-transgenic mice at 7 or 13 months.

Publication Title

Untangling the brain's neuroinflammatory and neurodegenerative transcriptional responses.

Sample Metadata Fields

Age, Subject

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accession-icon GSE87317
The colonic epithelium plays an active role in promoting colitis by shaping the tissue cytokine profile
  • organism-icon Mus musculus
  • sample-icon 10 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

BACKGROUND & AIMS: Inflammatory Bowel Disease (IBD) is a chronic inflammatory condition driven by loss of homeostasis between the mucosal immune system, the commensal gut microbiota, and the intestinal epithelium. Our overarching goal is to understand how these components of the intestinal ecosystem cooperate to control homeostasis and to identify novel signal transduction pathways that become dysregulated in IBD. METHODS: We have applied a multi-scale systems biology approach to a mouse model of chronic colitis. We combined quantitative measures of epithelial hyperplasia and immune infiltration with multivariate analysis of inter- and intra-cellular signaling molecules in order to generate a tissue level model of the inflamed disease state. We utilized the computational model to identify signaling pathways that were dysregulated in the context of colitis and then validated model predictions by measuring the effect of small molecule pathway inhibitors on colitis. RESULTS: Our data-driven computational model identified mTOR signaling as a potential driver of inflammation and mTOR inhibition reversed the molecular, immunological, and epithelial manifestations of colitis. Inhibition of Notch signaling, which induces epithelial differentiation, had the same effect, suggesting that the epithelial proliferation/differentiation state plays a key role in maintaining homeostasis of the colon. Confirming this, we found that colonic organoids grown ex vivo showed a similar relationship between proliferation and cytokine expression, even in the absence of gut bacteria and immune cells. CONCLUSIONS: Our study provides a tissue-level systems biology perspective of murine colitis and suggests that mTOR plays a key role in regulating colonic homeostasis by controlling epithelial proliferation/differentiation state.

Publication Title

The colonic epithelium plays an active role in promoting colitis by shaping the tissue cytokine profile.

Sample Metadata Fields

Specimen part

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accession-icon GSE46892
Generating mouse model with predominant nave or innate memory phenotype CD4+ T cells
  • organism-icon Mus musculus
  • sample-icon 11 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Innate memory phenotype (IMP) CD4+ T cells are non-conventional T cells exhibiting features of innate immune cells, characterized as CD44high and CD62Llow in periphery. It is recently reported by our group that bone marrow chimeric mice lacking thymic MHCI expression develop predominantly IMP CD8+ T cells, while those lacking hematopoietic MHCI develop predominantly nave CD8+ T cells. Here we perform hirarchical clustering analysis and found that CD4+ T cells share similar property: chimeras lacking thymic MHCII gave rise to predominantly CD4+ T cells that resemble IMP CD4+ T cells observed in WT mice, and vice versa, chimeras lacking hematopoietic MHCII had a majority of nave-like CD4+ T cells resembling naveCD4+ T cells seen in WT mice.

Publication Title

Dendritic cell-MHC class II and Itk regulate functional development of regulatory innate memory CD4+ T cells in bone marrow transplantation.

Sample Metadata Fields

Age, Specimen part

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accession-icon GSE66646
Expression data from ethanol and saline exposed mice
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Alteration of Gene Expression, DNA Methylation, and Histone Methylation in Free Radical Scavenging Networks in Adult Mouse Hippocampus following Fetal Alcohol Exposure.

Sample Metadata Fields

Sex, Specimen part, Treatment

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accession-icon GSE34305
brain expression data from adult mice prenatally exposed to ethanol
  • organism-icon Mus musculus
  • sample-icon 10 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

Moderate alcohol consumption during pregnancy can result in a heterogeneous range of neurobehavioural and cognitive effects, termed fetal alcohol spectrum disorders (FASD). We have developed a mouse moder of FASD that involves moderate ethanol exposure throughout gestation achieved by voluntary maternal consumption. This model results in phenotypes relevant to FASD. Since ethanol is known to directly affect the expression of genes in the developing brain leading to abnormal cell death, changes to cell proliferation, migration, and differentiation, and potential changes to epigenetic patterning, we hypothesize that this leaves a long-term footprint on the adult brain. However, the long-term effects of prenatal ethanol exposure on brain gene expression, when behavioural phenotypes are apparent, are unclear.

Publication Title

Long-term alterations to the brain transcriptome in a maternal voluntary consumption model of fetal alcohol spectrum disorders.

Sample Metadata Fields

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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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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