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accession-icon GSE38312
autologous pairs of cutaneous melanocyte and melanoma cell cultures
  • organism-icon Homo sapiens
  • sample-icon 10 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Early-passage (<10 passages) cultures of melanoma cells from metastatic lymph node lesions and normal adult melanocytes explanted in parallel from the adjacent, non-involved skin of 5 patients were compared by cDNA arrays. Differences between normal and neoplastic counterparts were then assessed upon adjustment for individual factors.

Publication Title

A melanoma immune response signature including Human Leukocyte Antigen-E.

Sample Metadata Fields

Sex, Specimen part

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accession-icon SRP073501
Complement protein C1q modulates macrophage molecular signaling and inflammatory responses during ingestion of atherogenic lipoproteins
  • organism-icon Homo sapiens
  • sample-icon 30 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

C1q suppresses JAK-STAT signal transduction and activates PPAR-mediated transcription in macrophages during clearance of modified forms of LDL leading to a reduction in inflammatory response. Overall design: Human monocyte-derived macrophages (HMDM) were incubated with either oxidized (oxLDL) or acetylated low-density lipoprotein (acLDL) in the presence or absence of C1q for 3 hours. Total RNA was extracted using the Qiagen RNeasy Mini Kit. RNA libraries were constructed using the Illumina TruSeq Stranded mRNA Sample Preparation Kit. Sequences were aligned to a reference genome (hg38), RPKM and raw counts were determined using CASAVA version 1.8.2.

Publication Title

Transcriptome data and gene ontology analysis in human macrophages ingesting modified lipoproteins in the presence or absence of complement protein C1q.

Sample Metadata Fields

Specimen part, Subject

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accession-icon SRP136108
RNA-seq of nine primary human cell types exposed in vitro to methylprednisolone
  • organism-icon Homo sapiens
  • sample-icon 130 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000, Illumina HiSeq 3000

Description

Glucocorticoids remain the most widely used class of anti-inflammatory and immunosuppressive agents. They act primarily by binding to the glucocorticoid receptor, resulting in direct and indirect effects on gene expression. The current understanding of glucocorticoid effects on transcription in human cells is based mostly on studies of cancer cell lines, immortalized cell lines, or highly mixed populations of primary cells (such as peripheral blood mononuclear cells). To advance the understanding of the transcriptome-wide effects of glucocorticoids on highly pure populations of primary human cells, we performed RNA-seq on nine such cell populations at two time points after in vitro exposure to methylprednisolone or vehicle. Overall design: Nine cell types were studied: four hematopoietic (circulating B cells, CD4+ T cells, monocytes, and neutrophils) and five non-hematopoietic (endothelial cells, fibroblasts, myoblasts, osteoblasts, and preadipocytes). Each cell type was obtained from a separate cohort of 4 unrelated healthy human donors (4 biological replicates per cell type: BR1 - BR4). Cells form each donor were independently cultured and exposed in vitro to glucocorticoid or vehicle. Non-hematopoietic cells were incubated until the early plateau phase of growth, then exposed to methylprednisolone or vehicle. Hematopoietic cells were collected from peripheral blood, purified by magnetic selection (negative selection for B cells, CD4+ T cells and neutrophils; positive selection for monocytes). Purified B cells, CD4+ T cells, and monocytes were incubated overnight, then exposed to methylprednisolone or vehicle. Purified neutrophils were cultured for 4 hours, then exposed to methylprednisolone or vehicle. Ethanol was used as a vehicle for methylprednisolone. Estimated final concentrations were 8500 mcg/L (22.7 mcM) for methylprednisolone and 0.07% (15.57 mM) for ethanol (vehicle). For each cell type, samples were collected at two time points after treatment with methylprednisolone or vehicle: 2 hours and 6 hours. Samples were collected into TRIzol reagent and frozen at -80°C prior to RNA extraction. RNA-seq data for all samples is made available in this GEO Series.

Publication Title

Immune regulation by glucocorticoids can be linked to cell type-dependent transcriptional responses.

Sample Metadata Fields

Specimen part, Subject, Time

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accession-icon GSE89962
mouse BMDM dual PAMP stimulation with poly(I:C), R848, LPS, Pam3CSK3
  • organism-icon Mus musculus
  • sample-icon 69 Downloadable Samples
  • Technology Badge IconIllumina MouseWG-6 v2.0 R2 expression beadchip

Description

Gene expression kinetics for BM-DM from C57BL/6 mouse stimulated with four different TLR ligands poly(I:C), R848, LPS, Pam3CSK4 either singly or in paired combination, for 1 hour, 4 hour, or 8 hour.

Publication Title

Systematic Investigation of Multi-TLR Sensing Identifies Regulators of Sustained Gene Activation in Macrophages.

Sample Metadata Fields

Treatment

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accession-icon GSE89988
Systematic investigation of multi-TLR sensing identifies novel regulators of sustained gene activation in macrophages.
  • organism-icon Mus musculus
  • sample-icon 66 Downloadable Samples
  • Technology Badge IconIllumina MouseWG-6 v2.0 R2 expression beadchip

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Systematic Investigation of Multi-TLR Sensing Identifies Regulators of Sustained Gene Activation in Macrophages.

Sample Metadata Fields

Treatment

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accession-icon GSE89987
mouse BMDM poly(I:C), R848, or poly(I:C)+R848 stimulation
  • organism-icon Mus musculus
  • sample-icon 47 Downloadable Samples
  • Technology Badge IconIllumina MouseWG-6 v2.0 R2 expression beadchip

Description

Gene expression kinetics for BM-DM from C57BL/6 mice challenged by poly(I:C) , R848, poly(I:C)+R848 examined at 6 time points including 0.5, 1, 2, 4, 8, 12 h.

Publication Title

Systematic Investigation of Multi-TLR Sensing Identifies Regulators of Sustained Gene Activation in Macrophages.

Sample Metadata Fields

Treatment

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accession-icon GSE4006
Estrogen effects on MCF-7 breast cancer cells co-expressing ERa and ERb
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

Two subtypes of the estrogen receptor, ERalpha and ERbeta, mediate the actions of estrogens, and the majority of human breast tumors contain both ERalpha and ERbeta. To examine the possible interactions and modulatory effects of ERbeta on ERalpha activity, we have used adenoviral gene delivery to produce human breast cancer (MCF-7) cells expressing ERbeta, along with their endogenous ERalpha. We have examined the effects of ER expression on genome-wide gene expression by Affymetrix GeneChip microarrays. We find that ERbeta modulated estrogen gene expression on nearly 24% of E2-stimulated genes but only 8% of E2-inhibited genes. We find that ERbeta modulation is gene-specific, enhancing or counteracting ERalpha regulation for distinct subsets of estrogen target genes. Introduction of ERbeta into ERalpha-containing cells induced up/down-regulation of many estrogen target in the absence of any added ligand. In addition, ERbeta presence elicited the expression of a unique set of genes that were not regulated by ERalpha alone. ERbeta modulated the expression of genes in many functional categories, but the greatest numbers were associated with transcription factor and signal transduction pathways. Regulation of multiple components in the TGF beta, SDF1, and semaphorin pathways, may contribute to the suppression of proliferation observed with ERbeta both in the presence and absence of estrogen. Hence, ERbeta modulates ERalpha gene regulation in diverse ways that may contribute to its growth-inhibiting beneficial effects in breast cancer

Publication Title

Impact of estrogen receptor beta on gene networks regulated by estrogen receptor alpha in breast cancer cells.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE30177
Complement protein C1q modulates macrophage activation and inflammasome activity during the uptake of apoptotic cells
  • organism-icon Homo sapiens
  • sample-icon 18 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

In this study, we developed a unique system using primary human autologous lymphocytes and HMDMs to characterize the effect of C1q on macrophage gene expression profiles during the uptake of apoptotic cells. Our results showed that C1q bound to autologous apoptotic lymphocytes (AL) significantly modulated the response of HMDMs to LPS by increasing expression of cytokines, chemokines and effector molecules associated with immunoregulation and by directly suppressing caspase-1 dependent cleavage of IL-1beta.

Publication Title

Complement protein C1q directs macrophage polarization and limits inflammasome activity during the uptake of apoptotic cells.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE83824
Genome-wide siRNA screen of genes regulating the Lipopolysaccharide-induced TNF- response in human macrophages
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V4.0 expression beadchip

Description

The mammalian innate immune system senses many bacterial stimuli through the toll-like receptor (TLR) family. Activation of the TLR4 receptor by bacterial lipopolysaccharide (LPS) is the most widely studied TLR pathway due to its central role in host responses to gram-negative bacterial infection and its contribution to endotoxemia and sepsis. Here we describe a genome-wide siRNA screen to identify genes regulating the human macrophage TNF- response to LPS. We include a secondary validation screen conducted with six independent siRNAs per gene to facilitate removal of off-target screen hits. We also provide microarray data from the same LPS-treated macrophage cells to facilitate downstream data analysis. These data provide a resource for analyzing gene function in the predominant pathway driving inflammatory cytokine expression in human macrophages.

Publication Title

Genome-wide siRNA screen of genes regulating the LPS-induced TNF-α response in human macrophages.

Sample Metadata Fields

Specimen part, Cell line

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accession-icon GSE53810
Switching of the Relative Dominance Between Feedback Mechanisms in Lipopolysaccharide-Induced NF-kB Signaling
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge IconIllumina MouseRef-8 v2.0 expression beadchip

Description

The bacterial product lipopolysaccharide (LPS) stimulates nuclear factor kB (NF-kB) signaling, which results in the production of proinflammatory cytokines, such as tumor necrosis factor-alpha (TNF-alpha), as part of the immune response. NF-kB target genes also include those encoding proteins that inhibit NF-kB signaling through negative feedback loops. By simultaneously studying the dynamics of the nuclear translocation of the NF-kB subunit RelA and the activity of a Tnf-driven reporter in a mouse macrophage cell line, Sung et al. found that the gene encoding RelA was also a target of NF-kB. Synthesis of RelA occurred only at higher concentrations of LPS and constituted a positive feedback loop that dominated over existing negative feedback mechanisms. Genes expressed in response to a high concentration of LPS were enriched for those involved in innate immune responses. Together, these data suggest that the RelA-dependent positive feedback loop enables macrophages to mount an effective immune only above a critical concentration of LPS.

Publication Title

Switching of the relative dominance between feedback mechanisms in lipopolysaccharide-induced NF-κB signaling.

Sample Metadata Fields

Specimen part

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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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