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accession-icon GSE35459
Transcriptome profiles of mouse and human monocyte and dendritic cell subsets
  • organism-icon Mus musculus, Homo sapiens
  • sample-icon 36 Downloadable Samples
  • Technology Badge IconIllumina MouseWG-6 v2.0 expression beadchip, Illumina HumanHT-12 V4.0 expression beadchip

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Human tissues contain CD141hi cross-presenting dendritic cells with functional homology to mouse CD103+ nonlymphoid dendritic cells.

Sample Metadata Fields

Sex, Specimen part, Disease, Disease stage

View Samples
accession-icon GSE35457
Transcriptome profiles of mouse and human monocyte and dendritic cell subsets (human data)
  • organism-icon Homo sapiens
  • sample-icon 21 Downloadable Samples
  • Technology Badge IconIllumina MouseWG-6 v2.0 expression beadchip, Illumina HumanHT-12 V4.0 expression beadchip

Description

Dendritic cells (DCs) are critical in mediating immunity to pathogens, vaccines, tumors and tolerance to self. Significant progress has been made in the study of DC subsets in murine models but the translation of these findings to human DC immunobiology has not been fully realized. Murine splenic CD8+ DC and CD103+ DC possess potent antigen cross-presenting capacity. Although recent evidence points to human blood CD141+ DCs as the functional equivalent of CD8+ DC, the precise identity of the human migratory cross-presenting DC has remained elusive. We performed phenotypic and functional analyses to interrogate the DC compartment of human non-lymphoid tissues and identified three distinct subsets: i) CD141high DCs, ii) CD1c DCs and iii) CD14+ DCs. Only CD141high DCs were capable of cross-presenting soluble antigen. Comparative transcriptome analysis of steady state monocyte and DC subsets between mouse and human confirmed conservation between species, aligning the following subsets together: i) human CD141high DCs with mouse CD8+ and CD103+ DCs, ii) human CD1c+ DCs with mouse CD4+ DCs and iii) human CD14+ DC with mouse monocyte subsets. The lack of positive association between human CD1c+ DCs and mouse non-lymphoid tissue CD11b+ DCs highlights heterogeneity and predicts the existence of a monocyte-like cell within the CD11b+ DCs.

Publication Title

Human tissues contain CD141hi cross-presenting dendritic cells with functional homology to mouse CD103+ nonlymphoid dendritic cells.

Sample Metadata Fields

Specimen part, Disease, Disease stage

View Samples
accession-icon GSE35458
Transcriptome profiles of mouse and human monocyte and dendritic cell subsets (mouse data)
  • organism-icon Mus musculus
  • sample-icon 15 Downloadable Samples
  • Technology Badge IconIllumina MouseWG-6 v2.0 expression beadchip

Description

Dendritic cells (DCs) are critical in mediating immunity to pathogens, vaccines, tumors and tolerance to self. Significant progress has been made in the study of DC subsets in murine models but the translation of these findings to human DC immunobiology has not been fully realized. Murine splenic CD8+ DC and CD103+ DC possess potent antigen cross-presenting capacity. Although recent evidence points to human blood CD141+ DCs as the functional equivalent of CD8+ DC, the precise identity of the human migratory cross-presenting DC has remained elusive. We performed phenotypic and functional analyses to interrogate the DC compartment of human non-lymphoid tissues and identified three distinct subsets: i) CD141high DCs, ii) CD1c DCs and iii) CD14+ DCs. Only CD141high DCs were capable of cross-presenting soluble antigen. Comparative transcriptome analysis of steady state monocyte and DC subsets between mouse and human confirmed conservation between species, aligning the following subsets together: i) human CD141high DCs with mouse CD8+ and CD103+ DCs, ii) human CD1c+ DCs with mouse CD4+ DCs and iii) human CD14+ DC with mouse monocyte subsets. The lack of positive association between human CD1c+ DCs and mouse non-lymphoid tissue CD11b+ DCs highlights heterogeneity and predicts the existence of a monocyte-like cell within the CD11b+ DCs.

Publication Title

Human tissues contain CD141hi cross-presenting dendritic cells with functional homology to mouse CD103+ nonlymphoid dendritic cells.

Sample Metadata Fields

Sex, Specimen part, Disease, Disease stage

View Samples
accession-icon GSE103339
Gene expression profiling of skin melanophages and macrophages positive or negative for MHC class II expression
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

The lack of mouse models permitting the specific ablation of tissue-resident macrophages and monocyte-derived cells complicates understanding of their contribution to tissue integrity and to immune responses. Here we use a new model permitting diphtheria-toxin (DT)-mediated depletion of those cells and in which dendritic cells are spared. We showed that the myeloid cells of the mouse ear skin dermis are dominated by a population of melanin-laden macrophages, called melanophages, that has been missed in most previous studies. By using gene expression profiling, DT-mediated ablation and parabiosis, we determined their identity including their similarity to other skin macrophages, their origin and their dynamics. Limited information exist on the identity of the skin cells responsible for long-term tattoo persistence. Benefiting of our knowledge on melanophages, we showed that they are responsible for retaining tattoo pigment particles through a dynamic process which characterization has direct implications for improving strategies aiming at removing tattoos.

Publication Title

Unveiling skin macrophage dynamics explains both tattoo persistence and strenuous removal.

Sample Metadata Fields

Specimen part, Treatment

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accession-icon GSE49507
Quantitative proteomics analysis of signalosome dynamics in primary T cells identifies the surface receptor CD6 as a Lat adaptor-independent TCR signaling hub
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.1 ST Array (mogene11st)

Description

The aim of the dataset was to study on a genome-wide level the impact of Lat deficiency on gene expression in resting and activated CD4+ T cells

Publication Title

Quantitative proteomics analysis of signalosome dynamics in primary T cells identifies the surface receptor CD6 as a Lat adaptor-independent TCR signaling hub.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE54202
SUMOylation modulates the transcriptional activity of androgen receptor in a target gene and pathway selective manner.
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V4.0 expression beadchip, Illumina HumanHT-12 V3.0 expression beadchip

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

SUMOylation modulates the transcriptional activity of androgen receptor in a target gene and pathway selective manner.

Sample Metadata Fields

Cell line, Treatment

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accession-icon GSE54137
Genome-wide analysis of androgen receptor (AR) SUMOylation effects on gene expression (HEK293).
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V3.0 expression beadchip

Description

Androgen receptor (AR) plays an important regulatory role during prostate cancer development. ARs transcriptional activity is regulated by androgenic ligands, but also by post-translational modifications. To study the role of the AR SUMOylation in genuine chromatin environment, we compared androgen-regulated gene expression and AR chromatin occupancy in PC-3 prostate cancer and HEK293 cell lines stably expressing wild-type (wt) or SUMOylation site-mutated AR (AR-K386R,K520R). Our genome-wide gene expression analyses reveal that the SUMOylation modulates the AR function in a target gene and pathway selective manner. The transcripts that are differentially regulated by androgen and SUMOylation are linked to cellular movement, cell death, cellular proliferation, cellular development and cell cycle. In line with these data, SUMOylation mutant AR cells proliferate faster and are more sensitive to apoptosis. Moreover, ChIP-seq analyses show that the SUMOylation modulates the chromatin occupancy of AR on many loci in a fashion that parallels with their differential androgen-regulated expression. De novo motif analyses show that other transcription factor-binding motifs are differentially enriched at the wtAR- and the AR-K386R,K520R-preferred genomic binding positions. Taken together, our data indicate that SUMOylation does not simply repress the AR activity, but it regulates ARs interaction with the chromatin and the receptors target gene selection.

Publication Title

SUMOylation modulates the transcriptional activity of androgen receptor in a target gene and pathway selective manner.

Sample Metadata Fields

Cell line, Treatment

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accession-icon GSE75034
Selection of reference genes for gene expression studies related to hypoxia in cervical cancer
  • organism-icon Homo sapiens
  • sample-icon 166 Downloadable Samples
  • Technology Badge IconIllumina HumanWG-6 v3.0 expression beadchip

Description

The present work aimed to identify reference genes for RT-qPCR studies of hypoxia in cervical cancer. From 422 candidate reference genes selected from the literature, we used Illumina array-based expression profiles to identify 182 genes not affected by hypoxia treatment in eight cervical cancer cell lines or correlated with the hypoxia-associated dynamic contrast-enhanced magnetic resonance imaging parameter ABrix in 42 patients. Among these genes, we selected nine candidates (CHCHD1, GNB2L1, IPO8, LASP1, RPL27A, RPS12, SOD1, SRSF9, TMBIM6) that were not associated with tumor volume, stage, lymph node involvement or disease progression in array data of 150 patients, for further testing by RT-qPCR. geNorm and NormFinder analyses of RT-qPCR data of 74 patients identified CHCHD1, SRSF9 and TMBIM6 as the most suitable set of reference genes, with stable expression both overall and across patient subgroups with different hypoxia status (ABrix) and clinical parameters. The suitability of the three candidates as reference genes were validated in studies of the hypoxia-induced genes DDIT3, ERO1A, and STC2. After normalizing with CHCHD1, SRSF9 and TMBIM6, the RT-qPCR data of these genes showed a significant correlation with Illumina expression (P<0.001, n=74) and ABrix (P<0.05, n=32), and the STC2 data were associated with clinical outcome, in accordance with the Illumina data. Thus, CHCHD1, SRSF9 and TMBIM6 seem to be suitable reference genes for studying hypoxia-related gene expression in cervical cancer samples by RT-qPCR. STC2 might be a useful prognostic hypoxia biomarker in cervical cancer that warrants further investigation.

Publication Title

Identification and Validation of Reference Genes for RT-qPCR Studies of Hypoxia in Squamous Cervical Cancer Patients.

Sample Metadata Fields

Specimen part, Cell line

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accession-icon SRP078536
Analysis of active enhancers and direct androgen receptor target genes in VCaP prostate cancer cells
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon

Description

Androgen receptor (AR) is typically overexpressed in castration-resistant prostate cancer (CRPC). CRPC-derived VCaP cells display an excessive number of chromatin AR-binding sites (ARBs). This study analyzed direct transcription programs of the AR, the prevalence of AR enhancers and the transcriptional regulators involved in the regulation of at the enhancer regions. The analysis utilized global nuclear run-on sequencing (GRO-seq). The GRO-seq data were integrated with the ARB and VCaP cell-specific transcription factor-binding data. Androgen in 30 min activated and repressed transcription of a large number of genes including novel AR targets IGF-1 receptor and EGF receptor. GRO-seq analysis also revealed that only a fraction of the ARBs resides at functional enhancers. Activation of AR bound enhancers was most potent at the sites that also bound PIAS1, ERG and HDAC3. Our genome-wide data provide new insights how AR can directly control growth-signaling pathways in CPRC cells. Overall design: ChIP-seq samples were collected from cells treated with vehicle (ethanol, EtOH) or 10 nM R1881 (synthetic androgen methyltrienolone). IgG sample was collected from EtOH- and R1881-treated cells and used as background control. Biological duplicate samples of the AR (R1881-treated) and CTCF (vehicle- and R1881-treated) ChIP-seq samples were analyzed by using Illumina HiSeq 2000 platform 1.9. Single IgG and H3K9me3 (R1881-treated) samples were analyzed with the same platform. GRO-seq was used to determine androgen-induced changes in nascent transcription in VCaP and LNCaP cells.

Publication Title

Global analysis of transcription in castration-resistant prostate cancer cells uncovers active enhancers and direct androgen receptor targets.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE146114
Combining imaging- and gene-based hypoxia biomarkers in cervical cancer improves prediction of treatment failure independent of intratumor heterogeneity
  • organism-icon Homo sapiens
  • sample-icon 80 Downloadable Samples
  • Technology Badge IconIllumina HumanWG-6 v3.0 expression beadchip

Description

Emerging biomarkers based on medical images and molecular characterization of tumor biopsies open up for combining the two disciplines and exploiting their synergy in treatment planning. We compared pretreatment classification of cervical cancer patients by two previously validated imaging- and gene-based hypoxia biomarkers, evaluated the influence of intratumor heterogeneity, and investigated the benefit of combining them in prediction of treatment failure. The imaging-based biomarker was hypoxic fraction, determined from diagnostic dynamic contrast enhanced (DCE)-MR images. The gene-based biomarker was a hypoxia gene expression signature determined from tumor biopsies. Paired data were available for 118 patients. Intratumor heterogeneity was assessed by variance analysis of MR images and multiple biopsies from the same tumor. The two biomarkers were combined using a dimension-reduction procedure. The biomarkers classified 75% of the tumors with the same hypoxia status. Both intratumor heterogeneity and distribution pattern of hypoxia from imaging were unrelated to inconsistent classification by the two biomarkers, and the hypoxia status of the slice covering the biopsy region was representative of the whole tumor. Hypoxia by genes was independent on tumor cell fraction and showed minor heterogeneity across multiple biopsies in 9 tumors. This suggested that the two biomarkers could contain complementary biological information. Combination of the biomarkers into a composite score led to improved prediction of treatment failure (HR:7.3) compared to imaging (HR:3.8) and genes (HR:3.0) and prognostic impact in multivariate analysis with clinical variables. In conclusion, combining imaging- and gene-based biomarkers enables more precise and informative assessment of hypoxia-related treatment resistance in cervical cancer, independent of intratumor heterogeneity.

Publication Title

Combining imaging- and gene-based hypoxia biomarkers in cervical cancer improves prediction of chemoradiotherapy failure independent of intratumour heterogeneity.

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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Developed by the Childhood Cancer Data Lab

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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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