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accession-icon SRP078563
Unbiased genomic analysis of multiple stages of lung cancer development
  • organism-icon Mus musculus
  • sample-icon 50 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

To uncover the gene expression alterations that occur during lung cancer progression, we interrogated the gene expression state of neoplastic cells at different stages of malignant progression. We initiated tumors in KrasLSL-G12D/+;p53flox/flox;R26LSL-tdTomato (KPT) mice with a pool of barcoded lentiviral-Cre vectors and purified Tomatopositive cancer cells away from the diverse and variable stromal cell populations. Five to nine months after tumor initiation, cancer cells were isolated from individual primary tumors and metastases using fluorescence-activated cell sorting. Sequencing of the barcode region of the integrated lentiviral vectors established primary tumor-metastasis and metastasis-metastasis relationships. Tumor barcoding allowed us to unequivocally distinguish non-metastatic primary tumors (TnonMet) from those primary tumors that had seeded metastases (TMet). We profiled 10 TnonMet samples as well as TMet and metastasis (Met) samples representing 12 metastatic events. To examine additional earlier stages of lung cancer development, we also analyzed premalignant cells from hyperplasias that develop in KPT mice shortly after tumor initiation (KPT-Early; KPT-E), as well as tumors from KrasG12D;R26LSL-tdTomato (KT) mice which rarely gain metastatic ability Overall design: This study includes 52 samples: 3 KP late samples, 3KPT early samples,10 non-metastatic primary tumors, 9 metastatic primary tumors, and 27 metastasis in different organs. total RNA was isolated and prepared for sequencing using the Ovation® RNA-Seq system and Illumina TruSeq DNA kit (v2) to generate 100bp paired end reads. Reads were aligned to mm10.

Publication Title

Molecular definition of a metastatic lung cancer state reveals a targetable CD109-Janus kinase-Stat axis.

Sample Metadata Fields

Subject

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accession-icon GSE25182
tTA/TDP Mice Expression Array
  • organism-icon Mus musculus
  • sample-icon 21 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430A 2.0 Array (mouse430a2)

Description

Transgenic (Tg) mice expressing nuclear or cytoplasmic human TDP-43 were generated.

Publication Title

Dysregulation of the ALS-associated gene TDP-43 leads to neuronal death and degeneration in mice.

Sample Metadata Fields

Sex

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accession-icon SRP144495
Identifying dormant cells in colorectal cancer spheroids
  • organism-icon Homo sapiens
  • sample-icon 384 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Cellular dormancy and heterogeneous cell cycle lengths provide important explanations for treatment failure following adjuvant therapy with S-phase cytotoxics in colorectal cancer (CRC) yet the molecular control of the dormant versus cycling state remains unknown. In CRCs dormant cells are found to be highly clonogenic and resistant to chemotherapies. We sought to understand the molecular features of dormant CRC cells to facilitate rationale identification of compounds to target both dormant and cycling tumour cells. Overall design: Six colorectal cancer cell lines (DLD1, HCT15, HT55, SW948, RKO and SW48) were labelled with the cell permeable dye CFSE and then grown in non-adherent spheroid culture for 6 days to enable identification of dormant cells that retain CFSE (LRC) and cycling cells (BULK). LRCs and BULK populations were then FACS sorted from each cell line in quadruplicate. As a control experiment, to identify off-target effects of the CFSE dye and culture artefacts, BULK populations from DLD1 cells at d1 and d6 after seeding both with and without CFSE labelling were included in the RNAseq analysis. RNA was extracted using the RNAeasy Micro Plus kit (Qiagen) and quantified using the Qubit RNA Assay Kit (Thermo Fisher Scientific). RNA quality was assessed using the Agilent Bioanalyser system as per manufacturer's instructions. Following normalisation and sample randomisation, Truseq library (Illumina) preparation was carried out at the CRUK CI genomics facility and subsequent single end, 50bp sequencing using the HiSeq system (Illumina). Following human genome alignment (hg19), read counts were normalised and differential expression tested using the DEseq protocol.

Publication Title

Itraconazole targets cell cycle heterogeneity in colorectal cancer.

Sample Metadata Fields

Specimen part, Cell line, Subject

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accession-icon SRP144496
Identifying the molecular mode of action of itraconazole in colorectal cancer
  • organism-icon Homo sapiens
  • sample-icon 16 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Two cell lines (HT55 and SW948) were found responsive to itraconazole treatment. To identify the mode of action cells were treated with itraconazole or control (DMSO) and then subjected to RNAseq analysis once the phenotype had developed Overall design: HT55 and SW948 cells were seeded in adherent culture and treated with 5uM itraconazole or DMSO for 6 days. Cells then underwent RNA extraction using the RNAeasy Micro Plus kit (Qiagen) and quantified using the Qubit RNA Assay Kit (Thermo Fisher Scientific). RNA quality was assessed using the Agilent Bioanalyser system as per manufacturer's instructions. Following normalisation and sample randomisation, Truseq library (Illumina) preparation was carried out at the CRUK CI genomics facility and subsequent single end, 50bp sequencing using the HiSeq system (Illumina). Following human genome alignment (hg19), read counts were normalised and differential expression tested using the DEseq protocol.

Publication Title

Itraconazole targets cell cycle heterogeneity in colorectal cancer.

Sample Metadata Fields

Specimen part, Cell line, Treatment, Subject

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accession-icon GSE43487
Mammary tumors
  • organism-icon Mus musculus
  • sample-icon 7 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

Inherited variation in miR-290 expression suppresses breast cancer progression by targeting the metastasis susceptibility gene Arid4b.

Sample Metadata Fields

Specimen part, Treatment

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accession-icon GSE43485
Expression profiling in miR-290 6dt1 mammary tumors
  • organism-icon Mus musculus
  • sample-icon 7 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

mRNA expression data from mammary tumors extracted 30 days after orthotopic injection of miR-290-expressing and negative control 6dt1 cells into female FVB/N mice.

Publication Title

Inherited variation in miR-290 expression suppresses breast cancer progression by targeting the metastasis susceptibility gene Arid4b.

Sample Metadata Fields

Specimen part, Treatment

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accession-icon SRP049257
A negative feedback loop of transcription factors specifies alternative dendritic cell chromatin states (RNA-Seq)
  • organism-icon Mus musculus
  • sample-icon 48 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq1500

Description

During hematopoiesis, cells originating from the same stem cell reservoir differentiate into distinct cell types. The mechanisms enabling common progenitors to differentiate into distinct cell fates are not fully understood. Here, we identify chromatin-regulating and cell-fate-determining transcription factors (TF) governing dendritic cell (DC) development by annotating the enhancer and promoter landscapes of the DC lineage. Combining these analyses with detailed over-expression, knockdown and ChIP-Seq studies, we show that Irf8 functions as a plasmacytoid DC epigenetic and fate-determining TF, regulating massive, cell-specific chromatin changes in thousands of pDC enhancers. Importantly, Irf8 forms a negative feedback loop with Cebpb, a monocyte-derived DC epigenetic fate-determining TF. We show that using this circuit logic, differential activity of TF can stably define epigenetic and transcriptional states, regardless of the microenvironment. More broadly, our study proposes a general paradigm that allows closely related cells with a similar set of signal-dependent factors to generate differential and persistent enhancer landscapes. Overall design: Here analyzed 2 experiments, each one contains samples of moDC and pDC ex vivo cultured cells. The first experiment contains 32 samples of moDC and pDC following stimulation with various TLR stimulators. The second experiment contains 8 samples of moDC and pDC following perturbations; Cebpb and Irf8 knock down or over expression.

Publication Title

A negative feedback loop of transcription factors specifies alternative dendritic cell chromatin States.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP007569
SuperSAGE evidence for CD14++CD16+ monocytes as a third monocyte subset
  • organism-icon Homo sapiens
  • sample-icon 3 Downloadable Samples
  • Technology Badge IconIlluminaGenomeAnalyzerIIx

Description

Monocytes are a heterogeneous cell population with subset-specific functions and phenotypes. The differential expression of CD14 and CD16 distinguishes classical CD14++CD16-, intermediate CD14++CD16+ and non-classical CD14+CD16++ monocytes. However, CD14++CD16+ monocytes remain the most poorly characterized subset so far. Therefore we analyzed the transcriptomes of the three monocyte subsets using SuperSAGE in combination with high-throughput sequencing. Analysis of 5,487,603 tags revealed unique identifiers of CD14++CD16+ monocytes, delineating these cells from the two other monocyte subsets. CD14++CD16+ monocytes were linked to antigen processing and presentation (e.g. CD74, HLA-DR, IFI30, CTSB), to inflammation and monocyte activation (e.g. TGFB1, AIF1, PTPN6), and to angiogenesis (e.g. TIE2, CD105). Therefore we provide genetic evidence for a distinct role of CD14++CD16+ monocytes in human immunity. Overall design: Human monocyte subsets (CD14++CD16-, CD14++CD16+, CD14+CD16++) were isolated from 12 healthy volunteers based on MACS technology. Total RNA from monocyte subsets was isolated and same aliquots from each donor and monocyte subset were matched for SuperSAGE. Three SuperSAGE libraries (CD14++CD16-, CD14++CD16+ and CD14+CD16++) were generated.

Publication Title

SuperSAGE evidence for CD14++CD16+ monocytes as a third monocyte subset.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP049942
Tissue-resident macrophage enhancer landscapes are shaped by the local microenvironment [RNA-seq]
  • organism-icon Mus musculus
  • sample-icon 26 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 1500

Description

Macrophages are hematopoietic cells critical for innate immune defense, but also control organ homeostasis in a tissue-specific manner. Tissue-resident macrophages, therefore, provide a well-defined model to study the impact of ontogeny and microenvironment on chromatin state. Here, we profile the dynamics of four histone modifications across seven tissue-resident macrophage populations, as well as monocytes and neutrophils. We identify 12,743 macrophage-specific enhancers and establish that tissue-resident macrophages have distinct enhancer landscapes. Our work suggests that a combination of tissue and lineage-specific transcription factors form the regulatory networks controlling chromatin specification in tissue-resident macrophages. The environment has the capacity to alter the chromatin landscape of macrophages derived from transplanted adult bone marrow in vivo and even differentiated macrophages are reprogramed when transferred into a new tissue. Altogether, these data provide a comprehensive view of macrophage regulation and highlight the importance of microenvironment along with pioneer factors in orchestrating macrophage identity and plasticity. Overall design: 7 tissue-resident macrophage populations were isolated, as well as monocytes and neutrophils, and transcriptome analysis was performed. Experiment was done in duplicates.

Publication Title

Tissue-resident macrophage enhancer landscapes are shaped by the local microenvironment.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE76148
Genome wide comparison of the inducible transcriptomes of CAR, PXR and PPAR in primary human hepatocytes
  • organism-icon Homo sapiens
  • sample-icon 24 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

To identify the CAR-, PXR- and PPAR-specific genome-wide expression changes, hepatocyte cultures from six individual donors were treated with the prototypical ligands for

Publication Title

Genomewide comparison of the inducible transcriptomes of nuclear receptors CAR, PXR and PPARα in primary human hepatocytes.

Sample Metadata Fields

Sex, Age

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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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