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accession-icon SRP073206
Transcriptome analysis in a radiosensitive and a radioresistant cell line after ionizing radiation
  • organism-icon Homo sapiens
  • sample-icon 20 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Differential gene expression profiling was performed in two lymphoblastoid cell lines with different radiosentivitity, one radiosensitive (RS) and another radioresistant (RR), after different post-irradiation times. A greater and a prolonged transcriptional response after irradiation was induced in the RS cell line. Functional analysis showed that 24 h after irradiation genes involved in DNA damage response, negative regulation of the cell cycle and apoptosis were still differentially up-regulated in the RS cell line but not in the RR cell line. Overall design: Sham-irradiated and irradiated (2 Gy) cell cultures of the RS and the RR cell line were incubated at 37ºC for 4 and 24 h and 14 days. After that, RNA was extracted and sequenced with QuantSeq technology

Publication Title

Differences in DNA Repair Capacity, Cell Death and Transcriptional Response after Irradiation between a Radiosensitive and a Radioresistant Cell Line.

Alternate Accession IDs

GSE80207

Sample Metadata Fields

Specimen part, Cell line, Treatment, Subject, Time

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accession-icon GSE46602
Expression data from prostate cancer and benign prostate glands
  • organism-icon Homo sapiens
  • sample-icon 42 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Prostate cancer is a leading cause of cancer death amongst males. The main clinical dilemma in treating prostate cancer is the high number of indolent cases that confer a significant risk of over diagnosis and over treatment. In this study we have performed a genome expression profiling of tumor tissue specimens from 36 patients with prostate cancer to identify transcripts that delineate aggressive and indolent cancer. We included normal prostate biopsies from 14 patients in our analysis. Unsupervised hierarchical cluster analysis separated the cancer samples into two groups with a significant overrepresentation of tumors from patients with biochemical recurrence in one of the groups (Chi2, p=0.02). The samples were separated by basically three clusters of genes that showed differential expression between the two sample clusters - totaling 371 transcripts. Ingenuity Pathway Analysis revealed that one cluster contained genes associated with invasive properties of the tumor, another genes associated with the cell cycle, and the last cluster genes involved in several biological functions. We successfully validated the transcripts association with recurrence using two publicly available patient datasets totaling 669 patients. Twelve genes were found to be independent predictors of recurrence in multivariate logistical regression analysis.

Publication Title

Expression profiling of prostate cancer tissue delineates genes associated with recurrence after prostatectomy.

Alternate Accession IDs

E-GEOD-46602

Sample Metadata Fields

Age, Specimen part

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accession-icon GSE44387
Transcriptomal profiling of C57BL/6 wild type and ER-alpha KO mice fetal mammary gland after fetal exposure to Bisphenol A (BPA) and 17alpha-ethynylestradiol (EE2)
  • organism-icon Mus musculus
  • sample-icon 36 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

To examine whether the BPA-induced morphological alterations of the fetal mouse mammary glands are a) associated with changes in mRNA expression reflecting estrogenic actions and/or b) dependent on the estrogen receptor (ER), we compared the transcriptomal effects of BPA and the steroidal estrogen ethinylestradiol (EE2) on fetal mammary tissues of wild type and ER knock-out mice.

Publication Title

Low-dose BPA exposure alters the mesenchymal and epithelial transcriptomes of the mouse fetal mammary gland.

Alternate Accession IDs

E-GEOD-44387

Sample Metadata Fields

Sex, Specimen part

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accession-icon GSE108404
A translational repression complex in developing mammalian neural stem cells that regulates neuronal specification
  • organism-icon Mus musculus
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 2.0 ST Array (mogene20st)

Description

The mechanisms instructing genesis of neuronal subtypes from mammalian neural precursors are not well-understood. To address this issue, we have characterized the transcriptional landscape of radial glial precursors (RPs) in the embryonic murine cortex. We show that individual RPs express mRNA but not protein for transcriptional specifiers of both deep and superficial layer cortical neurons. Some of these mRNAs, including the superficial versus deep layer neuron transcriptional regulators Brn1 and Tle4, are translationally repressed by their association with the RNA-binding protein Pumilio2 and the 4E-T protein. When these repressive complexes are disrupted in RPs mid-neurogenesis by knocking down 4E-T or Pum2, this causes aberrant co-expression of deep layer neuron specification proteins in newborn superficial neurons. Thus, cortical RPs are transcriptionally primed to generate diverse types of neurons, and a 4E-T-Pum2 complex represses translation of some of these neuronal identity mRNAs to ensure appropriate temporal specification of daughter neurons.

Publication Title

A Translational Repression Complex in Developing Mammalian Neural Stem Cells that Regulates Neuronal Specification.

Alternate Accession IDs

E-GEOD-108404

Sample Metadata Fields

Specimen part

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accession-icon SRP125263
Developmental emergence of adult neural stem cells as revealed by single cell transcriptional profiling
  • organism-icon Mus musculus
  • sample-icon 7 Downloadable Samples
  • Technology Badge IconNextSeq 500

Description

Adult neural stem cells (NSCs) derive from embryonic precursors, but little is known about how or when this occurs. We have addressed this issue using single cell RNAseq at multiple developmental timepoints to analyze the embryonic murine cortex, one source of adult forebrain NSCs. We computationally identify all major cortical cell types, including the embryonic radial precursors (RPs) that generate adult NSCs. We define the initial emergence of RPs from neuroepithelial stem cells at E11.5. We show that by E13.5 these RPs express a transcriptional identity that is maintained and reinforced throughout their transition to a non-proliferative state between E15.5 and E17.5. These slowly-proliferating late embryonic RPs share a core transcriptional phenotype with quiescent adult forebrain NSCs. Together, these findings support a model where cortical RPs maintain a core transcriptional identity from embryogenesis through to adulthood, and where the transition to a quiescent adult NSC occurs during late neurogenesis. Overall design: We applied the high-throughput single-cell mRNA sequencing technique, Drop-seq, to the embryonic mouse cortex. 2000-5000 single cells from wildtype CD1 embryos of gestational ages E11.5, E13.5, E15.5 and E17.5 were characterized.

Publication Title

Developmental Emergence of Adult Neural Stem Cells as Revealed by Single-Cell Transcriptional Profiling.

Alternate Accession IDs

GSE107122

Sample Metadata Fields

Specimen part, Cell line, Subject

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accession-icon GSE84482
Proneurogenic ligands defined by modeling developing cortex growth factor communication networks
  • organism-icon Mus musculus
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 2.0 ST Array (mogene20st)

Description

The neural stem cell decision to self-renew or differentiate is tightly regulated by its microenvironment. Here, we have asked about this microenvironment, focusing on growth factors in the embryonic cortex at a time when it is largely comprised of neural precursor cells (NPCs) and newborn neurons. We show that cortical NPCs secrete factors that promote their maintenance while cortical neurons secrete factors that promote differentiation. To define factors important for these activities, we used transcriptome profiling to identify ligands produced by NPCs and neurons, cell surface mass spectrometry to identify receptors on these cells, and computational modeling to integrate these data. The resultant model predicts a complex growth factor environment with multiple autocrine and paracrine interactions. We tested this communication model, focusing on neurogenesis, and identified IFN, Nrtn and glial-derived neurotrophic factor (GDNF) as ligands with unexpected roles in promoting neurogenic differentiation of NPCs in vivo.

Publication Title

Proneurogenic Ligands Defined by Modeling Developing Cortex Growth Factor Communication Networks.

Alternate Accession IDs

E-GEOD-84482

Sample Metadata Fields

Specimen part

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accession-icon SRP068907
mRNA-seq of nuclear RNA extracted from T4 and T5 neurons of D. melanogaster
  • organism-icon Drosophila melanogaster
  • sample-icon 2 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

T4 and T5 neurons are components of the neuronal circuit for motion vision in flies. To identify genes involved in neuronal computation of T4 and T5 neurons, we perfomed transcriptome analysis. Nuclei of T4 and T5 neurons were immunoprecipitated, total RNA was harvested and used for mRNA-seq with Illumina technology. In two biological replicates, we mapped 154 and 119 million reads to D. melanogaster genome. mRNA-seq provided information about expression levels of 17,468 annotated transcripts in the T4 and T5 neurons. Overall design: Cell type – specific transcriptome analysis of the RNA isolated from immunoprecipitated nuclei, performed in two biological replicates

Publication Title

RNA-Seq Transcriptome Analysis of Direction-Selective T4/T5 Neurons in Drosophila.

Alternate Accession IDs

GSE77198

Sample Metadata Fields

Subject

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accession-icon GSE56237
Microarray data of FACS purified population isolated from AML patients.
  • organism-icon Homo sapiens
  • sample-icon 21 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

We isolated hematopoietic stem and progenitor cells from AML patients by FACS.

Publication Title

Cellular origin of prognostic chromosomal aberrations in AML patients.

Alternate Accession IDs

E-GEOD-56237

Sample Metadata Fields

Specimen part

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accession-icon GSE42519
The Hematopoietic System - Myeloid arm
  • organism-icon Homo sapiens
  • sample-icon 33 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

We used microarray to create a normal cell landscape for the myeloid arm of the hematopoietic system.

Publication Title

Comparing cancer vs normal gene expression profiles identifies new disease entities and common transcriptional programs in AML patients.

Alternate Accession IDs

E-GEOD-42519

Sample Metadata Fields

Specimen part

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accession-icon GSE18113
Expression data from Human MicroVascular Endothelial Cells (HMVECS)
  • organism-icon Homo sapiens
  • sample-icon 18 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The activation of endothelium by tumor cells is one of the main steps by tumor metastasis. The role of the blood components (platelets and leukocytes) in this process remain unclear.

Publication Title

Selectin-mediated activation of endothelial cells induces expression of CCL5 and promotes metastasis through recruitment of monocytes.

Alternate Accession IDs

E-GEOD-18113

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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