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accession-icon GSE83722
Lipid biosynthesis coordinates a Mitochondrial to Cytosolic Stress Response
  • organism-icon Caenorhabditis elegans
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix C. elegans Genome Array (celegans)

Description

Defects in mitochondrial metabolism have been increasingly linked with age-onset protein misfolding diseases such as Alzheimers, Parkinsons, and Huntingtons. In response to protein folding stress, compartment-specific unfolded protein responses (UPRs) within the endoplasmic reticulum, mitochondria, and cytosol work in parallel to ensure cellular protein homeostasis. While perturbation of individual compartments can make other compartments more susceptible to protein stress, the cellular conditions that trigger cross-communication between the individual UPRs remain poorly understood.

Publication Title

Lipid Biosynthesis Coordinates a Mitochondrial-to-Cytosolic Stress Response.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE14897
Highly Efficient generation of Human Hepatic Cells from Induced Pluripotent Stem Cells.
  • organism-icon Homo sapiens
  • sample-icon 15 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Reprogrammed somatic cells offer a valuable source of pluripotent cells that have the potential to differentiate into many cells types and provide a new tool for regenerative medicine. In the present study we differentiated induced pluripotent stem cells (iPS cells) into hepatic cells. We first showed that mouse iPS cells could from a complete liver in mouse embryo (E14.5) including hepatocytes, endothelial cells, sinusoidal cells and resident macrophages. We then designed a highly efficient hepatocyte differentiation protocol using defined factors on human embryonic stem cells (ES cells). This protocol was found to generate more than 80% albumin expressing cells that show hepatic functions and express most of liver genes as shown by microarray analyses. Similar results were obtained when human iPS cells were induced to differentiate following the same procedure.

Publication Title

Highly efficient generation of human hepatocyte-like cells from induced pluripotent stem cells.

Sample Metadata Fields

Specimen part, Cell line

View Samples
accession-icon SRP099018
Single cell RNA expression of mouse embryonic basal forebrain
  • organism-icon Mus musculus
  • sample-icon 225 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Single-cell RNA-Seq RNA from medial ganglionic eminence at E11.5, E13.5, E15.5 or E17.5. The ID of this project in Genentech''s ExpressionPlot database is PRJ0007389 Overall design: Single-cell RNA-Seq from medial ganglionic eminence at E11.5, E13.5, E15.5 or E17.5.

Publication Title

Single-cell RNA sequencing identifies distinct mouse medial ganglionic eminence cell types.

Sample Metadata Fields

Specimen part, Subject

View Samples
accession-icon SRP098938
Embryonic stem cells-derived neural progenitor cells
  • organism-icon Mus musculus
  • sample-icon 140 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

J14 ES cells differentiated into MGE-like cells. Three groups of single-cell preparations were analyzed: ES cells (undifferentiated), differentiated cells (unsorted, of which less than 10% are GFP+) and GFP+ differentiated cells. These are specified in the "group" sample characteristic, with values "ES", "Unsorted" and "GFP+" respectively. The "SAMPLE_ID" sample characteristic is a sample identifier internal to Genentech. The ID of this project in Genentech''s ExpressionPlot database is PRJ0007904 Overall design: J14 ES cells differentiated into MGE-like cells

Publication Title

Single-cell RNA sequencing identifies distinct mouse medial ganglionic eminence cell types.

Sample Metadata Fields

Cell line, Subject

View Samples
accession-icon E-MEXP-1220
Transcription profiling by array of human T24 bladder cancer cells in response to hypericin-mediated photodynamic therapy in the absence or presence of the p38 MAPK inhibitor PD169316
  • organism-icon Homo sapiens
  • sample-icon 16 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A 2.0 Array (hgu133a2)

Description

Study of the gene expression of T24 bladder cancer cells in response to hypericin-mediated photodynamic therapy in the absence or presence of the p38 MAPK inhibitor PD169316

Publication Title

Molecular effectors and modulators of hypericin-mediated cell death in bladder cancer cells.

Sample Metadata Fields

Specimen part, Cell line, Compound

View Samples
accession-icon GSE94074
Expression data of Hematopoietic progenitor and stem cells after 18h of culture with or without extracellular vesicles secreted by AFT stromal cells
  • organism-icon Mus musculus
  • sample-icon 15 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 2.0 ST Array (mogene20st)

Description

Hematopoietic progenitor and stem cells from bone marrow have been sorted by FACS (LSK, Lineage -, Sca1 + and cKit +) and co-culture during 18h without cytokines with or without extracellular vesicles (EV) secreted by AFT stromal cells.

Publication Title

Extracellular vesicles of stromal origin target and support hematopoietic stem and progenitor cells.

Sample Metadata Fields

Specimen part

View Samples
accession-icon SRP132968
PolyA+ RNA-seq in a primary T-ALL patient cohort
  • organism-icon Homo sapiens
  • sample-icon 57 Downloadable Samples
  • Technology Badge IconNextSeq 500

Description

T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive type of blood cancer resulting from malignant transformation of T-cell precursors. Several oncogenes, including the 'T-cell leukemia homeobox 1' TLX1 (HOX11) transcription factor, have been identified as early driver events that cooperate with other genetic aberrations in leukemic transformation of progenitor T-cells. The TLX1 controlled transcriptome in T-ALL has been investigated extensively in the past in terms of protein-coding genes, but remains unexplored thus far at the level of long non-coding RNAs (lncRNAs), the latter renown as well-established versatile and key players implicated in various cancer hallmarks. In this study, we present the first extensive analysis of the TLX1 regulated transcriptome focusing on lncRNA expression patterns. We present an integrative analysis of polyA and total RNA sequencing of ALL-SIL lymphoblasts with perturbed TLX1 expression and a primary T-ALL patient cohort (including 5 TLX1+ and 12 TLX3+ cases). We expanded our initially presented dataset of TLX1 and H3K27ac ChIP data in ALL-SIL cells (Durinck et al., Leukemia, 2015) with H3K4me1, H3K4me3, and ATAC-seq data to accurately define (super-) enhancer marked lncRNAs and assigned potential functional annotations to candidate TLX1-controlled lncRNAs through an in silico guilt-by-association approach. Our study paves the way for further functional analysis of selected lncRNAs as potential novel therapeutic targets for a precision medicine approach in the context of T-ALL. Overall design: polyA+ RNA-seq data was generated for a primary T-ALL patient cohort

Publication Title

A comprehensive inventory of TLX1 controlled long non-coding RNAs in T-cell acute lymphoblastic leukemia through polyA+ and total RNA sequencing.

Sample Metadata Fields

Subject

View Samples
accession-icon SRP132970
Total RNA-seq in ALL-SIL upon TLX1 knockdown
  • organism-icon Homo sapiens
  • sample-icon 9 Downloadable Samples
  • Technology Badge IconNextSeq 500

Description

T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive type of blood cancer resulting from malignant transformation of T-cell precursors. Several oncogenes, including the 'T-cell leukemia homeobox 1' TLX1 (HOX11) transcription factor, have been identified as early driver events that cooperate with other genetic aberrations in leukemic transformation of progenitor T-cells. The TLX1 controlled transcriptome in T-ALL has been investigated extensively in the past in terms of protein-coding genes, but remains unexplored thus far at the level of long non-coding RNAs (lncRNAs), the latter renown as well-established versatile and key players implicated in various cancer hallmarks. In this study, we present the first extensive analysis of the TLX1 regulated transcriptome focusing on lncRNA expression patterns. We present an integrative analysis of polyA and total RNA sequencing of ALL-SIL lymphoblasts with perturbed TLX1 expression and a primary T-ALL patient cohort (including 5 TLX1+ and 12 TLX3+ cases). We expanded our initially presented dataset of TLX1 and H3K27ac ChIP data in ALL-SIL cells (Durinck et al., Leukemia, 2015) with H3K4me1, H3K4me3, and ATAC-seq data to accurately define (super-) enhancer marked lncRNAs and assigned potential functional annotations to candidate TLX1-controlled lncRNAs through an in silico guilt-by-association approach. Our study paves the way for further functional analysis of selected lncRNAs as potential novel therapeutic targets for a precision medicine approach in the context of T-ALL. Overall design: Total RNA-seq data was generated for the T-ALL cell line ALL-SIL upon TLX1 knockdown

Publication Title

A comprehensive inventory of TLX1 controlled long non-coding RNAs in T-cell acute lymphoblastic leukemia through polyA+ and total RNA sequencing.

Sample Metadata Fields

Cell line, Subject

View Samples
accession-icon SRP048603
RNA-sequencing of the GSI treatment of the CUTLL1 cell line
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2000

Description

Genetic studies in T-cell acute lymphoblastic leukemia have uncovered a remarkable complexity of oncogenic and loss-of-function mutations. Amongst this plethora of genetic changes, NOTCH1 activating mutations stand out as the most frequently occurring genetic defect, identified in more than 50% of T-cell acute lymphoblastic leukemias, supporting an essential driver role for this gene in T-cell acute lymphoblastic leukemia oncogenesis. In this study, we aimed to establish a comprehensive compendium of the long non-coding RNA transcriptome under control of Notch signaling. For this purpose, we measured the transcriptional response of all protein coding genes and long non-coding RNAs upon pharmacological Notch inhibition in the human T-cell acute lymphoblastic leukemia cell line CUTLL1 using RNA-sequencing. Similar Notch dependent profiles were established for normal human CD34+ thymic T-cell progenitors exposed to Notch signaling activity in vivo. In addition, we generated long non-coding RNA expression profiles (array data) from GSI treated T-ALL cell lines, ex vivo isolated Notch active CD34+ and Notch inactive CD4+CD8+ thymocytes and from a primary cohort of 15 T-cell acute lymphoblastic leukemia patients with known NOTCH1 mutation status. Integration of these expression datasets with publically available Notch1 ChIP-sequencing data resulted in the identification of long non-coding RNAs directly regulated by Notch activity in normal and malignant T-cell context. Given the central role of Notch in T-cell acute lymphoblastic leukemia oncogenesis, these data pave the way towards development of novel therapeutic strategies that target hyperactive Notch1 signaling in human T-cell acute lymphoblastic leukemia. Overall design: CUTLL1 cell lines were treated with Compound E (GSI) or DMSO (solvent control). Cells were collected 12 h and 48 h after treatment. This was performed for 3 replicates. RNA-sequencing was performed on these samples.

Publication Title

The Notch driven long non-coding RNA repertoire in T-cell acute lymphoblastic leukemia.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon SRP026537
Transcriptional profiling of a breast cancer cell line panel using RNAseq technology
  • organism-icon Homo sapiens
  • sample-icon 64 Downloadable Samples
  • Technology Badge IconIlluminaGenomeAnalyzerIIx

Description

56 breast cancer cell lines were profiled to identify patterns of gene expression associated with subtype and response to therapeutic compounds. Overall design: Cell lines were profiled in their baseline, unperturbed state.

Publication Title

Modeling precision treatment of breast cancer.

Sample Metadata Fields

No sample metadata fields

View Samples
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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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