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accession-icon SRP051765
Therapy induced tumour secretomes promote resistance and tumour progression
  • organism-icon Homo sapiens
  • sample-icon 41 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2000

Description

Drug resistance invariably limits the clinical efficacy of targeted therapy with kinase inhibitors against cancer. We found that targeted therapy with BRAF, ALK, or EGFR inhibitors induces a complex network of secreted signals in drug-stressed melanoma and lung adenocarcinoma cells. This therapy-induced secretome (TIS) stimulates the outgrowth, infiltration and metastasis of drug-resistant cancer clones in the tumour. Additionally, the TIS supports the survival of drug-sensitive cells, contributing to incomplete tumour regression. We used transcriptomic analysis of sensitive tumour cells and xenograft tumours treated with vehicle, vemurafenib, or crizotinib to identify the transcriptional drivers and to dissect the TIS in melanoma (A375, Colo800, UACC62) and lung adenocarcinoma (H3122). In addition, we utilize cell type–specific mRNA purification by translating ribosome affinity purification (TRAP) to identify pathways that are up-regulated in resistant cells (A375R) in response to the regressing tumour microenvironment. Overall design: Analysis of the response of drug sensitive melanoma and lung adenocarcinoma cells to pharmacological inhibition of their driver oncogene and gene expression analysis of drug resistant cancer cells responding to different tumor microenvironments.

Publication Title

Therapy-induced tumour secretomes promote resistance and tumour progression.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE31504
Impact of Gene Expression Profiling Based Risk Stratification in Patients with Myeloma Receiving Initial Therapy with Lenalidomide and Dexamethasone
  • organism-icon Homo sapiens
  • sample-icon 45 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Detection of specific chromosomal abnormalities by FISH and metaphase cytogenetics allows risk stratification in multiple myeloma (MM); however, gene expression profiling (GEP) based signatures may enable more specific risk categorization.

Publication Title

Impact of gene expression profiling-based risk stratification in patients with myeloma receiving initial therapy with lenalidomide and dexamethasone.

Sample Metadata Fields

Specimen part, Disease

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accession-icon GSE31452
Cereblon expression is required for the anti-myeloma activity of lenalidomide and pomalidomide
  • organism-icon Homo sapiens
  • sample-icon 15 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Cereblon expression is required for the antimyeloma activity of lenalidomide and pomalidomide.

Sample Metadata Fields

Cell line

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accession-icon GSE31421
Cereblon expression is required for the anti-myeloma activity of lenalidomide and pomalidomide [expression profiling]
  • organism-icon Homo sapiens
  • sample-icon 15 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The precise molecular mechanism of action and targets through which thalidomide and related immunomodulatory drugs (IMiDs) exert their anti-tumor effects remains unclear. We investigated the role of cereblon (CRBN), a primary teratogenic target of thalidomide, in the anti-myeloma activity of IMiDs. CRBN depletion is initially cytotoxic to human myeloma cells but surviving cells with stable CRBN depletion become highly resistant to both lenalidomide and pomalidomide, but not to the unrelated drugs bortezomib, dexamethasone and melphalan. Acquired deletion of CRBN was found to be the primary genetic event differentiating isogenic MM1.S cell lines cultured to be sensitive or resistant to lenalidomide and pomalidomide. Gene expression changes induced by lenalidomide were dramatically suppressed in the presence of CRBN depletion further demonstrating that CRBN is required for lenalidomide activity. Downstream targets of CRBN include interferon regulatory factor 4 (IRF4) previously reported to also be a target of lenalidomide. Patients exposed to and putatively resistant to lenalidomide had lower CRBN levels in paired samples before and after therapy. In summary, CRBN is an essential requirement for IMiD activity, and a possible biomarker for the clinical assessment of anti-myeloma efficacy.

Publication Title

Cereblon expression is required for the antimyeloma activity of lenalidomide and pomalidomide.

Sample Metadata Fields

Cell line

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accession-icon GSE48046
Gene expression analysis of Early immature and Late mature T-ALL cell lines
  • organism-icon Homo sapiens
  • sample-icon 16 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Early immature T-cell acute lymphoblastic leukemias (T-ALLs) account for about 5-10% of pediatric T-ALLs and are associated with poor prognosis. However, the genetic defects that drive the biology of these tumors remain largely unknown. Analysis of microarray gene expression signatures in adult T-ALL demonstrated a high prevalence of early immature leukemias and revealed a close relationship between these tumors and myeloid leukemias. Consistently, adult immature T- ALLs showed characteristic mutations in myeloid specific oncogenes and tumor suppressors including IDH1, IDH2, DNMT3A, FLT3 and NRAS. Moreover, we identified ETV6 mutations as a novel genetic lesion uniquely present in immature adult T-ALL. All together, our results demonstrate that early immature adult T- ALL represents a heterogeneous category of leukemias characterized by the presence of overlapping myeloid and T-ALL characteristics and highlight the role of ETV6 mutations in these tumors.

Publication Title

ETV6 mutations in early immature human T cell leukemias.

Sample Metadata Fields

Specimen part

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accession-icon GSE36825
Clonal competition with alternating dominance in multiple myeloma
  • organism-icon Homo sapiens
  • sample-icon 42 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Clonal competition with alternating dominance in multiple myeloma.

Sample Metadata Fields

Specimen part

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accession-icon GSE36824
Clonal competition with alternating dominance in multiple myeloma [GEP]
  • organism-icon Homo sapiens
  • sample-icon 42 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Copy number and expression profiling of multiple myeloma patients at multiple stages of their individual clinical course

Publication Title

Clonal competition with alternating dominance in multiple myeloma.

Sample Metadata Fields

Specimen part

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accession-icon SRP074299
A single-cell transcriptome atlas of the human pancreas
  • organism-icon Homo sapiens
  • sample-icon 18 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500, NextSeq 500

Description

To understand organ (dys)function it is important to have a complete inventory of its cell types and the corresponding markers that unambiguously identify these cell types. This is a challenging task, in particular in human tissues, because unique cell-type markers are typically unavailable, necessitating the analysis of complex cell type mixtures. Transcriptome-wide studies on pancreatic tissue are typically done on pooled islet material. To overcome this challenge we sequenced the transcriptome of thousands of single pancreatic cells from deceased organ donors with and without type 2 diabetes (T2D) allowing in silico purification of the different cell types. We identified the major pancreatic cell types resulting in the identification of many new cell-type specific and T2D-specific markers. Additionally we observed several subpopulations within the canonical pancreatic cell types, which we validated in situ. This resource will be useful for developing a deeper understanding of pancreatic biology and diabetes mellitus. Overall design: Human cadaveric pancreata were used to extract islets of Langerhans, which were kept in culture until single-cell dispersion and FACS sorting. Single-cell transcriptomics was performed on live cells from this mixture using CEL-seq or on cells stained for CD63, CD13, TGFBR3 or CD24 and CD44. The RaceID algorithm was used to identify clusters of cells corresponding to the major pancreatic cell types and to mine for novel cell type-specific genes as well as subpopulations within the known pancreatic cell types.

Publication Title

De Novo Prediction of Stem Cell Identity using Single-Cell Transcriptome Data.

Sample Metadata Fields

Specimen part, Subject

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accession-icon SRP067892
Single-cell RNA-seq reveals distinct maturation stages of the Paneth cell lineage
  • organism-icon Mus musculus
  • sample-icon 13 Downloadable Samples
  • Technology Badge IconNextSeq 500, Illumina HiSeq 2500

Description

Paneth cells (PCs) are long-lived secretory cells that reside at the bottoms of small intestinal crypts. Besides serving as niche cells for the neighboring Lgr5-positive stem cells, PCs secrete granules containing a broad spectrum of antimicrobial proteins, including lysozymes and defensins1. Here, we have used single-cell RNA sequencing to explore PC differentiation. We found a maturation gradient from early secretory progenitors to mature PCs, capturing the full maturation path of PCs. Moreover, differential expression of a subset of defensin genes in lysozyme-high PCs, e.g. Defa20, reveals at least two distinct stages of maturation. Overall design: We traced Lgr5+ stem cells from Lgr5-CreERT2 C57Bl6/J mice bred to a Rosa26LSL-YFP reporter mice and sorted YFP+ cells 5 days, 3 weeks and 8 weeks after tamoxifen injection.

Publication Title

De Novo Prediction of Stem Cell Identity using Single-Cell Transcriptome Data.

Sample Metadata Fields

Specimen part, Cell line, Subject

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accession-icon SRP073803
Producing enteroendocrine cells from Lgr5+ intestinal stem cells by manipulating quiescence
  • organism-icon Mus musculus
  • sample-icon 58 Downloadable Samples
  • Technology Badge IconNextSeq 500

Description

Lgr5+ adult intestinal stem cells are highly proliferative throughout life. Single Lgr5+ stem cells can be cultured into 3D epithelial organoids containing all cell types at nearnormal ratios. Culture conditions to generate the main cell types have been established previously, but signals inducing the various types of enteroendocrine cells (EECs) have remained elusive. Here we generate quiescent Lgr5+ stem cells in vitro by inhibition of the EGF-receptor (EGFR) and mitogen-associated protein kinase (MAPK) signaling pathways in organoids, a state that can be readily reversed. Quiescent Lgr5+ stem cells gain a distinct molecular signature, biased towards EEC differentiation. Indeed, combined inhibition of Wnt, Notch and MAPK pathways efficiently generates a diversity of EEC subtypes in vitro. Our observations uncouple Wnt-dependent stem cell maintenance from EGF-dependent proliferation and cell fate choice, and provide an in vitro approach for the study of the elusive EECs. Overall design: We established a stable culture of quiescent Lgr5+ intestinal stem cells in culture. These highly resemble quiescent secretory precursors, which has high EEC differentiation potential. Following on this lead, we elucidated what signals are required to generate EEC cells of all varieties, and provide a method to produce these EEC cells in large numbers.

Publication Title

Induced Quiescence of Lgr5+ Stem Cells in Intestinal Organoids Enables Differentiation of Hormone-Producing Enteroendocrine Cells.

Sample Metadata Fields

Specimen part, Cell line, Subject

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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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