refine.bio
  • Search
      • Normalized Compendia
      • RNA-seq Sample Compendia
  • Docs
  • About
  • My Dataset
github link
Showing
of 103 results
Sort by

Filters

Technology

Platform

accession-icon GSE24183
Genomic profiling of enzastaurin-treated B cell lymphoma RL cells
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Follicular lymphoma (FL) is an indolent lymphoma associated with follicular center B cells, and typically contains the Bcl-2 chromosomal translocation t(14;18), which leads to overexpression of the anti-apoptotic intracellular protein Bcl-2. FLs are sensitive to chemotherapy; however, patient relapses occur and response duration becomes progressively shorter, with the majority of patients eventually dying from the disease. Enzastaurin (LY317615), an acyclic bisindolylmaleimide, was initially developed as an ATP-competitive selective inhibitor of PKC. We found, in agreement with recent reports, that enzastaurin inhibits cell proliferation and induces apoptosis. These results are consistent with decreased phosphorylation of the Akt pathway and its downstream targets. To provide new insights into the anti-tumor action of enzastaurin on non-Hodgkin lymphoma, we investigated its effects on gene expression profiles of the B cell lymphoma RL cell line by oligonucleotide microarray analysis. We identified a set of 41 differentially expressed genes, mainly involved in cellular adhesion, apoptosis, inflammation, and immune and defense responses. These observations provide new insights into the mechanisms involved in the induction of apoptosis by enzastaurin in B cell lymphoma cell lines, and identify possible pathways that may contribute to the induction of apoptosis.

Publication Title

Genomic profiling of enzastaurin-treated B cell lymphoma RL cells.

Sample Metadata Fields

Specimen part, Cell line, Treatment

View Samples
accession-icon GSE87830
In silico characterization of miRNA and long non-coding RNA interplay in multiple myeloma
  • organism-icon Homo sapiens
  • sample-icon 256 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

In Silico Characterization of miRNA and Long Non-Coding RNA Interplay in Multiple Myeloma.

Sample Metadata Fields

Specimen part, Disease

View Samples
accession-icon GSE87829
In silico characterization of miRNA and long non-coding RNA interplay in multiple myeloma (95 MM lncRNA data sets)
  • organism-icon Homo sapiens
  • sample-icon 94 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

The identification of deregulated microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) in multiple myeloma (MM) has progressively added a further level of complexity to MM biology. In addition, the cross-regulation between lncRNAs and miRNAs has begun to emerge, and theoretical and experimental studies have demonstrated the competing endogenous RNAs (ceRNAs) activity of lncRNAs as natural miRNA decoys in pathophysiological conditions, including cancer. Currently, information concerning lncRNA and miRNA interplay in MM is virtually absent. Herein, we investigated in silico the lncRNA and miRNA relationship in a representative datasets encompassing 95 MM and 30 plasma cell leukemia patients at diagnosis and in four normal controls, whose expression profiles were generated by a custom annotation pipeline to detect specific lncRNAs. We applied target prediction analysis based on miRanda and RNA22 algorithms to 235 lncRNAs and 459 miRNAs selected with a potential pivotal role in the pathology of MM. Among pairs that showed significant correlation between lncRNA and miRNA expression levels, we identified 10 lncRNA-miRNA relationships suggestive of novel ceRNA network with relevance in MM.

Publication Title

In Silico Characterization of miRNA and Long Non-Coding RNA Interplay in Multiple Myeloma.

Sample Metadata Fields

Specimen part, Disease

View Samples
accession-icon GSE106745
In silico characterization of miRNA and long non-coding RNA interplay in multiple myeloma (30 PCL lncRNA data sets)
  • organism-icon Homo sapiens
  • sample-icon 33 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

The identification of deregulated microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) in multiple myeloma (MM) has progressively added a further level of complexity to MM biology. In addition, the cross-regulation between lncRNAs and miRNAs has begun to emerge, and theoretical and experimental studies have demonstrated the competing endogenous RNAs (ceRNAs) activity of lncRNAs as natural miRNA decoys in pathophysiological conditions, including cancer. Currently, information concerning lncRNA and miRNA interplay in MM is virtually absent. Herein, we investigated in silico the lncRNA and miRNA relationship in a representative datasets encompassing 95 MM and 30 plasma cell leukemia patients at diagnosis and in four normal controls, whose expression profiles were generated by a custom annotation pipeline to detect specific lncRNAs. We applied target prediction analysis based on miRanda and RNA22 algorithms to 235 lncRNAs and 459 miRNAs selected with a potential pivotal role in the pathology of MM. Among pairs that showed significant correlation between lncRNA and miRNA expression levels, we identified 10 lncRNA-miRNA relationships suggestive of novel ceRNA network with relevance in MM.

Publication Title

In Silico Characterization of miRNA and Long Non-Coding RNA Interplay in Multiple Myeloma.

Sample Metadata Fields

Specimen part, Disease

View Samples
accession-icon SRP149377
ADAR1-editing in HeLa, p150-KO and ADAR1-KO transcriptomes
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 4000

Description

RNAseq analysis of cell lines with ADAR1-p150 and ADAR1-p110 knock-outs and primary human tissue samples (from GSE57353 and GSE99392 data sets) to identify sites of ADAR1 editing Overall design: 12 samples: 3 cell lines (HeLa, HeLa-p150KO, HeLa-ADAR1KO) with four conditions each (no treatment, MeV-vac2(GFP)-infected, MeV-CKO(GFP)-infected, IFNA/D-treated). One biological replicate per sample. In addition, raw data files of 9 samples from series GSE57353 and GSE99392 were re-analyzed using the same data processing pipeline.

Publication Title

Extensive editing of cellular and viral double-stranded RNA structures accounts for innate immunity suppression and the proviral activity of ADAR1p150.

Sample Metadata Fields

Cell line, Subject

View Samples
accession-icon SRP075876
Cerebral Organoids Recapitulate Epigenomic Signatures of the Human Fetal Brain
  • organism-icon Homo sapiens
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon

Description

Organoids derived from human pluripotent stem cells recapitulate the early three-dimensional organization of human brain, but whether they establish the epigenomic and transcriptional programs essential for brain development is unknown. We compared epigenomic and gene regulatory features in cerebral organoids and human fetal brain, using genome-wide, base resolution DNA methylome and transcriptome sequencing. Transcriptomic dynamics in organoids faithfully modeled gene expression trajectories in early-to-mid human fetal brains. We found that early non-CG methylation accumulation at super-enhancers in both fetal brain and organoids marks forthcoming transcriptional repression in the fully developed brain. 74% of 35,627 demethylated regions identified during organoid differentiation overlapped with fetal brain regulatory elements. Interestingly, pericentromeric repeats showed widespread demethylation in multiple types of in vitro human neural differentiation models but not in fetal brain. Our study reveals that organoids recapitulate many epigenomic features of mid-fetal human brain and also identified novel non-CG methylation signatures of brain development. Overall design: MethylC-seq and RNA-seq of Cerebral Organoids differentiation

Publication Title

Cerebral Organoids Recapitulate Epigenomic Signatures of the Human Fetal Brain.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE21349
A compendium of myeloma associated chromosomal copy number abnormalities and their prognostic value
  • organism-icon Homo sapiens
  • sample-icon 255 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

To obtain a comprehensive genomic profile of presenting multiple myeloma cases we performed high resolution single nucleotide polymorphism (SNP) mapping array analysis in 114 samples alongside 258 samples analysed by U133 Plus 2.0 expression array (Affymetrix). We examined DNA copy number alterations and loss of heterozygosity (LOH) in order to define the spectrum of minimally deleted regions in which relevant genes of interest can be found. The most frequent deletions are located at 1p (30%), 6q (33%), 8q (25%), 12 (22%), 13q (59%), 14q (39%), 16q (35%), 17p (7%), 20 (12%) and 22 (18%). In addition, copy number-neutral LOH, or uniparental disomy, was also prevalent on 1q (8%), 16q (9%), and X (20%), and was associated with regions of gain and loss. Based on fluorescent in situ hybridisation (FISH) and expression quartile analysis, genes of prognostic importance were found to be located at 1p (FAF1, CDKN2C), 1q (ANP32E), and 17p (TP53). In addition, we identified common homozygously deleted genes which have functions relevant to myeloma biology. Taken together, the dysregulated genes from the myeloma genome indicate that the crucial pathways in myeloma pathogenesis include the NF-?B pathway, apoptosis, cell-cycle regulation and Wnt signalling.

Publication Title

Aberrant global methylation patterns affect the molecular pathogenesis and prognosis of multiple myeloma.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE44644
Dnmt3L-dependent regulation of DNA methylation promotes stem cells differentiation toward primitive germinal cells
  • organism-icon Mus musculus
  • sample-icon 3 Downloadable Samples
  • Technology Badge IconIllumina MouseWG-6 v2.0 expression beadchip

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Dnmt3L antagonizes DNA methylation at bivalent promoters and favors DNA methylation at gene bodies in ESCs.

Sample Metadata Fields

Specimen part, Cell line

View Samples
accession-icon GSE44643
Dnmt3L-dependent regulation of DNA methylation promotes stem cells differentiation toward primitive germinal cells [Expression array]
  • organism-icon Mus musculus
  • sample-icon 3 Downloadable Samples
  • Technology Badge IconIllumina MouseWG-6 v2.0 expression beadchip

Description

The de novo DNA methyltransferase 3-like (Dnmt3L) is a catalytically inactive DNA methylase that has been previously shown to cooperate with Dnmt3a and Dnmt3b to methylate DNA. Dnmt3L is highly expressed in mouse embryonic stem cells (ESC) but its function in these cells is unknown. We here report that Dnmt3L is required for the differentiation of ESC into primordial germ cells (PGC) through activation of the homeotic gene Rhox5. By genome-wide analysis we found that Dnmt3L is a positive regulator of methylation at gene bodies of housekeeping genes and a negative regulator of methylation at promoters of bivalent genes. We demonstrate that Dnmt3L interacts with the Polycomb PRC2 complex in competition with the DNA methyl transferases Dnmt3a and Dnmt3b to maintain low the methylation level at H3H27me3 regions. Thus in ESC, Dnmt3L counteracts the activity of de novo DNA methylases to keep low the level of DNA methylation at developmental gene promoters.

Publication Title

Dnmt3L antagonizes DNA methylation at bivalent promoters and favors DNA methylation at gene bodies in ESCs.

Sample Metadata Fields

Specimen part

View Samples
accession-icon SRP033646
TET1 is a tumour suppressor that inhibits colon cancer growth by derepressing inhibitors of the WNT pathway
  • organism-icon Homo sapiens
  • sample-icon 2 Downloadable Samples
  • Technology Badge IconIlluminaHiScanSQ

Description

Ten eleven translocation (TET) enzymes catalyse the oxidative reactions of 5-methylcytosine (5mC) to promote the demethylation process. The reaction intermediate 5-hydroxymethylcytosine (5hmC) has been shown to be abundant in embryonic stem cells and tissues, but strongly depleted in human cancers. Genetic mutations of TET2 gene were associated with lleukemia, whereas TET1 downregulation has been shown to promote malignancy in breast cancer. Here, we report that TET1 is downregulated in colon tumours from the initial stage. TET1 silencing in primary epithelial colon cells increase their cellular proliferation while its re-­­expression in colon cancer cells inhibits their proliferation and the growth of tumour xenografts even at later stages. We found that TET1 binds and maintains hypomethylated the promoter of the DKK genes inhibitors of the WNT signalling to promote their expression. Downregulation of TET1 during colon cancer initiation leads to repression, by DNA methylation the promoters of the inhibitors of the WNT pathway resulting in a constitutive activation of the WNT pathway. Thus the DNA hydroxymethylation mediated by TET1 controlling the WNT signalling is a key player of tumour growth. These results provide new insights for understanding how tumours escape cellular controls Overall design: Transcriptome analysis of Caco-2 cell line expressing TET1 protein.

Publication Title

TET1 is a tumour suppressor that inhibits colon cancer growth by derepressing inhibitors of the WNT pathway.

Sample Metadata Fields

No sample metadata fields

View Samples
...

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)

fund-icon Fund the CCDL

Developed by the Childhood Cancer Data Lab

Powered by Alex's Lemonade Stand Foundation

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.

BSD 3-Clause LicensePrivacyTerms of UseContact