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accession-icon GSE6928
Stonewalling Drosophila stem cell differentiation by epigenetic controls
  • organism-icon Drosophila melanogaster
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Drosophila Genome 2.0 Array (drosophila2)

Description

Abstract: During Drosophila oogenesis, germline stem cell (GSC) identity is maintained largely by preventing the expression of factors that promote differentiation. This is accomplished via the activity of several genes acting either in the GSC or its niche. The translational repressors, Nanos and Pumilio, act in GSCs to prevent differentiation, likely by inhibiting translation of early differentiation factors, while niche signals prevent differentiation by silencing transcription of the differentiation factor Bam. We have found that the DNA-associated protein Stonewall (Stwl) is also required for GSC maintenance. stwl is required cell-autonomously; clones of stwl- germ cells were lost by differentiation, and ectopic Stwl caused an expansion of GSCs. stwl mutants acted as Suppressors of Variegation, indicating stwl normally acts in chromatin-dependent gene repression. In contrast to several previously described GSC maintenance factors, Stwl likely functions epigenetically to prevent GSC differentiation. Stwl-dependent transcriptional repression does not target bam, but rather Stwl represses the expression of many genes, including those that may be targeted by Nanos/Pumilio translational inhibition.

Publication Title

Stonewalling Drosophila stem cell differentiation by epigenetic controls.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP115415
RNA seq_A375 gSMARCB1 + A549 etoposide, Aurora kinases inhibitors treated
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

To study the senescence gene signatures in the cells, which were genetic SMARCB1 depleted or treated with aurora kinase inhibitors or etoposide, we performed next generation RNA sequencing on these cell, and ''FRIDMAN_SENESCENCE_UP'' geneset was used to determine the enrichment of senescence-related genes. The RNA sequencing results include (1) A375 cells and SMARCB1 depleted counterparts. (2) A549 cells and aurora kinase inhibitor (Alisertib, barasertib or tozasertib) or etoposide treated counterparts. Overall design: RNA seq data of A375_gSMARCB1 + A549_etoposide, Aurora kinases inhibitors treated, to check senescence gene expression signature one replicate of A375 cells parental V.S SMARCB1 KO (by CRISPR) + duplicates of A549 parental V.S etoposide, or 3 indepdent aurora kinase inhibitors (MLN8237/Alisertib, VX680/Tozasertib, AZD1132/Barasertib)

Publication Title

High-Throughput Functional Genetic and Compound Screens Identify Targets for Senescence Induction in Cancer.

Sample Metadata Fields

Disease, Disease stage, Cell line, Subject

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accession-icon GSE40965
DICER1 hotspot mutations cause defective miRNA processing
  • organism-icon Mus musculus
  • sample-icon 28 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

Recurrent somatic hotspot mutations of DICER1 appear to be clustered around each of four critical metal binding residues in the RNase IIIB domain of DICER1. This domain is responsible for cleavage of the 3 end of the 5p-miRNA strand of a pre-mRNA hairpin. To investigate the effects of these cancer-associated hotspot mutations we engineered mouse Dicer1-deficient ES cells to express wild-type and an allelic series of the mutant human DICER1 variants. Global miRNA and mRNA profiles from cells carrying the metal binding site mutations were compared to each other and wild-type human DICER1. The miRNA and mRNA profiles generated through the expression of the hotspot mutations were virtually identical, and the DICER1 hotspot mutation carrying cells were distinct from both wild-type and Dicer1-deficient cells. Further, miRNA profiles showed mutant DICER1 results in a dramatic loss in processing of mature 5p-miRNA strands but were still able to create 3p-strand miRNAs. Messenger-RNA profile changes were consistent with the loss of 5p-strand miRNAs and showed enriched expression for predicted targets of the lost 5p derived miRNAs. We therefore conclude that cancer-associated somatic hotspot mutations of DICER1, affecting any one of four metal binding residues in the RNase IIIB domain, are functionally equivalent with respect to miRNA-processing and are hypomorphic alleles, yielding a global loss in processing of mature 5p-strand miRNA. We further propose that this resulting 3p-strand bias in mature miRNA expression likely underpins the oncogenic potential of these hotspot mutations.

Publication Title

Cancer-associated somatic DICER1 hotspot mutations cause defective miRNA processing and reverse-strand expression bias to predominantly mature 3p strands through loss of 5p strand cleavage.

Sample Metadata Fields

Specimen part

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accession-icon SRP165929
RNA seq data of Hep3B-control, Hep3B-sertraline, Hep3B-XL413, Hep3B-XL413-sertraline, Huh7-control, Huh7-sertraline, Huh7-XL413, Huh7-XL413-sertraline cells
  • organism-icon Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Hep3B and Huh7 cells pre-treated with XL413 for 10 days to induce senescence prior to sertraline treatment for 24 hours. For RNA sequencing, the library was prepared using TruSeq RNA sample prep kit according to the manufacturer's protocol (Illumina). Gene set enrichment analysis was performed using gene set enrichment analysis software. Overall design: RNA seq data of Hep3B-control, Hep3B-sertraline, Hep3B-XL413, Hep3B-XL413-sertraline, Huh7-control, Huh7-sertraline, Huh7-XL413, Huh7-XL413-sertraline cells, to check gene expression signatures

Publication Title

Inducing and exploiting vulnerabilities for the treatment of liver cancer.

Sample Metadata Fields

Specimen part, Cell line, Treatment, Subject

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accession-icon SRP165928
CDC7 inhibition induces a senescence-like state in Hep3B and Huh7 cells
  • organism-icon Homo sapiens
  • sample-icon 4 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Purpose: to check senescence gene expression signature in XL413 treated liver cancer cells. Methods: Hep3B and Huh7 cells are treated with XL413 for 4 days. For RNA sequencing, the library was prepared using TruSeq RNA sample prep kit according to the manufacturer's protocol (Illumina). Gene set enrichment analysis was performed using gene set enrichment analysis software. The FRIDMAN_SENESCENCE_UP gene set was used to assess the enrichment of senescence-associated genes in the XL413-treated versus control cells. Overall design: RNA seq data of Hep3B-control, Hep3B-XL413, Huh7-control, and Huh7-XL413 cells, to check senescence gene expression signature

Publication Title

Inducing and exploiting vulnerabilities for the treatment of liver cancer.

Sample Metadata Fields

Specimen part, Cell line, Treatment, Subject

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accession-icon GSE58643
An epigenetically distinct breast cancer cell subpopulation promotes collective invasion
  • organism-icon Homo sapiens
  • sample-icon 26 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V4.0 expression beadchip

Description

A distinct highly invasive subpopulation was identified in breast cancer cell lines. The molecular characteristics of these cells was investigated, revealing a set of genes whose high expression confers the ability to invade.

Publication Title

ΔNp63α Promotes Breast Cancer Cell Motility through the Selective Activation of Components of the Epithelial-to-Mesenchymal Transition Program.

Sample Metadata Fields

Cell line

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accession-icon SRP065305
Overexpression of PHF8 promotes an EMT-related gene signature in MCF10A cells
  • organism-icon Homo sapiens
  • sample-icon 22 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2500

Description

PHF8 exerts distinct functions in different types of cancer. However, the mechanisms underlying its specific functions in each case remain obscure. To establish whether overexpression of PHF8 regulates the TGF-ß induced the epithelial-mesenchymal transition (EMT), we treated MCF10A-Mock (control) and MCF10A-PHF8wt (overexpressing wild-type PHF8) cells with TGF-ß1 for 0, 24, 48 and 72 hours and performed RNA-seq in biological duplicates. Our data indicated that EMT gene signatures were significantly enriched in MCF10A-PHF8 cells with TGF-ß1 treatment at all time points, strongly indicating that PHF8 overexpression induces a sustained EMT signaling program. Overall design: mRNA profiles of MCF10A-Mock (control) and MCF10A-PHF8 with TGF-ß1 treatment for 0, 24, 48 and 72 hours were generated by RNA-seq, in duplicate, using HiSeq2500 instrument.

Publication Title

Histone demethylase PHF8 promotes epithelial to mesenchymal transition and breast tumorigenesis.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP178555
Multi-omics and genome-scale modeling reveal a metabolic shift during C. elegans ageing
  • organism-icon Caenorhabditis elegans
  • sample-icon 45 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

We conducted a time series of transcriptomics measurements during normal ageing in C. elegans in two non-reproductive strains (fem and gem) during normal ageing (days 1 to 10 of adulthood) and used this together with a multi-omics modelling pipeline to explore the changes that take place due to ageing. Overall design: Two strains and several time points with three replicates per strain and time point.

Publication Title

Multi-Omics and Genome-Scale Modeling Reveal a Metabolic Shift During <i>C. elegans</i> Aging.

Sample Metadata Fields

Age, Specimen part, Subject

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accession-icon SRP063910
Impact of Tcf1 and Lef1 deficiency on mature CD8 thymocytes
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Comparison of transcriptome between control and Tcf1/Lef1-deficient mature CD8 thymocytes Overall design: Control mice or those are deficient for Tcf1 and Lef1 transcription factors (deleted by CD4-Cre) were used to isolate thymocytes. The thymocytes were surface-stained to identify TCRbeta high, CD69–, CD24– CD8+ subsets. These cells were sorted for RNAseq analysis.

Publication Title

Tcf1 and Lef1 transcription factors establish CD8(+) T cell identity through intrinsic HDAC activity.

Sample Metadata Fields

Specimen part, Subject

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accession-icon GSE13280
Gene expression analysis of paediatric acute lymphoblastic leukaemia
  • organism-icon Homo sapiens
  • sample-icon 44 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

We addressed the clinical significance and mechanisms behind in vitro cellular responses to ionising radiation (IR)-induced DNA double strand breaks in 74 paediatric ALL patients. We found an apoptosis-resistant response in 36% of patients and an apoptosis-sensitive response in the remaining 64% of leukaemias. Global gene expression profiling of 11 apoptosis-resistant and 11 apoptosis-sensitive ALLs revealed abnormal up-regulation of multiple pro-survival pathways in response to IR in apoptosis-resistant leukaemias and differential post-transcriptional activation of the PI3-Akt pathway was observed in representative resistant cases. It is possible that abnormal pro-survival responses to DNA damage provide one of the mechanisms of primary resistance in ALL .

Publication Title

Stratification of pediatric ALL by in vitro cellular responses to DNA double-strand breaks provides insight into the molecular mechanisms underlying clinical response.

Sample Metadata Fields

No sample metadata fields

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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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