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SRP119636
Homo sapiens
127 Downloadable Samples
Illumina HiSeq 2000
Description
We investigated the expression profiles in the CD4+, CD8, and CD14+ peripheral blood cells (PBLs) of the stage IV melanoma patients and the healthy donors. Overall design: Examination of long noncoding RNA in the CD4+, CD8, and CD14+ peripheral blood cells (PBLs) of the stage IV melanoma patients and the healthy donors.
Publication Title
Integrative Genome-Wide Analysis of Long Noncoding RNAs in Diverse Immune Cell Types of Melanoma Patients.
Sample Metadata Fields
Specimen part, Subject
View Samples- Homo sapiens
- 6 Downloadable Samples
- Illumina HiSeq 2500
Description
To inhibit INS expression, we used shRNA to target the INS promoter. We find that knocking down INS expression with such an shRNA targeting the INS promoter significantly affects expression of 259 genes. Overall design: mRNA profiles of EndoC ßH1 with or without shRNA targetting INS promoter were generated by deep sequencing, in triplicate, using Illumina Hiseq 2500.
Publication Title
<i>Insulin</i> promoter in human pancreatic β cells contacts diabetes susceptibility loci and regulates genes affecting insulin metabolism.
Sample Metadata Fields
Specimen part, Cell line, Treatment, Subject
View Samples- Homo sapiens
- 9 Downloadable Samples
Affymetrix Human Gene 2.0 ST Array (hugene20st)
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
The miR-371∼373 Cluster Represses Colon Cancer Initiation and Metastatic Colonization by Inhibiting the TGFBR2/ID1 Signaling Axis.
Sample Metadata Fields
Specimen part, Cell line
View Samples- Homo sapiens
- 3 Downloadable Samples
Affymetrix Human Gene 2.0 ST Array (hugene20st)
Description
The colorectal cancer (CRC) cell line pair SW480/SW620 is an accepted model to study CRC progression and metastasis formation. Studying gene expression differences might allow to uncover molecular mechanisms that underlie metastasis initiation
Publication Title
The miR-371∼373 Cluster Represses Colon Cancer Initiation and Metastatic Colonization by Inhibiting the TGFBR2/ID1 Signaling Axis.
Sample Metadata Fields
Specimen part, Cell line
View Samples- Mus musculus
- 18 Downloadable Samples
- Affymetrix Mouse Gene 1.0 ST Array (mogene10st)
Description
We have developed an in vitro system of cancer cell redirection that employs the 1:50 ratio of cancer cells to normal cells. Using our in vitro system of cancer cell redirection we investigated the genetic profiles of erbB2-overexpressing mammary tumor-derived cells as they undergo the redirection phenomenon.
Publication Title
RNA Expression Profiling Reveals Differentially Regulated Growth Factor and Receptor Expression in Redirected Cancer Cells.
Sample Metadata Fields
Specimen part
View Samples- Homo sapiens
- 12 Downloadable Samples
- Affymetrix Human Gene 1.1 ST Array (hugene11st)
Description
Dental follicle is a loose connective tissue that surrounds the developing tooth. Dental follicle cells (DFCs) have a promising potential for tissue engineering applications including periodontal and bone regeneration. However, little is known about the molecular mechanisms underlying osteogenic differentiation. In a previous study we detected that more than 35 % of genes that are regulated during osteogenic differentiation of DFCs have promoter binding sites for the transcription factors TP53 and SP1. However, the role of these transcription factors in dental stem cells is still unknown. We hypothesize that both factors influence the processes of cell proliferation and differentiation in dental stem cells. Therefore, we transiently transfected DFCs and dental pulp stem cells (SHED; Stem cells from human exfoliated decidiuous teeth) with expression vectors for these transcription factors. After overexpression of SP1 and TP53, SP1 influenced cell proliferation and TP53 osteogenic differentiation in both dental cell types. The effects on cell proliferation and differentiation were less pronounced after siRNA mediated silencing of TP53 and SP1. This indicates that the effects we observed after TP53 and SP1 overexpression are indirect and subject of complex regulation. Interestingly, upregulated biological processes in DFCs after TP53-overexpression resemble the downregulated biological processes in SHED after SP1-overexpression. Here, regulated processes are involved in cell motility, wound healing and programmed cell death. In conclusion, our study demonstrates that SP1 and TP53 influence cell proliferation and differentiation and similar biological processes in both SHED and DFCs.
Publication Title
Transcription factors TP53 and SP1 and the osteogenic differentiation of dental stem cells.
Sample Metadata Fields
Specimen part
View Samples- Mus musculus
- 6 Downloadable Samples
- Illumina MouseWG-6 v2.0 expression beadchip
Description
The hypothesis is that genes involved in the immature schwann cell and promyelinating state will be upregulated and genes that are involved in the myelnating state will be down regulated.
Publication Title
MicroRNA-deficient Schwann cells display congenital hypomyelination.
Sample Metadata Fields
Sex, Specimen part
View Samples- Homo sapiens
- 12 Downloadable Samples
- Affymetrix Human Gene 1.0 ST Array (hugene10st)
Description
We analysed gene expression profiles in dental follicle cells after 7 days of osteogenic differentiation with different inducers.
Publication Title
The differentiation and gene expression profile of human dental follicle cells.
Sample Metadata Fields
Specimen part
View Samples- Drosophila melanogaster
- 4 Downloadable Samples
- Illumina HiSeq 2000
Description
Drosophila miRNAs show distinct change in isoform distribution pattern with age. Some miRNAs show accumulation of the short isoforms, while other miRNAs show the accumulation of the long isoforms with age. The increase of the long isoforms of some miRNAs reflects increased 2''-O-methylated miRNA isoforms with age. The increase in 2''-O-methylated miRNA isoforms reflected increased Ago2-loading, but not Ago1-loading of specific miRNA isoforms with age. This raised a question on whether there is global shift in small RNA loading pattern between Ago1 and Ago2 with age. To investigate change in small RNA loading pattern between Ago1 and Ago2 with age, we performed small RNA deep-sequencing of Ago1 vs Ago2-IP small RNAs at 3d and 30d in Drosophila. This analysis revealed global increase of miRNA loading into Ago2, but not into Ago1 with age. Overall design: 3d and 30d FLAG-HA-Ago2 male flies were collected. Ago1 and Ago2 were immunoprecipitated by anti-Ago1 and anti-FLAG M2 beads respectively. RNA was purified from the beads, P32-labeled, and small RNA fraction was gel-purififed. Small RNA libraries were prepared using Illumina''s TruSeq small RNA sample preparation kit (#RS-200-0012, Illumina, Inc. San Diego, CA), following the manufacturer''s protocol. The libraries were multiplexed and sequenced on HiSeq2000 platform (Illumina).
Publication Title
Impact of age-associated increase in 2'-O-methylation of miRNAs on aging and neurodegeneration in Drosophila.
Sample Metadata Fields
Sex, Specimen part, Subject
View Samples- Homo sapiens
- 448 Downloadable Samples
- Affymetrix Human Gene 1.0 ST Array (hugene10st)
Description
Genotypic differences greatly influence susceptibility and resistance to disease. Understanding genotype-phenotype relationships requires that phenotypes be viewed as manifestations of network properties, rather than simply as the result of individual genomic variations. Genome sequencing efforts have identified numerous germline mutations associated with cancer predisposition and large numbers of somatic genomic alterations. However, it remains challenging to distinguish between background, or passenger and causal, or driver cancer mutations in these datasets. Human viruses intrinsically depend on their host cell during the course of infection and can elicit pathological phenotypes similar to those arising from mutations. To test the hypothesis that genomic variations and tumour viruses may cause cancer via related mechanisms, we systematically examined host interactome and transcriptome network perturbations caused by DNA tumour virus proteins. The resulting integrated viral perturbation data reflects rewiring of the host cell networks, and highlights pathways that go awry in cancer, such as Notch signalling and apoptosis. We show that systematic analyses of host targets of viral proteins can identify cancer genes with a success rate on par with their identification through functional genomics and large-scale cataloguing of tumour mutations. These complementary approaches together result in increased specificity for cancer gene identification. Combining systems-level studies of pathogen-encoded gene products with genomic approaches will facilitate prioritization of cancer-causing driver genes so as to advance understanding of the genetic basis of human cancer.
Publication Title
Interpreting cancer genomes using systematic host network perturbations by tumour virus proteins.
Sample Metadata Fields
Cell line
View Samples