Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Embryonic Stem Cell Differentiation LIF vs no LIF

ABSTRACT: Description: The pluripotency of an embryonic stem cell makes it an attractive target for differentiation strategies aimed at producing tissues for therapeutic purposes. Yet, even though we know that ES cells have tremendous capacity for differentiation, we do not fully understand the molecular paths taken by these cells as they differentiate. In addition, it is unclear how important the removal of leukemia inhibitory factor is to ES cell differentiation. Moreover, it is unclear how the path of ES cell differentiation relates to the molecular decisions made by tissues undergoing normal development. The motivation behind this work is to increase our understanding of this relationship and its potential limitations. Dataset is a murine embryonic stem cell differentiation timecourse consisting of 14 timepoints spanning 17 days of differentiation. Samples were harvested at 24 hour intervals on days 0,1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 13, 15, and 17. There two replicates of each sample in this series. Additionally, there are 14 identically stated differentiation samples, where growth was conducted in ES cell media containing LIF. A common reference design was employed. Groups of assays that are related as part of a time series. Compound Based Treatment: Treatment or lack of treatment with LIF Elapsed Time: Samples were harvested at 24 hour intervals on days 0,1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 13, 15, and 17 Keywords: time_series_design Using regression correlation

ORGANISM(S): Mus musculus

SUBMITTER: Nesanet Mitiku

PROVIDER: E-GEOD-9048 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Similar Datasets

Project description:These 95 arrays are the basis for Figure 2 of our manuscript "An interferon-response induced by tumor-stroma interaction in a subset of human breast cancers". Abstract:Background Communication between different cell types is a cardinal feature of multi-cellular organisms and perturbations in these cell-cell interactions are a key feature of cancer. However, little is known about the systematic effects of cell-cell interaction on global gene expression in cancer. Methods and Findings We used an ex vivo culture model to simulate tumor-stroma interaction by systematically co-cultivating breast cancer cells with stromal fibroblasts and determined associated gene expression changes with cDNA microarrays. The picture of heterotypic interaction effects that emerged from this analysis is complex, reflecting the variation in signaling capacities and responsiveness of the involved cells. A frequent and prominent response to epithelial-mesenchymal interaction was an induction of interferon-response genes, observed in 4 of the 7 breast cancer cell lines in response to co-culture with fibroblasts, but not in normal mammary epithelial cells. In response to close contact with these breast cancer cells, the fibroblasts secreted type I interferons, which, in turn, induced expression of the IRGs in the tumor cells. Immunohistochemical analysis of human breast cancer tissues showed that STAT1, the key transcriptional activator of the interferon-response genes, and itself an IRG, was expressed in a subset of the cancers, with a striking pattern of elevated expression in the cancer cells in contact with, or close proximity to, the tumor stroma ? paralleling the response seen in our ex vivo model. In vivo, expression of the interferon-response genes was remarkably coherent, providing a basis for segregation of the 295 early-stage breast cancers into two groups. Tumors with high expression levels (n=161) of IRG were associated with significantly shorter overall survival; 59 % at 10 years versus 80% for tumors with low interferon-response gene expression levels (n=134) (log-rank p=0.001). Conclusion Our results suggest that an interaction between some breast cancer cells and stromal fibroblasts can induce an interferon response, and that this response may be associated with a greater propensity for tumor progression. Set of arrays organized by shared biological context, such as organism, tumors types, processes, etc. Computed

Project description:Patient Selection: Three hospitals were involved in the study: Dong Thap Provincial and An Giang Provincial hospitals, both located in the Mekong Delta Region of Vietnam where most of the Typhoid patients were admitted, and the Hospital for Tropical Diseases, Ho Chi Minh City, where the malarial patients were admitted. Infection status of each patient was determined by blood culture for the Typhoid patients and by microscopic examination of stained thick and thin peripheral-blood slides for the patients suspected of having Malaria. Patients with blood cultures positive for S. Typhi or S. enterica serovar Paratyphi A (S. Paratyphi A) (samples designated ST) or peripheral blood smears positive for Plasmodium falciparum or Plasmodium vivax (samples designated PF) were consented and enrolled in the study. A total of 28 S. Typhi positive patients and one S. Paratyphi A positive patient were enrolled in the first phase of the study and a further 9 S. Typhi and one S. Paratyphi A positive patient were enrolled in the second phase. Nine patients with Malaria caused by P. falciparum and one caused by P. vivax were enrolled. Sixteen uninfected healthy individuals (samples designated HC) were also enrolled in the study (one sample each). The Typhoid patients were randomly chosen to receive either Azithromycin or Gatifloxicin (20mg/kg/day for 7 days) antibiotics. Uncomplicated malaria patients were treated for 3 days with Artekin (dihydroartemisinin with piperaquine phosphate). Venous blood (2.5ml) was collected for total RNA extraction into PaxGene RNA collection tubes (Qiagen) at various times. The first sample (T1) was taken immediately on admission or entry into the study, then samples were collected, 3 (T3), 6-9 (T9 for Typhoid, T7 for Malaria), and 28-45 (T28) days following entry into the study and an average of 9 months (T9M) later. The PaxGene tubes were stored at 4degC until RNA was extracted as per the manufacturers instructions. Purified RNA was shipped on dry ice to Stanford University, CA for use in Microarray analyses. Microarrays: Experimental and reference samples (Human Universal RNA reference {Stratagene}) were amplified using the MessageAmp II aRNA Kit (Ambion) as per the manufacturer's instructions. Four micrograms amplified RNA was labeled through indirect incorporation of Cy5 (experimental) and Cy3 (reference) dyes (protocols can be found at http://cmgm.stanford.edu/pbrown/protocols/index.html). The labeled probes were then mixed and hybridized to Stanford Human cDNA arrays with 42 K features. Arrays were scanned using a Genepix 4000A laser scanner and data extracted with Genepix Pro Software version 5.1 (Axon Instruments). The data were then uploaded into the Stanford Microarray Database (SMD). A disease state experiment design type is where the state of some disease such as infection, pathology, syndrome, etc is studied. Compound Based Treatment: Drugs used for treatment Disease State: Malaria, Typhoid or Healthy Controls Keywords: disease_state_design Complex

Dataset Information

Embryonic Stem Cell Differentiation LIF vs no LIF

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets