E-GEOD-6740
Ontology highlight
ABSTRACT:
OTHER RELATED OMICS DATASETS IN: PRJNA98975
PROVIDER: E-GEOD-6740 | ExpressionAtlas | 2025-01-24
REPOSITORIES: ExpressionAtlas
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| E-GEOD-6740-analysis-methods.tsv | Tabular | |||
| E-GEOD-6740-atlasExperimentSummary.Rdata | Rdata | |||
| E-GEOD-6740-configuration.xml | Xml | |||
| E-GEOD-6740-percentile-ranks.tsv | Tabular | |||
| E-GEOD-6740.condensed-sdrf.tsv | Tabular |
Items per page: 5 1 - 5 of 127 |
Similar Datasets
Project description:This ordinary differential equation model simulating the interactions between tumor and immune cells is detailed in the publication:
Ahmed M. Makhlouf, Lamiaa El-Shennawy, Hesham A. Elkaranshawy, "Mathematical Modelling for the Role of CD4+T Cells in Tumor-Immune Interactions", Comput Math Methods Med. 2020 Feb 19;2020:7187602.
doi: 10.1155/2020/7187602
Comment:
This no treatment model is described by equations 1-7 of the publication manuscript.
Abstract:
Mathematical modelling has been used to study tumor-immune cell interaction. Some models were proposed to examine the effect of circulating lymphocytes, natural killer cells, and CD8+T cells, but they neglected the role of CD4+T cells. Other models were constructed to study the role of CD4+T cells but did not consider the role of other immune cells. In this study, we propose a mathematical model, in the form of a system of nonlinear ordinary differential equations, that predicts the interaction between tumor cells and natural killer cells, CD4+T cells, CD8+T cells, and circulating lymphocytes with or without immunotherapy and/or chemotherapy. This system is stiff, and the Runge–Kutta method failed to solve it. Consequently, the “Adams predictor-corrector” method is used. The results reveal that the patient’s immune system can overcome small tumors; however, if the tumor is large, adoptive therapy with CD4+T cells can be an alternative to both CD8+T cell therapy and cytokines in some cases. Moreover, CD4+T cell therapy could replace chemotherapy depending upon tumor size. Even if a combination of chemotherapy and immunotherapy is necessary, using CD4+T cell therapy can better reduce the dose of the associated chemotherapy compared to using combined CD8+T cells and cytokine therapy. Stability analysis is performed for the studied patients. It has been found that all equilibrium points are unstable, and a condition for preventing tumor recurrence after treatment has been deduced. Finally, a bifurcation analysis is performed to study the effect of varying system parameters on the stability, and bifurcation points are specified. New equilibrium points are created or demolished at some bifurcation points, and stability is changed at some others. Hence, for systems turning to be stable, tumors can be eradicated without the possibility of recurrence. The proposed mathematical model provides a valuable tool for designing patients’ treatment intervention strategies.
2024-09-02 | BIOMD0000001042 | BioModels
Project description:Genome-wide maps of nucleosome organization in human CD4+ T-cells, CD8+ T-cells, granulocytes, and from in vitro reconstitution. 8 samples include: nucleosome-bound DNA isolated from primary human CD4+ T-cells, nucleosome bound-DNA isolated from primary human CD8+ T-cells, nucleosome-bound DNA isolated from primary human granulocytes, nucleosome-bound DNA isoalted from in vitro reconstitution of nucleosomes with human genomic DNA, control DNA generated by micrococcal nuclease treatment of human genomic DNA, RNA-seq from human CD4+ T-cells, RNA-seq from human CD8+ T-cells, RNA-seq from human Granulocytes.
2011-04-19 | E-GEOD-25133 | biostudies-arrayexpress
Project description:The transcription factor Thpok is essential for CD4 T cell development in the thymus and remains expressed in post-thymic CD4 T cells. We post-thymically inactivated Thpok and compared microarray gene expression in Thpok-deficient CD4 T cells to that in their wildtype CD4 or CD8 counterparts We show that Thpok constrains the transcriptional circuitry to maintain CD4+-lineage integrity in naM-CM-/ve cells and to couple effector differentiation to environmental cues after antigenic stimulation. Redundantly with the related factor LRF, Thpok is continuously needed to prevent the trans-differentiation of mature CD4+ into -CD8+ T cells. We activated naM-CM-/ve CD4 T cells (either wild-type or Thpok-deficient) and CD8 T cells (wild-type) in vitro under Th1 conditions. Differentiated effectors were sorted 4 days after activation into CD4+CD8- and CD4-CD8+ (wild-type) and CD4+CD8- and CD4+CD8+ (Thpok-deficient) subsets. Total RNA was extracted from sorted subsets and processed for microarray analyses (Affymetrix Mouse Exon 1.0 ST array) at the NCI microarray facility, following the manufacturerM-bM-^@M-^Ys recommendation. Data is from 3 replicates (except wild-type CD4-CD8+ cells, for which two samples only were processed), generated from two distinct cell preparations.
2014-08-15 | E-GEOD-57846 | biostudies-arrayexpress
Project description:To determine the effect of mutation of the KIX domain of CBP and p300 on gene expression, thymuses dissected from four to seven week old wild type and CBP KIX/KIX;p300 +/KIX adult mice were dissociated into single cell suspesions, antibody stained for CD4 and CD8, sorted for CD4+ CD8+ double positive thymocytes, RNA was made from the sorted cells and transcriptional profiling by array was carried out. CD4+CD8+ double positive thymocytes were chosen because these cells express c-Myb.
2014-02-10 | E-MTAB-1974 | biostudies-arrayexpress
Project description:Although extensive studies have demonstrated the gene expression patterns of antigen-specific CD4+ and CD8+ T-cells during chronic hepatitis C virus (HCV) infection, the transcriptional profiles of global CD4+ and CD8+ T-cells remains unclear. In this report, we recruited 10 long-term (~20 years) treatment-naM-CM-/ve chronic HCV (CHC) patients and 5 healthy donors (HDs) to investigate differences in global CD4+ and CD8+ T-cells gene expression profile. Global CD4+ and CD8+ T-cells showed unique transcriptional profiles in the expression of apoptosis-related genes. We identified BCL2, PMAIP1, and CASP1 in CD4+ T-cells and IER3 and BCL2A1 in CD8+ T-cells from CHC patients as HCV-specific gene signatures. The unique apoptosis-related gene expression profilesin global CD4+ and CD8+ T-cells programmed by chronic HCV infection seemed to enhance activation-induced apoptosis, which was suffered by global CD4+ and CD8+ T-cells. We obtained 15 blood samples to identify the gene expression signatures of global CD4+ and CD8+ T-cells due to chronic HCV infection. The samples included: 5 samples from high HCV viral load patients (HCV-h), 5 samples from low HCV viral load (HCV-l) and 5 samples from healthy donors (HD). HCV patients were all Ab+ and treatment-naive prior to the study. Samples were taken once from each individual. Global CD4+ and CD8+ T-cells were enriched by microbeads, and total RNA were used in gene chip analysis.
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Project description:Patient with multiple sclerosis improves during pregnancy while temporarily worsening post-partum. The reasons behind the disease modulation during pregnancy remain unknown. In this study, we have investigated the effect of pregnancy on circulating CD4+ and CD8+ T cells from patients with multiple sclerosis and healthy controls to gain a deeper understanding why patients with multiple sclerosis improves during pregnancy. We assessed epigenome-wide DNA methylation in CD4+ and CD8+ T cells obtained during (1st, 2nd and 3rd trimester) and after pregnancy (6 weeks post-partum), using the Infinium MethylationEPIC 850K array.
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Project description:CD4+ and CD8+ T cells isolated from wild-type and Foxo1-deficient mice were analyzed by global gene expression profiling with Affymetrix array MOE 430 2.0. Results indicate Foxo1 regulates the expression of genes encoding positive regulators of T cell activation, differentiation, homeostasis, cell adhesion, cell migration, and cellular stress responses. CD4+ and CD8+ T cells were isolated for RNA extraction and hybridization on Affymetrix microarrays.
2009-02-28 | E-GEOD-15037 | biostudies-arrayexpress
Project description:The NOTCH1 signaling pathway is a critical determinant of cell fate decisions and drives oncogenesis through mechanisms that are incompletely understood. To elucidate tumorigenic pathways that cooperate with activated Notch1 in leukemogenesis,we performed miRNA expression profiling of normal CD4+CD8+ thymocytes, non-malignant ICN1 over-expressing CD4+CD8+ cells and ICN1-induced tumor CD4+CD8+ cells. Three groups of the murine T cells: Control CD4+CD8+ normal thymocytes vs.non-malignant ICN1-expressing CD4+CD8+ cells vs. ICN1-tumor CD4+CD8+ cells .
2011-02-19 | E-GEOD-27418 | biostudies-arrayexpress
Project description:CD8+ and CD4+ T cells from HIV infected patients with HIV-RNA viremia of >50 copies/ml and CD8+ and CD4+ T cells from healthy controls were isolated by negative selection (Miltenyi Biotech, Auburn, CA). Cell sorting of the CD4 and CD8 T cell subsets were performed based on surface staining of CD3+CD8+ or CD3+CD4+ and na ve CD45RA+CD27+CD127highHLA-DRlow, and CD3+CD8+ or CD3+CD4+ and memory CD45RA-CD27+CD127highHLA-DRlow. Sorted cell populations were spun down and stored as dry pellets at -80M-BM-0C. Samples analyzed by transcript levels of genes related to cytokine signaling were determined by the JAK/STAT Signaling Pathway microarray. CD8+ and CD4+ T cells from HIV infected patients with HIV-RNA viremia of >50 copies/ml and CD8+ and CD4+ T cells from healthy controls were isolated by negative selection (Miltenyi Biotech, Auburn, CA). Cell sorting of the CD4 and CD8 T cell subsets were performed based on surface staining of CD3+CD8+ or CD3+CD4+ and naM-CM-/ve CD45RA+CD27+CD127highHLA-DRlow, and CD3+CD8+ or CD3+CD4+ and memory CD45RA-CD27+CD127highHLA-DRlow. Sorted cell populations were spun down and stored as dry pellets at -80M-BM-0C. Samples analyzed by transcript levels of genes related to cytokine signaling were determined by the JAK/STAT Signaling Pathway microarray (http://www.sabiosciences.com/rt_pcr_product/HTML/PAHS-039A.html, SABiosciences Frederick, MD). Briefly, total RNA was harvested from each individual T cell subset from each patient or healthy control and contaminating DNA was digested with DNase. Messenger RNA was converted to cDNA and loaded onto PCR array plates for quantitative real-time PCR. Quantification of transcript levels was determined by normalizing to 5 housekeeping genes from each individual sample. Relative gene expression levels for each subset were averaged and compared between cell populations from the patient group and healthy controls. Because of the multiple comparisons only p values M-bM-^IM-$ 0.01 were considered significant.
2010-12-28 | E-GEOD-25456 | biostudies-arrayexpress
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