Ena-DATASET-CUHK-LVP-21-11-2018-04:15:34:492-233 - samples
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PROVIDER: EGAD00001004476 | EGA |
REPOSITORIES: EGA
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Project description:PacBio sequencing data of HKCI-2, HKCI-C1, HKCI-C2, HKCI-C3, HKCI-4, HKCI-9, HKCI-11, HKCI-5A and MIHA. All the data (9 samples) were saved in pacbio hdf5 format.
| EGAD00001004475 | EGA
Project description:Transcriptional analysis upon the overexpression of the folate gene cluster on a high copy plasmid when compared to an empty vector in the lactic acid bacterium L. plantarum. The transcriptional response was determined for both strains in the presence and absence of pABA thereby using the hybridisation sceme as described in the data processing section. Keywords: response to folate gene cluster overexpression and pABA treatment The batch experiment with and without pABA scheme consisted of a loop design with 21 microarrays with the following samples hybridized on one array and labeled with Cy3 and Cy5, respectively: C1+P and F1+P, F1+P and C2+P, C2+P and F3+P, F3+P and C3+P, C3+P and F2+P, F2+P and C1+P, C1+P and C2+P, F2+P and F3+P, C1-P and F1-P, F1-P and C2-P, C2-P and F3-P, F3-P and C3-P, C3-P and F2-P, F2-P and C1-P, C1-P and C2-P, F2-P and F3-P, C3-P and F1+P, F2+P and C1-P, C2+P and F3-P, F1-P and C3+P, and F2+P and F1-P. Here, C1+P, C2+P, C3+P, F1+P, F2+P, and F3+P represent biological triplicates of the L. plantarum harboring pNZ7021 and pNZ7026, respectively, when grown in batch in the presence of pABA. The C1-P, C2-P, C3-P, F1-P, F2-P, and F3-P, represents the L. plantarum harboring pNZ7021 and pNZ7026, respectively, when grown in batch in the absence of pABA.
2008-05-31 | E-GEOD-8956 | biostudies-arrayexpress
Project description:Triple-negative (TN) breast cancers need to be refined in order to identify therapeutic subgroups of patients. We conducted an unsupervised analysis of microarray gene-expression profiles of 107 TN breast cancer patients and undertook robust functional annotation of the molecular entities found by means of numerous approaches including immunohistochemistry and gene-expression signatures. An 87 TN external cohort was used for validation. Fuzzy clustering separated TN tumours into three clusters: C1 (22.4%), C2 (44.9%) and C3 (32.7%). C1 patients were older (mean = 64.6 years) than C2 (mean = 56.8 years; P = 0.03) and C3 patients (mean = 51.9 years; P = 0.0004). Histological grade and Nottingham prognostic index were higher in C2 and C3 than in C1 (P < 0.0001 for both comparisons). Significant event-free survival (EFS) (P = 0.03) was found according to cluster membership: patients belonging to C3 had a better outcome than patients in C1 (P = 0.01) and C2 (P = 0.02). EFS analysis results were confirmed when our cohort was pooled with external cohort (n = 194; P = 0.01). Functional annotation showed that 22% of TN patients were not basal-like (C1). C1 was enriched in luminal subtypes and positive androgen receptor (luminal androgen receptor [LAR]). C2 could be considered as an almost pure basal-like cluster. C3, enriched in basal-like subtypes, but to a lesser extent, included 26% of claudin-low subtypes. Dissection of immune response showed that high immune response (HIR) and low M2-like macrophages were a hallmark of C3, and that these patients had a better EFS than C2 patients, characterized by low immune response (LIR) and high M2-like macrophages: P = 0.02 for our cohort, and P = 0.03 for pooled cohorts. We identified 3 subtypes of TN patients: LAR (22%), basal-like with LIR and high M2-like macrophages (45%) and basal-enriched with HIR and low M2-like macrophages (33%). We pointed out that macrophages and other immune effectors offer a variety of therapeutic targets in breast cancer, and particularly in TN basal-like tumours. Furthermore, we showed that CK5 antibody was better suited than CK5/6 antibody to subtype TN patients.
2015-05-19 | GSE58812 | GEO
Project description:Triple-negative (TN) breast cancers need to be refined in order to identify therapeutic subgroups of patients. We conducted an unsupervised analysis of microarray gene-expression profiles of 107 TN breast cancer patients and undertook robust functional annotation of the molecular entities found by means of numerous approaches including immunohistochemistry and gene-expression signatures. An 87 TN external cohort was used for validation. Fuzzy clustering separated TN tumours into three clusters: C1 (22.4%), C2 (44.9%) and C3 (32.7%). C1 patients were older (mean = 64.6 years) than C2 (mean = 56.8 years; P = 0.03) and C3 patients (mean = 51.9 years; P = 0.0004). Histological grade and Nottingham prognostic index were higher in C2 and C3 than in C1 (P < 0.0001 for both comparisons). Significant event-free survival (EFS) (P = 0.03) was found according to cluster membership: patients belonging to C3 had a better outcome than patients in C1 (P = 0.01) and C2 (P = 0.02). EFS analysis results were confirmed when our cohort was pooled with external cohort (n = 194; P = 0.01). Functional annotation showed that 22% of TN patients were not basal-like (C1). C1 was enriched in luminal subtypes and positive androgen receptor (luminal androgen receptor [LAR]). C2 could be considered as an almost pure basal-like cluster. C3, enriched in basal-like subtypes, but to a lesser extent, included 26% of claudin-low subtypes. Dissection of immune response showed that high immune response (HIR) and low M2-like macrophages were a hallmark of C3, and that these patients had a better EFS than C2 patients, characterized by low immune response (LIR) and high M2-like macrophages: P = 0.02 for our cohort, and P = 0.03 for pooled cohorts. We identified 3 subtypes of TN patients: LAR (22%), basal-like with LIR and high M2-like macrophages (45%) and basal-enriched with HIR and low M2-like macrophages (33%). We pointed out that macrophages and other immune effectors offer a variety of therapeutic targets in breast cancer, and particularly in TN basal-like tumours. Furthermore, we showed that CK5 antibody was better suited than CK5/6 antibody to subtype TN patients. Subtyping molecular characterization within a cohort of 107 TN-IHC by means of gene expression profiling
2015-05-19 | E-GEOD-58812 | biostudies-arrayexpress
Project description:The goal of this study is to define biologically distinct subsets of Very Low Risk Wilms Tumors (VLRWT) using oligonucleotide arrays. Description: 52 tumors from the original case:cohort of 600 tumors from NWTS-5 met the criteria for VLRWT. Thirteen tumors were excluded for quality control reasons, resulting in 39 tumors for analysis. Global gene expression analysis was performed on these 39 tumors. A total of 4,000 probesets representing the greatest variability according to coefficient of variation was utilized for hierarchical clustering, and three clusters were identified. Two subsets within VLRWT are identified that have pathogenetic and molecular differences and apparent differences in risk for relapse. If these predictors can be prospectively validated, this would enable future clinical stratification and broadening the definition of VLRWT. Experiment Overall Design: Global gene expression analysis was performed on 39 tumors that met the criteria of VLRWT and passed quality control parameters in order to define biologically distinct subsets. Experiment Overall Design: Hierarchical clustering identified three tumor clusters (C1, C2 and C3). The top differentially expressed genes were identified by first filtering out probesets with a maximum expression of less than 6.5 in all 39 tumors. Using the remaining 14,452 probesets, the expression of each cluster was compared with the expression in the remaining tumors, and those genes with a p-value <0.00001 and positive or negative fold-change (FC) of greater than 2.5 were identified. This resulted in 161 probesets from the comparison of C1 with C2+C3, 43 probesets from the comparison of C2 with C1+C3, and 71 probesets from the comparison of C3 with C1+C2. The false discovery rates were 0.02%, 0.06% and 0.05% for C1, C2, and C3, respectively. These three lists were combined, resulting in 239 probesets (161 genes) which are provided in Supplemental Table 1, linked below.
2010-01-19 | E-GEOD-14767 | biostudies-arrayexpress
Project description:We reports transcriptomic changes observed in the liver of mice treated by 3 concentration of DPhP through drinking water (0.1 mg/L (C1), 1mg/L (C2), 10mg/L(C3)). Mice were treated from 5 to 17 weeks.
2020-09-22 | GSE158265 | GEO
Project description:We report epigenetic changes in the chromatin accessibility landscape of retinal myeloid cells from mice preconditioned with 4xLPS injections persist after the initial inflammation has subsided. We compared the data of scATAC-seq performed on nuclei extracted from sorted CX3CR1+ retinal cells from mice 3 days after CNV induction, preconditioned with either PBS or 4xLPS 1 month before, or Naïve retinas without CNV induction, preconditioned with PBS. After quality control, filtering and dimension reduction, a two-dimensional UMAP was performed on the remaining 835, 821, and 588 cells in the PBS, 4xLPS, and Naive groups respectively. Unbiased clustering was applied using Leiden algorithm, which partitioned CX3CR1+ myeloid cells into 8 distinct clusters (C1–C8). Based on previously described cell-specific gene signatures, we identified microglia (clusters C1, C2 and C3), monocytes (clusters C4 and C5), and macrophages (cluster C6). Gene expression scores identified C4 as circulating monocytes and C5 as a mixture of classical and inflammatory monocytes. The three microglial populations (C1, C2, and C3), harbor the greatest epigenetic diversity following induction of CNV or preconditioning. GSEA analysis revealed that the C2 subpopulation was characterized by considerable enrichment in opened chromatin regions corresponding to genes coding for inflammation-related pathways. In contrast, the C1 subpopulation showed higher numbers of closed chromatin in genes coding for inflammatory processes. Moreover, when compared to the C1 and C2 subpopulations, C3 had open chromatin regions only in two gene sets coding for inflammation-related pathways, and three gene sets with closed chromatin regions. Together, these data demonstrate that the chromatin landscape of retina-resident microglia is impacted differently by both the prior systemic exposure to LPS and by CNV.
2023-02-22 | GSE194226 | GEO
Project description:Interventions: capecitabine
Primary outcome(s): The correlation between the capecitabine dose and the C1 and C2 levels of 5-FU, unchanged capecitabine, 5’-DFCR, 5’-DFUR in the blood. C1=concentration an hour after administration of capecitabine C2=concentration two hours after administration of capecitabine.
Study Design: Single arm Non-randomized
| 2624254 | ecrin-mdr-crc
Project description:Analysis of gene expression levels altered by stable gelsolin overexpression. Results provide important information of the modulation of various genes by gelsolin. Total RNA obtained from stable gelsolin-overexpressing HCT116 clones (C1, C2, C3, C8) as well as emtpy vector control HCT116 cell lines (V4, V5)
2014-03-01 | E-GEOD-36588 | biostudies-arrayexpress
Project description:IgA nephropathy (IgAN) is a heterogeneous disease, which poses a series of challenges to accurate diagnosis and personalized therapy. Here, we present a systematic quantitative kidney tissue proteome atlas across 19 tumor-adjacent normal kidney tissues, 12 membranous nephropathy (MN) samples and 59 biopsies from IgAN patients. Consensus sub-clustering of proteome profiles divided IgAN into three subtypes (IgAN-C1, C2 and C3). Compared to IgAN-C2, the IgAN-C1, and C3 subtypes had a different regulating mechanism and exhibited higher levels of complement activation, more severe mitochondrial injury, and more significant extracellular matrix accumulation. Additionally, IgAN-C1 and C3 had worse clinical outcomes than C2 (30% serum creatinine increase as the end point, P<0.01). Overall, the novel proteomic prognostic subtyping of IgAN could help us understand the heterogeneity of IgAN and improve clinical outcomes.
2022-03-22 | PXD032710 | iProX