Development of a Clinical and Biological Database in Rectum Cancer
Ontology highlight
ABSTRACT:
DISEASE(S): Rectal Neoplasms,Colorectal Cancer,Cancer
PROVIDER: 2309929 | ecrin-mdr-crc |
REPOSITORIES: ECRIN MDR
Similar Datasets
Project description:Background: Many tools used to analyze microarrays in different conditions have been described. However, the integration of the deregulated genes within coherent metabolic pathways is lacking. Currently no objective selection criterion, based on biological functions exists, to determine a threshold demonstrating that a gene is indeed differentially expressed. Methodology/Principal Findings: To improve transcriptomic analysis of microarrays, we propose a new statistical approach, which takes into account biological parameters. We present an iterative method to optimise the selection of differentially expressed gene in two experimental conditions. The stringency level of gene selection was associated simultaneously with the p-value of expression variation and the occurrence rate parameter, which is associated with the percentage of donors whose transcriptomic profile is similar. Our method intertwines stringency level settings, biological data and a knowledge database to highlight molecular interactions using networks and pathways. Analysis performed during iterations helped us select the optimal threshold required for the most pertinent selection of differently expressed genes. Conclusions/significance: We have applied this approach to the well documented mechanism of human macrophage response to lipopolysaccharide stimulation. For example, we thus verified that our method was able to determine with the highest degree of accuracy the best threshold for selecting genes, which are truly differentially expressed. Macrophages isolated from six heathy donnor was/or not stimulated. Paired data, i.e. LPS stimulated macrophages versus unstimulated macrophages from the same donor have been compared (eg, Donor1_LPS vs Donor1_NT; see processed data file linked below). The six comparaisons have been globaly analyse using two parameters, i.e. threshod and occurency, associated with a request of a database knowledge. Both parameters has been tune to define the best setting allowing to optimize the selection of differentially expressed genes
2011-06-19 | E-GEOD-22858 | biostudies-arrayexpress
Project description:The events regulating human preimplantation development are still largely unknown, due to scarcity of material, ethical and legal limitations, and lack of reliable techniques to faithfully amplify the transcriptome of a single cell. Nonetheless, knowledge in human embryology is gathering renewed interest due to its close relationship with both stem cell biology and epigenetic reprogramming to pluripotency, and their centrality to regenerative medicine. Using carefully timed genome-wide transcript analyses on single oocytes and embryos, the analysis of the data allowed us to uncover a series of successive waves of embryonic transcriptional initiation which start as early as the 2 cell stage. In addition, we identified hierarchical activation of genes involved in the regulation of pluripotency. Finally, we developed HumER, a free database of human preimplantation human development gene expression to serve the scientific community. Importantly, our work links early transcription in the human embryo with the correct execution of the pluripotency program later in development, and paves the way for the identification of factors to improve epigenetic reprogramming. Gene expression profiling of human pre-implantation was followed with biological triplicates of oocyte to blastocyst stages, and compared with ESCs.
2011-07-18 | E-GEOD-29397 | biostudies-arrayexpress
Project description:A Transcriptome Database for Astrocytes, Neurons, and Oligodendrocytes: A New Resource for Understanding Brain Development and Function Understanding the cell-cell interactions that control CNS development and function has long been limited by the lack of methods to cleanly separate astrocytes, neurons, and oligodendrocytes. Here we describe the first method for the isolation and purification of developing and mature astrocytes from mouse forebrain. This method takes advantage of the expression of S100β by astrocytes. We used fluorescent activated cell sorting (FACS) to isolate EGFP positive cells from transgenic mice that express EGFP under the control of an S100β promoter. By depletion of astrocytes and oligodendrocytes we obtained purified populations of neurons, while by panning with oligodendrocyte-specific antibodies we obtained purified populations of oligodendrocytes. Using GeneChip Arrays we then created a transcriptome database of the expression levels of over 20,000 genes by gene profiling these three main CNS neural cell types at postnatal ages day 1 to 30. This database provides the first global characterization of the genes expressed by mammalian astrocytes in vivo and is the first direct comparison between the astrocyte, neuron, and oligodendrocyte transcriptomes. We demonstrate that Aldh1L1, a highly expressed astrocyte gene, is a highly specific antigenic marker for astrocytes with a substantially broader, and therefore potentially more useful, pattern of astrocyte expression than the traditional astrocyte marker GFAP. This transcriptome database of acutely isolated and highly pure populations of astrocytes, neurons and oligodendrocytes provides a resource to the neuroscience community by providing improved cell type specific markers and for better understanding of neural development, function, and disease. We acutely purified mouse astrocytes from early postnatal ages (P1) to later postnatal ages (P30), when astrocyte differentiation is morphologically complete (Bushong et al., 2004), and acutely purified mouse OL-lineage cells from stages ranging from OPCs to newly differentiated OLs to myelinating OLs. We extracted RNA from each of these highly purified, acutely isolated cell types and used GeneChip Arrays to determine the expression levels of over 20,000 genes and construct a comprehensive database of cell type specific gene expression in the mouse forebrain. Analysis of this database confirms cell type specific expression of many well characterized and functionally important genes. In addition, we have identified thousands of new cell type enriched genes, thereby providing important new information about astrocyte, OL, and neuron interactions, metabolism, development, and function. This database provides a comparison of the genome-wide transcriptional profiles of the main CNS cell types and is a resource to the neuroscience community for better understanding the development, physiology, and pathology of the CNS. Keywords: Developmental CNS Cell type comparision
2007-12-31 | GSE9566 | GEO
Project description:The events regulating human preimplantation development are still largely unknown, due to scarcity of material, ethical and legal limitations, and lack of reliable techniques to faithfully amplify the transcriptome of a single cell. Nonetheless, knowledge in human embryology is gathering renewed interest due to its close relationship with both stem cell biology and epigenetic reprogramming to pluripotency, and their centrality to regenerative medicine. Using carefully timed genome-wide transcript analyses on single oocytes and embryos, the analysis of the data allowed us to uncover a series of successive waves of embryonic transcriptional initiation which start as early as the 2 cell stage. In addition, we identified hierarchical activation of genes involved in the regulation of pluripotency. Finally, we developed HumER, a free database of human preimplantation human development gene expression to serve the scientific community. Importantly, our work links early transcription in the human embryo with the correct execution of the pluripotency program later in development, and paves the way for the identification of factors to improve epigenetic reprogramming.
2011-07-19 | GSE29397 | GEO
Project description:Background: Many tools used to analyze microarrays in different conditions have been described. However, the integration of the deregulated genes within coherent metabolic pathways is lacking. Currently no objective selection criterion, based on biological functions exists, to determine a threshold demonstrating that a gene is indeed differentially expressed. Methodology/Principal Findings: To improve transcriptomic analysis of microarrays, we propose a new statistical approach, which takes into account biological parameters. We present an iterative method to optimise the selection of differentially expressed gene in two experimental conditions. The stringency level of gene selection was associated simultaneously with the p-value of expression variation and the occurrence rate parameter, which is associated with the percentage of donors whose transcriptomic profile is similar. Our method intertwines stringency level settings, biological data and a knowledge database to highlight molecular interactions using networks and pathways. Analysis performed during iterations helped us select the optimal threshold required for the most pertinent selection of differently expressed genes. Conclusions/significance: We have applied this approach to the well documented mechanism of human macrophage response to lipopolysaccharide stimulation. For example, we thus verified that our method was able to determine with the highest degree of accuracy the best threshold for selecting genes, which are truly differentially expressed.
2011-06-19 | GSE22858 | GEO
Project description:Development of a Large-Scale Chemogenomics Database to Improve Drug Candidate Selection and to Understand Mechanisms of Chemical Toxicity and Action These data support the publication titled "Development of a Large-Scale Chemogenomics Database to Improve Drug Candidate Selection and to Understand Mechanisms of Chemical Toxicity and Action" Copyright (c) 2005 by Iconix Pharmaceuticals, Inc. Guidelines for commercial use: http://www.iconixbiosciences.com/guidelineCommUse.pdf Keywords: other
2005-06-01 | GSE2409 | GEO
Project description:Creation of circulating cancer cell-lines and caracterisation of these cell-lines which will be collected before any treatment in patients with metastatic colon adenocarcinoma
| 2323696 | ecrin-mdr-crc
Project description:MicroRNA profiling was performed on RNA samples matched to those included in the NIH Human Pluripotent Stem Cell Database (Series GSE32923). Twenty undifferentiated human embryonic stem cell lines and 4 human tissues were analyzed. Expanded descriptions of methods used are available at: http://stemcelldb.nih.gov.
2012-10-31 | GSE34199 | GEO
Project description:PiceaGenExpress database of transcription profiles
| PRJNA152465 | ENA
Project description:synthetic sequence dataset database metagenome
| PRJEB4579 | ENA