Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA151399 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:A Systems Biology Approach Reveals Common Metastatic Pathways in Osteosarcoma
| PRJNA161863 | ENA
Project description:A part of current research has intensively been focused on the proliferation and metabolic processes governing biological systems. Since the advent of high throughput methodologies like microarrays, the load of genomic data has increased geometrically and along with that the need for computational methods which will interpret these data. In the present work we study in vitro the common proliferation and metabolic processes, which are combined to the common oncogenic pathways, as far as gene expression is concerned, between the T-cell acute lymphoblastic leukemia (CCRF-CEM) and the rhabdomyosarcoma (TE-671) cell lines. We present a computational approach, using cDNA microarrays, in order to identify commonalities between diverse biological systems. Our analysis predicted that JAK1, STAT1, PIAS2 and CDK4 are the driving forces in the two cell lines. This type of analysis can lead to the understanding of the common mechanisms that transform physiological cells to malignant, as well as it reveals a new holistic way to understandthe the dynamics of tumor onset as well as the mechanistics of oncogenic drivers. The present work is concerned with the common expressional profile of two cell lines: the T-cell acute lymphoblastic leukemia (CCRF-CEM) and the rhabdomyosarcoma (TE-671) cell lines. Our investigation was focused on the identification of genes that share a common expression profile between the two cell lines. Both cell lines are characterized by the fact that their differentiation has stopped at an early stage, before they mature to their final cell type. Normally, these cells would have matured and progressed into differentiated cells, constituting blood and muscle cells, respectively. At some unknown point, normal differentiation ceased for these cells and they became malignant. From that point on, to the first manifestation of symptoms of malignancy, there is a lack of knowledge regarding the mechanisms underlying oncogenesis. From these observations, the question whether two distinct cell types destined to fulfill different functions, manifest similar mechanisms of growth and progression due to their malignant character, arises. The present study was focused on the identification of the differential expression profiles underlying the two cell lines. A previous report studied the expression profile of seven ARMS cell lines possessing the PAX3-FKHR fusion gene, along with other cell lines of different tumor types (22). To our knowledge, this is the first time that a comparison between two totally different types of neoplasia, such as the CCRF-CEM and TE-671 cell lines, is attempted. These mechanisms are examined with purpose to identify common drivers that lead to the progression of tumor cells. We hereby propose a new computational approach for the investigation of common oncogenic drivers.
2011-12-20 | E-GEOD-34522 | biostudies-arrayexpress
Project description:A part of current research has intensively been focused on the proliferation and metabolic processes governing biological systems. Since the advent of high throughput methodologies like microarrays, the load of genomic data has increased geometrically and along with that the need for computational methods which will interpret these data. In the present work we study in vitro the common proliferation and metabolic processes, which are combined to the common oncogenic pathways, as far as gene expression is concerned, between the T-cell acute lymphoblastic leukemia (CCRF-CEM) and the rhabdomyosarcoma (TE-671) cell lines. We present a computational approach, using cDNA microarrays, in order to identify commonalities between diverse biological systems. Our analysis predicted that JAK1, STAT1, PIAS2 and CDK4 are the driving forces in the two cell lines. This type of analysis can lead to the understanding of the common mechanisms that transform physiological cells to malignant, as well as it reveals a new holistic way to understandthe the dynamics of tumor onset as well as the mechanistics of oncogenic drivers.
2011-12-20 | GSE34522 | GEO
Project description:Classifying distinct grades of human non-alcoholic fatty liver disease employing a systems biology approach
| PRJNA198657 | ENA
Project description:Comparison of temporal gene expression profiles to identify genes/pathways changing during ageing. Jena Centre for Systems Biology of Ageing - JenAge (www.jenage.de)
2018-01-08 | GSE103232 | GEO
Project description:Background: Comparison of temporal gene expression profiles Jena Centre for Systems Biology of Ageing - JenAge (www.jenage.de)
2018-01-08 | GSE75337 | GEO
Project description:Homo sapiens Transcriptome Prostate Cancer Systems Biology
| PRJNA579899 | ENA
Project description:The use of a systems biology approach to analyze common and specific mechanisms of liver toxicity induced by munitions compounds TNT, 2,6-DNT, 2,4-DNT, 4A-DNT, and 2A-DNT The munitions compound 2,4,6-trinitrotoluene (TNT), its environmental degradation products 2-amino-4,6-dinitrotoluene (2A-DNT) and 4-amino-2,6-dinitrotoulene (4A-DNT), and two other munitions, 2,4-dinitrotoluene (2,4-DNT) and 2,4-dinitrotoluene (2,6-DNT) contaminate contaminate land, water and retired ammunitions plants. The release of these compounds to the environment is due to military activities and a series of manufacturing processes. Although toxicity has been characterized for these compounds, little is known of their mechanism of action. Here we describe to use an integrative systems biology approach including toxicology, pathology, transcriptomics, metabolomics, gene function classification, pathway analysis and gene network modeling to try to understand the mechanisms of toxicity of these compounds.
2009-12-25 | GSE19628 | GEO
Project description:Metabolic alterations can serve as targets for diagnosis and therapy of cancer. Due to the highly complex regulation of cellular metabolism, definite identification of metabolic pathway alterations remains challenging and requires sophisticated experimentation. Here, we applied a comprehensive kinetic model of the central carbon metabolism (CCM) to characterize metabolic reprogramming in murine liver cancer. We show that relative differences of protein abundances of metabolic enzymes obtained by mass spectrometry can be used to scale maximal enzyme capacities. Model simulations predicted tumor-specific alterations of various components of the CCM, a selected number of which were subsequently verified by in vitro and in vivo experiments. Furthermore, we demonstrate the ability of the kinetic model to identify metabolic pathways whose inhibition results in selective tumor cell killing. Our systems biology approach establishes that combining cellular experimentation with computer simulations of physiology-based metabolic models enables a comprehensive understanding of deregulated energetics in cancer.
2020-03-20 | PXD011162 | Pride
Project description:Crosstalk and complexity within signaling pathways has limited our ability to devise rational strategies for using network biology to treat human disease. This is particularly problematic in cancer where oncogenes that drive or maintain the tumorigenic state alter the normal flow of molecular information within signaling networks that control growth, survival and death. Understanding the architecture of oncogenic signaling pathways, and how these networks are re-wired by ligands or drugs, could provide opportunities for the specific targeting of oncogene-driven tumors. Here we use a systems biology-based approach to explore synergistic therapeutic strategies to optimize the killing of triple negative breast cancer cells, an incompletely understood tumor type with a poor treatment outcome. Using targeted inhibition of oncogenic signaling pathways combined with DNA damaging chemotherapy, we report the surprising finding that time-staggered EGFR inhibition, but not simultaneous co-administration, can dramatically sensitize the apoptotic response of a subset of triple-negative cells to conventional DNA damaging agents. A systematic analysis of the order and timing of inhibitor/genotoxin presentation—using a combination of high-density time-dependent activity measurements of signaling networks, gene expression profiles, cell phenotypic responses, and mathematical modeling—revealed an approach for altering the intrinsic oncogenic state of the cell through dynamic re-wiring of oncogenic signaling pathways. This process converts these cells to a less tumorigenic state that is more susceptible to DNA damage-induced cell death, through re-activation of an extrinsic apoptotic pathway whose function is suppressed in the oncogene-addicted state. Three or 4 replicates of 3 different cell lines at time points 0minutes, 30minutes, 6 hours and 1 day after EGFR inhibition with erlotinib
2012-05-14 | E-GEOD-30516 | biostudies-arrayexpress