Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1123148 | ENA |
REPOSITORIES: ENA
Similar Datasets
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Project description:A data mining paradigm for identifying key factors in biological processes using gene expression data
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Project description:The mechanistic links between transcription factors and the epigenetic landscape, which coordinate the deregulation of gene networks during cell transformation are largely unknown. We used an isogenic model of stepwise tumorigenic transformation of human primary cells to monitor the progressive deregulation of gene networks upon immortalization and oncogene-induced transformation. By combining transcriptome and epigenome data for each step during transformation and by integrating transcription factor (TF) - target gene associations, we identified 142 TFs and 24 chromatin remodelers/modifiers (CRMs), which are preferentially associated with specific co-expression paths that originate from deregulated gene programming during tumorigenesis. These TFs are involved in the regulation of divers processes, including cell differentiation, immune response and establishment/modification of the epigenome. Unexpectedly, the analysis of chromatin state dynamics revealed patterns that distinguish groups of genes, which are not only co-regulated but also functionally related. Further decortication of TF targets enabled us to define potential key regulators of cell transformation, which are engaged in RNA metabolism and chromatin remodelling. Our study suggests a direct implication of CRMs in oncogene-induced tumorigenesis and identifies new CRMs involved in this process. This is the first comprehensive view of gene regulatory networks that are altered during the process of stepwise human cellular tumorigenesis in a virtually isogenic system. Examination of 4 different histone modifications marks and RNA PolII in all 3 cell lines of stepwise tumorigenesis model with biological replicates
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Project description:Exploring the mechanism of transformation and propagation of acute myeloid leukemia is still the key to solving its refractory and relapse-prone problems. Phase separation refers to the process of specific aggregation of biological macromolecules through multivalent binding, and then leads to the functional sectorization in cell. Despite the fact that phase separation has been related to the dysregulation of various cellular processes, its role in the malignant transformation and development of AML is still less characterized. Nucleolus, as a multilayer condensate formed by phase separation, is an important place for the initiation of ribosome formation, and its function is directly related to protein translation.High-resolution imaging and fluorescence recovery after photo-bleaching experiments decode the positive regulatory relationship between the phase separation of FBL and the structure and function of nucleoli. Here, we used RiboMeth-seq to examine rRNA 2’-O-me modification changes influenced by FBL knockdown in AML cells.
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Project description:The BY-COVID Knowledge Graph integrates biological and chemical data from BY-COVID project partner sites. These data are further enriched with information such as biological processes, assays, drug candidates, drug indications, mechanism of action and side effects to form a dynamic and comprehensive network. This is achieved by using the UniProt, ChEMBL and OpenTargets API. The KG is compliant with FAIR annotations allowing seamless transformation and integration to/with other formats and infrastructures. Please check the github for more details: https://github.com/Fraunhofer-ITMP/BY-COVID-KG.
2022-10-17 | MODEL2209020001 | BioModels
Project description:This Agilent QTOF data consists of urine and liver of mice fed AFFF, as well as PFAS chemical standards treated with mouse enzymes for biotransformation. Data acquired by Sheng Liu and David A. Dukes.
It goes alongside the manuscript:
"Expanding PFAS Identification with Transformation Product Libraries: Non-Targeted Analysis Reveals Biotransformation Products in Mice" published in Environmental Science & Technology
An interactive dataset after FluoroMatch annotation for the urine data can be found here:
https://innovativeomics.com/datasets/non-targeted-pfas-dataset-from-urine-of-afff-fed-mice/
Software with the biotransformation libraries can also be found at:
https://innovativeomics.com
Per- and polyfluoroalkyl substances (PFAS) are widely used persistent synthetic chemicals that have been linked to adverse health effects. While the behavior of PFAS has been evaluated in the environment, our understanding of reaction products in mammalian systems is limited. This study identified biological PFAS transformation products and generated mass spectral libraries to facilitate automated search and identification. The biological transformation products of 27 PFAS, spanning 5 chemical subclasses (alcohols, sulfonamides, carboxylic acids, ethers, and esters), were evaluated following enzymatic reaction with mouse liver S9 fractions. Four major pathways were identified by liquid chromatography-high resolution mass spectrometry: glucuronidation; sulfation; dealkylation and oxidation. Class-based fragmentation rules and associated PFAS transformation product libraries were generated and integrated into an automated non-targeted PFAS data analysis software (FluoroMatch). Fragmentation was additionally predicted for the potential transformation products of more than 2,500 PFAS in the EPA CompTox Chemicals Dashboard PFASSTRUCTv4. Generated mass spectral libraries were validated by applying FluoroMatch to a dataset of urine from aqueous film-forming foam (AFFF)-dosed mice. Toxicity predictions showed identified PFAS transformation products as potential developmental and mutagenic toxicants. This research enables more comprehensive PFAS characterization in biological systems which will improve assessment of exposures and evaluation of the associated health impacts.
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Project description:Cell transformation by the Src tyrosine kinase is characterized by extensive changes in gene expression. To describe these changes, investigators have relied extensively on the study of immortalized rodent cell lines or heterogeneous tumor samples that limit the identification of differentially expressed genes or may not represent the full spectrum of biological processes regulated during transformation. In this study, we took advantage of transformation-deficient and temperature sensitive mutants of the Rous sarcoma virus to characterize the patterns of gene expression in two types of primary cells, namely chicken embryo fibroblasts (CEF) and chicken neuro-retinal (CNR) cells. Keywords: viral transformation of primary cells, transformation, transformation deficient mutant, temperature sensitive mutant, v-Src
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Project description:This study examines the long-term impact of polyethylene terephthalate nanoplastics (PET-NPLs) and cigarette smoke condensate (CSC) on human lung BEAS-2B cells, focusing on key biological hallmarks of carcinogenesis. True-to-life PET-NPLs were generated from plastic water bottles and characterized to simulate environmental exposure conditions; a comprehensive battery of assays was employed to assess genotoxicity, cellular transformation, and invasiveness. It was observed that, compared to passage control and individual exposures, co-exposure to PET-NPLs and CSC exacerbates oxidative stress, genotoxicity, and tumorigenic transformation, as evidenced by increased DNA damage, colony formation in soft agar, and enhanced cell migration and invasion. Transcriptomic analysis revealed a shift in cellular stress regulation including the upregulation of stress-response genes, including SLC7A11, NQO1, and HSPA1A, which are linked to oxidative stress adaptation and tumor survival. At the same time, key tumor-suppressor genes, such as GJA1, LOX, and FN1, were significantly downregulated, promoting cellular transformation and invasiveness. These results provide compelling evidence that the combination of PET-NPLs and CSC enhances carcinogenic traits through oxidative stress, genomic instability, and disruption of tumor-suppressive pathways. This study underscores the importance of evaluating the synergistic effects of combined environmental exposures and their implications for human health.
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