Single cell multi-omic data of glioblastoma evolution under therapy
Ontology highlight
ABSTRACT:
PROVIDER: EGAS00001004909 | EGA |
REPOSITORIES: EGA
Similar Datasets
Project description:Epithelial to Mesenchymal Transition (EMT) has been associated with cancer cell heterogeneity, plasticity and metastasis. It has been the subject of several modeling effort. This logical model of the EMT cellular network aims to assess microenvironmental signals controlling cancer-associated phenotypes amid the EMT continuum. Its outcomes relate to the qualitative degrees of cell adhesions by adherent junctions and focal adhesions, two features affected during EMT. Model attractors recover epithelial, mesenchymal and hybrid phenotypes, and simulations show that hybrid phenotypes may arise through independent molecular paths, involving stringent extrinsic signals.
Of particular interest, model predictions and their experimental validations indicated that: 1) ECM stiffening is a prerequisite for cells overactivating FAK-SRC to upregulate SNAIL1 and acquire a mesenchymal phenotype, and 2) FAK-SRC inhibition of cell-cell contacts through the Receptor Protein Tyrosine Phosphates kappa leads to the acquisition of a full mesenchymal rather than a hybrid phenotype.
2020-06-30 | MODEL2004040001 | BioModels
Project description:Extrinsic Phagocyte-Dependent STING-Signaling Dictates the Immunogenicity of Dying Cells
| PRJNA434824 | ENA
Project description:We profiled 87 primary-recurrentpatient-matched paired GBM specimens with single-nucleus RNA and bulk-DNA sequencing and single-cell open-chromatin and spatial transcriptomics/proteomics assays. We found that recurrent GBMs are characterized by a shift to a mesenchymal phenotype in response to therapy
| EGAD00001008811 | EGA
Project description:Schittler2010 - Cell fate of progenitor cells, osteoblasts or chondrocytes
Mathematical model describing the mechanism of differentiation of mesenchymal stem cells to bone (osteoblasts) or cartilage (chondrocytes) cells.
This model is described in the article:
Cell differentiation modeled via a coupled two-switch regulatory network.
Schittler D, Hasenauer J, Allgöwer F, Waldherr S.
Chaos 2010 Dec; 20(4): 045121
Abstract:
Mesenchymal stem cells can give rise to bone and other tissue cells, but their differentiation still escapes full control. In this paper we address this issue by mathematical modeling. We present a model for a genetic switch determining the cell fate of progenitor cells which can differentiate into osteoblasts (bone cells) or chondrocytes (cartilage cells). The model consists of two switch mechanisms and reproduces the experimentally observed three stable equilibrium states: a progenitor, an osteogenic, and a chondrogenic state. Conventionally, the loss of an intermediate (progenitor) state and the entailed attraction to one of two opposite (differentiated) states is modeled as a result of changing parameters. In our model in contrast, we achieve this by distributing the differentiation process to two functional switch parts acting in concert: one triggering differentiation and the other determining cell fate. Via stability and bifurcation analysis, we investigate the effects of biochemical stimuli associated with different system inputs. We employ our model to generate differentiation scenarios on the single cell as well as on the cell population level. The single cell scenarios allow to reconstruct the switching upon extrinsic signals, whereas the cell population scenarios provide a framework to identify the impact of intrinsic properties and the limiting factors for successful differentiation.
This model is hosted on BioModels Database
and identified
by: BIOMD0000000493
.
To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource
for published quantitative kinetic models
.
To the extent possible under law, all copyright and related or
neighbouring rights to this encoded model have been dedicated to the public
domain worldwide. Please refer to CC0 Public Domain
Dedication
for more information.
2024-09-02 | BIOMD0000000493 | BioModels
Project description:Effects of biobanking on chromatin accessibility
| PRJNA290920 | ENA
Project description:Dysregulation of alternative splicing of mRNA precursors is known to contribute to numerous human diseases. In this study we carried out the first systematic search for asthma-associated changes in alternative splicing events, using a model of Aspergillus fumigatus (A. fumigatus)-sensitized mice and an exon junction microarray to detect potential changes in alternative splicing. One of the sensitization-associated changes identified in the search was a shift in alternative splicing of the mRNA encoding cFLIP, a modulator of the caspase- mediated extrinsic apoptosis pathway. Expanding these studies to human asthma patients, we discovered a significant decrease in the expression of both cFLIP isoforms in severe corticosteroid- resistant asthmatics. Although it is unclear whether these changes were due solely to differences in alternative splicing, these findings provide evidence that dysregulation of the extrinsic apoptosis pathway is part of the underlying immunopathogenesis of severe refractory asthma. The technical side of the microarray experiment was essentially the Illumina protocol.
2014-01-14 | E-GEOD-28258 | biostudies-arrayexpress
Project description:Fetal hematopoietic stem and progenitor cells (HSPCs) migrate from fetal liver (FL) to bone marrow (BM) around birth. While adult BM HSPCs and their extrinsic regulation is well studied, little is known about the composition, function, and extrinsic regulation of the first HSPCs to enter the BM. Here, we show that HSPCs colonize multiple fetal bones by E15.5, shift from an MPP2 to an MPP3/4-dominant phenotype by birth, and display little function until E18.5, relative to their FL counterparts. We establish a transcriptional atlas of single perinatal HSPCs, and their putative BM niches, from E15.5 through P0 and show that early fetal BM (FBM) lacks HSPCs with intrinsic stem cell programs and niche cells supportive of HSPCs. In contrast, stem cell programs are preserved in neonatal BM HSPCs, which engage with a niche expressing HSC supportive factors distinct from those seen in adult BM (i.e., IGF).
2021-06-26 | GSE178951 | GEO
Project description:Recent advances in experimental biology allow creation of datasets where several genome-wide data types (called omics) are measured per sample. Integrative analysis of multi-omic datasets in general, and clustering of samples in such datasets specifically, can improve our understanding of biological processes and discover different disease subtypes. In this work we present MONET (Multi Omic clustering by Non-Exhaustive Types), which presents a unique approach to multi-omic clustering. MONET discovers modules of similar samples, such that each module is allowed to have a clustering structure for only a subset of the omics. This approach differs from most existent multi-omic clustering algorithms, which assume a common structure across all omics, and from several recent algorithms that model distinct cluster structures. We tested MONET extensively on simulated data, on an image dataset, and on ten multi-omic cancer datasets from TCGA. Our analysis shows that MONET compares favorably with other multi-omic clustering methods. We demonstrate MONET's biological and clinical relevance by analyzing its results for Ovarian Serous Cystadenocarcinoma. We also show that MONET is robust to missing data, can cluster genes in multi-omic dataset, and reveal modules of cell types in single-cell multi-omic data. Our work shows that MONET is a valuable tool that can provide complementary results to those provided by existent algorithms for multi-omic analysis.
| S-EPMC7518594 | biostudies-literature
Project description:Studies of genomic instability have historically focused on intrinsic mechanisms rather than extrinsic mechanisms based in the tumor microenvironment (TME). TGF-β is the most abundantly secreted cytokine in the TME where it imparts various aggressive characteristics including invasive migration, drug resistance and epithelial-to-mesenchymal transition (EMT). Here we show that TGF-β also promotes genomic instability in the form of DNA double strand breaks (DSB) in cancer cells which lack the tumor suppressor gene RUNX3. Loss of RUNX3 resulted in transcriptional downregulation of the redox regulator heme oxygenase-1 (HO-1 or HMOX1). Consequently, elevated oxidative DNA damage disrupted genomic integrity and triggered cellular senescence, which was accompanied by tumor-promoting inflammatory cytokine expression and acquisition of the senescence-associated secretory phenotype (SASP). Recapitulating the above findings, tumors harbouring a TGF-β gene expression signature and RUNX3 loss exhibited higher levels of genomic instability. In summary, RUNX3 creates an effective barrier against further TGF-β-dependent tumor progression by preventing genomic instability. These data suggest a novel cooperation between cancer cell-extrinsic TGF-β signaling and cancer cell-intrinsic RUNX3 inactivation as aggravating factors for genomic instability.
2019-06-20 | GSE133037 | GEO
Project description:This SuperSeries is composed of the following subset Series: GSE39108: UNG shapes the specifity of AID-induced somatic hypermutation in non B cells GSE39114: UNG shapes the specifity of AID-induced somatic hypermutation in B cells Refer to individual Series
2012-07-04 | E-GEOD-39115 | biostudies-arrayexpress