Stockholm-Tartu Atherosclerosis Reverse Network Engineering Task (STARNET)
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PROVIDER: PRJNA341430 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Stockholm-Tartu Atherosclerosis Reverse Network Engineering Task (STARNET)
| PRJNA341431 | ENA
Project description:This SuperSeries is composed of the following subset Series: GSE38584: Hierarchical regulation in a KRAS pathway-dependent transcriptional network revealed by a reverse-engineering approach (7TF and control) GSE38585: Hierarchical regulation in a KRAS pathway-dependent transcriptional network revealed by a reverse-engineering approach (RAS-ROSE and ROSE with siRNA) Refer to individual Series
2012-07-31 | E-GEOD-38614 | biostudies-arrayexpress
Project description:While our understanding of the single-cell gene expression patterns underlying the transformation of vascular cell types during the progression of atherosclerosis is rapidly improving, the clinical and pathophysiological relevance of these changes remain poorly understood. Single cell RNA sequencing (scRNAseq) data generated with SmartSeq2 (~8000 genes/cell) in nearly 19,000 single cells isolated during atherosclerosis progression in mice with human-like plasma lipoproteins and from humans with asymptomatic and symptomatic carotid plaques was clustered into multiple subtypes. For clinical and pathophysiological context, the advanced-stage and symptomatic subtype clusters were integrated with 135 tissue-specific (atherosclerotic aortic wall, mammary artery, liver, skeletal muscle, and visceral and subcutaneous, fat) gene-regulatory networks (GRNs) inferred from 600 coronary artery disease (CAD) patients in the Stockholm-Tartu Atherosclerosis Reverse Network Engineering Task (STARNET) study.Advanced stages of atherosclerosis progression and symptomatic carotid plaques were largely characterized by three smooth-muscle cells (SMC), and three macrophage (MP) subtype clusters with extracellular matrix organization/osteogenic (SMC), and M1-type pro-inflammatory/Trem2-high lipid-associated (MP) phenotypes. Integrative analysis of these 6 clusters with STARNET revealed significant enrichments of three arterial wall GRNs: GRN33 (MP), GRN39 (SMC) and GRN122(MP) with major contributions to CAD heritability and strong associations with clinical scores of coronary atherosclerosis severity (SYNTAX/Duke scores). The presence and pathophysiological relevance of GRN39 was verified in five independent RNAseq datasets obtained from the human coronary and aortic artery, and primary SMCs and by targeting its top-key drivers, FRZB and ALCAM, in cultured human vascular SMCs.By identifying and integrating the most gene-rich single-cell subclusters of atherosclerosis to date with a CAD framework of GRNs, GRN39 was identified and independently validated as being critical for the transformation of contractile SMCs into an osteogenic phenotype promoting advanced-stage, symptomatic atherosclerosis.
2024-03-05 | GSE260656 | GEO
Project description:While our understanding of the single-cell gene expression patterns underlying the transformation of vascular cell types during the progression of atherosclerosis is rapidly improving, the clinical and pathophysiological relevance of these changes remain poorly understood. Single cell RNA sequencing (scRNAseq) data generated with SmartSeq2 (~8000 genes/cell) in nearly 19,000 single cells isolated during atherosclerosis progression in mice with human-like plasma lipoproteins and from humans with asymptomatic and symptomatic carotid plaques was clustered into multiple subtypes. For clinical and pathophysiological context, the advanced-stage and symptomatic subtype clusters were integrated with 135 tissue-specific (atherosclerotic aortic wall, mammary artery, liver, skeletal muscle, and visceral and subcutaneous, fat) gene-regulatory networks (GRNs) inferred from 600 coronary artery disease (CAD) patients in the Stockholm-Tartu Atherosclerosis Reverse Network Engineering Task (STARNET) study.Advanced stages of atherosclerosis progression and symptomatic carotid plaques were largely characterized by three smooth-muscle cells (SMC), and three macrophage (MP) subtype clusters with extracellular matrix organization/osteogenic (SMC), and M1-type pro-inflammatory/Trem2-high lipid-associated (MP) phenotypes. Integrative analysis of these 6 clusters with STARNET revealed significant enrichments of three arterial wall GRNs: GRN33 (MP), GRN39 (SMC) and GRN122(MP) with major contributions to CAD heritability and strong associations with clinical scores of coronary atherosclerosis severity (SYNTAX/Duke scores). The presence and pathophysiological relevance of GRN39 was verified in five independent RNAseq datasets obtained from the human coronary and aortic artery, and primary SMCs and by targeting its top-key drivers, FRZB and ALCAM, in cultured human vascular SMCs.By identifying and integrating the most gene-rich single-cell subclusters of atherosclerosis to date with a CAD framework of GRNs, GRN39 was identified and independently validated as being critical for the transformation of contractile SMCs into an osteogenic phenotype promoting advanced-stage, symptomatic atherosclerosis.
2024-03-05 | GSE260657 | GEO
Project description:Mutations in RAS proteins occur in 30% of human tumours and have a high relevance in tumor progression. Despite the importance of the underlying genetic network that governs the effects of oncogenic RAS, it is still poorly understood. We developed and applied a reverse-engineering approach in order to reconstruct the network structure of the signaling and gene-regulatory network downstream of RAS from perturbation experiments. We performed microarray, RT-PCR and Western Blot analysis to detect mRNA and protein levels of cytoplasmatic and nuclear targets downstream of RAS after systematic perturbation of the signaling pathways and knock-down of selected transcription factors in KRAS-transformed ovarian surface epithelium cell lines. The reconstructed model shows that the investigated components are connected through a complex network. The transcription factors decomposed into two hierarchically arranged groups. While knock-down of all investigated transcription factors showed a partial reversion of the malignant phenotype, different growth assays show that these two groups of transcription factors control different functions in the malignant anchorage-independent growth and cell cycle regulation of the ROSE cells. Furthermore, the model showed strong regulatory interplay of inhibitory and activating interactions between the RAS-dependent trancriptional network and cytoplasmatic signaling components. Overall the study contains 32 samples. We studied the influence of seven transcription factors (Fosl1, Gfi1, Hmga2, Junb, Klf6, Otx1, Rela) being knocked down by means of RNA interference. Two independent siRNA duplexes (N1, N2) against the same gene were used. All experiments were done with Cy3/Cy5 dye-swaps. As a negative control, we used scrambled siRNAs. Off-target effect was estimated by comparison of the scrambled siRNA treatment and an unterated cell line ROSEA 25.
2011-03-01 | E-GEOD-24668 | biostudies-arrayexpress
Project description:Mutations in RAS proteins occur in 30% of human tumours and have a high relevance in tumor progression. Despite the importance of the underlying genetic network that governs the effects of oncogenic RAS, it is still poorly understood. We developed and applied a reverse-engineering approach in order to reconstruct the network structure of the signaling and gene-regulatory network downstream of RAS from perturbation experiments. We performed microarray, RT-PCR and Western Blot analysis to detect mRNA and protein levels of cytoplasmatic and nuclear targets downstream of RAS after systematic perturbation of the signaling pathways and knock-down of selected transcription factors in KRAS-transformed ovarian surface epithelium cell lines. The reconstructed model shows that the investigated components are connected through a complex network. The transcription factors decomposed into two hierarchically arranged groups. While knock-down of all investigated transcription factors showed a partial reversion of the malignant phenotype, different growth assays show that these two groups of transcription factors control different functions in the malignant anchorage-independent growth and cell cycle regulation of the ROSE cells. Furthermore, the model showed strong regulatory interplay of inhibitory and activating interactions between the RAS-dependent trancriptional network and cytoplasmatic signaling components.
2011-03-01 | GSE24668 | GEO
Project description:RAS mutations are highly relevant for progression and therapy response of human tumours, but the genetic network that ultimately executes the oncogenic effects is poorly understood. Here we used a reverse-engineering approach in an ovarian cancer model to reconstruct KRAS oncogene-dependent cytoplasmic and transcriptional networks from perturbation experiments based on gene silencing and pathway inhibitor treatments. We measured mRNA and protein levels in manipulated cells by microarray, RT-PCR and Western Blot analysis, respectively. The reconstructed model revealed complex interactions among the transcriptional and cytoplasmic components, some of which were confirmed by double pertubation experiments. Interestingly, the transcription factors decomposed into two hierarchically arranged groups. To validate the model predictions we analysed growth parameters and transcriptional deregulation in the KRAS-transformed epithelial cells. As predicted by the model, we found two functional groups among the selected transcription factors. The experiments thus confirmed the predicted hierarchical transcription factor regulation and showed that the hierarchy manifests itself in downstream gene expression patterns and phenotype. RAS-ROSE cells were treated with siRNA against 7 transcription factors or controls,
2012-07-31 | E-GEOD-38584 | biostudies-arrayexpress
Project description:The TLX1 and TLX3 transcription factor oncogenes play an important role in the pathogenesis of T-cell acute lymphoblastic leukemia (T-ALL)1,2. Here we used reverse engineering of global transcriptional networks to decipher the oncogenic regulatory circuit controlled by TLX1 and TLX3. This Systems Biology analysis defined TLX1 and TLX3 as master regulators of an oncogenic transcriptional circuit governing T-ALL. Notably, network structure analysis of this hierarchical network identified RUNX1 as an important mediator of TLX1 and TLX3 induced T-ALL, and predicted a tumor suppressor role for RUNX1 in T-cell transformation. Consistent with these results, we identified recurrent somatic loss of function mutations in RUNX1 in human T-ALL. Overall, these results place TLX1 and TLX3 atop of an oncogenic transcriptional network controlling leukemia development, demonstrate power of network analysis to identify key elements in the regulatory circuits governing human cancer and identify RUNX1 as a tumor suppressor gene in T-ALL. This SuperSeries is composed of the following subset Series: GSE33539: Expression data obtained from ALLSIL cell line GSE33540: Expression data obtained from HPBALL cell line GSE33549: Expression data from mouse T-cell lymphomas
2011-11-08 | E-GEOD-33550 | biostudies-arrayexpress
Project description:RAS mutations are highly relevant for progression and therapy response of human tumours, but the genetic network that ultimately executes the oncogenic effects is poorly understood. Here we used a reverse-engineering approach in an ovarian cancer model to reconstruct KRAS oncogene-dependent cytoplasmic and transcriptional networks from perturbation experiments based on gene silencing and pathway inhibitor treatments. We measured mRNA and protein levels in manipulated cells by microarray, RT-PCR and Western Blot analysis, respectively. The reconstructed model revealed complex interactions among the transcriptional and cytoplasmic components, some of which were confirmed by double pertubation experiments. Interestingly, the transcription factors decomposed into two hierarchically arranged groups. To validate the model predictions we analysed growth parameters and transcriptional deregulation in the KRAS-transformed epithelial cells. As predicted by the model, we found two functional groups among the selected transcription factors. The experiments thus confirmed the predicted hierarchical transcription factor regulation and showed that the hierarchy manifests itself in downstream gene expression patterns and phenotype. RAS-ROSE cells and ROSE cells treated with Scrambled siRNA
2012-07-31 | E-GEOD-38585 | biostudies-arrayexpress
Project description:RAS mutations are highly relevant for progression and therapy response of human tumours, but the genetic network that ultimately executes the oncogenic effects is poorly understood. Here we used a reverse-engineering approach in an ovarian cancer model to reconstruct KRAS oncogene-dependent cytoplasmic and transcriptional networks from perturbation experiments based on gene silencing and pathway inhibitor treatments. We measured mRNA and protein levels in manipulated cells by microarray, RT-PCR and Western Blot analysis, respectively. The reconstructed model revealed complex interactions among the transcriptional and cytoplasmic components, some of which were confirmed by double pertubation experiments. Interestingly, the transcription factors decomposed into two hierarchically arranged groups. To validate the model predictions we analysed growth parameters and transcriptional deregulation in the KRAS-transformed epithelial cells. As predicted by the model, we found two functional groups among the selected transcription factors. The experiments thus confirmed the predicted hierarchical transcription factor regulation and showed that the hierarchy manifests itself in downstream gene expression patterns and phenotype.
2012-08-01 | GSE38584 | GEO