0bef3263-51f7-4987-9a1d-e8684edfc3a0 - samples
Ontology highlight
ABSTRACT:
PROVIDER: EGAD00001008745 | EGA |
REPOSITORIES: EGA
Similar Datasets
Project description:The cellular origin and differentiation status of glioblastoma by scRNA-seq
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Project description:The cellular origin of perivasuclar glioblastoma by scRNA-seq
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Project description:Understanding the cellular origin and differentiation status of glioblastoma is critical to resolve the etiology of the disease. we profile 18 patient glioblastomas by single cell RNA sequencing (scRNAseq). From this, we uncovered two principal cell-of-origin relations. Each lineage displays unique directional differentiation trajectories and transcriptional cores from the naïve cell populations. Thus, glioblastoma is defined by robust cell lineage features which may provide insights into the cell origin of the diseases.
2022-04-19 | GSE159416 | GEO
Project description:Understanding the cellular origin and differentiation status of glioblastoma is critical to resolve the etiology of the disease. we profile 18 patient glioblastomas by single cell RNA sequencing (scRNAseq). From this, we uncovered two principal cell-of-origin relations. Each lineage displays unique directional differentiation trajectories and transcriptional cores from the naïve cell populations. Thus, glioblastoma is defined by robust cell lineage features which may provide insights into the cell origin of the diseases.
| EGAS00001006236 | EGA
Project description:Understanding the cellular origin and differentiation status of glioblastoma is critical to resolve the etiology of the disease. we profile control and genetically modified human brain perivasuclar fibroblasts by single cell RNA sequencing (scRNAseq). From this, we observed the potential tumorigenicity of brian perivascular fibroblasts.
2022-04-19 | GSE171287 | GEO
Project description:Glioblastoma is the most common type of malignant brain tumor among adults. We used single-cell RNA sequencing (scRNA-seq) to analyze the diversity of glioblastoma cells.
2024-07-25 | GSE214966 | GEO
Project description:scRNA-Seq analysis of adult glioblastoma patient samples
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Project description:Tumor microtubes (TMs) connect glioma cells to a network with considerable relevance for tumor progression and therapy resistance. The determination of TM-interconnectivity in individual tumors has been challenging and the impact on patient survival unresolved. Here, a connectivity signature from single-cell RNA-sequenced (scRNA-Seq) xenografted primary glioblastoma (GB) cells has been established using a dye uptake methodology, confirmed with recording of cellular calcium epochs and validated with clinical correlations. Astrocyte-like and mesenchymal-like GB cells have the highest connectivity signature scores in scRNA-sequenced patient-derived xenografts and patient samples. In large GB cohorts, network connectivity correlated with the mesenchymal subtype and dismal patient survival. CHI3L1 has been identified and validated as a robust molecular marker of connectivity with functional relevance. The connectivity signature allows novel insights into brain tumor biology, provides a proof-of-principle that tumor cell TM-connectivity is relevant for patients’ prognosis, and serves as a robust prognostic biomarker.
2023-11-27 | PXD044001 | Pride
Project description:Idiopathic pulmonary fibrosis (IPF) is a progressive lung disease characterized by repetitive alveolar injuries with excessive deposition of extracellular matrix (ECM) proteins. A crucial need in understanding IPF pathogenesis is identifying cell types associated with histopathological regions, particularly local fibrosis centers known as fibroblast foci. To address this, we integrated published spatial transcriptomics and single-cell RNA sequencing (scRNA-seq) transcriptomics and adopted the Query method and the Overlap method to determine cell type enrichments in histopathological regions. Distinct fibroblast cell types are highly associated with fibroblast foci, and transitional alveolar type 2 and aberrant KRT5-/KRT17+ epithelial cells are associated with morphologically normal alveoli in human IPF lungs. Furthermore, we employed laser capture microdissection directed mass spectrometry to profile proteins. By comparing with another published similar dataset, common differentially expressed proteins and enriched pathways related to ECM structure organization and collagen processing were identified in fibroblast foci. Importantly, cell type enrichment results from innovative spatial proteomics and scRNA-seq data integration accord with those from spatial transcriptomics and scRNA-seq data integration, supporting the capability and versatility of the entire approach. In summary, we integrated spatial multi-omics with scRNA-seq data to identify disease-associated cell types and potential targets for novel therapies in IPF intervention. The approach can be further applied to other disease areas characterized by spatial heterogeneity.
2025-01-27 | PXD058805 | Pride
Project description:Plasmodium-specific CD4+ T cells from mice infected with Plasmodium chabaudi chabaudi AS parasites were recovered at Days 0, 7, and 28 to undergo processing and generate scRNA-seq dataset. At Day 28, mice were administered with either saline or artesunate (intermittent artesunate therapy - IAT). scRNA-seq dataset was analysed to investigate transcriptome dynamics of CD4+ T cells from effector to memory states.
2020-10-14 | E-MTAB-9317 | biostudies-arrayexpress