Ontology highlight
ABSTRACT:
PROVIDER: PRJNA936151 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Investigative needle core biopsies support multimodal deep-data generation in glioblastoma [Spatial Transcriptomics]
| PRJNA1213852 | ENA
Project description:Kidney transplant rejections are classified as active antibody mediated rejection (AMR) and cell mediated rejection (TCMR), with AMR primarily driven by antibodies produced by B cells, whereas TCMR is mediated by T lymphocytes that orchestrate cellular immune responses against the graft. Emerging evidence highlights the essential roles of innate immune cells in rejections, especially monocytes/macrophages and natural killer (NK) cells. However, the roles of specific innate immune cell subpopulations in kidney allograft rejection remain incompletely understood. Exploiting the spatial transcriptomics and formalin-fixed paraffin-embedded (FFPE) core needle biopsies from human kidney allografts, we demonstrated that non-rejection, AMR, acute TCMR and chronic active AMR have distinct transcriptomic features. Subclusters of monocytes/macrophages with high Fc gamma receptor IIIA (FCGR3A) expression were identified in C4d-positive active AMR and acute TCMR, and the spatial distribution of these cells corresponded to the characteristic histopathological features. Key markers related to monocyte/macrophage activation and innate alloantigen recognition were upregulated, along with metabolic pathways associated with trained immunity in AMR and TCMR. Taking together, these findings revealed that intragraft monocytes/macrophages with high FCGR3A expression play a critical role in kidney transplant rejections.
2025-09-09 | GSE304669 | GEO
Project description:Glioblastoma, IDH wild type (GBM) is a primary brain cancer with a poor prognosis and few effective therapies. The ability to investigate the tumor and its microenvironment during treatment would greatly enhance understanding of disease response, progression and impact of therapeutics. Stereotactic needle core biopsies are routine surgical procedures performed primarily for tumor diagnosis. Use of these biopsies for investigations into tumor and microenvironmental responses to treatment is rarely performed but holds great potential to support therapeutic monitoring and understanding of tumor evolution. However, it is unclear whether needle core biopsies are sufficient for multi-omics analysis and tumor models. Here we test the depth of data generation possible from stereotactic needle core biopsy tissue in two separate patients. In the first patient with recurrent GBM we performed highly resolved multi-omics analyses including single cell RNA sequencing, spatial-transcriptomics, metabolomics, proteomics, phosphoproteomics, T-cell clonotype analysis, and MHC Class I immunopeptidomics from biopsy tissue obtained from a single procedure. In a second patient we analyzed multi-regional core biopsies to decipher spatial and genomic variance and quantify intra and inter-sample heterogeneity. We also investigated the utility of stereotactic biopsies as a method for generating patient derived xenograft (PDX) models in a separate patient cohort. Dataset integration across modalities highlighted spatially mapped immune cell associated metabolic pathways, revealed poor correlation between RNA expression and the tumor MHC Class I immunopeptidome, and validated inferred cell-cell ligand receptor interactions. In conclusion, stereotactic needle biopsy cores are of sufficient quality to generate multi-omics data and PDX models, provide data rich insight into a patient’s disease process and tumor immune microenvironment and can be of value in evaluating treatment responses.
2025-04-28 | GSE287629 | GEO
Project description:Glioblastoma, IDH wild type (GBM) is a primary brain cancer with a poor prognosis and few effective therapies. The ability to investigate the tumor and its microenvironment during treatment would greatly enhance understanding of disease response, progression and impact of therapeutics. Stereotactic needle core biopsies are routine surgical procedures performed primarily for tumor diagnosis. Use of these biopsies for investigations into tumor and microenvironmental responses to treatment is rarely performed but holds great potential to support therapeutic monitoring and understanding of tumor evolution. However, it is unclear whether needle core biopsies are sufficient for multi-omics analysis and tumor models. Here we test the depth of data generation possible from stereotactic needle core biopsy tissue in two separate patients. In the first patient with recurrent GBM we performed highly resolved multi-omics analyses including single cell RNA sequencing, spatial-transcriptomics, metabolomics, proteomics, phosphoproteomics, T-cell clonotype analysis, and MHC Class I immunopeptidomics from biopsy tissue obtained from a single procedure. In a second patient we analyzed multi-regional core biopsies to decipher spatial and genomic variance and quantify intra and inter-sample heterogeneity. We also investigated the utility of stereotactic biopsies as a method for generating patient derived xenograft (PDX) models in a separate patient cohort. Dataset integration across modalities highlighted spatially mapped immune cell associated metabolic pathways, revealed poor correlation between RNA expression and the tumor MHC Class I immunopeptidome, and validated inferred cell-cell ligand receptor interactions. In conclusion, stereotactic needle biopsy cores are of sufficient quality to generate multi-omics data and PDX models, provide data rich insight into a patient’s disease process and tumor immune microenvironment and can be of value in evaluating treatment responses.
2025-04-28 | GSE287630 | GEO
Project description:Glioblastoma, IDH wild type (GBM) is a primary brain cancer with a poor prognosis and few effective therapies. The ability to investigate the tumor and its microenvironment during treatment would greatly enhance understanding of disease response, progression and impact of therapeutics. Stereotactic needle core biopsies are routine surgical procedures performed primarily for tumor diagnosis. Use of these biopsies for investigations into tumor and microenvironmental responses to treatment is rarely performed but holds great potential to support therapeutic monitoring and understanding of tumor evolution. However, it is unclear whether needle core biopsies are sufficient for multi-omics analysis and tumor models. Here we test the depth of data generation possible from stereotactic needle core biopsy tissue in two separate patients. In the first patient with recurrent GBM we performed highly resolved multi-omics analyses including single cell RNA sequencing, spatial-transcriptomics, metabolomics, proteomics, phosphoproteomics, T-cell clonotype analysis, and MHC Class I immunopeptidomics from biopsy tissue obtained from a single procedure. In a second patient we analyzed multi-regional core biopsies to decipher spatial and genomic variance and quantify intra and inter-sample heterogeneity. We also investigated the utility of stereotactic biopsies as a method for generating patient derived xenograft (PDX) models in a separate patient cohort. Dataset integration across modalities highlighted spatially mapped immune cell associated metabolic pathways, revealed poor correlation between RNA expression and the tumor MHC Class I immunopeptidome, and validated inferred cell-cell ligand receptor interactions. In conclusion, stereotactic needle biopsy cores are of sufficient quality to generate multi-omics data and PDX models, provide data rich insight into a patient’s disease process and tumor immune microenvironment and can be of value in evaluating treatment responses.
2025-04-28 | GSE287631 | GEO
Project description:Comparison of miRNA expression profiles in a small set of prostate needle core biopsies or fine needle aspirates. Keywords: Expression profiling of prostate needle core biopsies
2006-04-05 | GSE4574 | GEO
Project description:Identification of cell types in the interphase between muscle and tendon by Visium Spatial Transcriptomics of four human semitendinous muscle-tendon biopsies. Cell types identified by single nuclei RNA seq on similar tissue were localized in situ with the use of Spatial Transcriptomics.
2023-03-02 | E-MTAB-12530 | biostudies-arrayexpress
Project description:Single-cell transcriptomics from dissociated organs lack information regarding the spatial origin of each cell, which limits their interpretation, particularly in complex and regionally heterogeneous tissues. This is relevant in the kidney, where cell types are exposed to a wide spectrum of cellular microenvironments along the corticomedullary axis, including steep gradients of extracellular osmolality and oxygen tension. Whether kidney single-cell transcriptomes can be exploited to predict spatial origins of cells and to provide physiological readouts of the cellular microenvironment is unknown. Here, we obtained single-cell transcriptomes of mouse kidney tissue from whole organs and from defined kidney zones (cortex, outer and inner medulla) and applied computational methods to reconstruct the spatial position of kidney tubule cells along the corticomedullary axis based on their transcriptomes. Our approach enabled a spatially resolved analysis of gene expression, showed a coordinated activation of osmolality-and hypoxia-associated genes towards the kidney medulla, and predicted that transcriptomes of a given cell type across different kidney zones change gradually rather than being clearly distinct in different anatomical zones. In genetically modified mice with a tubular concentration defect, spatial reconstruction of single-cell transcriptomics and osmogene expression quantitation accurately predicted reduced medullary osmolality. We conclude that our approach, which can be applied to any mouse whole kidney single-cell transcriptomic dataset, uncovers previously underappreciated information regarding spatial origin and microenvironment-dependent cellular states, adding improved readouts to existing and future datasets.
2020-11-26 | GSE145689 | GEO
Project description:Single-cell transcriptomics from dissociated organs lack information regarding the spatial origin of each cell, which limits their interpretation, particularly in complex and regionally heterogeneous tissues. This is relevant in the kidney, where cell types are exposed to a wide spectrum of cellular microenvironments along the corticomedullary axis, including steep gradients of extracellular osmolality and oxygen tension. Whether kidney single-cell transcriptomes can be exploited to predict spatial origins of cells and to provide physiological readouts of the cellular microenvironment is unknown. Here, we obtained single-cell transcriptomes of mouse kidney tissue from whole organs and from defined kidney zones (cortex, outer and inner medulla) and applied computational methods to reconstruct the spatial position of kidney tubule cells along the corticomedullary axis based on their transcriptomes. Our approach enabled a spatially resolved analysis of gene expression, showed a coordinated activation of osmolality-and hypoxia-associated genes towards the kidney medulla, and predicted that transcriptomes of a given cell type across different kidney zones change gradually rather than being clearly distinct in different anatomical zones. In genetically modified mice with a tubular concentration defect, spatial reconstruction of single-cell transcriptomics and osmogene expression quantitation accurately predicted reduced medullary osmolality. We conclude that our approach, which can be applied to any mouse whole kidney single-cell transcriptomic dataset, uncovers previously underappreciated information regarding spatial origin and microenvironment-dependent cellular states, adding improved readouts to existing and future datasets.
2020-11-26 | GSE145688 | GEO
Project description:Single-cell transcriptomics from dissociated organs lack information regarding the spatial origin of each cell, which limits their interpretation, particularly in complex and regionally heterogeneous tissues. This is relevant in the kidney, where cell types are exposed to a wide spectrum of cellular microenvironments along the corticomedullary axis, including steep gradients of extracellular osmolality and oxygen tension. Whether kidney single-cell transcriptomes can be exploited to predict spatial origins of cells and to provide physiological readouts of the cellular microenvironment is unknown. Here, we obtained single-cell transcriptomes of mouse kidney tissue from whole organs and from defined kidney zones (cortex, outer and inner medulla) and applied computational methods to reconstruct the spatial position of kidney tubule cells along the corticomedullary axis based on their transcriptomes. Our approach enabled a spatially resolved analysis of gene expression, showed a coordinated activation of osmolality-and hypoxia-associated genes towards the kidney medulla, and predicted that transcriptomes of a given cell type across different kidney zones change gradually rather than being clearly distinct in different anatomical zones. In genetically modified mice with a tubular concentration defect, spatial reconstruction of single-cell transcriptomics and osmogene expression quantitation accurately predicted reduced medullary osmolality. We conclude that our approach, which can be applied to any mouse whole kidney single-cell transcriptomic dataset, uncovers previously underappreciated information regarding spatial origin and microenvironment-dependent cellular states, adding improved readouts to existing and future datasets.
2020-11-26 | GSE145687 | GEO