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: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: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 | GSE287629 | 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 | 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 | 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 | GSE145687 | GEO
Project description:Glioblastoma (GBM) is a primary brain cancer with an abysmal prognosis with few effective therapies. The ability to investigate the tumor microenvironment before and during treatment would greatly enhance both our understanding of disease response and progression, as well as the delivery and impact of therapeutics. Stereotactic biopsies are a routine surgical procedure performed primarily for diagnostic histopathologic purposes. The adaptation of stereotactic biopsy tissue for complex and integrated investigative multi-modal molecular analyses (‘Multi-omics”) in the context of GBM regional heterogeneity is not routinely performed, Most of the tissue is consumed with standard of care clinical testing and the amount and quality of remaining cells, particularly in the context of recurrent GBMs that have failed previous treatments, has not previously been shown to be amenable to complex analyses. Here we performed highly resolved multi-modal analysis methods including single cell RNA sequencing, spatial-transcriptomics, metabolomics, proteomics, phosphoproteomics, T-cell clonal analysis, and immunopeptidomics on needle biopsy cores obtained from a single patient during the same procedure. In a second patient, we analyzed multi-regional core biopsies to decipher spatially associated tissue and genomic variance. Finally in a separate cohort of patients we investigated the utility of stereotactic biopsies as a method for generating patient derived xenograft models. Dataset integration across modalities showed good correspondence between spatial modalities and revealed tumor and immune cell associated metabolic profiles and cell signalling pathways. In conclusion, stereotactic needle biopsy cores are of sufficient quality for the purposes of investigative biopsy and can generate multi-omics data, providing data rich insight into a patient’s disease to interrogate the tumor immune microenvironment.
2025-05-06 | PXD046857 | Pride