9c58f453-6aea-4fb9-bcb2-3c46a867a576 - samples
Ontology highlight
ABSTRACT:
PROVIDER: EGAD00001008811 | EGA |
REPOSITORIES: EGA
Similar Datasets
Project description:Spatial transcriptomics is a rapidly advancing field, yet it lacks standardized metrics for evaluating imaging-based in situ hybridization technologies. In this study, we emphasize the importance of rigorous experimental design and standardized operating procedures (SOPs) in defining performance metrics across multiple modalities—from single-cell to spatial transcriptomics to spatial proteomics. Our Spatial Touchstone (ST) dataset, generated from six tissue types across three global sites (n=76 assays), provides a comprehensive evaluation of reproducibility, sensitivity, dynamic ranges, signal-to-noise ratio, false discovery rates, cell type annotation, and congruence with single-cell profiling. Using single-nucleus RNA sequencing (snRNA-seq) on the same formalin-fixed paraffin-embedded tissues, we created a reference for transcriptional profiles to assess cellular organization and biomarker localization. In the absence of an independent 'gold standard’ in the field, this study provides an objective assessment of technical performance through standardized protocols, Spatial Touchstone Protocols (STSOP). Our open-source software, SpatialQC, allows users to evaluate samples across all technical metrics and directly impute cell annotations from single-cell datasets. This study features the largest imaging-based spatial transcriptomics data repository available, with a total of 203 spatial profiles. It incorporates both public (n=127) and ST datasets (n=76) through the Spatial Touchstone Portal (STP), available at www.spatialtouchstone.org. This resource offers users easy access to analyze and compare their own data against an extensive collection of imaging-based datasets. We show that the ST datasets demonstrate high reproducibility (r=0.93 to 1.0) and set a new benchmark for the field. Finally, we establish metrics to evaluate and integrate imaging based multi omics data from single cell into spatial transcriptomics to spatial proteomics. The ST project provides a comprehensive, reproducible assessment across platforms and sites, establishing essential standards for imaging-based spatial multi omics (transcriptomics and proteomics) and paving the way for future research and technological advancements.
2025-07-28 | GSE277080 | GEO
Project description:To gain molecular insight into the prenatal neurobiology of DS, we performed single-nucleus sequencing, spatial transcriptomics, and proteomics on mid-gestational prenatal human brain tissue. We captured altered expression dynamics of lineage commitment genes in DS neural progenitor cells, which suggest changes to the fate and functionality of neuronal and glial cells.
2025-07-11 | GSE280175 | GEO
Project description:To gain molecular insight into the prenatal neurobiology of DS, we performed single-nucleus sequencing, spatial transcriptomics, and proteomics on mid-gestational prenatal human brain tissue. We captured altered expression dynamics of lineage commitment genes in DS neural progenitor cells, which suggest changes to the fate and functionality of neuronal and glial cells.
2025-07-11 | GSE280170 | GEO
Project description:Although tumor-propagating cells can be derived from glioblastomas (GBMs)of theproneural and mesenchymal subtypes,a gliomastem-like cell (GSC) of the classical subtype has not been identified. It is unclear if mesenchymal GSCs (mGSCs) and/orproneural GSCs (pGSCs) alone are sufficient to generate the heterogeneity observed in GBM.We performed single-cell/nuclei RNA-sequencing of 28 gliomas, and single-cell ATAC-sequencing for8 cases. We find that GBM GSCs reside ona single axis of variation, rangingfrom proneural to mesenchymal. In silico lineage tracing using both transcriptomics and genetics supports mGSCs as the progenitors of pGSCs.Dual inhibition of pGSC-enrichedand mGSC-enrichedgrowth and survival pathways provides a more complete treatment thancombinations targetingone GSC phenotype alone.This study sheds light on a long-standing debate regarding lineage relationships among GSCs and presents a paradigm by which personalized combination therapies can be derived from single-cell RNA signatures, to overcome intra-tumor heterogeneity.
2019-10-12 | GSE138794 | GEO
Project description:Most clinical trials for glioblastoma (GBM) enroll patients at recurrence. However, most pre-clinical animal models are of primary disease. Most studies have used tissues from primary tumors. Knowledge of GBM cellular composition at recurrence is limited. We profiled 80 human IDH-wild-type GBM specimens via single-nucleus RNA sequencing, 40 primary tumors and 40 patient-matched recurrent tumors. Select cohorts were also profiled via single-cell assay for transposase-accessible chromatin, single-cell digital-spatial, and single-cell spatial-transcriptomic assays. All patients were treated only with standard-of-care therapy: temozolomide, radiation and surgical resection. The cohort had a 1.2 male/female ratio, ages 35–76. We found a significant increase at recurrence in cells with the Verhaak mesenchymal phenotype and fewer proneural cells. Although there was an increase in the percentage of cycling cells overall, the fraction of cycling proneural cells decreased while the fraction of cycling mesenchymal cells increased. These changes were concomitant with a significant increase in the percentage of tumor-infiltrating monocytic-lineage cells derived from the periphery. Taken together, these findings support a proneural-to-mesenchymal shift at recurrence due to an increase in the birth rate of mesenchymal cells, supported by an expansion of myeloid-derived cells from peripheral blood. Although the percentages of glioblastoma-infiltrating T-cells are generally low (~1% on average in our data), we found a statistically significant increase in T-cell abundance at recurrence. We identified a cohort of T-cell outliers that demonstrate 2-to-8-fold increases in T-cells over average levels. We validated that T-cells in these tumors have extravasated beyond the perivascular space and into the cellular tumor via immunohistochemistry and spatial profiling. We present our ongoing analysis of the paracrine signals, upstream transcription-factor expression, and cis-regulatory grammars utilized in immune-outlier GBMs. We describe how these programs change under therapy. These studies shed light on the effect of standard therapy in shaping GBM composition at recurrence.
2022-07-05 | GSE174554 | GEO
Project description:We developed a mesoscale single cell transcriptomics data from hundreds of the dorsal motor nucleus of the vagus (DMV) neurons under homeostasis and following physiological perturbations. Our results revealed that homeostatic DMV neuronal states can be organized into distinguishable input-output signal processing units. Remote ischemic preconditioning induced a distinctive shift in the neuronal states towards diminishing the role of inhibitory inputs.
2021-01-29 | GSE155047 | GEO
Project description:We developed a mesoscale single cell transcriptomics data from hundreds of the dorsal motor nucleus of the vagus (DMV) neurons under homeostasis and following physiological perturbations. Our results revealed that homeostatic DMV neuronal states can be organized into distinguishable input-output signal processing units. Chronic cardiac ischemic injury resulted in a dramatic shift in DMV neuronal states suggestive of enhanced neurosecretory function.
2021-01-29 | GSE155049 | GEO
Project description:Single-nucleus transcriptomics of inducible Ngly1-/- cerebellum
| PRJNA1252763 | ENA
Project description:To profile off-target effects of psychoactive drugs, 87 genome-wide drug fitness assays (of which 5 were performed in duplicate) and 18 genome-wide control experiments were performed in Saccharomyces cerevisiae. Heterozygous and homozygous yeast single gene deletion strains from the BY collection of the Saccharomyces cerevisiae genome deletion consortium were used.
2008-07-07 | E-MTAB-34 | biostudies-arrayexpress