Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Single Cell and Spatial Analysis of Human Squamous Cell Carcinoma [single-cell RNA-seq]

ABSTRACT: To define the cellular composition and spatial architecture of the tumor micoenvironment, we combined single-cell RNA-sequencing, spatial transcriptomics, and multiplexed ion-beam imaging from 10 patient cutaneous squamous cell carcinoma tumors and site-matched normal skin

ORGANISM(S): Mus musculus Homo sapiens

PROVIDER: GSE144236 | GEO | 2020/06/22

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Similar Datasets

Single Cell and Spatial Analysis of Human Squamous Cell Carcinoma [ST]

Project description:To define the cellular composition and spatial architecture of the tumor micoenvironment, we combined single-cell RNA-sequencing, spatial transcriptomics, and multiplexed ion-beam imaging from 10 patient cutaneous squamous cell carcinoma tumors and site-matched normal skin

2020-06-22 | GSE144239 | GEO

Single Cell and Spatial Analysis of Human Squamous Cell Carcinoma [WES]

2020-06-22 | GSE144237 | GEO

Single Cell and Spatial Analysis of Human Squamous Cell Carcinoma [CRISPR screen]

2020-06-22 | GSE144238 | GEO

Single Cell Spatial Analysis Reveals the Topology of Immunomodulatory Purinergic Signaling in Glioblastoma

Project description:Abstract from manuscript Glioblastoma develops an immunosuppressive microenvironment that fosters tumorigenesis and resistance to current therapeutic strategies. Here we use multiplexed tissue imaging and single-cell RNA-sequencing to characterize the composition, spatial organization, and clinical significance of extracellular purinergic signaling in glioblastoma. We show that glioblastoma exhibit strong expression of CD39 and CD73 ectoenzymes, correlating with increased adenosine levels. Microglia are the predominant source of CD39, while CD73 is principally expressed by tumor cells, particularly in tumors with amplification of EGFR and astrocyte-like differentiation. Spatially-resolved single-cell analyses demonstrate strong spatial correlation between tumor CD73 and microglial CD39, and that their spatial proximity is associated with poor clinical outcomes. Together, this data reveals that tumor CD73 expression correlates with tumor genotype, lineage differentiation, and functional states, and that core purine regulatory enzymes expressed by neoplastic and tumor-associated myeloid cells interact to promote a distinctive adenosine-rich signaling niche and immunosuppressive microenvironment potentially amenable to therapeutic targeting.

2022-06-27 | ST002203 | MetabolomicsWorkbench

Gene expression profiles of primary tumors with radiotherapy and lung metastases in mouse squamous cell carcinoma model.

Project description:To examine whether the local carbon ion radiotherapy affects the characteristics of the metastatic tumors, the expression profiles of the primary tumors and the lung metastases were studied in a mouse squamous cell carcinoma model by applying local radiotherapy with no irradiation (negative control), gamma-ray irradiation (reference beam), and carbon-ion irradiation. Keywords: mouse, squamous cell carcinoma, primary tumor, lung metastases, radiotherapy, carbon ion, gamma ray A highly metastatic mouse squamous cell carcinoma NR-S1 was implanted into the hind leg of synergetic C3H/HeNrs mice and irradiated with 5 Gy of carbon ion beam. 8 Gy of gamma ray was used as a reference beam. At 2 weeks after the irradiation, the lung tissue was sampled. In order to collect samples of primary tumors, the tumors were implanted in other mice and irradiated in the same manner, and the primary tumors were collected at 1 week after the irradiation. The tumor cells of the primary and metastatic tumors were collected by laser microdissection, and oligonucleotide microarray analysis of the irradiated primary tumors and the metastatic tumors were all performed in comparison to the non-irradiated primary tumor by two-color methods.

2009-04-22 | E-GEOD-9305 | biostudies-arrayexpress

Spatial single-cell mass spectrometry defines zonation of the hepatocyte proteome

Project description:Single-cell proteomics by mass spectrometry (MS) is emerging as a powerful and unbiased method for the characterization of biological heterogeneity. So far, it has been limited to cultured cells, whereas an expansion of the method to complex tissues would greatly enhance biological insights. Here we describe single-cell Deep Visual Proteomics (scDVP), a technology that integrates high-content imaging, laser microdissection and multiplexed MS. scDVP resolves the context-dependent, spatial proteome of murine hepatocytes at a current depth of 1,700 proteins from a slice of a cell. Half of the proteome was differentially regulated in a spatial manner, with protein levels changing dramatically in proximity to the central vein. We applied machine learning to proteome classes and images, which subsequently inferred the spatial proteome from imaging data alone. scDVP is applicable to healthy and diseased tissues and complements other spatial proteomics or spatial omics technologies.

2023-10-02 | PXD038699 | Pride

Gene expression profiles of primary tumors with radiotherapy and lung metastases in mouse squamous cell carcinoma model.

2009-04-23 | GSE9305 | GEO

Multiplexed protein and drug imaging by super-resolution ion beam imaging

Project description:Multiplexed protein and drug imaging by super-resolution ion beam imaging

| PRJNA592191 | ENA

Single-Cell and Spatial Transcriptomics Analysis of Human Adrenal Aging (spatial transcriptomics)

Project description:These data were used in the spatial transcriptomics analysis of the article titled \\"Single-Cell and Spatial Transcriptomics Analysis of Human Adrenal Aging\\".

2024-04-22 | E-MTAB-13991 | biostudies-arrayexpress

Spatial reconstruction of single-cell gene expression

Project description:Spatial localization is a key determinant of cellular fate and behavior, but spatial RNA assays traditionally rely on staining for a limited number of RNA species. In contrast, single-cell RNA-seq allows for deep profiling of cellular gene expression, but established methods separate cells from their native spatial context. Here we present Seurat, a computational strategy to infer cellular localization by integrating single-cell RNA-seq data with in situ RNA patterns. We applied Seurat to spatially map 851 single cells from dissociated zebrafish (Danio rerio) embryos, inferring a transcriptome-wide map of spatial patterning. We confirmed Seurat’s accuracy using several experimental approaches, and used it to identify a set of archetypal expression patterns and spatial markers. Additionally, Seurat correctly localizes rare subpopulations, accurately mapping both spatially restricted and scattered groups. Seurat will be applicable to mapping cellular localization within complex patterned tissues in diverse systems. We generated single-cell RNA-seq profiles from dissociated cells from developing zebrafish embryos (late blastula stage - 50% epiboly)

2015-04-13 | E-GEOD-66688 | biostudies-arrayexpress

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data