Ontology highlight
ABSTRACT:
PROVIDER: PRJNA523041 | ENA |
REPOSITORIES: ENA
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Project description:Spatially resolved single-cell RNA-sequencing reveals expression heterogeneity in tumor microenvironment
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Project description:Advancing our understanding of embryonic development is heavily dependent on identification of novel pathways or regulators. While genome-wide techniques such as RNA sequencing are ideally suited for discovering novel candidate genes, they are unable to yield spatially resolved information in embryos or tissues. Microscopy-based approaches, using for example in situ hybridization, can provide spatial information about gene expression, but are limited to analyzing one or a few genes at a time. Here, we present a method where we combine traditional histological techniques with low-input RNA sequencing and mathematical image reconstruction to generate a high-resolution genome-wide 3D atlas of gene expression in the zebrafish embryo at three developmental stages. We also demonstrate that our technique is suitable for spatially-resolved differential expression analysis in wildtype and Gli3 mutant mouse forelimbs. Importantly, our method enables searching for genes that are expressed in specific spatial patterns without manual image annotation. We envision broad applicability of RNA tomography as an accurate and sensitive approach for spatially resolved transcriptomics in whole embryos and dissected organs. To generate spatially-resolved RNA-seq data for zebrafish embryos (shield stage, 10 somites, 15 somites, 18 somites) and mouse forelimbs (E10.5), we cryosectioned samples, extracted RNA from the individual sections, and amplified and barcoded mRNA using the CEL-seq protocol (Hashimshony et al., Cell Reports, 2012) with a few modifications. Libraries were sequenced on Illumina HiSeq 2500 using 50bp paired end sequencing. Selected zebrafish libraries were sequenced on MiSeq 250bp paired-end to improve 3' annotations.
2014-10-23 | E-GEOD-59873 | biostudies-arrayexpress
Project description:Available genetically-defined cancer models are limited in genotypic and phenotypic complexity and underrepresent the heterogeneity of human cancer. Herein, we describe a combinatorial genetic strategy applied to an organoid transformation assay to rapidly generate diverse, clinically relevant models of bladder and prostate cancer. Importantly, the clonal architecture of the resultant tumors can be resolved using single-cell or spatially resolved next-generation sequencing to uncover polygenic drivers of cancer phenotypes.
2023-12-01 | GSE231543 | GEO
Project description:Available genetically-defined cancer models are limited in genotypic and phenotypic complexity and underrepresent the heterogeneity of human cancer. Herein, we describe a combinatorial genetic strategy applied to an organoid transformation assay to rapidly generate diverse, clinically relevant models of bladder and prostate cancer. Importantly, the clonal architecture of the resultant tumors can be resolved using single-cell or spatially resolved next-generation sequencing to uncover polygenic drivers of cancer phenotypes.
2023-12-01 | GSE231542 | GEO
Project description:Available genetically-defined cancer models are limited in genotypic and phenotypic complexity and underrepresent the heterogeneity of human cancer. Herein, we describe a combinatorial genetic strategy applied to an organoid transformation assay to rapidly generate diverse, clinically relevant models of bladder and prostate cancer. Importantly, the clonal architecture of the resultant tumors can be resolved using single-cell or spatially resolved next-generation sequencing to uncover polygenic drivers of cancer phenotypes.
2023-12-01 | GSE229782 | GEO
Project description:Available genetically-defined cancer models are limited in genotypic and phenotypic complexity and underrepresent the heterogeneity of human cancer. Herein, we describe a combinatorial genetic strategy applied to an organoid transformation assay to rapidly generate diverse, clinically relevant models of bladder and prostate cancer. Importantly, the clonal architecture of the resultant tumors can be resolved using single-cell or spatially resolved next-generation sequencing to uncover polygenic drivers of cancer phenotypes.
2023-12-01 | GSE229781 | GEO
Project description:Available genetically-defined cancer models are limited in genotypic and phenotypic complexity and underrepresent the heterogeneity of human cancer. Herein, we describe a combinatorial genetic strategy applied to an organoid transformation assay to rapidly generate diverse, clinically relevant models of bladder and prostate cancer. Importantly, the clonal architecture of the resultant tumors can be resolved using single-cell or spatially resolved next-generation sequencing to uncover polygenic drivers of cancer phenotypes.
2023-12-01 | GSE229780 | GEO
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.
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2024-01-24 | PXD044197 | Pride
Project description:Spatially resolved RNA-sequencing of the embryonic zebrafish heart
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