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Single-cell RNA-sequencing reveals an intratumor heterogeneity in pancreatic adenocarcinoma [ATAC-seq]

ABSTRACT: Single-cell RNA-sequencing reveals an intratumor heterogeneity in pancreatic adenocarcinoma [ATAC-seq]

PROVIDER: PRJNA790445 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR17268351.fastq.gz	Fastqsanger.gz
	SRR17268352.fastq.gz	Fastqsanger.gz
	SRR17268353.fastq.gz	Fastqsanger.gz

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Single-cell RNA-sequencing reveals an intratumor heterogeneity in pancreatic adenocarcinoma [ATAC-seq]

Project description:We examined the intratumor heterogeneity in S2-VP10 xenograft by single-cell RNA-sequencing. We found a hierarchical tumor progression originating from ROR1high cells with a partial EMT gene signature. We also found that ROR1high cells have the strong capacity as tumor-initiating cells to support tumorigenecity, chemoresistance, and metastasis. CUT&RUN and ATAC-sequencing revealed that ROR1 gene expression is regulated through YAP-BRD4 axis. Together, these data uncover a role for ROR1high cells in tumor progression, suggesting that ablating ROR1high tumor-initiating cells may be the alternative therapeutic strategy in pancreatic adenocarcinoma.

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Spatially Annotated Single Cell Sequencing for Unraveling Intratumor Heterogeneity

Project description:Intratumor heterogeneity is a major obstacle to effective cancer treatment. Current methods to study intratumor heterogeneity using single-cell RNA sequencing (scRNAseq) lack information on the spatial organization of cells. While state-of-the art spatial transcriptomics methods capture the spatial distribution, they either lack single cell resolution or have relatively low transcript counts. Here, we introduce spatially annotated single cell sequencing, based on the previously developed functional single cell sequencing (FUNseq) technique, to spatially profile tumor cells with deep scRNA-seq and single cell resolution. Using our approach, we profiled cells located at different distances from the center of a 2D epithelial cell mass. By profiling the cell patch in concentric bands of varying width, we showed that cells at the outermost edge of the patch responded strongest to their local microenvironment, behaved most invasively, and activated the process of epithelial-to-mesenchymal transition (EMT) to migrate to lowconfluence areas. We inferred cell-cell communication networks and demonstrated that cells in the outermost ~10 cell wide band, which we termed the invasive edge, induced similar phenotypic plasticity in neighboring regions. Applying FUNseq to spatially annotate and profile tumor cells enables deep characterization of tumor subpopulations, thereby unraveling the mechanistic basis for intratumor heterogeneity.

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