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Computational identification of surface markers for isolating distinct subpopulations from heterogeneous cancer cell populations [scRNA-seq]

ABSTRACT: Computational identification of surface markers for isolating distinct subpopulations from heterogeneous cancer cell populations [scRNA-seq]

PROVIDER: PRJNA1115792 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR29152041_1.fastq.gz	Fastqsanger.gz
	SRR29152041_2.fastq.gz	Fastqsanger.gz
	SRR29152042_1.fastq.gz	Fastqsanger.gz
	SRR29152042_2.fastq.gz	Fastqsanger.gz
	SRR29152043_1.fastq.gz	Fastqsanger.gz

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Computational identification of surface markers for isolating distinct subpopulations from heterogeneous cancer cell populations [scRNA-seq]

Project description:Intratumoral heterogeneity reduces treatment efficacy and complicates our understanding of tumor progression. There is a pressing need to understand how heterogeneous tumor cell subpopulations coexist within a tumor, yet biological systems to study these processes in vitro are limited. With the advent of single-cell RNA sequencing (scRNA-seq), it has been found that some cancer cell lines contain distinct subpopulations. These heterogeneous cell lines provide a unique opportunity to study coexistence and evolution between genetically similar cancer cell subpopulations in controlled experimental settings. Here, we present scEMD, a computational package that returns candidate surface makers maximally unique to transcriptomic subpopulations in scRNA-seq which may be used for FACS isolation. scEMD was experimentally validated using the MDA-MB-231 and MDA-MB-436 cell lines. ESAM and BST2/Tetherin were experimentally confirmed to identify and separate scRNA-seq cluster-matched subpopulations of MDA-MB-231 and MDA-MB-436 cells, respectively. Identification and enrichment of distinct subpopulations within cell line models using this computationally efficient and experimentally validated workflow paves the way for studies on the generation and maintenance of cellular heterogeneity in low-complexity in vitro systems.

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Computational identification of surface markers for isolating distinct subpopulations from heterogeneous cancer cell populations [3’-Tag RNAseq]

Project description:Computational identification of surface markers for isolating distinct subpopulations from heterogeneous cancer cell populations [3’-Tag RNAseq]

| PRJNA1115791 | ENA

Computational identification of surface markers for isolating distinct subpopulations from heterogeneous cancer cell populations.

Project description:Intratumor heterogeneity reduces treatment efficacy and complicates our understanding of tumor progression and there is a pressing need to understand the functions of heterogeneous tumor cell subpopulations within a tumor, yet systems to study these processes in vitro are limited. Single-cell RNA sequencing (scRNA-seq) has revealed that some cancer cell lines include distinct subpopulations. Here, we present clusterCleaver, a computational package that uses metrics of statistical distance to identify candidate surface markers maximally unique to transcriptomic subpopulations in scRNA-seq which may be used for FACS isolation. With clusterCleaver, ESAM and BST2/tetherin were experimentally validated as surface markers which identify and separate major transcriptomic subpopulations within MDA-MB-231 and MDA-MB-436 cells, respectively. clusterCleaver is a computationally efficient and experimentally validated workflow for identification of surface markers for tracking and isolating transcriptomically distinct subpopulations within cell lines. This tool paves the way for studies on coexisting cancer cell subpopulations in well-defined in vitro systems.

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Project description:To characterize the progenitor-enriched CD44+NGFR+ cells present in the crypt and surface regions of the tonsil, we used an Illumina array system to analyze the transcriptome of these cells isolated from the tonsillar crypt and surface regions of three different individuals as well as the total epithelial (CD45-CD31-) populations obtained from two of these. To enrich for epithelial progeniors in human palatine tonsil tissue, hematopoietic and endothelial cells were depleted from freshly isolated cell suspensions derived from palatine tonsils using fluorescence-activated cell sorting (FACS). The resultant CD45-CD31- population was further fractionated into four subpopulations using antibodies against CD44 and NGFR. Based on the immunohistochemical phenotype and in vitro functional assays, CD44+NGFR+ subpopulations were identified as epithelial progenitor-enriched subsets. Microarray profiling was used to derive gene expression signatures of CD45-CD31- subsets (total epithelial-enriched) and CD45-CD31-CD44+NGFR+ subpopulations (progenitor-enriched).

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