Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

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

ACCESS DATA

Json Xml

Similar Datasets

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.

2024-06-26 | GSE268249 | GEO

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

2024-06-26 | GSE268250 | GEO

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

Gene expression profiles of normal human tonsillar cell subpopulations FACS sorted based on expression of cell surface markers

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).

2015-10-29 | E-GEOD-69767 | biostudies-arrayexpress

Heterogeneous expression of cell surface markers in human myeloma cell lines: implications for disease modelling and therapeutic targeting

Project description:This RNAseq analysis is performed as a part of the work "Heterogeneous expression of cell surface markers in human myeloma cell lines: implications for disease modelling and therapeutic targeting", where expression levels both at the cell surface level and transcriptomic level are analysed.

2024-10-03 | GSE250236 | GEO

Proteomic characterization of SEC-fractionated sEV subpopulations

Project description:The use of cardiac progenitor cell (CPC)-derived small extracellular vesicles (sEVs) has shown potential to stimulate cardiac repair. sEVs are released by cells and play a role in intercellular communication through transfer of their bioactive content. Increasing evidence indicates that sEVs present a heterogeneous population of vesicles. In the context of cardiac regeneration, studying sEV heterogeneity could provide new insights into mechanisms underlying sEV-mediated cardiac repair properties and help to improve the therapeutic application of CPC-derived sEVs. Here we used size-exclusion chromatography to isolate and fractionate EV subpopulations dervied from CPCs. We then applied a bottom-up proteomic approach to characterize the contents of individual EV subpopulations.

2024-01-26 | PXD032334 | Pride

Gene expression of clonal subpopulations derived from the 4T1 murine mammary carcinoma cell line

Project description:Breast tumors often exhibit intratumoral heterogeneity. We hypothesized that phenotypically distinct clonal subpopulations in heterogeneous tumors may affect overall tumor morphology and cancer cell invasion. In order to study heterogeneous tumors, we isolated individual cells from a parental 4T1 murine mammary carcinoma cell line and generated four clonal subpopulations (E1, E2, A, and M). To characterize these subpopulations, we examined gene expression by performing bulk RNA-sequencing.

2024-01-31 | GSE252177 | GEO

Isolating metastatic cell populations from zebrafish

Project description:Isolating metastatic cell populations from zebrafish

| PRJNA641651 | ENA

Using intracellular markers to identify a novel set of surface markers for live cell purification from a heterogeneous hIPSC culture

Project description:We differentiated human iPSC to day 14 using our dopaminergic neuron protocol. At day 14, the cells were fixed, stained and FACS sorted in to the FOXA2/LMX1 double positive (wanted neural progenitor population) and double negative pools. We compared the RNA of the pools via microarray to identify surface markers in the double positive pool to be able to live purify the neural progenitors from the rest of the cells. Human embryonic stem cells (ESCs) and induced pluripotent stem cells (iPSCs) can provide sources for midbrain dopaminergic (mDA) neural progenitors (NPCs) for cell therapy to treat Parkinson’s disease (PD) patients. However, the well-known line-to-cell line variability in the differentiation capacity of individual cell lines needs to be improved for the success of this therapy. To address this issue, we sought to identify mDA NPC specific cell surface markers for fluorescence activated cell sorting (FACS). Through RNA isolation after sorting for NPCs based on staining for cell-specific transcription factors followed by microarray, we identified two positive cell surface markers (CORIN and CD166) and one negative cell surface marker (CXCR4) for mDA NPC sorting. These three markers can enrich dopaminergic NPCs to 90% purity, and the sorted NPCs more efficiently differentiate to mature dopaminergic neurons compared to unsorted or CORIN+ alone mDA NPCs. This surface marker identification strategy can be used broadly to facilitate isolation of cell subtypes of interest from heterogeneous cultures. Complete processed data are not available

2017-05-23 | GSE99139 | GEO

Computational Genomics of Preeclampsia

Project description:Computational Genomics of Preeclampsia

| PRJNA809817 | ENA