Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Defining the Regulatory Logic of Breast Cancer Using Single-Cell Epigenetic and Transcriptome Profiling

ABSTRACT: Defining the Regulatory Logic of Breast Cancer Using Single-Cell Epigenetic and Transcriptome Profiling

PROVIDER: PRJNA1018859 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Similar Datasets

Defining the Regulatory Logic of Breast Cancer Using Single-Cell Epigenetic and Transcriptome Profiling.

Project description:Annotation of the cis-regulatory elements that drive transcriptional dysregulation in cancer cells is critical to improving our understanding of tumor biology. Herein, we present a compendium of matched chromatin accessibility (scATAC-seq) and transcriptome (scRNA-seq) profiles at single-cell resolution from human breast tumors and healthy mammary tissues processed immediately following surgical resection. We identify the most likely cell-of-origin for luminal breast tumors and basal breast tumors and then introduce a novel methodology that implements linear mixed-effects models to systematically quantify associations between regions of chromatin accessibility (i.e. regulatory elements) and gene expression in malignant cells versus normal mammary epithelial cells. These data unveil regulatory elements with that switch from silencers of gene expression in normal cells to enhancers of gene expression in cancer cells, leading to the upregulation of clinically relevant oncogenes. To translate the utility of this dataset into tractable models, we generated matched scATAC-seq and scRNA-seq profiles for breast cancer cell lines, revealing, for each subtype, a conserved oncogenic gene expression program between in vitro and in vivo cells. Together, this work highlights the importance of non-coding regulatory mechanisms that underlie oncogenic processes and the ability of single-cell multi-omics to define the regulatory logic of BC cells at single-cell resolution.

| S-EPMC11212881 | biostudies-literature

Defining the regulatory logic of breast cancer using single-cell epigenetic and transcriptome profiling.

Project description:Annotation of cis-regulatory elements that drive transcriptional dysregulation in cancer cells is critical to understanding tumor biology. Herein, we present matched chromatin accessibility (single-cell assay for transposase-accessible chromatin by sequencing [scATAC-seq]) and transcriptome (single-cell RNA sequencing [scRNA-seq]) profiles at single-cell resolution from human breast tumors and healthy mammary tissues processed immediately following surgical resection. We identify the most likely cell of origin for subtype-specific breast tumors and implement linear mixed-effects modeling to quantify associations between regulatory elements and gene expression in malignant versus normal cells. These data unveil cancer-specific regulatory elements and putative silencer-to-enhancer switching events in cells that lead to the upregulation of clinically relevant oncogenes. In addition, we generate matched scATAC-seq and scRNA-seq profiles for breast cancer cell lines, revealing a conserved oncogenic gene expression program between in vitro and in vivo cells. This work highlights the importance of non-coding regulatory mechanisms that underlie oncogenic processes and the ability of single-cell multi-omics to define the regulatory logic of cancer cells.

| S-EPMC11872555 | biostudies-literature

Defining the Regulatory Logic of Breast Cancer Using Single-Cell Epigenetic and Transcriptome Profiling

Project description:Annotation of the cis-regulatory elements mediating oncogenic transcription is essential to understanding breast cancer biology. In this work, we quantitatively linked variation in chromatin accessibility to gene expression within human breast tumors, normal mammary reduction tissue samples, and breast cancer cell lines using single-cell chromatin accessibility sequencing (scATAC-seq) and single-cell transcriptomic sequencing (scRNA-seq). Our analysis resolved the underlying cellular heterogeneity in chromatin accessibility and transcriptional output for each patient sample. We also showed that our findings were recapitulated in the breast cancer cell line samples. These data will serve as an important resource for the single-cell genomics and breast cancer research communities.

2024-12-31 | GSE243526 | GEO

The Regulatory Logic of Planarian Stem Cell Differentiation

Project description:The Regulatory Logic of Planarian Stem Cell Differentiation

| PRJNA1145864 | ENA

Spatially varying cis-regulatory divergence in Drosophila embryos elucidates cis-regulatory logic

Project description:Spatially varying cis-regulatory divergence in Drosophila embryos elucidates cis-regulatory logic

| PRJNA397062 | ENA

Deciphering cis-regulatory logic with 100 million synthetic promoters

Project description:In order to generate data suitable to decipher cis-regulatory logic, we generated ~100 million synthetic promoters (in yeast) comprised of random DNA and measured their expression by FACS (sorting into 18 bins).

2019-01-01 | GSE104878 | GEO

Deciphering cis-regulatory logic with 100 million synthetic promoters

Project description:Deciphering cis-regulatory logic with 100 million synthetic promoters

| PRJNA414104 | ENA

The Regulatory Logic of Planarian Stem Cell Differentiation [scRNAseq]

Project description:The Regulatory Logic of Planarian Stem Cell Differentiation [scRNAseq]

| PRJNA1145872 | ENA

Deciphering cis-regulatory logic with 100 million synthetic promoters (MNase)

Project description:Deciphering cis-regulatory logic with 100 million synthetic promoters (MNase)

| PRJNA414115 | ENA

The Regulatory Logic of Planarian Stem Cell Differentiation [ATAC-Seq]

Project description:The Regulatory Logic of Planarian Stem Cell Differentiation [ATAC-Seq]