Defining the Regulatory Logic of Breast Cancer Using Single-Cell Epigenetic and Transcriptome Profiling.
Matthew J RegnerSusana Garcia-RecioAatish ThennavanKamila WisniewskaRaul Mendez-GiraldezBrooke FelsheimPhilip M SpanheimerJoel S ParkerCharles M PerouHector L FrancoPublished in: bioRxiv : the preprint server for biology (2024)
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.
Keyphrases
- single cell
- gene expression
- rna seq
- transcription factor
- induced apoptosis
- dna methylation
- high throughput
- cell cycle arrest
- genome wide
- signaling pathway
- endoplasmic reticulum stress
- dna damage
- quality improvement
- pi k akt
- long non coding rna
- cell proliferation
- electronic health record
- endothelial cells
- deep learning