Dataset Information

Defining super-enhancer landscape in triple-negative breast cancer by multiomic profiling

ABSTRACT: Here we apply integrated epigenomic and transcriptomic profiling to uncover super-enhancer heterogeneity between breast cancer subtypes, and provide clinically relevant biological insights towards TNBC. Using CRISPR/Cas9-mediated gene editing, we identify genes that are specifically regulated by TNBC-specific super-enhancers, including FOXC1 and MET, thereby unveiling a mechanism for specific overexpression of the key oncogenes in TNBC. We also identify ANLN as a novel TNBC-specific gene regulated by super-enhancer. Our studies reveal a TNBC-specific epigenomic landscape, contributing to the dysregulated oncogene expression in breast tumorigenesis.

ORGANISM(S): Homo Sapiens

SUBMITTER: Liang Zhang

PROVIDER: PXD024505 | iProX | Thu Mar 04 00:00:00 GMT 2021

REPOSITORIES: iProX

ACCESS DATA

Publications

Defining super-enhancer landscape in triple-negative breast cancer by multiomic profiling.

Huang Hao H Hu Jianyang J Maryam Alishba A Huang Qinghua Q Zhang Yuchen Y Ramakrishnan Saravanan S Li Jingyu J Ma Haiying H Ma Victor W S VWS Cheuk Wah W So Grace Y K GYK Wang Wei W Cho William C S WCS Zhang Liang L Chan Kui Ming KM Wang Xin X Chin Y Rebecca YR

Nature communications 20210414 1

Breast cancer is a heterogeneous disease, affecting over 3.5 million women worldwide, yet the functional role of cis-regulatory elements including super-enhancers in different breast cancer subtypes remains poorly characterized. Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer with a poor prognosis. Here we apply integrated epigenomic and transcriptomic profiling to uncover super-enhancer heterogeneity between breast cancer subtypes, and provide clinically relevant ...[more]

PMID: 33854062

Similar Datasets

Project description:Breast cancer is a heterogeneous disease for which prognosis and treatment strategies are largely governed by the receptor status (estrogen, progesterone and Her2-neu) of the tumor cells. Gene expression profiling of whole breast tumors further stratifies breast cancer into several molecular subtypes which also co-segregate with the receptor status of the tumor cells. We postulated that cancer associated fibroblasts (CAFs) within the tumor stroma may exhibit subtype specific gene expression profiles and thus contribute to the biology of the disease in a subtype specific manner. Several studies have reported gene expression profile differences between CAFs and normal breast fibroblasts but in none of these studies were the results stratified based on tumor subtypes. To address whether gene expression in breast cancer associated fibroblasts varies between breast cancer subtypes, we compared the gene expression profiles of early passage primary CAFs isolated from twenty human breast cancer samples representing three main subtypes; seven ER+, seven triple negative (TNBC) and six Her2+. We observed significant expression differences between CAFs derived from Her2+ breast cancer and CAFs from TNBC and ER+ cancers, particularly in pathways associated with cytoskeleton and integrin signaling. In the case of Her2+ breast cancer, the signaling pathways found to be selectively up regulated in CAFs may contribute to the more invasive properties and unfavorable prognosis of Her2+ breast cancer. These data demonstrate that in addition to the distinct molecular profiles that characterize the neoplastic cells, CAF gene expression is also differentially regulated in distinct subtypes of breast cancer. We isolated CAFs from twenty primary breast cancer samples representing three main subtypes (ER+ (n=7), TNBC (n=7), Her2+ (n=6)) and performed gene expression profile analyses on RNA isolated from these early passage CAFs. Those samples were done in two batches with 4 samples repeated in both batches. One TNBC sample was found to be an outlier and not used in the analysis.

Dataset Information

Defining super-enhancer landscape in triple-negative breast cancer by multiomic profiling

Publications

Defining super-enhancer landscape in triple-negative breast cancer by multiomic profiling.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure