BRRIAR lncRNA alters breast cancer risk by modulating interferon signaling in cis and in trans through BHLHE40 and RIG-I [RNA-Seq]
收藏NIAID Data Ecosystem2026-05-10 收录
下载链接:
https://www.ncbi.nlm.nih.gov/sra/SRP586616
下载链接
链接失效反馈官方服务:
资源简介:
Interferons (IFNs) are key regulators of cell proliferation and anti-tumor immunity. We identified a breast cancer-associated long noncoding RNA (lncRNA), BRRIAR, that modulates IFN signaling in estrogen receptor-positive (ER+) breast cancer. BRRIAR is transcribed from an 11 kb enhancer cluster at 3p26, and its reduced expression is linked to breast cancer GWAS risk variants. Primarily expressed in ER+ breast tumors, BRRIAR exhibits dual functionality, acting both in cis and in trans. Nuclear BRRIAR regulates BHLHE40 expression through its enhancer, while cytoplasmic BRRIAR binds to the pattern recognition receptor RIG-I, modulating its activation. BRRIAR RNA overexpression activates RIG-I signaling, inducing IFN responses that selectively trigger apoptosis in ER+ breast tumor cells in vitro and in vivo, while promoting immune activation in human peripheral blood mononuclear cells. These findings emphasize the complex regulatory mechanisms at GWAS risk regions, reveal the critical role of lncRNAs as modulators of tumor immunity and identify BRRIAR as a promising RNA-based therapeutic for ER+ breast cancer. Overall design: For RNAseq: Total RNA was extracted from T47D cells using the RNeasy Plus mini kit (Qiagen). Libraries were prepared using the TruSeq stranded mRNA library prep kit (Illumina) as per the manufacturer's protocol. Samples were barcoded and run on a NextSeq 550 (PE75; 20M reads per sample). The quality of sequencing data was confirmed with FastQC both before and after trimming. Paired-end reads were independently trimmed with Trimmomatic and aligned to the human reference genome (hg38) using STAR. SAMtools and NovoSort were respectively used to filter reads with proper mapping and sort the read pairs by name. RSEM was used to estimate read counts per transcript and generate transcript per million (TPM) counts.
创建时间:
2026-01-15



