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BRRIAR lncRNA alters breast cancer risk by modulating interferon signaling in cis and in trans through BHLHE40 and RIG-I [RNA-Seq]

GSE297682 Homo sapiens (human) RNA-seq (gene expression) 27 samples Submitted 2026/01/14 Platform GPL21697
At a glance

RNA-seq (gene expression) · human · 27 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Homo sapiens (human)
Topic
Breast cancerThis series is part of our curated briefing on it.
Samples
27 samples: 27 samples, each with a distinct title — no replicated groupsGroups are read from the sample names, not from the paper. Check the list below.
Data you can get
A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Paper
BRRIAR lncRNA alters breast cancer risk by modulating interferon signaling in cis and in transMolecular cancer · 2026
Summary (written by the submitters)
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.
Read the full summary ↓
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.
Published in
BRRIAR lncRNA alters breast cancer risk by modulating interferon signaling in cis and in trans
Sivakumaran H, Nair S, Bitar M et al. · Molecular cancer 2026 · PMID 41501810 · doi:10.1186/s12943-025-02510-8
This dataset
Download · which file do I need?

Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE297682_RAW.tar (it can run to tens of gigabytes).

3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

What the files usually look like: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1265681 and SRA study SRP586616. Searching any of these in the dataset finder brings you back here.

Study design
27 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 27 sample titles: 27 distinct titles with little repetition. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study
More Breast cancer datasets

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