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Mapping the FOXA1 Interactome in ER+ Breast Cancer Cells using Proximity Labeling Reveals Novel Interactions with the Orphan Nuclear Receptor NR2C2 [RNA-Seq]

GSE299760 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2025/09/01 Platform GPL18573
At a glance

RNA-seq (gene expression) · human · 12 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
12 samples: 3 × MCF7, control, vs 3 × MCF7, siNR2C2, vs 3 × T47D, control, vs 2 × T47D, siNR2C2,Groups 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
Mapping the FOXA1 Interactome in ER+ Breast Cancer Cells Using Proximity Labeling Reveals Novel Interactions with the Orphan Nuclear Receptor NR2C2Molecular cancer research : MCR · 2025
Summary (written by the submitters)
FOXA1 is a pioneer transcription factor essential for chromatin accessibility and transcriptional regulation in hormone-driven cancers. In breast cancer, FOXA1 plays a central role in facilitating nuclear receptor binding, reprogramming enhancer landscapes, and promoting transcriptional changes associated with therapy resistance. While FOXA1’s function has been primarily studied in the context of estrogen receptor-α (ER), its broader protein interaction network remains incompletely defined.
Read the full summary ↓
Here, we systematically map FOXA1-interacting proteins in ER-positive breast cancer cells using proximity-dependent biotin labeling (miniTurbo) combined with quantitative LC-MS/MS proteomics. We engineered MCF-7 cell lines stably expressing miniTurbo-tagged FOXA1 at either the N-terminus or C-terminus to ensure comprehensive coverage of interaction interfaces. This approach recovered known FOXA1 partners, including AR, MLL3, YAP1, and GATA3, and identified 157 previously unreported FOXA1 interactors. Notably, 42 of these novel partners, including NR2C2, were significantly associated with poor relapse-free survival in ER+ breast cancer patients. To demonstrate the utility of this resource, we characterized the FOXA1-NR2C2 interaction in depth. Integrating ChIP-seq and RNA-seq, we show that FOXA1 and NR2C2 co-occupy a subset of genomic regions and drive co-regulated transcriptional programs involved in tumor progression. Our study reveals an expanded FOXA1 interactome and new insights into its functional network in breast cancer, providing candidate proteins for further exploration as biomarkers or therapeutic targets.
Published in
Mapping the FOXA1 Interactome in ER+ Breast Cancer Cells Using Proximity Labeling Reveals Novel Interactions with the Orphan Nuclear Receptor NR2C2
Plagens RN, Tirado CSR, Li S et al. · Molecular cancer research : MCR 2025 · PMID 40874905 · doi:10.1158/1541-7786.MCR-25-0085
This dataset
Open GSE299760 in finder → Find more human RNA-seq datasets → Breast cancer landscape →
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.

Series matrix ↓
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 GSE299760_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
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.

Raw reads on ENA ↗

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 PRJNA1276456 and SRA study SRP591858. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40874905) ↗
Study design
3 × MCF7, control, vs 3 × MCF7, siNR2C2, vs 3 × T47D, control, vs 2 × T47D, siNR2C2,

Supports a between-group comparison across 11 samples.

How we read this: 4 replicated groups read from 12 sample titles; they account for 11 of them. 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

Search all human RNA-seq datasets in GEO →

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