GEO series

ANP32E drives vulnerabiliy to ATR inhibitors in Triple Negative Breast Cancer by accumulation of R-loops [RNA-Seq]

GSE250561 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2025/03/27 Platform GPL24676

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)
Samples: 12 samples: 4 × tIMEC cells, RNA-Seq, vs 4 × tIMEC cells, RNA-Seq, ANP32E overexpression, vs 4 × tIMEC cells, RNA-Seq, ANP32E and RNaseH1 overexpression,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: ANP32E drives vulnerability to ATR inhibitors by inducing R-loops-dependent transcription replication conflicts in triple negative breast cancerNature communications · 2025

Summary (written by the submitters)

Triple Negative Breast Cancer (TNBC) is often characterized by MYC oncogene overactivation, causing dysregulation of gene expression and uncontrolled proliferation. We found that the expression of ANP32E chaperone protein is increased in dependency of MYC in human mammary epithelial cells, with associated induction of genome instability.

Read the full summary ↓

TCGA data confirmed that ANP32E is overexpressed in TNBCs with respect to the other BC subtypes. TNBC patients show higher frequency of genomic mutations, correlating with higher ANP32E expression. Investigation of the DNA damage response (DDR) pathways showed an upregulation of several involved genes in correlation with ANP32E overexpression. We demonstrated that inhibiting the DDR master regulator ATR triggers vulnerability of TNBC overexpressing ANP32E in vivo and leads to Double-Strand Breaks and micronuclei accumulation in vitro. We hypothesized the involvement of R-loops (DNA:RNA hybrids) in DDR sensitization, due to their accumulation after ANP32E overexpression and the generation of R-loop dependent Transcription Replication Conflicts. To clarify the underlying mechanism, we tested several DDR players, showing that ANP32E overexpressing cells have: i) sustained stimulation of DDR measured as phRPA32, phChk1, γH2A.X and 53BP1 activation; ii) enhanced recruitment of DDR players to specific chromatin loci; iii) R-loops accumulation at ANP32E chromatin bound sites; ii) elongating RNApolII stalled at R-loops sites, resulting in reduced nascent RNA. With the advantage of Next Generation Sequencing technologies, we mapped R-loops genome wide and observed an accumulation of longer, thus more stable, R-loops in dependency to ANP32E overexpression. Those sites also showed an increased phosphorylation of RPA32, a surrogate marker for Transcription Replication Conflicts. The consequent dependency of cancers with such biological condition from a constant activation of DDR puts the bases for a successful therapy based on ATR inhibitor drugs, which is also empowered thanks to the synergic effect with anti-proliferative molecules such as Navitoclax. In summary, dissection of the molecular mechanism linking ANP32E overexpression to the dependency on DDR specific players and fragile sites will help to rationally design patient-specific therapies and identify novel biomarkers for TNBC diagnosis.

Published in

ANP32E drives vulnerability to ATR inhibitors by inducing R-loops-dependent transcription replication conflicts in triple negative breast cancer

Lago S, Poli V, Fol L et al. · Nature communications 2025 · PMID 40382323 · doi:10.1038/s41467-025-59804-0

This dataset

Open GSE250561 in finder → Find more human RNA-seq datasets →

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 GSE250561_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 PRJNA1054540 and SRA study SRP479039. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40382323) ↗

Study design

4 × tIMEC cells, RNA-Seq, vs 4 × tIMEC cells, RNA-Seq, ANP32E overexpression, vs 4 × tIMEC cells, RNA-Seq, ANP32E and RNaseH1 overexpression,

Supports a between-group comparison across 12 samples.

How we read this: 3 replicated groups read from 12 sample titles; they account for 12 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

GSM7981597 tIMEC cells, RNA-Seq, rep1 tIMEC cells, RNA-Seq,
GSM7981598 tIMEC cells, RNA-Seq, rep2 tIMEC cells, RNA-Seq,
GSM7981599 tIMEC cells, RNA-Seq, rep3 tIMEC cells, RNA-Seq,
GSM7981600 tIMEC cells, RNA-Seq, rep4 tIMEC cells, RNA-Seq,
GSM7981601 tIMEC cells, RNA-Seq, ANP32E overexpression, rep1 tIMEC cells, RNA-Seq, A…
GSM7981602 tIMEC cells, RNA-Seq, ANP32E overexpression, rep2 tIMEC cells, RNA-Seq, A…
GSM7981603 tIMEC cells, RNA-Seq, ANP32E overexpression, rep3 tIMEC cells, RNA-Seq, A…
GSM7981604 tIMEC cells, RNA-Seq, ANP32E overexpression, rep4 tIMEC cells, RNA-Seq, A…
GSM7981605 tIMEC cells, RNA-Seq, ANP32E and RNaseH1 overexpression, rep1 tIMEC cells, RNA-Seq, A…
GSM7981606 tIMEC cells, RNA-Seq, ANP32E and RNaseH1 overexpression, rep2 tIMEC cells, RNA-Seq, A…
GSM7981607 tIMEC cells, RNA-Seq, ANP32E and RNaseH1 overexpression, rep3 tIMEC cells, RNA-Seq, A…
GSM7981608 tIMEC cells, RNA-Seq, ANP32E and RNaseH1 overexpression, rep4 tIMEC cells, RNA-Seq, A…

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