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Chemotherapeutic Induction of Single-Stranded DNA Accumulation Sensitizes Triple-Negative Breast Cancer to Immunotherapy [scRNA-seq]

GSE311488 Mus musculus (mouse) Single-cell RNA-seq 32 samples Submitted 2026/06/20 Platform GPL34328
At a glance

Single-cell RNA-seq · mouse · 32 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Mus musculus (mouse)
Samples
32 samples: 9 × 4T1 IgG+Vehicle vs 8 × 4T1 Anti-PD1+Vehicle vs 8 × 4T1 Anti-PD1+LP-184 vs 7 × 4T1 IgG+LP-184Groups 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.
Summary (written by the submitters)
Despite the widespread adoption of chemo-immunotherapy in triple-negative breast cancer (TNBC), how cytotoxic chemotherapy engages antitumor immunity remains poorly defined. Here, we identify cytosolic single-stranded DNA (ssDNA) accumulation as the mechanistic bridge linking genotoxic stress to immune activation. By integrating in vivo TREX1-deficiency transcriptional signatures, we show that ssDNA-driven immunostimulatory programs—rather than TREX1 expression—robustly predict clinical response to chemo-immunotherapy across independent TNBC cohorts.
Read the full summary ↓
Through a chemotherapeutic screen, we identify LP-184, an acylfulvene-derived alkylating agent in clinical development, as a potent pharmacologic inducer of cytosolic ssDNA and type I interferon signaling. LP-184 enhances antigen presentation, reduces M2-like tumor-suppressive macrophages, and promotes CD8⁺ T-cell priming, thereby synergizing with anti-PD-1 therapy in vivo. These findings redefine the interface between DNA damage and immune activation, establishing ssDNA-driven immune programs as both a predictive biomarker and a therapeutic axis for next-generation chemo-immunotherapy design.
This dataset
Open GSE311488 in finder → Find more mouse 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 GSE311488_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1369543 and SRA study SRP648972. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
9 × 4T1 IgG+Vehicle vs 8 × 4T1 Anti-PD1+Vehicle vs 8 × 4T1 Anti-PD1+LP-184 vs 7 × 4T1 IgG+LP-184

Supports a between-group comparison across 32 samples.

How we read this: 4 replicated groups read from 32 sample titles; they account for 32 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
Datasets on a similar topic

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Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.