GEO series

Ferroptotic neutrophils eradicate chemotherapy-induced immunity in breast cancer (Neutrophils)

GSE280204 Homo sapiens (human) RNA-seq (gene expression) 10 samples Submitted 2025/09/01 Platform GPL24676

At a glance

RNA-seq (gene expression) · human · 10 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: 10 samples: 5 × Neutrophil_S vs 5 × NeutrophilGroups 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)

Inducing ferroptosis in tumor cells serves as a promising strategy for treating malignancies that are refractory to traditional treatment modalities. However, the consequences of ferroptosis in immune cells in the tumor microenvironment (TME) are not completely understood. In this study, we found that neutrophils in chemoresistant breast cancer exhibited notable vulnerability to ferroptosis.

Read the full summary ↓

In chemoresistant neutrophils, the cellular phospholipid profile was reprogrammed owing to a deficiency in membrane-bound O-acyltransferase domain-containing 1 (MBOAT1), shifting the preference of the phospholipid fatty acid pattern from monounsaturated fatty acids (MUFAs) to polyunsaturated fatty acids (PUFAs), thereby increasing susceptibility to ferroptosis. Ferroptotic neutrophils significantly suppress the proliferation and cytotoxicity of antitumor CD8 T cells via PGE2, IDO, and oxidized lipids. Furthermore, we found that neutrophil ferroptosis was closely associated with a distinctive subset of IL-1+ CXCL3+ CD4 (Fer-CD4) T lymphocytes that were enriched in chemoresistant tumors. Fer-CD4 T cells regulated neutrophil ferroptosis through MBOAT1 modulation via IL-1/IL-1R1/NF-B signaling. Moreover, we revealed that there is crosstalk between neutrophils and Fer-CD4 T cells, during which Fer-CD4 T cells replenish the neutrophil pool of the TME via CXCL3, IL-8, and S100A9. The ferroptotic neutrophils in turn promote Fer-CD4 T cell differentiation, resulting in extensive neutrophil ferroptosis. In spontaneously tumorigenic mice, targeting IL-1+ CD4 T cells or IL-1R1+ neutrophils disrupted this crosstalk, suppressed neutrophil ferroptosis, enhanced antitumor immunity, and overcame chemoresistance. Our findings revealed the immune-reshaping capacity of neutrophil ferroptosis and its reciprocal feedback regulation with Fer-CD4 T cells, identifying promising targets for restoring anticancer immunosurveillance and reversing chemoresistance

This dataset

Open GSE280204 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 GSE280204_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 PRJNA1177346 and SRA study SRP540580. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

5 × Neutrophil_S vs 5 × Neutrophil

Supports a between-group comparison across 10 samples.

How we read this: 2 replicated groups read from 10 sample titles; they account for 10 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

GSM8591504 Neutrophil_S1 Neutrophil_S
GSM8591505 Neutrophil_S2 Neutrophil_S
GSM8591506 Neutrophil_S3 Neutrophil_S
GSM8591507 Neutrophil_S4 Neutrophil_S
GSM8591508 Neutrophil_S5 Neutrophil_S
GSM8591509 Neutrophil_R1 Neutrophil
GSM8591510 Neutrophil_R2 Neutrophil
GSM8591511 Neutrophil_R3 Neutrophil
GSM8591512 Neutrophil_R4 Neutrophil
GSM8591513 Neutrophil_R5 Neutrophil

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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.